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Mas, S., Torro, A., Fernández, L., Bec, N., Gongora, C., Larroque, C., Martineau, P., de Juan, A., Marco, S., (2020). MALDI imaging mass spectrometry and chemometric tools to discriminate highly similar colorectal cancer tissues Talanta 208, 120455

Intratumour heterogeneity due to cancer cell clonal evolution and microenvironment composition and tumor differences due to genetic variations between patients suffering of the same cancer pathology play a crucial role in patient response to therapies. This study is oriented to show that matrix-assisted laser-desorption ionization-Mass spectrometry imaging (MALDI-MSI), combined with an advanced multivariate data processing pipeline can be used to discriminate subtle variations between highly similar colorectal tumors. To this aim, experimental tumors reproducing the emergence of drug-resistant clones were generated in athymic mice using subcutaneous injection of different mixes of two isogenic cell lines, the irinotecan-resistant HCT116-SN50 (R) and its sibling human colon adenocarcinoma sensitive cell line HCT116 (S). Because irinotecan-resistant and irinotecan-sensitive are derived from the same original parental HCT116 cell line, their genetic characteristics and molecular compositions are closely related. The multivariate data processing pipeline proposed relies on three steps: (a) multiset multivariate curve resolution (MCR) to separate biological contributions from background; (b) multiset K-means segmentation using MCR scores of the biological contributions to separate between tumor and necrotic parts of the tissues; and (c) partial-least squares discriminant analysis (PLS-DA) applied to tumor pixel spectra to discriminate between R and S tumor populations. High levels of correct classification rates (0.85), sensitivity (0.92) and specificity (0.77) for the PLS-DA classification model were obtained. If previously labelled tissue is available, the multistep modeling strategy proposed constitutes a good approach for the identification and characterization of highly similar phenotypic tumor subpopulations that could be potentially applicable to any kind of cancer tissue that exhibits substantial heterogeneity. © 2019 Elsevier B.V.

Keywords: Chemometrics, Colorectal cancer, MALDI imaging, Multivariate analysis, Tumor heterogeneity

Rodriguez, J., Schulz, S., Voss, A., Giraldo, B. F., (2020). Cardiorespiratory and vascular variability analysis to classify patients with ischemic and dilated cardiomyopathy* Engineering in Medicine & Biology Society (EMBC) 42nd Annual International Conference of the IEEE , IEEE (Montreal, Canada) , 2764-2767

Heart diseases are the leading cause of death in developed countries. Ascertaining the etiology of cardiomyopathies is still a challenge. The objective of this study was to classify cardiomyopathy patients through cardio, respiratory and vascular variability analysis, considering the vascular activity as the input and output of the baroreflex response. Forty-one cardiomyopathy patients (CMP) classified as ischemic (ICM, 24 patients) and dilated (DCM, 17 patients) were analyzed. Thirty-nine elderly control subjects (CON) were used as reference. From the electrocardiographic, respiratory flow, and blood pressure signals, following temporal series were extracted: beat-to-beat intervals (BBI), total respiratory cycle time series (TT), and end– systolic (SBP) and diastolic (DBP) blood pressure amplitudes, respectively. Three-dimensional representation of the cardiorespiratory and vascular activities was characterized geometrically, by fitting a polygon that contains 95% of data, and by statistical descriptive indices. The best classifiers were used to build support vector machine models. The optimal model to classify ICM versus DCM patients achieved 92.7% accuracy, 94.1% sensitivity, and 91.7% specificity. When comparing CMP patients and CON subjects, the best model achieved 86.2% accuracy, 82.9% sensitivity, and 89.7% specificity. These results suggest a limited ability of cardiac and respiratory systems response to regulate the vascular variability in these patients.

Keywords: Time series analysis, Support vector machines, Blood pressure, Sensitivity, Indexes, Electrocardiography, Kernel

Garcia-Puig, A., Mosquera, J. L., Jiménez-Delgado, S., García-Pastor, C., Jorba, I., Navajas, D., Canals, F., Raya, A., (2019). Proteomics analysis of extracellular matrix remodeling during zebrafish heart regeneration Molecular & cellular proteomics 18, (9), 1745-1755

Adult zebrafish, in contrast to mammals, are able to regenerate their hearts in response to injury or experimental amputation. Our understanding of the cellular and molecular bases that underlie this process, although fragmentary, has increased significantly over the last years. However, the role of the extracellular matrix (ECM) during zebrafish heart regeneration has been comparatively rarely explored. Here, we set out to characterize the ECM protein composition in adult zebrafish hearts, and whether it changed during the regenerative response. For this purpose, we first established a decellularization protocol of adult zebrafish ventricles that significantly enriched the yield of ECM proteins. We then performed proteomic analyses of decellularized control hearts and at different times of regeneration. Our results show a dynamic change in ECM protein composition, most evident at the earliest (7 days post-amputation) time-point analyzed. Regeneration associated with sharp increases in specific ECM proteins, and with an overall decrease in collagens and cytoskeletal proteins. We finally tested by atomic force microscopy that the changes in ECM composition translated to decreased ECM stiffness. Our cumulative results identify changes in the protein composition and mechanical properties of the zebrafish heart ECM during regeneration.

Keywords: Animal models, Atomic force microscopy, Cardiovascular disease, Cardiovascular function or biology, Developmental biology, Extracellular matrix, Heart regeneration, Proteomic analysis

Burgués, J., Marco, S., (2019). Wind-independent estimation of gas source distance from transient features of metal oxide sensor signals IEEE Access 7, 140460-140469

The intermittency of the instantaneous concentration of a turbulent chemical plume is a fundamental cue for estimating the chemical source distance using chemical sensors. Such estimate is useful in applications such as environmental monitoring or localization of fugitive gas emissions by mobile robots or sensor networks. However, the inherent low-pass filtering of metal oxide (MOX) gas sensors-typically used in odor-guided robots and dense sensor networks due to their low cost, weight and size-hinders the quantification of concentration intermittency. In this paper, we design a digital differentiator to invert the low-pass dynamics of the sensor response, thus obtaining a much faster signal from which the concentration intermittency can be effectively computed. Using a fast photo-ionization detector as a reference instrument, we demonstrate that the filtered signal is a good approximation of the instantaneous concentration in a real turbulent plume. We then extract transient features from the filtered signal-the so-called “bouts”-to predict the chemical source distance, focusing on the optimization of the filter parameters and the noise threshold to make the predictions robust against changing wind conditions. This represents an advantage over previous bout-based models which require wind measurements-typically taken with expensive and bulky anemometers-to produce accurate predictions. The proposed methodology is demonstrated in a wind tunnel scenario where a MOX sensor is placed at various distances downwind of an emitting chemical source and the wind speed varies in the range 10-34 cm/s. The results demonstrate that models optimized with our methodology can provide accurate source distance predictions at different wind speeds.

Keywords: Gas detectors, Chemical sensors, Signal processing, Machine learning, Time series analysis

Rodríguez, J., Schulz, S., Giraldo, B. F., Voss, A., (2019). Risk stratification in idiopathic dilated cardiomyopathy patients using cardiovascular coupling analysis Frontiers in Physiology 10, 841

Cardiovascular diseases are one of the most common causes of death; however, the early detection of patients at high risk of sudden cardiac death (SCD) remains an issue. The aim of this study was to analyze the cardio-vascular couplings based on heart rate variability (HRV) and blood pressure variability (BPV) analyses in order to introduce new indices for noninvasive risk stratification in idiopathic dilated cardiomyopathy patients (IDC). High-resolution electrocardiogram (ECG) and continuous noninvasive blood pressure (BP) signals were recorded in 91 IDC patients and 49 healthy subjects (CON). The patients were stratified by their SCD risk as high risk (IDCHR) when after two years the subject either died or suffered life-threatening complications, and as low risk (IDCLR) when the subject remained stable during this period. Values were extracted from ECG and BP signals, the beat-to-beat interval, and systolic and diastolic blood pressure, and analyzed using the segmented Poincaré plot analysis (SPPA), the high-resolution joint symbolic dynamics (HRJSD) and the normalized short time partial directed coherence methods. Support vector machine (SVM) models were built to classify these patients according to SCD risk. IDCHR patients presented lowered HRV and increased BPV compared to both IDCLR patients and the control subjects, suggesting a decrease in their vagal activity and a compensation of sympathetic activity. Both, the cardio -systolic and -diastolic coupling strength was stronger in high-risk patients when comparing with low-risk patients. The cardio-systolic coupling analysis revealed that the systolic influence on heart rate gets weaker as the risk increases. The SVM IDCLR vs. IDCHR model achieved 98.9% accuracy with an area under the curve (AUC) of 0.96. The IDC and the CON groups obtained 93.6% and 0.94 accuracy and AUC, respectively. To simulate a circumstance in which the original status of the subject is unknown, a cascade model was built fusing the aforementioned models, and achieved 94.4% accuracy. In conclusion, this study introduced a novel method for SCD risk stratification for IDC patients based on new indices from coupling analysis and non-linear HRV and BPV. We have uncovered some of the complex interactions within the autonomic regulation in this type of patient.

Keywords: Idiopathic dilated cardiomyopathy, Heart rate variability, Blood pressure variability, Coupling analysis, Sudden cardiac death, Risk stratification

Lozano-García, M., Davidson, C. M., Jané, R., (2019). Analysis of tracheal and pulmonary continuous adventitious respiratory sounds in asthma Engineering in Medicine and Biology Society (EMBC) 41st Annual International Conference of the IEEE , IEEE (Berlín, Germany) , 4930-4933

Continuous adventitious sounds (CAS) are commonly observed in obstructive pulmonary diseases and are of great clinical interest. However, their evaluation is generally subjective. We have previously developed an automatic CAS segmentation and classification algorithm for CAS recorded on the chest surface. The aim of this study is to establish whether these pulmonary CAS can be identified in a similar way using a tracheal microphone. Respiratory sounds were originally recorded from 25 participants using five contact microphones, four on the chest and one on the trachea, during three progressive respiratory maneuvers. In this work CAS component detection was performed on the tracheal channel using our automatic algorithm based on the Hilbert spectrum. The tracheal CAS detected were then compared to the previously analyzed pulmonary CAS. The sensitivity of CAS identification was lower at the tracheal microphone, with CAS that appeared simultaneously in all four pulmonary recordings more likely to be identified in the tracheal recordings. These observations could be due to the CAS being obscured by the lower SNR present in the tracheal recordings or not being transmitted through the airways to the trachea. Further work to optimize the algorithm for the tracheal recordings will be conducted in the future.

Keywords: Microphones, Lung, Diseases, Time-frequency analysis, Spectrogram, Sensitivity

Rodriguez, J., Schulz, S., Voss, A., Giraldo, B. F., (2019). Cardiovascular coupling-based classification of ischemic and dilated cardiomyopathy patients Engineering in Medicine and Biology Society (EMBC) 41st Annual International Conference of the IEEE , IEEE (Berlín, Germany) , 2007-2010

Cardiovascular diseases are one of the most common causes of death in elderly patients. The etiology of cardiomyopathies is difficult to discern clinically. The objective of this study was to classify cardiomyopathy patients using coupling analysis, through their cardiovascular behavior and the baroreflex response. A total of thirty-eight cardiomyopathy patients (CMP) classified as ischemic (ICM, 25 patients) and dilated (DCM, 13 patients) were analyzed. Thirty elderly control subjects (CON) were used as reference. Their electrocardiographic (ECG) and blood pressure (BP) signals were studied. To characterize the cardiovascular activity, the following temporal series were extracted: beat-to-beat intervals (from the ECG signal), and end- systolic and diastolic blood pressure amplitudes (from the BP signal). Non-linear characterization techniques like high resolution joint symbolic dynamics, segmented Poincaré plot analysis, normalized shorttime partial directed coherence, and dual sequence method were used to characterize these times series. The best indices were used to build support vector machine models for classification. The optimal model for ICM versus DCM patients achieved 84.2% accuracy, 76.9% sensitivity, and 88% specificity. When CMP patients and CON subjects were compared, the best model achieved 95.5% accuracy, 97.3% sensitivity, and 93.3% specificity. These results suggest a disfunction in the baroreflex mechanism in cardiomyopathies patients.

Keywords: Couplings, Time series analysis, Support vector machines, Electrocardiography, Baroreflex, Coherence, Sensitivity

López-Carral, Héctor, Santos-Pata, D., Zucca, R., Verschure, P., (2019). How you type is what you type: Keystroke dynamics correlate with affective content ACII 2019 8th International Conference on Affective Computing and Intelligent Interaction , IEEE (Cabride, UK) , 1-5

Estimating the affective state of a user during a computer task traditionally relies on either subjective reports or analysis of physiological signals, facial expressions, and other measures. These methods have known limitations, can be intrusive and may require specialized equipment. An alternative would be employing a ubiquitous device of everyday use such as a standard keyboard. Here we investigate if we can infer the emotional state of a user by analyzing their typing patterns. To test this hypothesis, we asked 400 participants to caption a set of emotionally charged images taken from a standard database with known ratings of arousal and valence. We computed different keystroke pattern dynamics, including keystroke duration (dwell time) and latency (flight time). By computing the mean value of all of these features for each image, we found a statistically significant negative correlation between dwell times and valence, and between flight times and arousal. These results highlight the potential of using keystroke dynamics to estimate the affective state of a user in a non-obtrusive way and without the need for specialized devices.

Keywords: Feature extraction, Correlation, Keyboards, Task analysis, Statistical analysis, Affective computing, Standards, Keystroke, Keyboard, Typing, Arousal, Valence, Affect

Romero, D., Jané, R., (2019). Non-linear HRV analysis to quantify the effects of intermittent hypoxia using an OSA rat model Engineering in Medicine and Biology Society (EMBC) 41st Annual International Conference of the IEEE , IEEE (Berlín, Germany) , 4994-4997

In this paper, a non-linear HRV analysis was performed to assess fragmentation signatures observed in heartbeat time series after intermittent hypoxia (IH). Three markers quantifying short-term fragmentation levels, PIP, IALS and PSS, were evaluated on R-R interval series obtained in a rat model of recurrent apnea. Through airway obstructions, apnea episodes were periodically simulated in six anesthetized Sprague-Dawley rats. The number of apnea events per hour (AHI index) was varied during the first half of the experiment while apnea episodes lasted 15 s. For the second part, apnea episodes lasted 5, 10 or 15 s, but the AHI index was fixed. Recurrent apnea was repeated for 15-min time intervals in all cases, alternating with basal periods of the same duration. The fragmentation markers were evaluated in segments of 5 minutes, selected at the beginning and end of the experiment. The impact of the heart and breathing rates (HR and BR, respectively) on the parameter estimates was also investigated. The results obtained show a significant increase (from 5 to 10%, p <; 0.05) in fragmentation measures of heartbeat time series after IH, indicating a clear deterioration of the initial conditions. Moreover, there was a strong linear relationship (r > 0.9) between these markers and BR, as well as with the ratio given by HR/BR. Although fragmentation may be impacted by IH, we found that it is highly dependent on HR and BR values and thus, they should be considered during its calculation or used to normalize the fragmentation estimates.

