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Badiola-Mateos, M., Hervera, A., del Río, J. A., Samitier, J., (2018). Challenges and future prospects on 3D in-vitro modeling of the neuromuscular circuit Frontiers in Bioengineering and Biotechnology 6, Article 194

Movement of skeletal-muscle fibers is generated by the coordinated action of several cells taking part within the locomotion circuit (motoneurons, sensory-neurons, Schwann cells, astrocytes, microglia, and muscle-cells). Failures in any part of this circuit could impede or hinder coordinated muscle movement and cause a neuromuscular disease (NMD) or determine its severity. Studying fragments of the circuit cannot provide a comprehensive and complete view of the pathological process. We trace the historic developments of studies focused on in-vitro modeling of the spinal-locomotion circuit and how bioengineered innovative technologies show advantages for an accurate mimicking of physiological conditions of spinal-locomotion circuit. New developments on compartmentalized microfluidic culture systems (cμFCS), the use of human induced pluripotent stem cells (hiPSCs) and 3D cell-cultures are analyzed. We finally address limitations of current study models and three main challenges on neuromuscular studies: (i) mimic the whole spinal-locomotion circuit including all cell-types involved and the evaluation of independent and interdependent roles of each one; (ii) mimic the neurodegenerative response of mature neurons in-vitro as it occurs in-vivo; and (iii) develop, tune, implement, and combine cμFCS, hiPSC, and 3D-culture technologies to ultimately create patient-specific complete, translational, and reliable NMD in-vitro model. Overcoming these challenges would significantly facilitate understanding the events taking place in NMDs and accelerate the process of finding new therapies.

Keywords: 3D-culture, Compartmentalized microfluidic culture systems (cμFCS), HiPSC, In-vitro models, Neuromuscular circuit

Moulin-Frier, C., Fischer, T., Petit, M., Pointeau, G., Puigbo, J., Pattacini, U., Low, S. C., Camilleri, D., Nguyen, P., Hoffmann, M., Chang, H. J., Zambelli, M., Mealier, A., Damianou, A., Metta, G., Prescott, T. J., Demiris, Y., Dominey, P. F., Verschure, P. F. M. J., (2018). DAC-h3: A proactive robot cognitive architecture to acquire and express knowledge about the world and the self IEEE Transactions on Cognitive and Developmental Systems 10, (4), 1005-1022

This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based on a biologically-grounded theory of the brain and mind, integrates a reactive interaction engine, a number of state-of-the art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The architecture as a whole drives the robot behavior to solve the symbol grounding problem, acquire language capabilities, execute goal-oriented behavior, and express a verbal narrative of its own experience in the world. We validate our approach in human-robot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in real time within a realistic scenario and that it can be used with naive users.

Keywords: Autobiographical Memory., Biology, Cognition, Cognitive Robotics, Computer architecture, Distributed Adaptive Control, Grounding, Human-Robot Interaction, Humanoid robots, Robot sensing systems, Symbol Grounding

Freire, I. T., Moulin-Frier, C., Sanchez-Fibla, M., Arsiwalla, X. D., Verschure, P., (2018). Modeling the formation of social conventions in multi-agent populations ARXIV Computer Science, (Multiagent Systems), 1-30

In order to understand the formation of social conventions we need to know the specific role of control and learning in multi-agent systems. To advance in this direction, we propose, within the framework of the Distributed Adaptive Control (DAC) theory, a novel Control-based Reinforcement Learning architecture (CRL) that can account for the acquisition of social conventions in multi-agent populations that are solving a benchmark social decision-making problem. Our new CRL architecture, as a concrete realization of DAC multi-agent theory, implements a low-level sensorimotor control loop handling the agent's reactive behaviors (pre-wired reflexes), along with a layer based on model-free reinforcement learning that maximizes long-term reward. We apply CRL in a multi-agent game-theoretic task in which coordination must be achieved in order to find an optimal solution. We show that our CRL architecture is able to both find optimal solutions in discrete and continuous time and reproduce human experimental data on standard game-theoretic metrics such as efficiency in acquiring rewards, fairness in reward distribution and stability of convention formation.

