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Rafols-de-Urquia, M., Estrada, L., Estevez-Piorno, J., Sarlabous, L., Jane, R., Torres, A., (2019). Evaluation of a wearable device to determine cardiorespiratory parameters from surface diaphragm electromyography IEEE Journal of Biomedical and Health Informatics Early Access

The use of wearable devices in clinical routines could reduce healthcare costs and improve the quality of assessment in patients with chronic respiratory diseases. The purpose of this study is to evaluate the capacity of a Shimmer3 wearable device to extract reliable cardiorespiratory parameters from surface diaphragm electromyography (EMGdi). Twenty healthy volunteers underwent an incremental load respiratory test whilst EMGdi was recorded with a Shimmer3 wearable device (EMGdiW). Simultaneously, a second EMGdi (EMGdiL), inspiratory mouth pressure (Pmouth) and lead-I electrocardiogram (ECG) were recorded via a standard wired laboratory acquisition system. Different cardiorespiratory parameters were extracted from both EMGdiW and EMGdiL signals: heart rate, respiratory rate, respiratory muscle activity and mean frequency of EMGdi signals. Alongside these, similar parameters were also extracted from reference signals (Pmouth and ECG). High correlations were found between the data extracted from the EMGdiW and the reference signal data: heart rate (R = 0.947), respiratory rate (R = 0.940), respiratory muscle activity (R = 0.877), and mean frequency (R = 0.895). Moreover, similar increments in EMGdiW and EMGdiL activity were observed when Pmouth was raised, enabling the study of respiratory muscle activation. In summary, the Shimmer3 device is a promising and cost-effective solution for the ambulatory monitoring of respiratory muscle function in chronic respiratory diseases. IEEE

Keywords: Cardiorespiratory monitoring, Chronic respiratory diseases, Fixed sample entropy, Non-invasive respiratory monitoring, Surface diaphragm electromyography, Wearable wireless device


Oliveira, V. R., Uriarte, J. J., Falcones, B., Zin, W. A., Navajas, D., Farré, R., Almendros, I., (2019). Escherichia coli lipopolysaccharide induces alveolar epithelial cell stiffening Journal of Biomechanics 83, 315-318

Introduction: Application of lipopolysaccharide (LPS) is a widely employed model to mimic acute respiratory distress syndrome (ARDS). Available data regarding LPS-induced biomechanical changes on pulmonary epithelial cells are limited only to P. aeruginosa LPS. Considering that LPS from different bacteria could promote a specific mechanical response in epithelial cells, we aim to assess the effect of E. coli LPS, widely employed as a model of ARDS, in the biomechanics of alveolar epithelial cells. Methods: Young’s modulus (E) of alveolar epithelial cells (A549) was measured by atomic force microscopy every 5 min throughout 60 min of experiment after treatment with LPS from E. coli (100 μg/mL). The percentage of cells presenting actin stress fibers (F-actin staining) was also evaluated. Control cells were treated with culture medium and the values obtained were compared with LPS-treated cells for each time-point. Results: Application of LPS induced significant increase in E after 20 min (77%) till 60 min (104%) in comparison to controls. Increase in lung epithelial cell stiffness induced by LPS was associated with a higher number of cells presenting cytoskeletal remodeling. Conclusions: The observed effects of E. coli LPS on alveolar epithelial cells suggest that this widely-used LPS is able to promote a quick formation of actin stress fibers and stiffening cells, thereby facilitating the disruption of the pulmonary epithelial barrier.

Keywords: Acute respiratory distress syndrome model, Alveolar epithelium, Biomechanics, E. coli, Lipopolysaccharide


Lozano-García, M., Estrada, L., Jané, R., (2019). Performance evaluation of fixed sample entropy in myographic signals for inspiratory muscle activity estimation Entropy 21, (2), 183

Fixed sample entropy (fSampEn) has been successfully applied to myographic signals for inspiratory muscle activity estimation, attenuating interference from cardiac activity. However, several values have been suggested for fSampEn parameters depending on the application, and there is no consensus standard for optimum values. This study aimed to perform a thorough evaluation of the performance of the most relevant fSampEn parameters in myographic respiratory signals, and to propose, for the first time, a set of optimal general fSampEn parameters for a proper estimation of inspiratory muscle activity. Different combinations of fSampEn parameters were used to calculate fSampEn in both non-invasive and the gold standard invasive myographic respiratory signals. All signals were recorded in a heterogeneous population of healthy subjects and chronic obstructive pulmonary disease patients during loaded breathing, thus allowing the performance of fSampEn to be evaluated for a variety of inspiratory muscle activation levels. The performance of fSampEn was assessed by means of the cross-covariance of fSampEn time-series and both mouth and transdiaphragmatic pressures generated by inspiratory muscles. A set of optimal general fSampEn parameters was proposed, allowing fSampEn of different subjects to be compared and contributing to improving the assessment of inspiratory muscle activity in health and disease.