Keywords: Rats, Time series analysis, Radio access technologies, Protocols, Heart beat

García-Díaz, María, Birch, Ditlev, Wan, Feng, Mørck Nielsen, Hanne, (2018). The role of mucus as an invisible cloak to transepithelial drug delivery by nanoparticles Advanced Drug Delivery Reviews 124, 107-124

Mucosal administration of drugs and drug delivery systems has gained increasing interest. However, nanoparticles intended to protect and deliver drugs to epithelial surfaces require transport through the surface-lining mucus. Translation from bench to bedside is particularly challenging for mucosal administration since a variety of parameters will influence the specific barrier properties of the mucus including the luminal fluids, the microbiota, the mucus composition and clearance rate, and the condition of the underlying epithelia. Besides, after administration, nanoparticles interact with the mucosal components, forming a biomolecular corona that modulates their behavior and fate after mucosal administration. These interactions are greatly influenced by the nanoparticle properties, and therefore different designs and surface-engineering strategies have been proposed. Overall, it is essential to evaluate these biomolecule-nanoparticle interactions by complementary techniques using complex and relevant mucus barrier matrices.

Keywords: Nanoparticle formulation strategies, Corona formation, Digestive tract, Respiratory tract, Luminal content, Methodologies, Analysis

Romeo, Agostino, Moya, Ana, Leung, Tammy S., Gabriel, Gemma, Villa, Rosa, Sánchez, Samuel, (2018). Inkjet printed flexible non-enzymatic glucose sensor for tear fluid analysis Applied Materials Today 10, 133-141

Here, we present a flexible and low-cost inkjet printed electrochemical sensor for enzyme-free glucose analysis. Versatility, short fabrication time and low cost make inkjet printing a valuable alternative to traditional sensor manufacturing techniques. We fabricated electro-chemical glucose sensors by inkjet printing electrodes on a flexible polyethylene terephthalate substrate. CuO microparticles were used to modify our electrodes, leading to a sensitive, stable and cost-effective platform for non-enzymatic detection of glucose. Selectivity, reproducibility, and life-time provided by the CuO functionalization demonstrated that these sensors are reliable tools for personalized diagnostics and self-assessment of an individual's health. The detection of glucose at concentrations matching that of tear fluid allows us to envisage applications in ocular diagnostics, where painless and non-invasive monitoring of diabetes can be achieved by analyzing glucose contained in tears.

Keywords: Inkjet printing, Non-enzymatic sensor, Glucose, Copper oxide, Tear analysis

Rodríguez-Pérez, R., Fernández, L., Marco, S., (2018). Overoptimism in cross-validation when using partial least squares-discriminant analysis for omics data: a systematic study Analytical and Bioanalytical Chemistry 410, (23), 5981-5992

Advances in analytical instrumentation have provided the possibility of examining thousands of genes, peptides, or metabolites in parallel. However, the cost and time-consuming data acquisition process causes a generalized lack of samples. From a data analysis perspective, omics data are characterized by high dimensionality and small sample counts. In many scenarios, the analytical aim is to differentiate between two different conditions or classes combining an analytical method plus a tailored qualitative predictive model using available examples collected in a dataset. For this purpose, partial least squares-discriminant analysis (PLS-DA) is frequently employed in omics research. Recently, there has been growing concern about the uncritical use of this method, since it is prone to overfitting and may aggravate problems of false discoveries. In many applications involving a small number of subjects or samples, predictive model performance estimation is only based on cross-validation (CV) results with a strong preference for reporting results using leave one out (LOO). The combination of PLS-DA for high dimensionality data and small sample conditions, together with a weak validation methodology is a recipe for unreliable estimations of model performance. In this work, we present a systematic study about the impact of the dataset size, the dimensionality, and the CV technique used on PLS-DA overoptimism when performance estimation is done in cross-validation. Firstly, by using synthetic data generated from a same probability distribution and with assigned random binary labels, we have obtained a dataset where the true classification rate (CR) is 50%. As expected, our results confirm that internal validation provides overoptimistic estimations of the classification accuracy (i.e., overfitting). We have characterized the CR estimator in terms of bias and variance depending on the internal CV technique used and sample to dimensionality ratio. In small sample conditions, due to the large bias and variance of the estimator, the occurrence of extremely good CRs is common. We have found that overfitting peaks when the sample size in the training subset approaches the feature vector dimensionality minus one. In these conditions, the models are neither under- or overdetermined with a unique solution. This effect is particularly intense for LOO and peaks higher in small sample conditions. Overoptimism is decreased beyond this point where the abundance of noisy produces a regularization effect leading to less complex models. In terms of overfitting, our study ranks CV methods as follows: Bootstrap produces the most accurate estimator of the CR, followed by bootstrapped Latin partitions, random subsampling, K-Fold, and finally, the very popular LOO provides the worst results. Simulation results are further confirmed in real datasets from mass spectrometry and microarrays.

Keywords: Metabolomics, Mass spectrometry, Microarrays, Chemometrics, Data analysis, Classification, Method validation

Laguna, Pablo, Garde, Ainara, Giraldo, Beatriz F., Meste, Olivier, Jané, Raimon, Sörnmo, Leif, (2018). Eigenvalue-based time delay estimation of repetitive biomedical signals Digital Signal Processing 75, 107-119

The time delay estimation problem associated with an ensemble of misaligned, repetitive signals is revisited. Each observed signal is assumed to be composed of an unknown, deterministic signal corrupted by Gaussian, white noise. This paper shows that maximum likelihood (ML) time delay estimation can be viewed as the maximization of an eigenvalue ratio, where the eigenvalues are obtained from the ensemble correlation matrix. A suboptimal, one-step time delay estimate is proposed for initialization of the ML estimator, based on one of the eigenvectors of the inter-signal correlation matrix. With this approach, the ML estimates can be determined without the need for an intermediate estimate of the underlying, unknown signal. Based on respiratory flow signals, simulations show that the variance of the time delay estimation error for the eigenvalue-based method is almost the same as that of the ML estimator. Initializing the maximization with the one-step estimates, rather than using the ML estimator alone, the computation time is reduced by a factor of 5M when using brute force maximization (M denoting the number of signals in the ensemble), and a factor of about 1.5 when using particle swarm maximization. It is concluded that eigenanalysis of the ensemble correlation matrix not only provides valuable insight on how signal energy, jitter, and noise influence the estimation process, but it also leads to a one-step estimator which can make the way for a substantial reduction in computation time.

Keywords: Biomedical signals, Time delay estimation, Eigenanalysis, Ensemble analysis

Ino, Kosuke, Nashimoto, Yuji, Taira, Noriko, Ramón-Azcon, Javier, Shiku, Hitoshi, (2018). Intracellular electrochemical sensing Electroanalysis 30, (10), 2195-2209

Observing biochemical processes within living cell is imperative for biological and medical research. Fluoresce imaging is widely used for intracellular sensing of cell membranes, nuclei, lysosomes, and pH. Electrochemical assays have been proposed as an alternative to fluorescence-based assays because of excellent analytical features of electrochemical devices. Notably, thanks to the rapid progress of micro/nanotechnologies and electrochemical techniques, intracellular electrochemical sensing is making rapid progress, leading to a successful detection of intracellular components. Such insight can provide a deep understanding of cellular biological processes and, ultimately, define the human healthy and diseased states. In this review, we present an overview of recent research progress in intracellular electrochemical sensing. We focus on two main topics, electrochemical extraction of cytosolic contents from cells and intracellular electrochemical sensing in situ.

Keywords: Micro/nanoelectrode, Analytical electrochemistry, Intracellular sensing, Cell analysis

Aviles, A. I., Widlak, T., Casals, A., Nillesen, M. M., Ammari, H., (2017). Robust cardiac motion estimation using ultrafast ultrasound data: A low-rank topology-preserving approach Physics in Medicine and Biology , 62, (12), 4831-4851

Cardiac motion estimation is an important diagnostic tool for detecting heart diseases and it has been explored with modalities such as MRI and conventional ultrasound (US) sequences. US cardiac motion estimation still presents challenges because of complex motion patterns and the presence of noise. In this work, we propose a novel approach to estimate cardiac motion using ultrafast ultrasound data. Our solution is based on a variational formulation characterized by the L 2-regularized class. Displacement is represented by a lattice of b-splines and we ensure robustness, in the sense of eliminating outliers, by applying a maximum likelihood type estimator. While this is an important part of our solution, the main object of this work is to combine low-rank data representation with topology preservation. Low-rank data representation (achieved by finding the k-dominant singular values of a Casorati matrix arranged from the data sequence) speeds up the global solution and achieves noise reduction. On the other hand, topology preservation (achieved by monitoring the Jacobian determinant) allows one to radically rule out distortions while carefully controlling the size of allowed expansions and contractions. Our variational approach is carried out on a realistic dataset as well as on a simulated one. We demonstrate how our proposed variational solution deals with complex deformations through careful numerical experiments. The low-rank constraint speeds up the convergence of the optimization problem while topology preservation ensures a more accurate displacement. Beyond cardiac motion estimation, our approach is promising for the analysis of other organs that exhibit motion.

Keywords: Cardiac analysis, Low-rank representation, Motion estimation, Topology preservation, Ultrafast ultrasound

Rodriguez, J., Voss, A., Caminal, P., Bayes-Genis, A., Giraldo, B. F., (2017). Characterization and classification of patients with different levels of cardiac death risk by using Poincaré plot analysis Engineering in Medicine and Biology Society (EMBC) 39th Annual International Conference of the IEEE , IEEE (Seogwipo, South Korea) , 1332-1335

Cardiac death risk is still a big problem by an important part of the population, especially in elderly patients. In this study, we propose to characterize and analyze the cardiovascular and cardiorespiratory systems using the Poincaré plot. A total of 46 cardiomyopathy patients and 36 healthy subjets were analyzed. Left ventricular ejection fraction (LVEF) was used to stratify patients with low risk (LR: LVEF > 35%, 16 patients), and high risk (HR: LVEF ≤ 35%, 30 patients) of heart attack. RR, SBP and TTot time series were extracted from the ECG, blood pressure and respiratory flow signals, respectively. Parameters that describe the scatterplott of Poincaré method, related to short- and long-term variabilities, acceleration and deceleration of the dynamic system, and the complex correlation index were extracted. The linear discriminant analysis (LDA) and the support vector machines (SVM) classification methods were used to analyze the results of the extracted parameters. The results showed that cardiac parameters were the best to discriminate between HR and LR groups, especially the complex correlation index (p = 0.009). Analising the interaction, the best result was obtained with the relation between the difference of the standard deviation of the cardiac and respiratory system (p = 0.003). When comparing HR vs LR groups, the best classification was obtained applying SVM method, using an ANOVA kernel, with an accuracy of 98.12%. An accuracy of 97.01% was obtained by comparing patients versus healthy, with a SVM classifier and Laplacian kernel. The morphology of Poincaré plot introduces parameters that allow the characterization of the cardiorespiratory system dynamics.

Keywords: Time series analysis, Electrocardiography, Support vector machines, Kernel, Standards, Correlation, RF signals

Castillo, Y., Blanco, D., Whitney, J., Mersky, B., Jané, R., (2017). Characterization of a tooth microphone coupled to an oral appliance device: A new system for monitoring OSA patients Engineering in Medicine and Biology Society (EMBC) 39th Annual International Conference of the IEEE , IEEE (Seogwipo, South Korea) , 1543-1546

Obstructive sleep apnea (OSA) is a highly prevalent chronic disease, especially in elderly and obese populations. Despite constituting a serious health, social and economic problem, most patients remain undiagnosed and untreated due to limitations in current equipment. In this work, we propose a novel method to diagnose OSA and monitor therapy adherence and effectiveness at home in a non-invasive and inexpensive way: combining acoustic analysis of breathing and snoring sounds with oral appliance therapy (OA). Audiodontics has introduced a new sensor, a tooth microphone coupled to an OA device, which is the main pillar of this system. The objective of this work is to characterize the response of this sensor, comparing it with a commercial tracheal microphone (Biopac transducer). Signals containing OSA-related sounds were acquired simultaneously with the two microphones for that purpose. They were processed and analyzed in time, frequency and time-frequency domains, in a custom MATLAB interface. We carried out a single-event approach focused on breaths, snores and apnea episodes. We found that the quality of the signals obtained by both microphones was quite similar, although the tooth microphone spectrum concentrated more energy at the high-frequency band. This opens a new field of study about high-frequency components of snores and breathing sounds. These characteristics, together with its intraoral position, wireless option and combination with customizable OAs, give the tooth microphone a great potential to reduce the impact of sleep disorders, by enabling prompt detection and continuous monitoring of patients at home.

Keywords: Microphones, Teeth, Sleep apnea, Time-frequency analysis, Signal to noise ratio, Monitoring, Acoustics

Schulz, S., Legorburu Cladera, B., Giraldo, B., Bolz, M., Bar, K. J., Voss, A., (2017). Neuronal desynchronization as marker of an impaired brain network Engineering in Medicine and Biology Society (EMBC) 39th Annual International Conference of the IEEE , IEEE (Seogwipo, South Korea) , 2251-2254

Synchronization is a central key feature of neural information processing and communication between different brain areas. Disturbance of oscillatory brain rhythms and decreased synchronization have been associated with different disorders including schizophrenia. The aim of this study was to investigate whether synchronization (in relaxed conditions with no stimuli) between different brain areas within the delta, theta, alpha (alpha1, alpha2), beta (beta1, beta2), and gamma bands is altered in patients with a neurological disorder in order to generate significant cortical enhancements. To achieve this, we investigated schizophrenic patients (SZO; N=17, 37.5±10.4 years, 15 males) and compared them to healthy subjects (CON; N=21, 36.7±13.4 years, 15 males) applying the phase locking value (PLV). We found significant differences between SZO and CON in different brain areas of the theta, alpha1, beta2 and gamma bands. These areas are related to the central and parietal lobes for the theta band, the parietal lobe for the alpha1, the parietal and frontal for the beta2 and the frontal-central for the gamma band. The gamma band revealed the most significant differences between CON and SZO. PLV were 61.7% higher on average in SZO in most of the clusters when compared to CON. The related brain areas are directly related to cognition skills which are proved to be impaired in SZO. The results of this study suggest that synchronization in SZO is also altered when the patients were not asked to perform a task that requires their cognitive skills (i.e., no stimuli are applied - in contrast to other findings).

Keywords: Synchronization, Electroencephalography, Electrodes, Brain, Time series analysis, Oscillators, Frequency synchronization

Trapero, J. I., Arizmendi, C. J., Gonzalez, H., Forero, C., Giraldo, B. F., (2017). Nonlinear dynamic analysis of the cardiorespiratory system in patients undergoing the weaning process Engineering in Medicine and Biology Society (EMBC) 39th Annual International Conference of the IEEE , IEEE (Seogwipo, South Korea) , 3493-3496

In this work, the cardiorespiratory pattern of patients undergoing extubation process is studied. First, the respiratory and cardiac signals were resampled, next the Symbolic Dynamics (SD) technique was implemented, followed of a dimensionality reduction applying Forward Selection (FS) and Moving Window with Variance Analysis (MWVA) methods. Finally, the Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM) classifiers were used. The study analyzed 153 patients undergoing weaning process, classified into 3 groups: Successful Group (SG: 94 patients), Failed Group (FG: 39 patients), and patients who had been successful during the extubation and had to be reintubated before 48 hours, Reintubated Group (RG: 21 patients). According to the results, the best classification present an accuracy higher than 88.98 ± 0.013% in all proposed combinations.