Keywords: Computer Science, Multiagent Systems

Silva, N., Riveros, A., Yutronic, N., Lang, E., Chornik, B., Guerrero, S., Samitier, J., Jara, P., Kogan, M. J., (2018). Photothermally controlled methotrexate release system using β-cyclodextrin and gold nanoparticles Nanomaterials 8, (12), 985

The inclusion compound (IC) of cyclodextrin (CD) containing the antitumor drug Methotrexate (MTX) as a guest molecule was obtained to increase the solubility of MTX and decrease its inherent toxic effects in nonspecific cells. The IC was conjugated with gold nanoparticles (AuNPs), obtained by a chemical method, creating a ternary intelligent delivery system for MTX molecules, based on the plasmonic properties of the AuNPs. Irradiation of the ternary system, with a laser wavelength tunable with the corresponding surface plasmon of AuNPs, causes local energy dissipation, producing the controlled release of the guest from CD cavities. Finally, cell viability was evaluated using MTS assays for β-CD/MTX and AuNPs + β-CD/MTX samples, with and without irradiation, against HeLa tumor cells. The irradiated sample of the ternary system AuNPs + β-CD/MTX produced a diminution in cell viability attributed to the photothermal release of MTX.

Keywords: Cyclodextrin, Delivery system, Gold nanoparticles, Inclusion compound, Irradiation, Laser, Methotrexate, Photothermal release

Garreta, E., González, F., Montserrat, N., (2018). Studying kidney disease using tissue and genome engineering in human pluripotent stem cells Nephron , 138, 48-59

Kidney morphogenesis and patterning have been extensively studied in animal models such as the mouse and zebrafish. These seminal studies have been key to define the molecular mechanisms underlying this complex multistep process. Based on this knowledge, the last 3 years have witnessed the development of a cohort of protocols allowing efficient differentiation of human pluripotent stem cells (hPSCs) towards defined kidney progenitor populations using two-dimensional (2D) culture systems or through generating organoids. Kidney organoids are three-dimensional (3D) kidney-like tissues, which are able to partially recapitulate kidney structure and function in vitro. The current possibility to combine state-of-the art tissue engineering with clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated systems 9 (Cas9)-mediated genome engineering provides an unprecedented opportunity for studying kidney disease with hPSCs. Recently, hPSCs with genetic mutations introduced through CRISPR/Cas9-mediated genome engineering have shown to produce kidney organoids able to recapitulate phenotypes of polycystic kidney disease and glomerulopathies. This mini review provides an overview of the most recent advances in differentiation of hPSCs into kidney lineages, and the latest implementation of the CRISPR/Cas9 technology in the organoid setting, as promising platforms to study human kidney development and disease.

Keywords: Clustered regularly interspaced short palindromic repeats/CRISPR-associated systems 9, Disease modeling, Gene editing, Human pluripotent stem cells, Kidney genetics, Tissue engineering

Verschure, P., (2018). The architecture of mind and brain Living machines: A handbook of research in biomimetics and biohybrid systems (ed. Prescott, T. J., Lepora, Nathan, Verschure, P.), Oxford Scholarship (Oxford, UK) , 338-345

The components of a Living Machine must be integrated into a functioning whole, which requires a detailed understanding of the architecture of living machines. This chapter starts with a conceptual and historical analysis which from Plato brings us to nineteenth-century neuroscience and early concepts of the layered structure of nervous systems. These concepts were further captured in the cognitive behaviorism of Tolman and came to full fruition in the cognitive revolution of the second half of the twentieth century. Verschure subsequently describes the most relevant proposals of cognitive architectures followed by an overview of the few proposals stemming from modern neuroscience on the architecture of the brain. Subsequently, we will look at contemporary contenders that mediate between cognitive and brain architecture. An important challenge to any model of cognitive architectures is how to benchmark it. Verschure proposes the Unified Theories of Embodied Minds (UTEM) benchmark which advances from Newell’s classic Unified Theories of Cognition benchmark.

Keywords: Architecture, Mind, Brain, Organization, System, Virtualization, Abstraction layers

Verschure, P., (2018). A chronology of Distributed Adaptive Control Living machines: A handbook of research in biomimetics and biohybrid systems (ed. Prescott, T. J., Lepora, Nathan, Verschure, P.), Oxford Scholarship (Oxford, UK) , 346-360

This chapter presents the Distributed Adaptive Control (DAC) theory of the mind and brain of living machines. DAC provides an explanatory framework for biological brains and an integration framework for synthetic ones. DAC builds on several themes presented in the handbook: it integrates different perspectives on mind and brain, exemplifies the synthetic method in understanding living machines, answers well-defined constraints faced by living machines, and provides a route for the convergent validation of anatomy, physiology, and behavior in our explanation of biological living machines. DAC addresses the fundamental question of how a living machine can obtain, retain, and express valid knowledge of its world. We look at the core components of DAC, specific benchmarks derived from the engagement with the physical and the social world (the H4W and the H5W problems) in foraging and human–robot interaction tasks. Lastly we address how DAC targets the UTEM benchmark and the relation with contemporary developments in AI.