Keywords: Electromyography, Fixed sample entropy, Mechanomyography, Non-invasive physiological measurements, Oesophageal electromyography, Respiratory muscle


Blanco-Almazan, D., Groenendaal, W., Catthoor, F., Jane, R., (2019). Wearable bioimpedance measurement for respiratory monitoring during inspiratory loading IEEE Access 7, 89487-89496

Bioimpedance is an unobtrusive noninvasive technique to measure respiration and has a linear relation with volume during normal breathing. The objective of this paper was to assess this linear relation during inspiratory loading protocol and determine the best electrode configuration for bioimpedance measurement. The inspiratory load is a way to estimate inspiratory muscle function and has been widely used in studies of respiratory mechanics. Therefore, this protocol permitted us to evaluate bioimpedance performance under breathing pattern changes. We measured four electrode configurations of bioimpedance and airflow simultaneously in ten healthy subjects using a wearable device and a standard wired laboratory acquisition system, respectively. The subjects were asked to perform an incremental inspiratory threshold loading protocol during the measurements. The load values were selected to increase progressively until the 60% of the subject's maximal inspiratory pressure. The linear relation of the signals was assessed by Pearson correlation (r ) and the waveform agreement by the mean absolute percentage error (MAPE), both computed cycle by cycle. The results showed a median greater than 0.965 in r coefficients and lower than 11 % in the MAPE values for the entire population in all loads and configurations. Thus, a strong linear relation was found during all loaded breathing and configurations. However, one out of the four electrode configurations showed robust results in terms of agreement with volume during the highest load. In conclusion, bioimpedance measurement using a wearable device is a noninvasive and a comfortable alternative to classical methods for monitoring respiratory diseases in normal and restrictive breathing.

Keywords: Bioimpedance, Chronic respiratory diseases, Electrode configurations, Inspiratory threshold protocol, Wearable


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


Garcia-Esparcia, P., Koneti, A., Rodríguez-Oroz, M. C., Gago, B., del Rio, J. A., Ferrer, Isidro, (2018). Mitochondrial activity in the frontal cortex area 8 and angular gyrus in Parkinson's disease and Parkinson's disease with dementia Brain Pathology 28, (1), 43-57

Altered mitochondrial function is characteristic in the substantia nigra in Parkinson's disease (PD). Information about mitochondria in other brain regions such as the cerebral cortex is conflicting mainly because most studies have not contemplated the possibility of variable involvement depending on the region, stage of disease progression and clinical symptoms such as the presence or absence of dementia. RT-qPCR of 18 nuclear mRNAs encoding subunits of mitochondrial complexes and 12 mRNAs encoding energy metabolism-related enzymes; western blotting of mitochondrial proteins; and analysis of enzymatic activities of complexes I, II, II, IV and V of the respiratory chain were assessed in frontal cortex area 8 and the angular gyrus of middle-aged individuals (MA), and those with incidental PD (iPD), long-lasting PD with parkinsonism without dementia (PD) and long-lasting PD with dementia (PDD). Up-regulation of several genes was found in frontal cortex area 8 in PD when compared with MA and in the angular gyrus in iPD when compared with MA. Marked down-regulation of genes encoding mitochondrial subunits and energy metabolism-related enzymes occurs in frontal cortex but only of genes coding for energy metabolism-related enzymes in the angular gyrus in PDD. Significant decrease in the protein expression levels of several mitochondrial subunits encoded by these genes occurs in frontal cortex area 8 and angular gyrus in PDD. Moreover, expression of MT-ND1 which is encoded by mitochondrial DNA is also reduced in PDD. Reduced enzymatic activity of complex III in frontal cortex area 8 and angular gyrus is observed in PD, but dramatic reduction in the activity of complexes I, II, II and IV in both regions characterizes PDD. Dementia in the context of PD is linked to region-specific deregulation of genomic genes encoding subunits of mitochondrial complexes and to marked reduction in the activity of mitochondrial complexes I, II, III and IV.

Keywords: Cerebral cortex, Dementia, Energy metabolism, Incidental PD, Mitochondria, Oxidative phosphorylation, Parkinson disease, PDD, Respiratory chain


Estrada, L., Torres, A., Sarlabous, L., Jané, R., (2018). Onset and offset estimation of the neural inspiratory time in surface diaphragm electromyography: A pilot study in healthy subjects IEEE Journal of Biomedical and Health Informatics 22, (1), 67-76

This study evaluates the onset and offset of neural inspiratory time estimated from surface diaphragm electromyographic (EMGdi) recordings. EMGdi and airflow signals were recorded in ten healthy subjects according to two respiratory protocols based on respiratory rate (RR) increments, from 15 to 40 breaths per minute (bpm), and fractional inspiratory time (Ti/Ttot) decrements, from 0.54 to 0.18. The analysis of diaphragm electromyographic (EMGdi) signal amplitude is an alternative approach for the quantification of neural respiratory drive (NRD). The EMGdi amplitude was estimated using the fixed sample entropy computed over a 250 ms moving window of the EMGdi signal (EMGdifse). The neural onset was detected through a dynamic threshold over the EMGdifse using the kernel density estimation method, while neural offset was detected by finding when the EMGdifse had decreased to 70 % of the peak value reached during inspiration. The Bland-Altman analysis between airflow and neural onsets showed a global bias of 46 ms in the RR protocol and 22 ms in the Ti/Ttot protocol. The Bland-Altman analysis between airflow and neural offsets reveals a global bias of 11 ms in the RR protocol and -2 ms in the Ti/Ttot protocol. The relationship between pairs of RR values (Pearson’s correlation coefficient of 0.99, Bland- Altman limits of -2.39 to 2.41 bpm, and mean bias of 0.01 bpm) and between pairs of Ti/Ttot values (Pearson’s correlation coefficient of 0.86, Bland-Altman limits of -0.11 to 0.10, and mean bias of -0.01) showed a good agreement. In conclusion, we propose a method for determining neural onset and neural offset based on non-invasive recordings of the electrical activity of the diaphragm that requires no filtering of cardiac muscle interference.