Keywords: Support vector machines, Standards, Time series analysis, Resonant frequency, Nonlinear dynamical systems, Ventilation

Torras, Núria, Agusil, Juan Pablo, Vázquez, Patricia, Duch, Marta, Hernández-Pinto, Alberto M., Samitier, Josep, de la Rosa, Enrique J., Esteve, Jaume, Suárez, Teresa, Pérez-García, Lluïsa, Plaza, José A., (2016). Suspended planar-array chips for molecular multiplexing at the microscale Advanced Materials , 28, (7), 1449–1454

A novel suspended planar-array chips technology is described, which effectively allows molecular multiplexing using a single suspended chip to analyze extraordinarily small volumes. The suspended chips are fabricated by combining silicon-based technology and polymer-pen lithography, obtaining increased molecular pattern flexibility, and improving miniaturization and parallel production. The chip miniaturization is so dramatic that it permits the intracellular analysis of living cells.

Keywords: Chip-in-a-cell, Suspended-arrays, Planar-arrays, Silicon chips, Single-cell analysis

Wills, C. R., Malandrino, A., Van Rijsbergen, M., Lacroix, D., Ito, K., Noailly, J., (2016). Simulating the sensitivity of cell nutritive environment to composition changes within the intervertebral disc Journal of the Mechanics and Physics of Solids 90, 108-123

Altered nutrition in the intervertebral disc affects cell viability and can generate catabolic cascades contributing to extracellular matrix (ECM) degradation. Such degradation is expected to affect couplings between disc mechanics and nutrition, contributing to accelerate degenerative processes. However, the relation of ECM changes to major biophysical events within the loaded disc remains unclear. A L4-L5 disc finite element model including the nucleus (NP), annulus (AF) and endplates was used and coupled to a transport-cell viability model. Solute concentrations and cell viability were evaluated along the mid-sagittal plane path. A design of experiment (DOE) was performed. DOE parameters corresponded to AF and NP biochemical tissue measurements in discs with different degeneration grades. Cell viability was not affected by any parameter combinations defined. Nonetheless, the initial water content was the parameter that affected the most the solute contents, especially glucose. Calculations showed that altered NP composition could negatively affect AF cell nutrition. Results suggested that AF and NP tissue degeneration are not critical to nutrition-related cell viability at early-stage of disc degeneration. However, small ECM degenerative changes may alter significantly disc nutrition under mechanical loads. Coupling disc mechano-transport simulations and enzyme expression studies could allow identifying spatiotemporal sequences related to tissue catabolism.

Keywords: Cell nutrition, Finite element analysis, Intervertebral disc degeneration, Multiphysics, Tissue composition

Estrada, L., Torres, A., Garcia-Casado, J., Sarlabous, L., Prats-Boluda, G., Jané, R., (2016). Time-frequency representations of the sternocleidomastoid muscle electromyographic signal recorded with concentric ring electrodes Engineering in Medicine and Biology Society (EMBC) 38th Annual International Conference of the IEEE , IEEE (Orlando, USA) , 3785-3788

The use of non-invasive methods for the study of respiratory muscle signals can provide clinical information for the evaluation of the respiratory muscle function. The aim of this study was to evaluate time-frequency characteristics of the electrical activity of the sternocleidomastoid muscle recorded superficially by means of concentric ring electrodes (CREs) in a bipolar configuration. The CREs enhance the spatial resolution, attenuate interferences, as the cardiac activity, and also simplify the orientation problem associated to the electrode location. Five healthy subjects underwent a respiratory load test in which an inspiratory load was imposed during the inspiratory phase. During the test, the electromyographic signal of the sternocleidomastoid muscle (EMGsc) and the inspiratory mouth pressure (Pmouth) were acquired. Time-frequency characteristics of the EMGsc signal were analyzed by means of eight time-frequency representations (TFRs): the spectrogram (SPEC), the Morlet scalogram (SCAL), the Wigner-Ville distribution (WVD), the Choi-Williams distribution (CHWD), two generalized exponential distributions (GED1 and GED2), the Born-Jordan distribution (BJD) and the Cone-Kernel distribution (CKD). The instantaneous central frequency of the EMGsc showed an increasing behavior during the inspiratory cycle and with the increase of the inspiratory load. The bilinear TFRs (WVD, CHWD, GEDs and BJD) were less sensitive to cardiac activity interference than classical TFRs (SPEC and SCAL). The GED2 was the TFR that shown the best results for the characterization of the instantaneous central frequency of the EMGsc.

Keywords: Electrodes, Interference, Kernel, Mouth, Muscles, Spectrogram, Time-frequency analysis

del Moral-Zamora, Beatriz, Punter-Villagrassa, Jaime, Oliva-Brañas, Ana M., Álvarez-Azpeitia, Juan Manuel, Colomer-Farrarons, Jordi, Samitier, Josep, Homs-Corbera, Antoni, Miribel-Català, Pere Ll, (2015). Combined dielectrophoretic and impedance system for on-chip controlled bacteria concentration: application to Escherichia coli Electrophoresis , 36, (9-10), 1130-1141

The present paper reports a bacteria autonomous controlled concentrator prototype with a user-friendly interface for bench-top applications. It is based on a micro-fluidic lab-on-a-chip and its associated custom instrumentation, which consists in a dielectrophoretic actuator, to pre-concentrate the sample, and an impedance analyser, to measure concentrated bacteria levels. The system is composed by a single micro-fluidic chamber with interdigitated electrodes and a instrumentation with custom electronics. The prototype is supported by a real-time platform connected to a remote computer, which automatically controls the system and displays impedance data used to monitor the status of bacteria accumulation on-chip. The system automates the whole concentrating operation. Performance has been studied for controlled volumes of Escherichia coli (E. coli) samples injected into the micro-fluidic chip at constant flow rate of 10 μL/min. A media conductivity correcting protocol has been developed, as the preliminary results showed distortion of the impedance analyser measurement produced by bacterial media conductivity variations through time. With the correcting protocol, the measured impedance values were related to the quantity of bacteria concentrated with a correlation of 0.988 and a coefficient of variation of 3.1%. Feasibility of E. coli on-chip automated concentration, using the miniaturized system, has been demonstrated. Furthermore, the impedance monitoring protocol had been adjusted and optimized, to handle changes in the electrical properties of the bacteria media over time.

Keywords: Autonomous Device, Bacteria Concentrator, Dielectrophoresis, Escherichia coli, Impedance Analysis

Garde, A., Giraldo, B. F., Jané, R., Latshang, T. D., Turk, A. J., Hess, T., Bosch, M-.M., Barthelmes, D., Merz, T. M., Hefti, J. Pichler, Schoch, O. D., Bloch, K. E., (2015). Time-varying signal analysis to detect high-altitude periodic breathing in climbers ascending to extreme altitude Medical & Biological Engineering & Computing , 53, (8), 699-712

This work investigates the performance of cardiorespiratory analysis detecting periodic breathing (PB) in chest wall recordings in mountaineers climbing to extreme altitude. The breathing patterns of 34 mountaineers were monitored unobtrusively by inductance plethysmography, ECG and pulse oximetry using a portable recorder during climbs at altitudes between 4497 and 7546 m on Mt. Muztagh Ata. The minute ventilation (VE) and heart rate (HR) signals were studied, to identify visually scored PB, applying time-varying spectral, coherence and entropy analysis. In 411 climbing periods, 30–120 min in duration, high values of mean power (MPVE) and slope (MSlopeVE) of the modulation frequency band of VE, accurately identified PB, with an area under the ROC curve of 88 and 89 %, respectively. Prolonged stay at altitude was associated with an increase in PB. During PB episodes, higher peak power of ventilatory (MPVE) and cardiac (MP LF HR ) oscillations and cardiorespiratory coherence (MP LF Coher ), but reduced ventilation entropy (SampEnVE), was observed. Therefore, the characterization of cardiorespiratory dynamics by the analysis of VE and HR signals accurately identifies PB and effects of altitude acclimatization, providing promising tools for investigating physiologic effects of environmental exposures and diseases.

Keywords: High-altitude periodic breathing, Cardiorespiratory characterization, Time-varying spectral analysis, Acclimatization, Hypoxia

Alsaleh, S. M., Aviles, A. I., Sobrevilla, P., Casals, A., Hahn, J. K., (2015). Automatic and robust single-camera specular highlight removal in cardiac images Engineering in Medicine and Biology Society (EMBC) 37th Annual International Conference of the IEEE , IEEE (Milan, Italy) , 675-678

In computer-assisted beating heart surgeries, accurate tracking of the heart's motion is of huge importance and there is a continuous need to eliminate any source of error that might disturb the tracking process. One source of error is the specular reflection that appears on the glossy surface of the heart. In this paper, we propose a robust solution for the detection and removal of specular highlights. A hybrid color attributes and wavelet based edge projection approach is applied to accurately identify the affected regions. These regions are then recovered using a dynamic search-based inpainting with adaptive windowing. Experimental results demonstrate the precision and efficiency of the proposed method. Moreover, it has a real-time performance and can be generalized to various other applications.

Keywords: Heart, Image color analysis, Image edge detection, Surgery, Tracking, Wavelet transforms

Giraldo, B. F., Rodriguez, J., Caminal, P., Bayes-Genis, A., Voss, A., (2015). Cardiorespiratory and cardiovascular interactions in cardiomyopathy patients using joint symbolic dynamic analysis Engineering in Medicine and Biology Society (EMBC) 37th Annual International Conference of the IEEE , IEEE (Milan, Italy) , 306-309

Cardiovascular diseases are the first cause of death in developed countries. Using electrocardiographic (ECG), blood pressure (BP) and respiratory flow signals, we obtained parameters for classifying cardiomyophaty patients. 42 patients with ischemic (ICM) and dilated (DCM) cardiomyophaties were studied. The left ventricular ejection fraction (LVEF) was used to stratify patients with low risk (LR: LVEF>35%, 14 patients) and high risk (HR: LVEF≤ 35%, 28 patients) of heart attack. RR, SBP and TTot time series were extracted from the ECG, BP and respiratory flow signals, respectively. The time series were transformed to a binary space and then analyzed using Joint Symbolic Dynamic with a word length of three, characterizing them by the probability of occurrence of the words. Extracted parameters were then reduced using correlation and statistical analysis. Principal component analysis and support vector machines methods were applied to characterize the cardiorespiratory and cardiovascular interactions in ICM and DCM cardiomyopaties, obtaining an accuracy of 85.7%.

Keywords: Blood pressure, Electrocardiography, Joints, Kernel, Principal component analysis, Support vector machines, Time series analysis

Estrada, L., Torres, A., Sarlabous, L., Jané, R., (2015). Respiratory signal derived from the smartphone built-in accelerometer during a Respiratory Load Protocol Engineering in Medicine and Biology Society (EMBC) 37th Annual International Conference of the IEEE , IEEE (Milan, Italy) , 6768-6771

The scope of our work focuses on investigating the potential use of the built-in accelerometer of the smartphones for the recording of the respiratory activity and deriving the respiratory rate. Five healthy subjects performed an inspiratory load protocol. The excursion of the right chest was recorded using the built-in triaxial accelerometer of a smartphone along the x, y and z axes and with an external uniaxial accelerometer. Simultaneously, the respiratory airflow and the inspiratory mouth pressure were recorded, as reference respiratory signals. The chest acceleration signal recorded in the z axis with the smartphone was denoised using a scheme based on the ensemble empirical mode decomposition, a noise data assisted method which decomposes nonstationary and nonlinear signals into intrinsic mode functions. To distinguish noisy oscillatory modes from the relevant modes we use the detrended fluctuation analysis. We reported a very strong correlation between the acceleration of the z axis of the smartphone and the reference accelerometer across the inspiratory load protocol (from 0.80 to 0.97). Furthermore, the evaluation of the respiratory rate showed a very strong correlation (0.98). A good agreement was observed between the respiratory rate estimated with the chest acceleration signal from the z axis of the smartphone and with the respiratory airflow signal: Bland-Altman limits of agreement between -1.44 and 1.46 breaths per minute with a mean bias of -0.01 breaths per minute. This preliminary study provides a valuable insight into the use of the smartphone and its built-in accelerometer for respiratory monitoring.

Keywords: Acceleration, Accelerometers, Correlation, Empirical mode decomposition, Fluctuations, Protocols, Time series analysis

Aviles, A. I., Sobrevilla, P., Casals, A., (2014). An approach for physiological motion compensation in robotic-assisted cardiac surgery Experimental & Clinical Cardiology , 20, (11), 6713-6724

The lack of physiological motion compensation is a major problem in robotic-assisted cardiac surgery. Since the heart is beating while the surgeon carried out the procedure, dexterity of the surgeon’s and precision are compromised. Due to the operative space and the visibility of the surgical field are reduced, the most practical solution is the use of computer vision techniques. The lack of efficiency and robustness of the existing proposals make physiological motion compensation to be considered an open problem. In this work a novel solution to solve this problem based on the minimization of an energy functional is presented. It is described in the three-dimensional space using the l1−regularized optimization class in which cubic b-splines are used to represent the changes produced on the heart surface. Moreover, the logarithmic barrier function is applied to create an approximation of the total energy in order to avoid its non-differentiability. According to the results, this proposal is able to deal with complex deformations, requires a short computational time and gives a small error.

Keywords: Beating heart surgery, Image analysis, Motion compensation

Eckelt, Kay, Masanas, Helena, Llobet, Artur, Gorostiza, P., (2014). Automated high-throughput measurement of body movements and cardiac activity of Xenopus tropicalis tadpoles Journal of Biological Methods , 1, (2), e9

Xenopus tadpoles are an emerging model for developmental, genetic and behavioral studies. A small size, optical accessibility of most of their organs, together with a close genetic and structural relationship to humans make them a convenient experimental model. However, there is only a limited toolset available to measure behavior and organ function of these animals at medium or high-throughput. Herein, we describe an imaging-based platform to quantify body and autonomic movements of Xenopus tropicalis tadpoles of advanced developmental stages. Animals alternate periods of quiescence and locomotor movements and display buccal pumping for oxygen uptake from water and rhythmic cardiac movements. We imaged up to 24 animals in parallel and automatically tracked and quantified their movements by using image analysis software. Animal trajectories, moved distances, activity time, buccal pumping rates and heart beat rates were calculated and used to characterize the effects of test compounds. We evaluated the effects of propranolol and atropine, observing a dose-dependent bradycardia and tachycardia, respectively. This imaging and analysis platform is a simple, cost-effective high-throughput in vivo assay system for genetic, toxicological or pharmacological characterizations.

Keywords: Xenopus tropicalis, Animal behavior, Cardiac imaging, Motion analysis, Animal tracking, Hhigh-throughput in vivo assay

Cuervo, A., Dans, P. D., Carrascosa, J. L., Orozco, M., Gomila, G., Fumagalli, L., (2014). Direct measurement of the dielectric polarization properties of DNA Proceedings of the National Academy of Sciences of the United States of America 111, (35), E3624-E3630

The electric polarizability of DNA, represented by the dielectric constant, is a key intrinsic property that modulates DNA interaction with effector proteins. Surprisingly, it has so far remained unknown owing to the lack of experimental tools able to access it. Here, we experimentally resolved it by detecting the ultraweak polarization forces of DNA inside single T7 bacteriophages particles using electrostatic force microscopy. In contrast to the common assumption of low-polarizable behavior like proteins (εr ~ 2–4), we found that the DNA dielectric constant is ~ 8, considerably higher than the value of ~ 3 found for capsid proteins. State-of-the-art molecular dynamic simulations confirm the experimental findings, which result in sensibly decreased DNA interaction free energy than normally predicted by Poisson–Boltzmann methods. Our findings reveal a property at the basis of DNA structure and functions that is needed for realistic theoretical descriptions, and illustrate the synergetic power of scanning probe microscopy and theoretical computation techniques.

Keywords: Atomic force microscopy, Atomistic simulations, DNA packaging, DNA-ligand binding, Poisson-Boltzmann equation, capsid protein, DNA, double stranded DNA, amino acid composition, article, atomic force microscopy, bacteriophage, bacteriophage T7, dielectric constant, dipole, DNA binding, DNA packaging, DNA structure, electron microscopy, ligand binding, nonhuman, polarization, priority journal, protein analysis, protein DNA interaction, scanning probe microscopy, static electricity, virion, virus capsid, virus particle, atomic force microscopy, atomistic simulations, DNA packaging, DNA-ligand binding, Poisson-Boltzmann equation, Bacteriophage T7, Capsid, Cations, Dielectric Spectroscopy, DNA, DNA, Viral, DNA-Binding Proteins, Electrochemical Techniques, Ligands, Microscopy, Atomic Force, Models, Chemical, Nuclear Proteins

Malandrino, A., Noailly, J., Lacroix, D., (2014). Numerical exploration of the combined effect of nutrient supply, tissue condition and deformation in the intervertebral disc Journal of Biomechanics 47, (6), 1520-1525

Novel strategies to heal discogenic low back pain could highly benefit from comprehensive biophysical studies that consider both mechanical and biological factors involved in intervertebral disc degeneration. A decrease in nutrient availability at the bone-disc interface has been indicated as a relevant risk factor and as a possible initiator of cell death processes. Mechanical behaviour of both healthy and degenerated discs could highly interact with cell death in these compromised situations. In the present study, a mechano-transport finite element model was used to investigate the nature of mechanical effects on cell death processes via load-induced metabolic transport variations. Cycles of static sustained compression were chosen to simulate daily human activity. Healthy and degenerated cases were simulated as well as a reduced supply of solutes and an increase in solute exchange area at the bone-disc interface. Results showed that a reduction in metabolite concentrations at the bone-disc boundaries induced cell death, even when the increased exchange area was simulated. Slight local mechanical enhancements of glucose in the disc centre were capable of decelerating cell death but occurred only with healthy mechanical properties. However, mechanical deformations were responsible for a worsening in terms of cell death in the inner annulus, a disadvantaged zone far from the boundary supply with both an increased cell demand and a strain-dependent decrease of diffusivity. Such adverse mechanical effects were more accentuated when degenerative properties were simulated. Overall, this study paves the way for the use of biophysical models for a more integrated understanding of intervertebral disc pathophysiology.

Keywords: Boundary conditions, Cell nutrition, Cell viability, Computational analysis, Intervertebraldisc, Softtissuebiomechanics

Sánchez Egea, Antonio J., Valera, Marius, Parraga Quiroga, Juan Manuel, Proubasta, Ignasi, Noailly, J., Lacroix, Damien, (2014). Impact of hip anatomical variations on the cartilage stress: A finite element analysis towards the biomechanical exploration of the factors that may explain primary hip arthritis in morphologically normal subjects Clinical Biomechanics , 29, (4), 444-450

AbstractBackground Hip arthritis is a pathology linked to hip-cartilage degeneration. Although the aetiology of this disease is not well defined, it is known that age is a determinant risk factor. However, hip arthritis in young patients could be largely promoted by biomechanical factors. The objective of this paper is to analyze the impact of some normal anatomical variations on the cartilage stress distributions numerically predicted at the hip joint during walking. Methods A three-dimensional finite element model of the femur and the pelvis with the most relevant axial components of muscle forces was used to simulate normal walking activity. The hip anatomical condition was defined by: neck shaft angle, femoral anteversion angle, and acetabular anteversion angle with a range of 110-130º, 0-20º, and 0-20º, respectively. The direct boundary method was used to simulate the hip contact. Findings The hydrostatic stress found at the cartilage and labrum showed that a ± 10º variation with respect to the reference brings significant differences between the anatomic models. Acetabular anteversion angle of 0º and femoral anteversion angle of 0º were the most affected anatomical conditions with values of hydrostatic stress in the cartilage near 5 MPa under compression. Interpretation Cartilage stresses and contact areas were equivalent to the results found in literature and the most critical anatomical regions in terms of tissue loads were in a good accordance with clinical evidence. Altogether, results showed that decreasing femoral or acetabular anteversion angles isolately causes a dramatic increase in cartilage loads.

Keywords: Hip arthritis, Neck shaft angle, Femoral and acetabular anteversions, Cartilage load, Hip joint contact, Finite element analysis

Tellez, J. P., Herrera, S., Benito, S., Giraldo, B. F., (2014). Analysis of the breathing pattern in elderly patients using the hurst exponent applied to the respiratory flow signal Engineering in Medicine and Biology Society (EMBC) 36th Annual International Conference of the IEEE , IEEE (Chicago, USA) , 3422-3425

Due to the increasing elderly population and the extensive number of comorbidities that affect them, studies are required to determine future increments in admission to emergency departments. Some of these studies could focus on the relation between chronic diseases and breathing pattern in elderly patients. Variations in the fractal properties of respiratory signals can be associated with several diseases. To determine the relationship between these variations and breathing patterns, and to quantify the fractal properties of respiratory flow signals, we estimated the Hurst exponent (H). Detrended fluctuation analysis (DFA) and discrete wavelet transform-based estimation (DWTE) methods were applied. The estimation methods were analyzed using simulated data series generated by fractional Gaussian noise. 43 elderly patients (19 patients with a non-periodic breathing pattern - nPB, and 24 patients with a periodic breathing pattern - PB) were studied. The results were evaluated according to the length of data and the number of averaged data series used to obtain a good estimation. The DWTE method estimated the respiratory flow signals better than the DFA method, and obtained Hurst values clustered by group. We found significant differences in the H exponent (p = 0.002) between PB and nPB patients, which showed different behavior in the fractal properties.

Keywords: Discrete wavelet transforms, Diseases, Estimation, Fractals, Modulation, Senior citizens, Time series analysis

Chaparro, J. A., Giraldo, B. F., (2014). Power index of the inspiratory flow signal as a predictor of weaning in intensive care units Engineering in Medicine and Biology Society (EMBC) 36th Annual International Conference of the IEEE , IEEE (Chicago, USA) , 78-81

Disconnection from mechanical ventilation, called the weaning process, is an additional difficulty in the management of patients in intensive care units (ICU). Unnecessary delays in the discontinuation process and a weaning trial that is undertaken too early are undesirable. In this study, we propose an extubation index based on the power of the respiratory flow signal (Pi). A total of 132 patients on weaning trials were studied: 94 patients with successful trials (group S) and 38 patients who failed to maintain spontaneous breathing and were reconnected (group F). The respiratory flow signals were processed considering the following three stages: a) zero crossing detection of the inspiratory phase, b) inflection point detection of the flow curve during the inspiratory phase, and c) calculation of the signal power on the time instant indicated by the inflection point. The zero crossing detection was performed using an algorithm based on thresholds. The inflection points were marked considering the zero crossing of the second derivative. Finally, the inspiratory power was calculated from the energy contained over the finite time interval (between the instant of zero crossing and the inflection point). The performance of this parameter was evaluated using the following classifiers: logistic regression, linear discriminant analysis, the classification and regression tree, Naive Bayes, and the support vector machine. The best results were obtained using the Bayesian classifier, which had an accuracy, sensitivity and specificity of 87%, 90% and 81% respectively.

Keywords: Bayes methods, Bayesian classifier, Indexes, Logistics, Niobium, Regression tree analysis, Support vector machines, Ventilation

Vaca, R., Aranda, J., (2014). Triangular-fan-based algorithm for computing the closure conditions of planar linkages Advanced Numerical Methods IV 11th World Congress on Computational Mechanics (WCCM XI) 5th European Conference on Computational Mechanics (ECCM V) 6th European Conference on Computational Fluid Dynamics (ECFD VI) , CIMNE (Barcelona, Spain) , 1-2

The position analysis of a planar mechanism is based on obtaining the roots of its characteristic polynomial. In general, this polynomial is the result of a system of kinematic equations which they are derived from closure condition of the mechanism, widely known as independent kinematic loop equations or loop closure equations . This way of solving the position analysis of kinematic chains introduces complex variable eliminations, and in general trigonometric substitutions. Recently, the use of methods based on bilateration to solve the position analysis, has been shown to avoid these variable eliminations and trigonometric substitutions in planar mechanism. In this work it is shown how this method based on bilateration can be use to automatically generate closure conditions of a planar mechanism.

Keywords: Position analysis, Bilateration, Rigidity, Isomorphism, Kinematic

Giraldo, B. F., Tellez, J. P., Herrera, S., Benito, S., (2013). Analysis of heart rate variability in elderly patients with chronic heart failure during periodic breathing CinC 2013 Computing in Cardiology Conference (CinC) , IEEE (Zaragoza, Spain) , 991-994

Assessment of the dynamic interactions between cardiovascular signals can provide valuable information that improves the understanding of cardiovascular control. Heart rate variability (HRV) analysis is known to provide information about the autonomic heart rate modulation mechanism. Using the HRV signal, we aimed to obtain parameters for classifying patients with and without chronic heart failure (CHF), and with periodic breathing (PB), non-periodic breathing (nPB), and Cheyne-Stokes respiration (CSR) patterns. An electrocardiogram (ECG) and a respiratory flow signal were recorded in 36 elderly patients: 18 patients with CHF and 18 patients without CHF. According to the clinical criteria, the patients were classified into the follow groups: 19 patients with nPB pattern, 7 with PB pattern, 4 with Cheyne-Stokes respiration (CSR), and 6 non-classified patients (problems with respiratory signal). From the HRV signal, parameters in the time and frequency domain were calculated. Frequency domain parameters were the most discriminant in comparisons of patients with and without CHF: PTot (p = 0.02), PLF (p = 0.022) and fpHF (p = 0.021). For the comparison of the nPB vs. CSR patients groups, the best parameters were RMSSD (p = 0.028) and SDSD (p = 0.028). Therefore, the parameters appear to be suitable for enhanced diagnosis of decompensated CHF patients and the possibility of developed periodic breathing and a CSR pattern.

Keywords: cardiovascular system, diseases, electrocardiography, frequency-domain analysis, geriatrics, medical signal processing, patient diagnosis, pneumodynamics, signal classification, Cheyne-Stokes respiration patterns, ECG, autonomic heart rate modulation mechanism, cardiovascular control, cardiovascular signals, chronic heart failure, decompensated CHF patients, dynamic interaction assessment, elderly patients, electrocardiogram, enhanced diagnosis, frequency domain parameters, heart rate variability analysis, patient classification, periodic breathing, respiratory flow signal recording, Electrocardiography, Frequency modulation, Frequency-domain analysis, Heart rate variability, Senior citizens, Standards

Arcentales, A., Voss, A., Caminal, P., Bayes-Genis, A., Domingo, M. T., Giraldo, B. F., (2013). Characterization of patients with different ventricular ejection fractions using blood pressure signal analysis CinC 2013 Computing in Cardiology Conference (CinC) , IEEE (Zaragoza, Spain) , 795-798

Ischemic and dilated cardiomyopathy are associated with disorders of myocardium. Using the blood pressure (BP) signal and the values of the ventricular ejection fraction, we obtained parameters for stratifying cardiomyopathy patients as low- and high-risk. We studied 48 cardiomyopathy patients characterized by NYHA ≥2: 19 patients with dilated cardiomyopathy (DCM) and 29 patients with ischemic cardiomyopathy (ICM). The left ventricular ejection fraction (LVEF) percentage was used to classify patients in low risk (LR: LVEF > 35%, 17 patients) and high risk (HR: LVEF ≤ 35%, 31 patients) groups. From the BP signal, we extracted the upward systolic slope (BPsl), the difference between systolic and diastolic BP (BPA), and systolic time intervals (STI). When we compared the LR and HR groups in the time domain analysis, the best parameters were standard deviation (SD) of 1=STI, kurtosis (K) of BPsl, and K of BPA. In the frequency domain analysis, very low frequency (VLF) and high frequency (HF) bands showed statistically significant differences in comaprisons of LR and HR groups. The area under the curve of power spectral density was the best parameter in all classifications, and particularly in the very-low-and high- frequency bands (p <; 0.001). These parameters could help to improve the risk stratification of cardiomyopathy patients.

Keywords: blood pressure measurement, cardiovascular system, diseases, medical disorders, medical signal processing, statistical analysis, time-domain analysis, BP signal, HR groups, LR groups, blood pressure signal analysis, cardiomyopathy patients, diastolic BP, dilated cardiomyopathy, frequency domain analysis, high-frequency bands, ischemic cardiomyopathy, left ventricular ejection fraction, low-frequency bands, myocardium disorders, patient characterization, power spectral density curve, standard deviation, statistical significant differences, systolic BP, systolic slope, systolic time intervals, time domain analysis, ventricular ejection fraction, Abstracts, Databases, Parameter extraction, Telecommunication standards, Time-frequency analysis

Giraldo, B. F., Chaparro, J. A., Caminal, P., Benito, S., (2013). Characterization of the respiratory pattern variability of patients with different pressure support levels Engineering in Medicine and Biology Society (EMBC) 35th Annual International Conference of the IEEE , IEEE (Osaka, Japan) , 3849-3852

One of the most challenging problems in intensive care is still the process of discontinuing mechanical ventilation, called weaning process. Both an unnecessary delay in the discontinuation process and a weaning trial that is undertaken too early are undesirable. In this study, we analyzed respiratory pattern variability using the respiratory volume signal of patients submitted to two different levels of pressure support ventilation (PSV), prior to withdrawal of the mechanical ventilation. In order to characterize the respiratory pattern, we analyzed the following time series: inspiratory time, expiratory time, breath duration, tidal volume, fractional inspiratory time, mean inspiratory flow and rapid shallow breathing. Several autoregressive modeling techniques were considered: autoregressive models (AR), autoregressive moving average models (ARMA), and autoregressive models with exogenous input (ARX). The following classification methods were used: logistic regression (LR), linear discriminant analysis (LDA) and support vector machines (SVM). 20 patients on weaning trials from mechanical ventilation were analyzed. The patients, submitted to two different levels of PSV, were classified as low PSV and high PSV. The variability of the respiratory patterns of these patients were analyzed. The most relevant parameters were extracted using the classifiers methods. The best results were obtained with the interquartile range and the final prediction errors of AR, ARMA and ARX models. An accuracy of 95% (93% sensitivity and 90% specificity) was obtained when the interquartile range of the expiratory time and the breath duration time series were used a LDA model. All classifiers showed a good compromise between sensitivity and specificity.