Keywords: Kernel density estimation (KDE),, Surface diaphragm electromyographic,, (EMGdi) signal,, Inspiratory time,, Neural respiratory drive (NRD),, Neural inspiratory time,, Fixed sample entropy (fSampEn)


Frau-Méndez, Margalida A., Fernández-Vega, Iván, Ansoleaga, Belén, Blanco, Rosa, Carmona, Margarita, Antonio del Rio, Jose, Zerr, Inga, Llorens, Franc, Zarranz, Juan José, Ferrer, Isidro, (2017). Fatal familial insomnia: Mitochondrial and protein synthesis machinery decline in the mediodorsal thalamus Brain Pathology 27, (1), 95-106

The expression of subunits of mitochondrial respiratory complexes and components of the protein synthesis machinery from the nucleolus to the ribosome was analyzed in the mediodorsal thalamus in seven cases of Fatal Familial Insomnia (FFI) compared with age-matched controls. NDUFB8 (complex I subunit), SDHB (complex II subunit), UQCRC2 (complex III subunit), COX2 (complex IV subunit) and ATP50 (complex V subunit) expression levels, as revealed by western blotting, were reduced in FFI. Voltage-dependent anion channel (VDAC) and ATP5H were also reduced due to the marked depopulation of neurons. In contrast, a marked increase in superoxide dismutase 2 (SOD2) was found in reactive astrocytes thus suggesting that astrocytes are key factors in oxidative stress responses. The histone-binding chaperones nucleolin and nucleoplasmin 3, and histone H3 di-methylated K9 were markedly reduced together with a decrease in the expression of protein transcription elongation factor eEF1A. These findings show severe impairment in the expression of crucial components of mitochondrial function and protein synthesis in parallel with neuron loss in mediodorsal thalamus at terminal stages of FFI. Therapeutic measures must be taken long before the appearance of clinical symptoms to prevent the devastating effects of FFI.

Keywords: Fatal familial insomnia, Mitochondria, Protein synthesis, Mitochondrial respiratory chain, Nucleolus, Ribosome


Estrada, L., Torres, A., Sarlabous, L., Jané, R., (2017). Influence of parameter selection in fixed sample entropy of surface diaphragm electromyography for estimating respiratory activity Entropy 19, (9), 460

Fixed sample entropy (fSampEn) is a robust technique that allows the evaluation of inspiratory effort in diaphragm electromyography (EMGdi) signals, and has potential utility in sleep studies. To appropriately estimate respiratory effort, fSampEn requires the adjustment of several parameters. The aims of the present study were to evaluate the influence of the embedding dimension m, the tolerance value r, the size of the moving window, and the sampling frequency, and to establish recommendations for estimating the respiratory activity when using the fSampEn on surface EMGdi recorded for different inspiratory efforts. Values of m equal to 1 and r ranging from 0.1 to 0.64, and m equal to 2 and r ranging from 0.13 to 0.45, were found to be suitable for evaluating respiratory activity. fSampEn was less affected by window size than classical amplitude parameters. Finally, variations in sampling frequency could influence fSampEn results. In conclusion, the findings suggest the potential utility of fSampEn for estimating muscle respiratory effort in further sleep studies.

Keywords: Fixed sample entropy (fSampEn), Non-invasive respiratory monitoring, Respiratory activity, Respiratory effort, Surface diaphragm electromyography


Garde, A., Sörnmo, L., Laguna, P., Jané, R., Benito, S., Bayés-Genís, A., Giraldo, B. F., (2017). Assessment of respiratory flow cycle morphology in patients with chronic heart failure Medical and Biological Engineering and Computing , 55, (2), 245-255

Breathing pattern as periodic breathing (PB) in chronic heart failure (CHF) is associated with poor prognosis and high mortality risk. This work investigates the significance of a number of time domain parameters for characterizing respiratory flow cycle morphology in patients with CHF. Thus, our primary goal is to detect PB pattern and identify patients at higher risk. In addition, differences in respiratory flow cycle morphology between CHF patients (with and without PB) and healthy subjects are studied. Differences between these parameters are assessed by investigating the following three classification issues: CHF patients with PB versus with non-periodic breathing (nPB), CHF patients (both PB and nPB) versus healthy subjects, and nPB patients versus healthy subjects. Twenty-six CHF patients (8/18 with PB/nPB) and 35 healthy subjects are studied. The results show that the maximal expiratory flow interval is shorter and with lower dispersion in CHF patients than in healthy subjects. The flow slopes are much steeper in CHF patients, especially for PB. Both inspiration and expiration durations are reduced in CHF patients, mostly for PB. Using the classification and regression tree technique, the most discriminant parameters are selected. For signals shorter than 1 min, the time domain parameters produce better results than the spectral parameters, with accuracies for each classification of 82/78, 89/85, and 91/89 %, respectively. It is concluded that morphologic analysis in the time domain is useful, especially when short signals are analyzed.