Keywords: autoregressive moving average processes, feature extraction, medical signal processing, patient care, pneumodynamics, signal classification, support vector machines, time series, ARX, autoregressive modeling techniques, autoregressive models with exogenous input, autoregressive moving average model, breath duration time series, classification method, classifier method, discontinuing mechanical ventilation, expiratory time, feature extraction, final prediction errors, fractional inspiratory time, intensive care, interquartile range, linear discriminant analysis, logistic regression analysis, mean inspiratory flow, patient respiratory volume signal, pressure support level, pressure support ventilation, rapid shallow breathing, respiratory pattern variability characterization, support vector machines, tidal volume, weaning trial, Analytical models, Autoregressive processes, Biological system modeling, Estimation, Support vector machines, Time series analysis, Ventilation

Hernando, D., Alcaine, A., Pueyo, E., Laguna, P., Orini, M., Arcentales, A., Giraldo, B., Voss, A., Bayes-Genis, A., Bailon, R., (2013). Influence of respiration in the very low frequency modulation of QRS slopes and heart rate variability in cardiomyopathy patients CinC 2013 Computing in Cardiology Conference (CinC) , IEEE (Zaragoza, Spain) , 117-120

This work investigates the very low frequency (VLF) modulation of QRS slopes and heart rate variability (HRV). Electrocardiogram (ECG) and respiratory flow signal were acquired from patients with dilated cardiomyopathy and ischemic cardiomyopathy. HRV as well as the upward QRS slope (IUS) and downward QRS slope (IDS) were extracted from the ECG. The relation between HRV and QRS slopes in the VLF band was measured using ordinary coherence in 5-minute segments. Partial coherence was then used to remove the influence that respiration simultaneously exerts on HRV and QRS slopes. A statistical threshold was determined, below which coherence values were considered not to represent a linear relation. 7 out of 276 segments belonging to 5 out of 29 patients for IUS and 10 segments belonging to 5 patients for IDS presented a VLF modulation in QRS slopes, HRV and respiration. In these segments spectral coherence was statistically significant, while partial coherence decreased, indicating that the coupling HRV and QRS slopes was related to respiration. 4 segments had a partial coherence value below the threshold for IUS, 3 segments for IDS. The rest of the segments also presented a notable decrease in partial coherence, but still above the threshold, which means that other non-linearly effects may also affect this modulation.

Keywords: diseases, electrocardiography, feature extraction, medical signal processing, pneumodynamics, statistical analysis, ECG, QRS slopes, cardiomyopathy patients, dilated cardiomyopathy, electrocardiogram, feature extraction, heart rate variability, ischemic cardiomyopathy, ordinary coherence, partial coherence value, respiration, respiratory flow signal acquisition, spectral coherence, statistical threshold, time 5 min, very low frequency modulation, Coherence, Educational institutions, Electrocardiography, Frequency modulation, Heart rate variability

Giraldo, B. F., Tellez, J. P., Herrera, S., Benito, S., (2013). Study of the oscillatory breathing pattern in elderly patients Engineering in Medicine and Biology Society (EMBC) 35th Annual International Conference of the IEEE , IEEE (Osaka, Japan) , 5228-5231

Some of the most common clinical problems in elderly patients are related to diseases of the cardiac and respiratory systems. Elderly patients often have altered breathing patterns, such as periodic breathing (PB) and Cheyne-Stokes respiration (CSR), which may coincide with chronic heart failure. In this study, we used the envelope of the respiratory flow signal to characterize respiratory patterns in elderly patients. To study different breathing patterns in the same patient, the signals were segmented into windows of 5 min. In oscillatory breathing patterns, frequency and time-frequency parameters that characterize the discriminant band were evaluated to identify periodic and non-periodic breathing (PB and nPB). In order to evaluate the accuracy of this characterization, we used a feature selection process, followed by linear discriminant analysis. 22 elderly patients (7 patients with PB and 15 with nPB pattern) were studied. The following classification problems were analyzed: patients with either PB (with and without apnea) or nPB patterns, and patients with CSR versus PB, CSR versus nPB and PB versus nPB patterns. The results showed 81.8% accuracy in the comparisons of nPB and PB patients, using the power of the modulation peak. For the segmented signal, the power of the modulation peak, the frequency variability and the interquartile ranges provided the best results with 84.8% accuracy, for classifying nPB and PB patients.

Keywords: cardiovascular system, diseases, feature extraction, geriatrics, medical signal processing, oscillations, pneumodynamics, signal classification, time-frequency analysis, Cheyne-Stokes respiration, apnea, cardiac systems, chronic heart failure, classification problems, discriminant band, diseases, elderly patients, feature selection process, frequency variability, interquartile ranges, linear discriminant analysis, nonperiodic breathing, oscillatory breathing pattern, periodic breathing, respiratory How signal, respiratory systems, signal segmentation, time 5 min, time-frequency parameters, Accuracy, Aging, Frequency modulation, Heart, Senior citizens, Time-frequency analysis

Juanola-Feliu, E., Colomer-Farrarons, J., Miribel-Català , P., Samitier, J., Valls-Pasola, J., (2012). Market challenges facing academic research in commercializing nano-enabled implantable devices for in-vivo biomedical analysis Technovation , 32, (3-4), 193-204

This article reports on the research and development of a cutting-edge biomedical device for continuous in-vivo glucose monitoring. This entirely public-funded process of technological innovation has been conducted at the University of Barcelona within a context of converging technologies involving the fields of medicine, physics, chemistry, biology, telecommunications, electronics and energy. The authors examine the value chain and the market challenges faced by in-vivo implantable biomedical devices based on nanotechnologies. In so doing, they trace the process from the point of applied research to the final integration and commercialization of the product, when the social rate of return from academic research can be estimated. Using a case-study approach, the paper also examines the high-tech activities involved in the development of this nano-enabled device and describes the technology and innovation management process within the value chain conducted in a University-Hospital-Industry-Administration-Citizens framework. Here, nanotechnology is seen to represent a new industrial revolution, boosting the biomedical devices market. Nanosensors may well provide the tools required for investigating biological processes at the cellular level in vivo when embedded into medical devices of small dimensions, using biocompatible materials, and requiring reliable and targeted biosensors, high speed data transfer, safely stored data, and even energy autonomy.

Keywords: Biomedical device, Diabetes, Innovation management, Nanobiosensor, Nanotechnology, Research commercialization, Technology transfer, Academic research, Applied research, Barcelona, Biocompatible materials, Biological process, Biomedical analysis, Biomedical devices, Cellular levels, Converging technologies, Glucose monitoring, High-speed data transfer, Implantable biomedical devices, Implantable devices, In-vivo, Industrial revolutions, Innovation management, Medical Devices, Nanobiosensor, Rate of return, Research and development, Technological innovation, Value chains, Biological materials, Biomedical engineering, Biosensors, Commerce, Data transfer, Earnings, Engineering education, Glucose, Implants (surgical), Industrial research, Innovation, Medical problems, Nanosensors, Nanotechnology, Technology transfer, Equipment

Antelis, J.M., Montesano, L., Giralt, X., Casals, A., Minguez, J., (2012). Detection of movements with attention or distraction to the motor task during robot-assisted passive movements of the upper limb Engineering in Medicine and Biology Society (EMBC) 34th Annual International Conference of the IEEE , IEEE (San Diego, USA) , 6410-6413

Robot-assisted rehabilitation therapies usually focus on physical aspects rather than on cognitive factors. However, cognitive aspects such as attention, motivation, and engagement play a critical role in motor learning and thus influence the long-term success of rehabilitation programs. This paper studies motor-related EEG activity during the execution of robot-assisted passive movements of the upper limb, while participants either: i) focused attention exclusively on the task; or ii) simultaneously performed another task. Six healthy subjects participated in the study and results showed lower desynchronization during passive movements with another task simultaneously being carried out (compared to passive movements with exclusive attention on the task). In addition, it was proved the feasibility to distinguish between the two conditions.

Keywords: Electrodes, Electroencephalography, Induction motors, Medical treatment, Robot sensing systems, Time frequency analysis, Biomechanics, Cognition, Electroencephalography, Medical robotics, Medical signal detection, Medical signal processing, Patient rehabilitation, Attention, Cognitive aspects, Desynchronization, Engagement, Motivation, Motor learning, Motor task, Motor-related EEG activity, Physical aspects, Robot-assisted passive movement detection, Robot-assisted rehabilitation therapies, Upper limb

Chaparro, J.A., Giraldo, B.F., Caminal, P., Benito, S., (2012). Performance of respiratory pattern parameters in classifiers for predict weaning process Engineering in Medicine and Biology Society (EMBC) 34th Annual International Conference of the IEEE , IEEE (San Diego, USA) , 4349-4352

Weaning trials process of patients in intensive care units is a complex clinical procedure. 153 patients under extubation process (T-tube test) were studied: 94 patients with successful trials (group S), 38 patients who failed to maintain spontaneous breathing and were reconnected (group F), and 21 patients with successful test but that had to be reintubated before 48 hours (group R). The respiratory pattern of each patient was characterized through the following time series: inspiratory time (TI), expiratory time (TE), breathing cycle duration (TTot), tidal volume (VT), inspiratory fraction (TI/TTot), half inspired flow (VT/TI), and rapid shallow index (f/VT), where f is respiratory rate. Using techniques as autoregressive models (AR), autoregressive moving average models (ARMA) and autoregressive models with exogenous input (ARX), the most relevant parameters of the respiratory pattern were obtained. We proposed the evaluation of these parameters using classifiers as logistic regression (LR), linear discriminant analysis (LDA), support vector machines (SVM) and classification and regression tree (CART) to discriminate between patients from groups S, F and R. An accuracy of 93% (98% sensitivity and 82% specificity) has been obtained using CART classification.

Keywords: Accuracy, Indexes, Logistics, Regression tree analysis, Support vector machines, Time series analysis, Autoregressive moving average processes, Medical signal processing, Pattern classification, Pneumodynamics, Regression analysis, Sensitivity, Signal classification, Support vector machines, Time series, SVM, T-tube testing, Autoregressive models-with-exogenous input, Autoregressive moving average models, Breathing cycle duration, Classification-and-regression tree, Expiratory time, Extubation process, Half inspired flow, Inspiratory fraction, Inspiratory time, Intensive care units, Linear discriminant analysis, Logistic regression, Rapid shallow index, Respiratory pattern parameter performance, Sensitivity, Spontaneous breathing, Support vector machines, Tidal volume, Time 48 hr, Time series, Weaning process classifiers

Garde, A., Giraldo, B.F., Jané, R., Latshang, T.D., Turk, A.J., Hess, T., Bosch, M-.M., Barthelmes, D., Hefti, J.P., Maggiorini, M., Hefti, U., Merz, T.M., Schoch, O.D., Bloch, K.E., (2012). Periodic breathing during ascent to extreme altitude quantified by spectral analysis of the respiratory volume signal Engineering in Medicine and Biology Society (EMBC) 34th Annual International Conference of the IEEE , IEEE (San Diego, USA) , 707-710

High altitude periodic breathing (PB) shares some common pathophysiologic aspects with sleep apnea, Cheyne-Stokes respiration and PB in heart failure patients. Methods that allow quantifying instabilities of respiratory control provide valuable insights in physiologic mechanisms and help to identify therapeutic targets. Under the hypothesis that high altitude PB appears even during physical activity and can be identified in comparison to visual analysis in conditions of low SNR, this study aims to identify PB by characterizing the respiratory pattern through the respiratory volume signal. A number of spectral parameters are extracted from the power spectral density (PSD) of the volume signal, derived from respiratory inductive plethysmography and evaluated through a linear discriminant analysis. A dataset of 34 healthy mountaineers ascending to Mt. Muztagh Ata, China (7,546 m) visually labeled as PB and non periodic breathing (nPB) is analyzed. All climbing periods within all the ascents are considered (total climbing periods: 371 nPB and 40 PB). The best crossvalidated result classifying PB and nPB is obtained with Pm (power of the modulation frequency band) and R (ratio between modulation and respiration power) with an accuracy of 80.3% and area under the receiver operating characteristic curve of 84.5%. Comparing the subjects from 1st and 2nd ascents (at the same altitudes but the latter more acclimatized) the effect of acclimatization is evaluated. SaO2 and periodic breathing cycles significantly increased with acclimatization (p-value <; 0.05). Higher Pm and higher respiratory frequencies are observed at lower SaO2, through a significant negative correlation (p-value <; 0.01). Higher Pm is observed at climbing periods visually labeled as PB with >; 5 periodic breathing cycles through a significant positive correlation (p-value <; 0.01). Our data demonstrate that quantification of the respiratory volum- signal using spectral analysis is suitable to identify effects of hypobaric hypoxia on control of breathing.

Keywords: Frequency domain analysis, Frequency modulation, Heart, Sleep apnea, Ventilation, Visualization, Cardiology, Medical disorders, Medical signal processing, Plethysmography, Pneumodynamics, Sensitivity analysis, Sleep, Spectral analysis, Cheyne-Stokes respiration, Climbing periods, Dataset, Heart failure patients, High altitude PB, High altitude periodic breathing, Hypobaric hypoxia, Linear discriminant analysis, Pathophysiologic aspects, Physical activity, Physiologic mechanisms, Power spectral density, Receiver operating characteristic curve, Respiratory control, Respiratory frequency, Respiratory inductive plethysmography, Respiratory pattern, Respiratory volume signal, Sleep apnea, Spectral analysis, Spectral parameters

Melchels, Ferry P. W., Tonnarelli, Beatrice, Olivares, Andy L., Martin, Ivan, Lacroix, Damien, Feijen, Jan, Wendt, David J., Grijpma, Dirk W., (2011). The influence of the scaffold design on the distribution of adhering cells after perfusion cell seeding Biomaterials 32, (11), 2878-2884

In natural tissues, the extracellular matrix composition, cell density and physiological properties are often non-homogeneous. Here we describe a model system, in which the distribution of cells throughout tissue engineering scaffolds after perfusion seeding can be influenced by the pore architecture of the scaffold. Two scaffold types, both with gyroid pore architectures, were designed and built by stereolithography: one with isotropic pore size (412 ± 13 [mu]m) and porosity (62 ± 1%), and another with a gradient in pore size (250-500 [mu]m) and porosity (35%-85%). Computational fluid flow modelling showed a uniform distribution of flow velocities and wall shear rates (15-24 s-1) for the isotropic architecture, and a gradient in the distribution of flow velocities and wall shear rates (12-38 s-1) for the other architecture. The distribution of cells throughout perfusion-seeded scaffolds was visualised by confocal microscopy. The highest densities of cells correlated with regions of the scaffolds where the pores were larger, and the fluid velocities and wall shear rates were the highest. Under the applied perfusion conditions, cell deposition is mainly determined by local wall shear stress, which, in turn, is strongly influenced by the architecture of the pore network of the scaffold.

Keywords: Scaffolds, Microstructure, Cell adhesion, Confocal microscopy, Image analysis, Computational fluid dynamics

Garrido-Delgado, R., Arce, L., Guaman, A. V., Pardo, A., Marco, S., Valcárcel, M., (2011). Direct coupling of a gas-liquid separator to an Ion Mobility Spectrometer for the classification of different white wines using chemometrics tools Talanta 84, (2), 471-479

The potential of a vanguard technique as is the Ion Mobility Spectrometry with Ultraviolet ionization (UV-IMS) coupled to a Continuous Flow System (CFS) have been demonstrated in this work by using a Gas Phase Separator (GPS). This vanguard system (CFS-GPS-UV-IMS) has been used for the analysis of different types of white wines to obtain a characteristic profile for each type of wine and their posterior classification using different chemometric tools. Precision of the method was 3.1% expressed as relative standard deviation. A deep chemometric study was carried out for the classification of the four types of wines selected. The best classification performance was obtained by first reducing the data dimensionality by Principal Component Analysis (PCA) followed by Linear Discriminant Analysis (LDA) and finally using a K-Nearest Neighbour (kNN) classifier. The classification rate in an independent validation set were 92.0% classification rate value with confidence interval [89.0%, 95.0%] at P = 0.05 confidence level. The same white wines analyzed by using CFS-GPS-UV-IMS were analyzed by using Gas Chromatography with a Flame Detector (GC-FID) as conventional technique. The chromatographic method used for the determination of superior alcohols in wine samples shown in the Regulation CEE 1238/1992 was selected to carry out the analysis of the same samples set and later the classification using appropriate chemometric tools. In this case, strategies PCA-LDA and kNN classifier were also used for the correct classification of the wine samples. This combination showed similar results to the ones obtained with the proposed method.

Keywords: Classification, White wines, Ultraviolet-Ion Mobility Spectrometry, Gas Phase Separate, Vanguard method, Continuous Flow System, Chemometric analysis.

Mir, Monica, Martinez-Rodriguez, Sergio, Castillo-Fernandez, Oscar, Homs-Corbera, Antoni, Samitier, Josep, (2011). Electrokinetic techniques applied to electrochemical DNA biosensors Electrophoresis , 32, (8), 811-821

Electrokinetic techniques are contact-free methods currently used in many applications, where precise handling of biological entities, such as cells, bacteria or nucleic acids, is needed. These techniques are based on the effect of electric fields on molecules suspended in a fluid, and the corresponding induced motion, which can be tuned according to some known physical laws and observed behaviours. Increasing interest on the application of such strategies in order to improve the detection of DNA strands has appeared during the recent decades. Classical electrode-based DNA electrochemical biosensors with combined electrokinetic techniques present the advantage of being able to improve the working electrode's bioactive part during their fabrication and also the hybridization yield during the sensor detection phase. This can be achieved by selectively manipulating, driving and directing the molecules towards the electrodes increasing the speed and yield of the floating DNA strands attached to them. On the other hand, this technique can be also used in order to make biosensors reusable, or reconfigurable, by simply inverting its working principle and pulling DNA strands away from the electrodes. Finally, the combination of these techniques with nanostructures, such as nanopores or nanochannels, has recently boosted the appearance of new types of electrochemical sensors that exploit the time-varying position of DNA strands in order to continuously scan these molecules and to detect their properties. This review gives an insight into the main forces involved in DNA electrokinetics and discusses the state of the art and uses of these techniques in recent years.

Keywords: Electrochemical DNA biosensors, Lab-on-a-chip (LOC), Micro-total analysis systems (mu TAS), Nanopore

Byrne, Damien P., Lacroix, Damien, Prendergast, Patrick J., (2011). Simulation of fracture healing in the tibia: Mechanoregulation of cell activity using a lattice modeling approach Journal of Orthopaedic Research , 29, (10), 1496-1503

In this study, a three-dimensional (3D) computational simulation of bone regeneration was performed in a human tibia under realistic muscle loading. The simulation was achieved using a discrete lattice modeling approach combined with a mechanoregulation algorithm to describe the cellular processes involved in the healing process namely proliferation, migration, apoptosis, and differentiation of cells. The main phases of fracture healing were predicted by the simulation, including the bone resorption phase, and there was a qualitative agreement between the temporal changes in interfragmentary strain and bending stiffness by comparison to experimental data and clinical results. Bone healing was simulated beyond the reparative phase by modeling the transition of woven bone into lamellar bone. Because the simulation has been shown to work with realistic anatomical 3D geometry and muscle loading, it demonstrates the potential of simulation tools for patient-specific pre-operative treatment planning.

Keywords: Tissue differentiation, Computational analysis, Mechanical conditions, Bone regeneration, Weight-bearing, Proliferation, Osteoblast, Stiffness, Ingrowth, Scaffold

Barthelmebs, L., Jonca, J., Hayat, A., Prieto-Simon, B., Marty, J. L., (2011). Enzyme-Linked Aptamer Assays (ELAAs), based on a competition format for a rapid and sensitive detection of Ochratoxin A in wine Food Control , 22, (5), 737-743

Ochratoxin A (OTA) is one of the most important mycotoxins because of its high toxicity to both humans and animals and its occurrence in a number of basic foods and agro-products. The need to develop high-performing methods for OTA analysis able to improve the traditional ones is evident. In this work, through in vitro SELEX (Systematic Evolution of Ligands by EXponential enrichment) two aptamers, designated H8 and H12 were produced that bind with nanomolar affinity with Ochratoxin A (OTA). Two strategies were investigated by using an indirect and a direct competitive Enzyme-Linked Aptamer Assay (ELAA) and were compared to the classical competitive Enzyme-Linked Immunosorbent Assay (ELISA) for the determination of OTA in spiked red wine samples. The limit of detection attained (1 ng/mL), the midpoint value obtained (5 ng/mL) and the analysis time needed (125 min) for the real sample analysis validate the direct competitive ELAA as useful screening tool for routine use in the control of OTA level in wine.

Keywords: Competitive Enzyme-Linked Aptamer Assay (ELAA), DNA aptamer, Ochratoxin A, SELEX, Wine analysis

Ziyatdinov, Andrey, Fernandez-Diaz, Eduard, Chaudry, A., Marco, Santiago, Persaud, Krishna, Perera, Alexandre, (2011). A large scale virtual gas sensor array Olfaction and Electronic Nose: Proceedings of the 14th International Symposium on Olfaction and Electronic Nose AIP Conference Proceedings (ed. Perena Gouma, SUNY Stony Brook), AIP (New York City, USA) 1362, (1), 151-152

This paper depicts a virtual sensor array that allows the user to generate gas sensor synthetic data while controlling a wide variety of the characteristics of the sensor array response: arbitrary number of sensors, support for multi-component gas mixtures and full control of the noise in the system such as sensor drift or sensor aging. The artificial sensor array response is inspired on the response of 17 polymeric sensors for three analytes during 7 month. The main trends in the synthetic gas sensor array, such as sensitivity, diversity, drift and sensor noise, are user controlled. Sensor sensitivity is modeled by an optionally linear or nonlinear method (spline based). The toolbox on data generation is implemented in open source R language for statistical computing and can be freely accessed as an educational resource or benchmarking reference. The software package permits the design of scenarios with a very large number of sensors (over 10000 sensels), which are employed in the test and benchmarking of neuromorphic models in the Bio-ICT European project NEUROCHEM.

Keywords: Data analysis, Circuit noise, Data acquisition, Signal processing

Fumagalli, L., Gramse, G., Esteban-Ferrer, D., Edwards, M. A., Gomila, G., (2010). Quantifying the dielectric constant of thick insulators using electrostatic force microscopy Applied Physics Letters , 96, (18), 183107

Quantitative measurement of the low-frequency dielectric constants of thick insulators at the nanoscale is demonstrated utilizing ac electrostatic force microscopy combined with finite-element calculations based on a truncated cone with hemispherical apex probe geometry. The method is validated on muscovite mica, borosilicate glass, poly(ethylene naphthalate), and poly(methyl methacrylate). The dielectric constants obtained are essentially given by a nanometric volume located at the dielectric-air interface below the tip, independently of the substrate thickness, provided this is on the hundred micrometer-length scale, or larger.

Keywords: Borosilicate glasses, Finite element analysis, Insulating thin films, Mica, Nanostructured materials, Permittivity, Polymers, Scanning probe microscopy

Iranzo, A., Isetta, V., Molinuevo, J. L., Serradell, M., Navajas, D., Farre, R., Santamaria, J., (2010). Electroencephalographic slowing heralds mild cognitive impairment in idiopathic REM sleep behavior disorder Sleep Medicine , 11, (6), 534-539

Objective: Patients with idiopathic rapid eye movement (REM) sleep behavior disorder (IRBD) may show electroencephalographic (EEG) slowing reflecting cortical dysfunction and are at risk for developing neurological conditions characterized by cognitive dysfunction including mild cognitive impairment (MCI), dementia with Lewy bodies and Parkinson's disease with associated dementia. We hypothesized that those IRBD patients who later developed MCI had pronounced cortical EEG slowing at presentation. Methods: Power EEG spectral analysis was blindly quantified from the polysomnographic studies of 23 IRBD patients without cognitive complaints and 10 healthy controls without RBD. After a mean clinical follow-up of 2.40 +/- 1.55 years, 10 patients developed MCI (RBD + MCI) and the remaining 13 remained idiopathic. Results: Patients with RBD + MCI had marked EEG slowing (increased delta and theta activity) in central and occipital regions during wakefulness and REM sleep, particularly in the right hemisphere, when compared with controls and, to a lesser extent, with IRBD subjects who remained idiopathic. The EEG spectral pattern of the RBD + MCI group was similar to that seen in patients with dementia with Lewy bodies and Parkinson's disease associated with dementia. Conclusion: Our findings suggest that the presence of marked EEG slowing on spectral analysis might be indicative of the short-term development of MCI in patients initially diagnosed with IRBD.

Keywords: Idiopathic REM sleep behavior disorder, Power EEG spectral analysis, Mild cognitive impairment, REM sleep, Parkinson's disease, Dementia with Lewy bodies

Ziyatdinov, A., Marco, S., Chaudry, A., Persaud, K., Caminal, P., Perera, A., (2010). Drift compensation of gas sensor array data by common principal component analysis Sensors and Actuators B: Chemical 146, (2), 460-465

A new drift compensation method based on Common Principal Component Analysis (CPCA) is proposed. The drift variance in data is found as the principal components computed by CPCA. This method finds components that are common for all gasses in feature space. The method is compared in classification task with respect to the other approaches published where the drift direction is estimated through a Principal Component Analysis (PCA) of a reference gas. The proposed new method - employing no specific reference gas, but information from all gases -has shown the same performance as the traditional approach with the best-fitted reference gas. Results are shown with data lasting 7-months including three gases at different concentrations for an array of 17 polymeric sensors.

Keywords: Gas sensor array, Drift, Common principal component, Analysis, Component correction, Electronic nose

Milan, J. L., Planell, J. A., Lacroix, D., (2010). Simulation of bone tissue formation within a porous scaffold under dynamic compression Biomechanics and Modeling in Mechanobiology 9, (5), 583-596

A computational model of mechanoregulation is proposed to predict bone tissue formation stimulated mechanically by overall dynamical compression within a porous polymeric scaffold rendered by micro-CT. Dynamic compressions of 0.5-5% at 0.0025-0.025 s(-1) were simulated. A force-controlled dynamic compression was also performed by imposing a ramp of force from 1 to 70 N. The model predicts homogeneous mature bone tissue formation under strain levels of 0.5-1% at strain rates of 0.0025-0.005 s(-1). Under higher levels of strain and strain rates, the scaffold shows heterogeneous mechanical behaviour which leads to the formation of a heterogeneous tissue with a mixture of mature bone and fibrous tissue. A fibrous tissue layer was also predicted under the force-controlled dynamic compression, although the same force magnitude was found promoting only mature bone during a strain-controlled compression. The model shows that the mechanical stimulation of bone tissue formation within a porous scaffold closely depends on the loading history and on the mechanical behaviour of the scaffold at local and global scales.

Keywords: Bone tissue engineering, Scaffold, Tissue differentiation, Mechanoregulation, Finite element analysis

Caminal, P., Giraldo, B. F., Vallverdu, M., Benito, S., Schroeder, R., Voss, A., (2010). Symbolic dynamic analysis of relations between cardiac and breathing cycles in patients on weaning trials Annals of Biomedical Engineering , 38, (8), 2542-52

Traditional time-domain techniques of data analysis are often not sufficient to characterize the complex dynamics of the cardiorespiratory interdependencies during the weaning trials. In this paper, the interactions between the heart rate (HR) and the breathing rate (BR) were studied using joint symbolic dynamic analysis. A total of 133 patients on weaning trials from mechanical ventilation were analyzed: 94 patients with successful weaning (group S) and 39 patients that failed to maintain spontaneous breathing (group F). The word distribution matrix enabled a coarse-grained quantitative assessment of short-term nonlinear analysis of the cardiorespiratory interactions. The histogram of the occurrence probability of the cardiorespiratory words presented a higher homogeneity in group F than in group S, measured with a higher number of forbidden words in group S as well as a higher number of words whose probability of occurrence is higher than a probability threshold in group S. The discriminant analysis revealed the best results when applying symbolic dynamic variables. Therefore, we hypothesize that joint symbolic dynamic analysis provides enhanced information about different interactions between HR and BR, when comparing patients with successful weaning and patients that failed to maintain spontaneous breathing in the weaning procedure.

Keywords: Dynamical nonlinearities analysis, Cardiorespiratory interdependencies, Joint symbolic dynamic, Weaning procedure

Salleras, M., Carmona, M., Marco, S., (2010). Issues in the use of thermal transients to achieve accurate time-constant spectrums and differential structure functions IEEE Transactions on Advanced Packaging , 33, (4), 918-923

An analysis of accuracy of time-constant spectrum extraction from thermal transients has been performed. Numerical calculations based on analytical models and finite element method simulations have been used in order to obtain the thermal transients. Simple geometries have been used such that analytical expressions for their time-constant spectrums are known. Results show that a large error in the time-constant spectrum is obtained for very small rms error ( 1 mK) in the thermal transient. The estimation problem is ill-conditioned. Moreover, the differential structure function shows a low accuracy identifying stacked structures. The initial part of the differential structure function shows numerical oscillations and the final part has an asymptotic behavior to infinity that has been identified as an artifact related to errors in the time-constant spectrum estimation. Peak identification from the differential structure function heavily depends on an accurate determination of the time-constant spectrum. The limited spectral resolution and dynamic range of the differential structure function are a direct consequence of the time-constant spectrum imprecision.