Keywords: Chronic heart failure, Ensemble average, Periodic and non-periodic breathing, Respiratory pattern


Estrada, L., Torres, A., Sarlabous, L., Jané, R., (2016). Improvement in neural respiratory drive estimation from diaphragm electromyographic signals using fixed sample entropy IEEE Journal of Biomedical and Health Informatics 20, (2), 476-485

Diaphragm electromyography is a valuable technique for the recording of electrical activity of the diaphragm. The analysis of diaphragm electromyographic (EMGdi) signal amplitude is an alternative approach for the quantification of neural respiratory drive (NRD). The EMGdi signal is, however, corrupted by electrocardiographic (ECG) activity, and this presence of cardiac activity can make the EMGdi interpretation more difficult. Traditionally, the EMGdi amplitude has been estimated using the average rectified value (ARV) and the root mean square (RMS). In this work, surface EMGdi signals were analyzed using the fixed sample entropy (fSampEn) algorithm, and compared to traditional ARV and RMS methods. The fSampEn is calculated using a tolerance value fixed and independent of the standard deviation of the analysis window. Thus, this method quantifies the amplitude of the complex components of stochastic signals (such as EMGdi), and being less affected by changes in amplitude due to less complex components (such as ECG). The proposed method was tested in synthetic and recorded EMGdi signals. fSampEn was less sensitive to the effect of cardiac activity on EMGdi signals with different levels of NRD than ARV and RMS amplitude parameters. The mean and standard deviation of the Pearson’s correlation values between inspiratory mouth pressure (an indirect measure of the respiratory muscle activity) and fSampEn, ARV and RMS parameters, estimated in the recorded EMGdi signal at tidal volume (without inspiratory load), were 0.38???0.12, 0.27???0.11 and 0.11???0.13, respectively. Whereas at 33 cmH2O (maximum inspiratory load) were 0.83???0.02, 0.76???0.07 and 0.61???0.19, respectively. Our findings suggest that the proposed method may improve the evaluation of NRD.

Keywords: Electromyography, diaphragm muscle, neural respiratory drive


Farré, R., Navajas, D., (2016). Forced oscillation: A poorly exploited tool for simply assessing respiratory function in children Respirology , 21, (6), 982-983

Lozano-Garcia, M., Fiz, J. A., Jané, R., (2016). Performance evaluation of the Hilbert–Huang transform for respiratory sound analysis and its application to continuous adventitious sound characterization Signal Processing , 120, 99-116

Abstract The use of the Hilbert–Huang transform in the analysis of biomedical signals has increased during the past few years, but its use for respiratory sound (RS) analysis is still limited. The technique includes two steps: empirical mode decomposition (EMD) and instantaneous frequency (IF) estimation. Although the mode mixing (MM) problem of EMD has been widely discussed, this technique continues to be used in many RS analysis algorithms. In this study, we analyzed the MM effect in RS signals recorded from 30 asthmatic patients, and studied the performance of ensemble EMD (EEMD) and noise-assisted multivariate EMD (NA-MEMD) as means for preventing this effect. We propose quantitative parameters for measuring the size, reduction of MM, and residual noise level of each method. These parameters showed that EEMD is a good solution for MM, thus outperforming NA-MEMD. After testing different IF estimators, we propose Kay׳s method to calculate an EEMD-Kay-based Hilbert spectrum that offers high energy concentrations and high time and high frequency resolutions. We also propose an algorithm for the automatic characterization of continuous adventitious sounds (CAS). The tests performed showed that the proposed EEMD-Kay-based Hilbert spectrum makes it possible to determine CAS more precisely than other conventional time-frequency techniques.

Keywords: Hilbert–Huang transform, Ensemble empirical mode decomposition, Instantaneous frequency, Respiratory sounds, Continuous adventitious sounds


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


Lozano-Garcia, M., Fiz, J. A., Jané, R., (2014). Analysis of normal and continuous adventitious sounds for the assessment of asthma IFMBE Proceedings XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013 (ed. Roa Romero, Laura M.), Springer International Publishing (London, UK) 41, 981-984

Assessment of asthma is a difficult procedure which is based on the correlation of multiple factors. A major component in the diagnosis of asthma is the assessment of BD response, which is performed by traditional spirometry. In this context, the analysis of respiratory sounds (RS) provides relevant and complementary information about the function of the respiratory system. In particular, continuous adventitious sounds (CAS), such as wheezes, contribute to assess the severity of patients with obstructive diseases. On the other hand, the intensity of normal RS is dependent on airflow level and, therefore, it changes depending on the level of obstruction. This study proposes a new approach to RS analysis for the assessment of asthmatic patients, by combining the quantification of CAS and the analysis of the changes in the normal sound intensity-airflow relationship. According to results obtained from three patients with different characteristics, the proposed technique seems more sensitive and promising for the assessment of asthma.

Keywords: Asthma, Bronchodilator response, Continuous adventitious sound, Respiratory sound intensity, Wheezes


Sarlabous, L., Torres, A., Fiz, J. A., Morera, J., Jané, R., (2013). Index for estimation of muscle force from mechanomyography based on the Lempel-Ziv algorithm Journal of Electromyography and Kinesiology , 23, (3), 548-557

The study of the amplitude of respiratory muscle mechanomyographic (MMG) signals could be useful in clinical practice as an alternative non-invasive technique to assess respiratory muscle strength. The MMG signal is stochastic in nature, and its amplitude is usually estimated by means of the average rectified value (ARV) or the root mean square (RMS) of the signal. Both parameters can be used to estimate MMG activity, as they correlate well with muscle force. These estimations are, however, greatly affected by the presence of structured impulsive noise that overlaps in frequency with the MMG signal. In this paper, we present a method for assessing muscle activity based on the Lempel-Ziv algorithm: the Multistate Lempel-Ziv (MLZ) index. The behaviour of the MLZ index was tested with synthesised signals, with various amplitude distributions and degrees of complexity, and with recorded diaphragm MMG signals. We found that this index, like the ARV and RMS parameters, is positively correlated with changes in amplitude of the diaphragm MMG components, but is less affected by components that have non-random behaviour (like structured impulsive noise). Therefore, the MLZ index could provide more information to assess the MMG-force relationship.

Keywords: Diaphragm, Electromyography, Lempel-Ziv, Mechanomyography, Muscle force, Respiratory muscles


Garde, Ainara, Voss, Andreas, Caminal, Pere, Benito, Salvador, Giraldo, Beatriz F., (2013). SVM-based feature selection to optimize sensitivity-specificity balance applied to weaning Computers in Biology and Medicine , 43, (5), 533-540

Classification algorithms with unbalanced datasets tend to produce high predictive accuracy over the majority class, but poor predictive accuracy over the minority class. This problem is very common in biomedical data mining. This paper introduces a Support Vector Machine (SVM)-based optimized feature selection method, to select the most relevant features and maintain an accurate and well-balanced sensitivity–specificity result between unbalanced groups. A new metric called the balance index (B) is defined to implement this optimization. The balance index measures the difference between the misclassified data within each class. The proposed optimized feature selection is applied to the classification of patients' weaning trials from mechanical ventilation: patients with successful trials who were able to maintain spontaneous breathing after 48 h and patients who failed to maintain spontaneous breathing and were reconnected to mechanical ventilation after 30 min. Patients are characterized through cardiac and respiratory signals, applying joint symbolic dynamic (JSD) analysis to cardiac interbeat and breath durations. First, the most suitable parameters (C+,C−,σ) are selected to define the appropriate SVM. Then, the feature selection process is carried out with this SVM, to maintain B lower than 40%. The best result is obtained using 6 features with an accuracy of 80%, a B of 18.64%, a sensitivity of 74.36% and a specificity of 82.42%.

Keywords: Support vector machines, Balance index, Sensitivity-specificity balance, Cardiorespiratory interaction, Joint symbolic dynamics, Feature selection, Weaning procedure


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


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


Gonzalez, H., Acevedo, H., Arizmendi, C., Giraldo, B. F., (2013). Methodology for determine the moment of disconnection of patients of the mechanical ventilation using discrete wavelet transform Complex Medical Engineering (CME) 2013 ICME International Conference , IEEE (Beijing, China) , 483-486

The process of weaning from mechanical ventilation is one of the challenges in intensive care units. 66 patients under extubation process (T-tube test) were studied: 33 patients with successful trials and 33 patients who failed to maintain spontaneous breathing and were reconnected. Each patient was characterized using 7 time series from respiratory signals, and for each serie was evaluated the discrete wavelet transform. It trains a neural network for discriminating between patients from the two groups.

Keywords: discrete wavelet transforms, neural nets, patient treatment, pneumodynamics, time series, ventilation, T-tube test, discrete wavelet transform, extubation process, intensive care units, mechanical ventilation, moment of disconnection, neural network, patients, respiratory signals, spontaneous breathing, time series, weaning, Mechanical Ventilation, Neural Networks, Time series from respiratory signals, Wavelet Transform


Jané, R., Lazaro, J., Ruiz, P., Gil, E., Navajas, D., Farre, R., Laguna, P., (2013). Obstructive Sleep Apnea in a rat model: Effects of anesthesia on autonomic evaluation from heart rate variability measures CinC 2013 Computing in Cardiology Conference (CinC) , IEEE (Zaragoza, Spain) , 1011-1014

Rat model of Obstructive Sleep Apnea (OSA) is a realistic approach for studying physiological mechanisms involved in sleep. Rats are usually anesthetized and autonomic nervous system (ANS) could be blocked. This study aimed to assess the effect of anesthesia on ANS activity during OSA episodes. Seven male Sprague-Dawley rats were anesthetized intraperitoneally with urethane (1g/kg). The experiments were conducted applying airway obstructions, simulating 15s-apnea episodes for 15 minutes. Five signals were acquired: respiratory pressure and flow, SaO2, ECG and photoplethysmography (PPG). In total, 210 apnea episodes were studied. Normalized power spectrum of Pulse Rate Variability (PRV) was analyzed in the Low Frequency (LF) and High Frequency (HF) bands, for each episode in consecutive 15s intervals (before, during and after the apnea). All episodes showed changes in respiratory flow and SaO2 signal. Conversely, decreases in the amplitude fluctuations of PPG (DAP) were not observed. Normalized LF presented extremely low values during breathing (median=7,67%), suggesting inhibition of sympathetic system due to anesthetic effect. Subtle increases of LF were observed during apnea. HRV and PPG analysis during apnea could be an indirect tool to assess the effect and deep of anesthesia.

Keywords: electrocardiography, fluctuations, medical disorders, medical signal detection, medical signal processing, neurophysiology, photoplethysmography, pneumodynamics, sleep, ECG, SaO2 flow, SaO2 signal, airway obstructions, amplitude fluctuations, anesthesia effects, anesthetized nervous system, autonomic evaluation, autonomic nervous system, breathing, heart rate variability, high-frequency bands, low-frequency bands, male Sprague-Dawley rats, normalized power spectrum, obstructive sleep apnea, photoplethysmography, physiological mechanisms, pulse rate variability, rat model, respiratory flow, respiratory pressure, signal acquisition, sympathetic system inhibition, time 15 min, time 15 s, Abstracts, Atmospheric modeling, Computational modeling, Electrocardiography, Rats, Resonant frequency


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


Giraldo, B.F., Gaspar, B.W., Caminal, P., Benito, S., (2012). Analysis of roots in ARMA model for the classification of patients on weaning trials Engineering in Medicine and Biology Society (EMBC) 34th Annual International Conference of the IEEE , IEEE (San Diego, USA) , 698-701

One objective of mechanical ventilation is the recovery of spontaneous breathing as soon as possible. Remove the mechanical ventilation is sometimes more difficult that maintain it. This paper proposes the study of respiratory flow signal of patients on weaning trials process by autoregressive moving average model (ARMA), through the location of poles and zeros of the model. A total of 151 patients under extubation process (T-tube test) were analyzed: 91 patients with successful weaning (GS), 39 patients that failed to maintain spontaneous breathing and were reconnected (GF), and 21 patients extubated after the test but before 48 hours were reintubated (GR). The optimal model was obtained with order 8, and statistical significant differences were obtained considering the values of angles of the first four poles and the first zero. The best classification was obtained between GF and GR, with an accuracy of 75.3% on the mean value of the angle of the first pole.