Keywords: Finite element analysis, Spectral analysis

Morgenstern, C., Schwaibold, M., Randerath, W., Bolz, A., Jané, R., (2010). Automatic non-invasive differentiation of obstructive and central hypopneas with nasal airflow compared to esophageal pressure Engineering in Medicine and Biology Society (EMBC) 32nd Annual International Conference of the IEEE , IEEE (Buenos Aires, Argentina) , 6142-6145

The differentiation of obstructive and central respiratory events is a major challenge in the diagnosis of sleep disordered breathing. Esophageal pressure (Pes) measurement is the gold-standard method to identify these events but its invasiveness deters its usage in clinical routine. Flattening patterns appear in the airflow signal during episodes of inspiratory flow limitation (IFL) and have been shown with invasive techniques to be useful to differentiate between central and obstructive hypopneas. In this study we present a new method for the automatic non-invasive differentiation of obstructive and central hypopneas solely with nasal airflow. An overall of 36 patients underwent full night polysomnography with systematic Pes recording and a total of 1069 hypopneas were manually scored by human experts to create a gold-standard annotation set. Features were automatically extracted from the nasal airflow signal to train and test our automatic classifier (Discriminant Analysis). Flattening patterns were non-invasively assessed in the airflow signal using spectral and time analysis. The automatic non-invasive classifier obtained a sensitivity of 0.71 and an accuracy of 0.69, similar to the results obtained with a manual non-invasive classification algorithm. Hence, flattening airflow patterns seem promising for the non-invasive differentiation of obstructive and central hypopneas.

Keywords: Practical, Experimental/ biomedical measurement, Feature extraction, Flow measurement, Medical disorders, Medical signal processing, Patient diagnosis, Pneumodynamics, Pressure measurement, Signal classification, Sleep, Spectral analysis/ automatic noninvasive differentiation, Obstructive hypopnea, Central hypopnea, Inspiratory flow limitation, Nasal airflow, Esophageal pressure, Polysomnography, Feature extraction, Discriminant analysis, Spectral analysis

Garde, A., Sörnmo, L., Jané, R., Giraldo, B. F., (2010). Correntropy-based nonlinearity test applied to patients with chronic heart failure Engineering in Medicine and Biology Society (EMBC) 32nd Annual International Conference of the IEEE , IEEE (Buenos Aires, Argentina) , 2399-2402

In this study we propose the correntropy function as a discriminative measure for detecting nonlinearities in the respiratory pattern of chronic heart failure (CHF) patients with periodic or nonperiodic breathing pattern (PB or nPB, respectively). The complexity seems to be reduced in CHF patients with higher risk level. Correntropy reflects information on both, statistical distribution and temporal structure of the underlying dataset. It is a suitable measure due to its capability to preserve nonlinear information. The null hypothesis considered is that the analyzed data is generated by a Gaussian linear stochastic process. Correntropy is used in a statistical test to reject the null hypothesis through surrogate data methods. Various parameters, derived from the correntropy and correntropy spectral density (CSD) to characterize the respiratory pattern, presented no significant differences when extracted from the iteratively refined amplitude adjusted Fourier transform (IAAFT) surrogate data. The ratio between the powers in the modulation and respiratory frequency bands R was significantly different in nPB patients, but not in PB patients, which reflects a higher presence of nonlinearities in nPB patients than in PB patients.

Keywords: Practical, Theoretical or Mathematical, Experimental/cardiology diseases, Fourier transforms, Medical signal processing, Pattern classification, Pneumodynamics, Spectral analysis, Statistical analysis, Stochastic processes/ correntropy based nonlinearity test, Chronic heart failure, Correntropy function, Respiratory pattern nonlinearities, CHF patients, Nonperiodic breathing pattern, Dataset statistical distribution, Dataset temporal structure, Nonlinear information, Null hypothesis, Gaussian linear stochastic process, Statistical test, Correntropy spectral density, Iteratively refined amplitude adjusted Fourier transform, Surrogate data, Periodic breathing pattern

Padilla, M., Perera, A., Montoliu, I., Chaudry, A., Persaud, K., Marco, S., (2010). Fault detection, identification, and reconstruction of faulty chemical gas sensors under drift conditions, using Principal Component Analysis and Multiscale-PCA Theoretical or Mathematical; Experimental The 2010 International Joint Conference on Neural Networks (IJCNN 2010) , IEEE, Piscataway, NJ, USA (Barcelona, Spain) , 7 pp.

Statistical methods like Principal Components Analysis (PCA) or Partial Least Squares (PLS) and multiscale approaches, have been reported to be very useful in the task of fault diagnosis of malfunctioning sensors for several types of faults. In this work, we compare the performance of PCA and Multiscale-PCA on a fault based on a change of sensor sensitivity. This type of fault affects chemical gas sensors and it is one of the effects of the sensor poisoning. These two methods will be applied on a dataset composed by the signals of 17 conductive polymer gas sensors, measuring three analytes at several concentration levels during 10 months. Therefore, additionally to performance's comparison, both method's stability along the time will be tested. The comparison between both techniques will be made regarding three aspects; detection, identification of the faulty sensors and correction of faulty sensors response.

Keywords: Fault diagnosis, Gas sensors, Principal component analysis

Correa, L. S., Laciar, E., Mut, V., Giraldo, B. F., Torres, A., (2010). Multi-parameter analysis of ECG and Respiratory Flow signals to identify success of patients on weaning trials Engineering in Medicine and Biology Society (EMBC) 32nd Annual International Conference of the IEEE , IEEE (Buenos Aires, Argentina) -----, 6070-6073

Statistical analysis, power spectral density, and Lempel Ziv complexity, are used in a multi-parameter approach to analyze four temporal series obtained from the Electrocardiographic and Respiratory Flow signals of 126 patients on weaning trials. In which, 88 patients belong to successful group (SG), and 38 patients belong to failure group (FG), i.e. failed to maintain spontaneous breathing during trial. It was found that mean values of cardiac inter-beat and breath durations give higher values for SG than for FG; Kurtosis coefficient of the spectrum of the rapid shallow breathing index is higher for FG; also Lempel Ziv complexity mean values associated with the respiratory flow signal are bigger for FG. Patients were then classified with a pattern recognition neural network, obtaining 80% of correct classifications (81.6% for FG and 79.5% for SG).

Keywords: Electrocardiography, Medical signal processing, Neural nets, Pattern recognition, Pneumodynamics, Signal classification, Statistical analysis, ECG, Kurtosis coefficient, Lempel Ziv complexity, Breath durations, Cardiac interbeat durations, Electrocardiography, Multiparameter analysis, Pattern recognition neural network, Power spectral density, Respiratory flow signals, Signal classification, Spontaneous breathing, Statistical analysis, Weaning trials

Leder, R. S., Schlotthauer, G., Penzel, T., Jané, R., (2010). The natural history of the sleep and respiratory engineering track at EMBC 1988 to 2010 Engineering in Medicine and Biology Society (EMBC) 32nd Annual International Conference of the IEEE , IEEE (Buenos Aires, Argentina) , 288-291

Sleep science and respiratory engineering as medical subspecialties and research areas grew up side-by-side with biomedical engineering. The formation of EMBS in the 1950's and the discovery of REM sleep in the 1950's led to parallel development and interaction of sleep and biomedical engineering in diagnostics and therapeutics.

Keywords: Practical/ biomedical equipment, Biomedical measurement, Patient diagnosis, Patient monitoring, Patient treatment, Pneumodynamics, Sleep/ sleep engineering, Respiratory engineering, Automatic sleep analysis, Automatic sleep interpretation systems, Breathing, Biomedical, Engineering, Diagnostics, Therapeutics, REM sleep, Portable, Measurement, Ambulatory measurement, Monitoring

Arcentales, A., Giraldo, B. F., Caminal, P., Diaz, I., Benito, S., (2010). Spectral analysis of the RR series and the respiratory flow signal on patients in weaning process Engineering in Medicine and Biology Society (EMBC) 32nd Annual International Conference of the IEEE , IEEE (Buenos Aires, Argentina) , 2485-2488

A considerable number of patients in weaning process have problems to keep spontaneous breathing during the trial and after it. This study proposes to extract characteristic parameters of the RR series and respiratory flow signal according to the patients' condition in weaning test. Three groups of patients have been considered: 93 patients with successful trials (group S), 40 patients that failed to maintain spontaneous breathing (group F), and 21 patients who had successful weaning trials, but that had to be reintubated before 48 hours (group R). The characterization was performed using spectral analysis of the signals, through the power spectral density, cross power spectral density and Coherence method. The parameters were extracted on the three frequency bands (VLF, LF and HF), and the principal statistical differences between groups were obtained in bands of VLF and HF. The results show an accuracy of 76.9% in the classification of the groups S and F.

Keywords: Biomedical measurement, Electrocardiography, Medical signal processing, Pneumodynamics, Spectral analysis, RR series, Coherence method, Cross power spectral density, Electrocardiography, Principal statistical differences, Respiratory flow signal, Spectral analysis, Spontaneous breathing, Weaning test

Pairo, E., Marco, S., Perera, A., (2010). A subspace method for the detection of transcription factor binding sites BIOINFORMATICS 2010. Proceedings of the First International Conference on Bioinformatics BIOINFORMATICS 2010. First International Conference on Bioinformatics (ed. Fred, A., Filipe, J., Gamboa, H.), INSTICC Press (Valencia, Spain) , 102-107

Transcription Factor binding sites are short and degenerate sequences, located mostly at the promoter of the gene, where some proteins bind in order to regulate transcription. Locating these sequences is an important issue, and many experimental and computational methods have been developed. Algorithms to search binding sites are usually based on Position Specific Scoring Matrices (PSSM), where each position is treated independently. Mapping symbolical DNA to numerical sequences, a detector has been built with a Principal Component Analysis of the numerical sequences, taking into account covariances between positions. When a treatment of missing values is incorporated the Q-residuals detector, based on PCA, performs better than a PSSM algorithm. The performance on the detector depends on the estimation of missing values and the percentage of missing values considered in the model.

Keywords: Binding sites, BPCA, Missing values, Numerical DNA, Principal components analysis, Transcription factors

Milan, J. L., Planell, J. A., Lacroix, D., (2009). Computational modelling of the mechanical environment of osteogenesis within a polylactic acid-calcium phosphate glass scaffold Biomaterials 30, (25), 4219-4226

A computational model based on finite element method (FEM) and computational fluid dynamics (CFD) is developed to analyse the mechanical stimuli in a composite scaffold made of polylactic acid (PLA) matrix with calcium phosphate glass (Glass) particles. Different bioreactor loading conditions were simulated within the scaffold. In vitro perfusion conditions were reproduced in the model. Dynamic compression was also reproduced in an uncoupled fluid-structure scheme: deformation level was studied analyzing the mechanical response of scaffold alone under static compression while strain rate was studied considering the fluid flow induced by compression through fixed scaffold. Results of the model show that during perfusion test an inlet velocity of 25mum/s generates on scaffold surface a fluid flow shear stress which may stimulate osteogenesis. Dynamic compression of 5% applied on the PLA-Glass scaffold with a strain rate of 0.005s(-1) has the benefit to generate mechanical stimuli based on both solid shear strain and fluid flow shear stress on large scaffold surface area. Values of perfusion inlet velocity or compression strain rate one order of magnitude lower may promote cell proliferation while values one order of magnitude higher may be detrimental for cells. FEM-CFD scaffold models may help to determine loading conditions promoting bone formation and to interpret experimental results from a mechanical point of view.

Keywords: Bone tissue engineering, Scaffold, Finite element analysis, Computational fluid dynamics, Mechanical stimuli

Mir, M., Cameron, P. J., Zhong, X., Azzaroni, O., Alvarez, M., Knoll, W., (2009). Anti-fouling characteristics of surface-confined oligonucleotide strands bioconjugated on streptavidin platforms in the presence of nanomaterials Talanta 78, (3), 1102-6

This work describes our studies on the molecular design of interfacial architectures suitable for DNA sensing which could resist non-specific binding of nanomaterials commonly used as labels for amplifying biorecognition events. We observed that the non-specific binding of bio-nanomaterials to surface-confined oligonucleotide strands is highly dependent on the characteristics of the interfacial architecture. Thiolated double stranded oligonucleotide arrays assembled on Au surfaces evidence significant fouling in the presence of nanoparticles (NPs) at the nanomolar level. The non-specific interaction between the oligonucleotide strands and the nanomaterials can be sensitively minimized by introducing streptavidin (SAv) as an underlayer conjugated to the DNA arrays. The role of the SAv layer was attributed to the significant hydrophilic repulsion between the SAv-modified surface and the nanomaterials in close proximity to the interface, thus conferring outstanding anti-fouling characteristics to the interfacial architecture. These results provide a simple and straightforward strategy to overcome the limitations introduced by the non-specific binding of labels to achieve reliable detection of DNA-based biorecognition events.

Keywords: DNA/ analysis, Gold, Nanostructures/ chemistry, Oligonucleotide Array Sequence Analysis/ instrumentation, Oligonucleotides/ chemistry, Streptavidin/ chemistry, Sulfhydryl Compounds

Mir, M., Homs, A., Samitier, J., (2009). Integrated electrochemical DNA biosensors for lab-on-a-chip devices Electrophoresis , 30, (19), 3386-3397

Analytical devices able to perform accurate and fast automatic DNA detection or sequencing procedures have many potential benefits in the biomedical and environmental fields. The conversion of biological or biochemical responses into quantifiable optical, mechanical or electronic signals is achieved by means of biosensors. Most of these transducing elements can be miniaturized and incorporated into lab-on-a-chip devices, also known as Micro Total Analysis Systems. The use of multiple DNA biosensors integrated in these miniaturized laboratories, which perform several analytical operations at the microscale, has many cost and efficiency advantages. Tiny amounts of reagents and samples are needed and highly sensitive, fast and parallel assays can be done at low cost. A particular type of DNA biosensors are the ones used based on electrochemical principles. These sensors offer several advantages over the popular fluorescence-based detection schemes. The resulting signal is electrical and can be processed by conventional electronics in a very cheap and fast manner. Furthermore, the integration and miniaturization of electrochemical transducers in a microsystem makes easier its fabrication in front of the most common currently used detection method. In this review, different electrochemical DNA biosensors integrated in analytical microfluidic devices are discussed and some early stage commercial products based on this strategy are presented.

Keywords: DNA, Electrochemical DNA biosensors, Electrochemistry, Lab-on-a-chip, Micro Total Analysis systems, Field-effect transistors, Sequence-specific detection, Chemical-analysis systems, Solid-state nanopores, Carbon nanotubes, Microfluidic device, Electrical detection, Hybridization, Molecules, Sensor

Malandrino, A., Planell, J. A., Lacroix, D., (2009). Statistical factorial analysis on the poroelastic material properties sensitivity of the lumbar intervertebral disc under compression, flexion and axial rotation Journal of Biomechanics 42, (16), 2780-2788

A statistical factorial analysis approach was conducted on a poroelastic finite element model of a lumbar intervertebral disc to analyse the influence of six material parameters (permeabilities of annulus, nucleus, trabecular vertebral bone, cartilage endplate and Young's moduli of annulus and nucleus) on the displacement, fluid pore pressure and velocity fields. Three different loading modes were investigated: compression, flexion and axial rotation. Parameters were varied considering low and high levels in agreement with values found in the literature for both healthy and degenerated lumbar discs. Results indicated that annulus stiffness and cartilage endplate permeability have a strong effect on the overall fluid- and solid-phase responses in all loading conditions studied. Nucleus stiffness showed its main relevance in compression while annulus permeability influenced mainly the annular pressure field. This study confirms the permeability's central role in biphasic modelling and highlights for the lumbar disc which experiments of material property characterization should be performed. Moreover, such sensitivity study gives important guidelines in poroelastic material modelling and finite element disc validation.