Keywords: Analytical models, Biological system modeling, Computational modeling, Estimation, Hospitals, Poles and zeros, Ventilation, Autoregressive moving average processes, Patient care, Patient monitoring, Pneumodynamics, Poles and zeros, Ventilation, ARMA model, T-tube test, Autoregressive moving average model, Extubation process, Mechanical ventilation, Optimal model, Patient classification, Respiratory flow signal, Roots, Spontaneous breathing, Weaning trials


Sarlabous, L., Torres, A., Fiz, J. A., Morera, J., Jané, R., (2012). Evaluation and adaptive attenuation of the cardiac vibration interference in mechanomyographic signals Engineering in Medicine and Biology Society (EMBC) 34th Annual International Conference of the IEEE , IEEE (San Diego, USA) , 3400-3403

The study of the mechanomyographic signal of the diaphragm muscle (MMGdi) is a promising technique in order to evaluate the respiratory muscles effort. The relationship between amplitude and frequency parameters of this signal with the respiratory effort performed during respiration is of great interest for researchers and physicians due to its diagnostic potentials. However, MMGdi signals are frequently contaminated by a cardiac vibration or mechanocardiographic (MCG) signal. An adaptive noise cancellation (ANC) can be used to reduce the MCG interference in the recorded MMGdi activity. In this paper, it is evaluated the proposed ANC scheme by means of a synthetic MMGdi signal with a controlled MCG interference. The Pearson's correlation coefficient (PCC) between both root mean square (RMS) and mean frequency (fm) of the synthetic MMGdi signal are considerably reduced with the presence of cardiac vibration noise (from 0.95 to 0.87, and from 0.97 to 0.76, respectively). With the ANC algorithm proposed the effect of the MCG noise on the amplitude and frequency of MMG parameters is reduced considerably (PCC of 0.93 and 0.97 for the RMS and fm, respectively). The ANC method proposed in this work is an interesting technique to attenuate the cardiac interference in respiratory MMG signals. Further investigation should be carried out to evaluate the performance of the ANC algorithm in real MMGdi signals.

Keywords: Adaptive filters, Frequency modulation, Interference, Muscles, Noise cancellation, Vibrations, Cardiology, Medical signal processing, Muscle, Signal denoising, ANC algorithm, MCG interference, Pearson correlation coefficient, Adaptive noise cancellation, Cardiac vibration interference, Cardiac vibration noise, Diaphragm muscle, Mechanocardiographic signal, Mechanomyographic signals, Respiratory muscles effort


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


Mesquita, J., Poree, F., Carrault, G., Fiz, J. A., Abad, J., Jané, R., (2012). Respiratory and spontaneous arousals in patients with Sleep Apnea Hypopnea Syndrome Engineering in Medicine and Biology Society (EMBC) 34th Annual International Conference of the IEEE , IEEE (San Diego, USA) , 6337-6340

Sleep in patients with Sleep Apnea-Hypopnea Syndrome (SAHS) is frequently interrupted with arousals. Increased amounts of arousals result in shortening total sleep time and repeated sleep-arousal change can result in sleep fragmentation. According to the American Sleep Disorders Association (ASDA) an arousal is a marker of sleep disruption representing a detrimental and harmful feature for sleep. The nature of arousals and its role on the regulation of the sleep process raises controversy and has sparked the debate in the last years. In this work, we analyzed and compared the EEG spectral content of respiratory and spontaneous arousals on a database of 45 SAHS subjects. A total of 3980 arousals (1996 respiratory and 1984 spontaneous) were analyzed. The results showed no differences between the spectral content of the two kinds of arousals. Our findings raise doubt as to whether these two kinds of arousals are truly triggered by different organic mechanisms. Furthermore, they may also challenge the current beliefs regarding the underestimation of the importance of spontaneous arousals and their contribution to sleep fragmentation in patients suffering from SAHS.

Keywords: Adaptive filters, Correlation, Databases, Electroencephalography, Hospitals, Sleep apnea, Electroencephalography, Medical signal processing, Pneumodynamics, Sleep, EEG spectral content, Organic mechanism, Respiratory, Sleep apnea hypopnea syndrome, Sleep fragmentation, Spectral content, Spontaneous arousal


Cagido, Viviane Ramos, Zin, Walter Araujo, Ramirez, Jose, Navajas, Daniel, Farre, Ramon, (2011). Alternating ventilation in a rat model of increased abdominal pressure Respiratory Physiology & Neurobiology , 175, (3), 310-315

During alternating ventilation (AV) one lung is inflating while the other is deflating. Considering the possible respiratory and hemodynamic advantages of AV, we investigated its effects during increased intra-abdominal pressure (IAP = 10 mmHg). In Sprague-Dawley rats (n = 6, 270–375 g) the main bronchi were independently cannulated, and respiratory mechanics determined while animals underwent different ventilatory patterns: synchronic ventilation without increased IAP (SV-0), elevated IAP during SV (SV-10), and AV with elevated IAP (AV-10). Thirty-three other animals (SV-0, n = 10; SV-10, n = 11 and AV-10, n = 12) were ventilated during 3 h. Mean arterial pressure (MAP), and lung histology were assessed. Increased IAP resulted in significantly higher elastances (p < 0.001), being AV-10 lower than SV-10 (p < 0.020). SV-10 showed higher central venous pressure (p < 0.003) than S-0; no change was observed in AV-10. Wet/dry lung weight ratio was lower in AV-10 than SV-10 (p = 0.009). Application of AV reduced hemodynamic and lung impairments induced by increased IAP during SV.