Keywords: Intervertebral disc, Permeability, Fractional factorial design, Design of experiments, Finite element analysis

Marco, S., Pomareda, V., Pardo, A., Kessler, M., Goebel, J., Mueller, G., (2009). Blind source separation for ion mobility spectra Olfaction and Electronic Nose: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose 13th International Symposium on Olfaction and the Electronic Nose (ed. Pardo, M., Sberveglieri, G.), Amer Inst Physics (Brescia, Italy) 1137, 551-553

Miniaturization is a powerful trend for smart chemical instrumentation in a diversity of applications.. It is know that miniaturization in IMS leads to a degradation of the system characteristics. For the present work, we are interested in signal processing solutions to mitigate limitations introduced by limited drift tube length that basically involve a loss of chemical selectivity. While blind source separation techniques (BSS) are popular in other domains, their application for smart chemical instrumentation is limited. However, in some conditions, basically linearity, BSS may fully recover the concentration time evolution and the pure spectra with few underlying hypothesis. This is extremely helpful in conditions where non-expected chemical interferents may appear, or unwanted perturbations may pollute the spectra. SIMPLISMA has been advocated by Harrington et al. in several papers. However, more modem methods of BSS for bilinear decomposition with the restriction of positiveness have appeared in the last decade. In order to explore and compare the performances of those methods a series of experiments were performed.

Keywords: Ion Mobility Spectrometry (IMS), Blind Source Separation (BSS), Multivariate Analysis, SIMPLISMA, MCR, Non-Negative Matrix Factorization (NMF)

Falasconi, M., Gutierrez, A., Auffarth, B., Sberveglieri, G., Marco, S., (2009). Cluster analysis of the rat olfactory bulb activity in response to different odorants Olfaction and Electronic Nose: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose 13th International Symposium on Olfaction and the Electronic Nose (ed. Pardo, M., Sberveglieri, G.), Amer Inst Physics (Brescia, Italy) 1137, 169-172

With the goal of deepen in the understanding of coding of chemical information in the olfactory system, a large data set consisting of rat's olfactory bulb activity values in response to several different volatile compounds has been analyzed by fuzzy c-means clustering methods. Clustering should help to discover groups of glomeruli that are similary activated according to their response profiles across the odorants. To investigate the significance of the achieved fuzzy partitions we developed and applied a novel validity approach based on cluster stability. Our results show certain level of glomerular clustering in the olfactory bulb and indicate that exist a main chemo-topic subdivision of the glomerular layer in few macro-area which are rather specific to particular functional groups of the volatile molecules.

Keywords: Olfactory bulb, 2-deoxyglucose mapping, Olfactory coding, Cluster analysis, Cluster validity

Pairo, E., Marco, S., Perera, A., (2009). A preliminary study on the detection of transcription factor binding sites Biosignals 2009: Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing 2nd International Conference on Bio-Inspired Systems and Signal Processing (ed. Encarnacao, P., Veloso, A.), Insticc-Inst Syst Technologies Information Control & Communication (Oporto, Portugal) , 506-509

Transcription starts when multiple proteins, known as transcription factors recognize and bind to transcription start site in DNA sequences. Since mutation in transcription factor binding sites are known to underlie diseases it remains a major challenge to identify these binding sites. Conversion from symbolic DNA to numerical sequences and genome data make it possible to construct a detector based on a numerical analysis of DNA binding sites. A subspace model for the TFBS is built. TFBS will show a very small distance to this particular subspace. Using this distance binding sites are distinguished from random sequences and from genome data.

Keywords: Transcription factors, Binding sites, Principal components analysis

Seeck, A., Garde, A., Schuepbach, M., Giraldo, B., Sanz, E., Huebner, T., Caminal, P., Voss, A., (2009). Diagnosis of ischemic heart disease with cardiogoniometry - linear discriminant analysis versus support vector machines IFMBE Proceedings 4th European Conference of the International Federation for Medical and Biological Engineering (ed. Vander Sloten, Jos, Verdonck, Pascal, Nyssen, Marc, Haueisen, Jens), Springer Berlin Heidelberg (Berlin, Germany) 22, 389-392

The Ischemic Heart Disease (IHD) is characterized by an insufficient supply with blood of the myocardium usually caused by an artherosclerotic disease of the coronary arteries (coronary artery disease CAD). The IHD and its consequences have become a leading problem in the industrialized nations. The aim of this study was to evaluate a new diagnosing method, the cardiogoniometry, using two different classifying techniques: the method of linear discriminant function analysis (LDA) and the method of Support Vector Machines (SVM). Data of a group of 109 female subjects (62 healthy, 47 with IHD) were analyzed on the basis of extracted parameters from the three-dimensional vector loops of the heart. The LDA achieved an accuracy of 83,5% (Sensitivity 78,7%, Specificity 87,1%), whereas the SVM achieved an accuracy of 86% (Sensitivity 80,5%, Specificity 89,8%). It could be shown that cardiogoniometry, an electrophysiological diagnostic method performed at rest, detects variables that are helpful in identifying ischemic heart disease. As it is easy to apply, non-invasive, and provides an automated interpretation it may become an inexpensive addition to the cardiologic diagnostic armamentarium, possibly useful for early diagnosis of IHD or CAD, as well as in patients who do not tolerate exercise testing. It was also proven that by applying Support Vector Machines an increased diagnostic precision in comparison to the conventional discriminant function analysis can be achieved.

Keywords: Cardiogoniometry, Support Vector Machines, Nonlinear classifier, Linear discriminant analysis, Vector loop

Roca, Ignasi, Torrents, Eduard, Sahlin, Margareta, Gibert, Isidre, Sjoberg, Britt-Marie, (2008). NrdI essentiality for class Ib ribonucleotide reduction in streptococcus pyogenes Journal of Bacteriology , 190, (14), 4849-4858

The Streptococcus pyogenes genome harbors two clusters of class Ib ribonucleotide reductase genes, nrdHEF and nrdF*I*E*, and a second stand-alone nrdI gene, designated nrdI2. We show that both clusters are expressed simultaneously as two independent operons. The NrdEF enzyme is functionally active in vitro, while the NrdE*F* enzyme is not. The NrdF* protein lacks three of the six highly conserved iron-liganding side chains and cannot form a dinuclear iron site or a tyrosyl radical. In vivo, on the other hand, both operons are functional in heterologous complementation in Escherichia coli. The nrdF*I*E* operon requires the presence of the nrdI* gene, and the nrdHEF operon gained activity upon cotranscription of the heterologous nrdI gene from Streptococcus pneumoniae, while neither nrdI* nor nrdI2 from S. pyogenes rendered it active. Our results highlight the essential role of the flavodoxin NrdI protein in vivo, and we suggest that it is needed to reduce met-NrdF, thereby enabling the spontaneous reformation of the tyrosyl radical. The NrdI* flavodoxin may play a more direct role in ribonucleotide reduction by the NrdF*I*E* system. We discuss the possibility that the nrdF*I*E* operon has been horizontally transferred to S. pyogenes from Mycoplasma spp.

Keywords: Group-a streptococcus, Bacillus-subtilis genes, Escherichia-coli, Corynebacterium-ammoniagenes, Mycobacterium-tuberculosis, Expression analysis, Genome sequence, Small-subunit, Salmonella-typhimurium, Iron center

Banos, R. C., Pons, J. I., Madrid, C., Juarez, A., (2008). A global modulatory role for the Yersinia enterocolitica H-NS protein Microbiology , 154, (5), 1281-1289

The H-NS protein plays a significant role in the modulation of gene expression in Gram-negative bacteria. Whereas isolation and characterization of hns mutants in Escherichia coli, Salmonella and Shigella represented critical steps to gain insight into the modulatory role of H-NS, it has hitherto not been possible to isolate hns mutants in Yersinia. The hns mutation is considered to be deleterious in this genus. To study the modulatory role of H-NS in Yersinia we circumvented hns lethality by expressing in Y. enterocolitica a truncated H-NS protein known to exhibit anti-H-NS activity in E. coli (H-NST(EPEC)). Y. enterocolitica cells expressing H-NST(EPEC) showed an altered growth rate and several differences in the protein expression pattern, including the ProV protein, which is modulated by H-NS in other enteric bacteria. To further confirm that H-NST(EPEC) expression in Yersinia can be used to demonstrate H-NS-dependent regulation in this genus, we used this approach to show that H-NS modulates expression of the YmoA protein.

Keywords: Bacterial Proteins/biosynthesis/genetics/ physiology, DNA-Binding Proteins/biosynthesis/genetics/ physiology, Electrophoresis, Gel, Two-Dimensional, Gene Expression Profiling, Gene Expression Regulation, Bacterial, Genes, Essential, Proteome/analysis, RNA, Bacterial/biosynthesis, RNA, Messenger/biosynthesis, Reverse Transcriptase Polymerase Chain Reaction, Sequence Deletion, Yersinia enterocolitica/chemistry/genetics/growth & development/ physiology

Sandino, C., Planell, J. A., Lacroix, D., (2008). A finite element study of mechanical stimuli in scaffolds for bone tissue engineering Journal of Biomechanics 41, (5), 1005-1014

Mechanical stimuli are one of the factors that affect cell proliferation and differentiation in the process of bone tissue regeneration. Knowledge on the specific deformation sensed by cells at a microscopic level when mechanical loads are applied is still missing in the development of biomaterials for bone tissue engineering. The objective of this study was to analyze the behavior of the mechanical stimuli within some calcium phosphate-based scaffolds in terms of stress and strain distributions in the solid material phase and fluid velocity, fluid pressure and fluid shear stress distributions in the pores filled of fluid, by means of micro computed tomographed (CT)-based finite element (FE) models. Two samples of porous materials, one of calcium phosphate-based cement and another of biodegradable glass, were used. Compressive loads equivalent to 0.5% of compression applied to the solid material phase and interstitial fluid flows with inlet velocities of 1, 10 and 100 mu m/s applied to the interconnected pores were simulated, changing also the inlet side and the viscosity of the medium. Similar strain distributions for both materials were found, with compressive and tensile strain maximal values of 1.6% and 0.6%, respectively. Mean values were consistent with the applied deformation. When 10 mu m/s of inlet fluid velocity and 1.45 Pa s viscosity, maximal values of fluid velocity were 12.76 mm/s for CaP cement and 14.87 mm/s for glass. Mean values were consistent with the inlet ones applied, and mean values of shear stress were around 5 x 10(-5) Pa. Variations on inlet fluid velocity and fluid viscosity produce proportional and independent changes in fluid velocity, fluid shear stress and fluid pressure. This study has shown how mechanical loads and fluid flow applied on the scaffolds cause different levels of mechanical stimuli within the samples according to the morphology of the materials.

Keywords: Bone tissue engineering, Finite element analysis, Scaffolds, Mechanical stimuli

Navarro, M., Engel, E., Planell, J. A., Amaral, I., Barbosa, M., Ginebra, M. P., (2008). Surface characterization and cell response of a PLA/CaP glass biodegradable composite material Journal of Biomedical Materials Research - Part A , 85A, (2), 477-486

Bioabsorbable materials are of great interest for bone regeneration applications, since they are able to degrade gradually as new tissue is formed. In this work, a fully biodegradable composite material containing polylactic acid (PLA) and calcium phosphate (CaP) soluble glass particles has been characterized in terms of surface properties and cell response. Cell cultures were performed in direct contact with the materials and also with their extracts, and were evaluated using the MTT assay, alkaline phosphatase activity, and osteocalcin measurements. The CaP glass and PLA were used as reference materials. No significant differences were observed in cell proliferation with the extracts containing the degradation by-products of the three materials studied. A relation between the materials wettability and the material-cell interactions at the initial stages of contact was observed. The most hydrophilic material (CaP glass) presented the highest cell adhesion values as well as an earlier differentiation, followed by the PLA/glass material. The incorporation of glass particles into the PLA matrix increased surface roughness. SEM images showed that the heterogeneity of the composite material induced morphological changes in the cells cytoskeleton.

Keywords: Glass, Polylactic acid, Surface analysis, Cell culture, In vitro test

Diez, Pablo F., Laciar, Eric, Mut, Vicente, Avila, Enrique, Torres, Abel, (2008). A comparative study of the performance of different spectral estimation methods for classification of mental tasks IEEE Engineering in Medicine and Biology Society Conference Proceedings 30th Annual International Conference of the Ieee Engineering in Medicine and Biology Society (ed. IEEE), IEEE (Vancouver, Canada) 1-8, 1155-1158

In this paper we compare three different spectral estimation techniques for the classification of mental tasks. These techniques are the standard periodogram, the Welch periodogram and the Burg method, applied to electroencephalographic (EEG) signals. For each one of these methods we compute two parameters: the mean power and the root mean square (RMS), in various frequency bands. The classification of the mental tasks was conducted with a linear discriminate analysis. The Welch periodogram and the Burg method performed better than the standard periodogram. The use of the RMS allows better classification accuracy than the obtained with the power of EEG signals.

Keywords: Adult, Algorithms, Artificial Intelligence, Cognition, Electroencephalography, Female, Humans, Male, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity, Task Performance and Analysis, User-Computer Interface

Charles-Harris, M., del Valle, S., Hentges, E., Bleuet, P., Lacroix, D., Planell, J. A., (2007). Mechanical and structural characterisation of completely degradable polylactic acid/calcium phosphate glass scaffolds Biomaterials 28, (30), 4429-4438

This study involves the mechanical and structural characterisation of completely degradable scaffolds for tissue engineering applications. The scaffolds are a composite of polylactic acid (PLA) and a soluble calcium phosphate glass, and are thus completely degradable. A factorial experimental design was applied to optimise scaffold composition prior to simultaneous microtomography and micromechanical testing. Synchrotron X-ray microtomography combined with in situ micromechanical testing was performed to obtain three-dimensional 3D images of the scaffolds under compression. The 3D reconstruction was converted into a finite element mesh which was validated by simulating a compression test and comparing it with experimental results. The experimental design reveals that larger glass particle and pore sizes reduce the stiffness of the scaffolds, and that the porosity is largely unaffected by changes in pore sizes or glass weight content. The porosity ranges between 93% and 96.5%, and the stiffness ranges between 50 and 200 kPa. X-ray projections show a homogeneous distribution of the glass particles within the PLA matrix, and illustrate pore-wall breakage under strain. The 3D reconstructions are used qualitatively to visualise the distribution of the phases of the composite material, and to follow pore deformation under compression. Quantitatively, scaffold porosity, pore interconnectivity and surface/volume ratios have been calculated. Finite element analysis revealed the stress and strain distribution in the scaffold under compression, and could be used in the future to characterise the mechanical properties of the scaffolds.

Keywords: Synchrotron x-ray microtomography, Mechanical test, Biodegradable, Glass, Scaffold, Finite element analysis