Keywords: Alternating ventilation, Respiratory mechanics, Intra-abdominal pressure, Hemodynamic, Mechanical ventilation, Animal model


Carreras, Alba, Wang, Yang, Gozal, David, Montserrat, Josep M., Navajas, Daniel, Farre, Ramon, (2011). Non-invasive system for applying airway obstructions to model obstructive sleep apnea in mice Respiratory Physiology & Neurobiology , 175, (1), 164-168

Obstructive sleep apnea (OSA) is characterized by recurrent upper airway obstructions during sleep. The most common animal model of OSA is based on subjecting rodents to intermittent hypoxic exposures and does not mimic important OSA features, such as recurrent hypercapnia and increased inspiratory efforts. To circumvent some of these issues, a novel murine model involving non-invasive application of recurrent airway obstructions was developed. An electronically controlled airbag system is placed in front of the mouse's snout, whereby inflating the airbag leads to obstructed breathing and spontaneous breathing occurs with the airbag deflated. The device was tested on 29 anesthetized mice by measuring inspiratory effort and arterial oxygen saturation (SaO(2)). Application of recurrent obstructive apneas (6s each, 120/h) for 6h resulted in SaO(2) oscillations to values reaching 84.4 +/- 2.5% nadir, with swings mimicking OSA patients. This novel system, capable of applying controlled recurrent airway obstructions in mice, is an easy-to-use tool for investigating pertinent aspects of OSA.

Keywords: Animal model, Upper airway Obstruction, Mouse model, Non-invasive system, Model sleep apnea, Respiratory disease


Garde, A., Sörnmo, L., Jané, R., Giraldo, B., (2010). Breathing pattern characterization in chronic heart failure patients using the respiratory flow signal Annals of Biomedical Engineering , 38, (12), 3572-3580

This study proposes a method for the characterization of respiratory patterns in chronic heart failure (CHF) patients with periodic breathing (PB) and nonperiodic breathing (nPB), using the flow signal. Autoregressive modeling of the envelope of the respiratory flow signal is the starting point for the pattern characterization. Spectral parameters extracted from the discriminant frequency band (DB) are used to characterize the respiratory patterns. For each classification problem, the most discriminant parameter subset is selected using the leave-one-out cross-validation technique. The power in the right DB provides an accuracy of 84.6% when classifying PB vs. nPB patterns in CHF patients, whereas the power of the DB provides an accuracy of 85.5% when classifying the whole group of CHF patients vs. healthy subjects, and 85.2% when classifying nPB patients vs. healthy subjects.

Keywords: Chronic heart failure, AR modeling, Respiratory pattern, Discriminant band, Periodic and nonperiodic breathing


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


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


Sarlabous, L., Torres, A., Fiz, J. A., Gea, J., Marti nez-Llorens, J. M., Morera, J., Jané, R., (2010). Interpretation of the approximate entropy using fixed tolerance values as a measure of amplitude variations in biomedical signals Engineering in Medicine and Biology Society (EMBC) 32nd Annual International Conference of the IEEE , IEEE (Buenos Aires, Argentina) , 5967-5970

A new method for the quantification of amplitude variations in biomedical signals through moving approximate entropy is presented. Unlike the usual method to calculate the approximate entropy (ApEn), in which the tolerance value (r) varies based on the standard deviation of each moving window, in this work ApEn has been computed using a fixed value of r. We called this method, moving approximate entropy with fixed tolerance values: ApEn/sub f/. The obtained results indicate that ApEn/sub f/ allows determining amplitude variations in biomedical data series. These amplitude variations are better determined when intermediate values of tolerance are used. The study performed in diaphragmatic mechanomyographic signals shows that the ApEn/sub f/ curve is more correlated with the respiratory effort than the standard RMS amplitude parameter. Furthermore, it has been observed that the ApEn/sub f/ parameter is less affected by the existence of impulsive, sinusoidal, constant and Gaussian noises in comparison with the RMS amplitude parameter.

Keywords: Practical, Theoretical or Mathematical/ biomechanics, Entropy, Gaussian noise, Medical signal processing, Muscle, Random processes/ approximate entropy interpretation, Fixed tolerance values, Diaphragmatic mechanomyographic signals, ApEnf curve, Respiratory effort, Gaussian noises


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


Sellares, J., Acerbi, I., Loureiro, H., Dellaca, R. L., Ferrer, M., Torres, A., Navajas, D., Farre, R., (2009). Respiratory impedance during weaning from mechanical ventilation in a mixed population of critically ill patients British Journal of Anaesthesia , 103, (6), 828-832

Worsening of respiratory mechanics during a spontaneous breathing trial (SBT) has been traditionally associated with weaning failure, although this finding is based on studies with chronic obstructive pulmonary disease patients only. The aim of our study was to assess the course of respiratory impedance non-invasively measured by forced oscillation technique (FOT) during a successful and failed SBT in a mixed population. Thirty-four weaning trials were reported in 29 consecutive mechanically ventilated patients with different causes of initiation of ventilation. During the SBT, the patient was breathing through a conventional T-piece connected to the tracheal tube. FOT (5 Hz, +/- 1 cm H2O, 30 s) was applied at 5, 10, 15, 20, 25, and 30 min. Respiratory resistance (Rrs) and reactance (Xrs) were computed from pressure and flow measurements. The frequency to tidal volume ratio f/V-t was obtained from the flow signal. At the end of the trial, patients were divided into two groups: SBT success and failure. Mixed model analysis showed no significant differences in Rrs and Xrs over the course of the SBT, or between the success (n=16) and the failure (n=18) groups. In contrast, f/V-t was significantly (P < 0.001) higher in the failure group. Worsening of respiratory impedance measured by FOT is not a common finding during a failed SBT in a typically heterogeneous intensive care unit population of mechanically ventilated patients.

Keywords: Ventilation, High frequency oscillation, Ventilation, Mechanical, Ventilation, Respiratory impedance


Puig, F., Gavara, N., Sunyer, R., Carreras, A., Farre, R., Navajas, D., (2009). Stiffening and contraction induced by dexamethasone in alveolar epithelial cells Experimental Mechanics , 49, (1), 47-55

The structural integrity of the alveolar monolayer, which is compromised during lung inflammation, is determined by the balance between cell-cell and cell-matrix tethering forces and the centripetal forces owing to cell viscoelasticity and contraction. Dexamethasone is an anti-inflammatory glucocorticoid with protective effects in lung injury. To determine the effects of Dexamethasone on the stiffness and contractility of alveolar epithelial cells. Cell stiffness (G') and average traction exerted by the cell (T) were measured by magnetic twisting cytometry and by traction microscopy, respectively. A549 cells were treated 24 h with Dexamethasone (1 mu M) or vehicle (control). G' and T were measured before and 5 min after challenge with the inflammatory mediator Thrombin (0.5 U/ml). Changes induced by Dexamethasone in actin cytoskeleton polymerization were assessed by the fluorescent ratio between F-actin and G-actin obtained by staining cells with phalloidin and DNase I. Dexamethasone significantly increased G' and T by 56% (n = 11; p < 0.01) and by 80% (n = 17; p < 0.05), respectively. Dexamethasone also increased F/G-actin ratio from 2.68 +/- 0.07 to 2.96 +/- 0.09 (n = 10; p < 0.05). The relative increase in stiffness and contraction induced by Thrombin in control cells was significantly (p < 0.05) reduced by Dexamethasone treatment: from 190 to 98% in G' and from 318 to 105% in T. The cytoskeleton remodelling and the increase in cell stiffness and contraction induced by Dexamethasone could account for its protective effect in the alveolar epithelium when subjected to inflammatory challenge.

Keywords: Cell mechanics, Cytoskeleton, Magnetic twisting cytometry, Traction microscopy, Respiratory diseases


Farre, R., Montserrat, J. M., Navajas, D., (2008). Assessment of upper airway mechanics during sleep Respiratory Physiology & Neurobiology , 163, (1-3), 74-81

Obstructive sleep apnea, which is the most prevalent sleep breathing disorder, is characterized by recurrent episodes of upper airway collapse and reopening. However, the mechanical properties of the upper airway are not directly measured in routine polysomnography because only qualitative sensors (thermistors for flow and thoraco-abdominal bands for pressure) are used. This review focuses on two techniques that quantify upper airway obstruction during sleep. A Starling model of collapsible conduit allows us to interpret the mechanics of the upper airway by means of two parameters: the critical pressure (Pcrit) and the upstream resistance (Rup). A simple technique to measure Pcrit and Rup involves the application of different levels of continuous positive airway pressure (CPAP) during sleep. The forced oscillation technique is another non-invasive procedure for quantifying upper airway impedance during the breathing cycle in sleep studies. The latest developments in these two methods allow them to be easily applied on a routine basis in order to more fully characterize upper airway mechanics in patients with sleep breathing disorders.

Keywords: Obstructive sleep apnea, Upper airway, Airway resistance, Critical pressure, Respiratory impedance


Orini, Michele, Giraldo, Beatriz F., Bailon, Raquel, Vallverdu, Montserrat, Mainardi, Luca, Benito, Salvador, Diaz, Ivan, Caminal, Pere, (2008). Time-frequency analysis of cardiac and respiratory parameters for the prediction of ventilator weaning 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, 2793-2796

Mechanical ventilators are used to provide life support in patients with respiratory failure. Assessing autonomic control during the ventilator weaning provides information about physiopathological imbalances. Autonomic parameters can be derived and used to predict success in discontinuing from the mechanical support. Time-frequency analysis is used to derive cardiac and respiratory parameters, as well as their evolution in time, during ventilator weaning in 130 patients. Statistically significant differences have been observed in autonomic parameters between patients who are considered ready for spontaneous breathing and patients who are not. A classification based on respiratory frequency, heart rate and heart rate variability spectral components has been proposed and has been able to correctly classify more than 80% of the cases.

Keywords: Automatic Data Processing, Databases, Factual, Electrocardiography, Humans, Models, Statistical, Respiration, Respiration, Artificial, Respiratory Insufficiency, Respiratory Mechanics, Respiratory Muscles, Signal Processing, Computer-Assisted, Time Factors, Ventilator Weaning, Ventilators, Mechanical, Work of Breathing