Keywords: Distributed Adaptive Control, Problem of priors, Symbol grounding problem, Convergent validation, Foraging, brain, Architecture, system

Vouloutsi, Vasiliki, Halloy, José, Mura, Anna, Mangan, Michael, Lepora, Nathan, Prescott, T. J., Verschure, P., (2018). Biomimetic and Biohybrid Systems 7th International Conference, Living Machines 2018, Paris, France, July 17–20, 2018, Proceedings , Springer International Publishing (Lausanne, Switzerland) 10928, 1-551

This book constitutes the proceedings of the 7th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2018, held in Paris, France, in July 2018. The 40 full and 18 short papers presented in this volume were carefully reviewed and selected from 60 submissions. The theme of the conference targeted at the intersection of research on novel life-like technologies inspired by the scientific investigation of biological systems, biomimetics, and research that seeks to interface biological and artificial systems to create biohybrid systems.

Keywords: Artificial neural network, Bio-actuators, Bio-robotics, Biohybrid systems, Biomimetics, Bipedal robots, Earthoworm-like robots, Robotics, Decision-making, Tactile sensing, Soft robots, Locomotion, Insects, Sensors, Actuators, Robots, Artificial intelligence, Neural networks, Motion planning, Learning algorithms

Prescott, T. J., Lepora, Nathan, Verschure, P., (2018). Living machines: A handbook of research in biomimetics and biohybrid systems Oxford Scholarship , 1-623

Biomimetics is the development of novel technologies through the distillation of ideas from the study of biological systems. Biohybrids are formed through the combination of at least one biological component—an existing living system—and at least one artificial, newly engineered component. These two fields are united under the theme of Living Machines—the idea that we can construct artifacts that not only mimic life but also build on the same fundamental principles. The research described in this volume seeks to understand and emulate life’s ability to self-organize, metabolize, grow, and reproduce; to match the functions of living tissues and organs such as muscles, skin, eyes, ears, and neural circuits; to replicate cognitive and physical capacities such as perception, attention, locomotion, grasp, emotion, and consciousness; and to assemble all of these elements into integrated systems that can hold a technological mirror to life or that have the capacity to merge with it. We conclude with contributions from philosophers, ethicists, and futurists on the potential impacts of this remarkable research on society and on how we see ourselves.

Keywords: Novel technologies, Biomimetics, Biohybrids, Living systems, Living machines, Biological principles, Technology ethics, Societal impacts

Solorzano, A., Fonollosa, J., Fernandez, L., Eichmann, J., Marco, S., (2017). Fire detection using a gas sensor array with sensor fusion algorithms IEEE Conference Publications ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) , IEEE (Montreal, Canada) , 1-3

Conventional fire alarms are based on smoke detection. Nevertheless, in some fire scenarios volatiles are released before smoke. Fire detectors based only on chemical sensors have already been proposed as they may provide faster response, but they are still prone to false alarms in the presence of nuisances. These systems rely heavily on pattern recognition techniques to discriminate fires from nuisances. In this context, it is important to test the systems according to international standards for fires and testing the system against a diversity of nuisances. In this work, we investigate the behavior of a gas sensor array coupled to sensor fusion algorithms for fire detection when exposed to standardized fires and several nuisances. Results confirmed the ability to detect fires (97% Sensitivity), although the system still produces a significant rate of false alarms (35%) for nuisances not presented in the training set.

Keywords: Fire alarm, Gas sensor array, Machine Olfaction, Multisensor system, Sensor fusion

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

Tomas-Roig, J., Piscitelli, F., Gil, V., del Río, J. A., Moore, T. P., Agbemenyah, H., Salinas-Riester, G., Pommerenke, C., Lorenzen, S., Beißbarth, T., Hoyer-Fender, S., Di Marzo, V., Havemann-Reinecke, U., (2016). Social defeat leads to changes in the endocannabinoid system: An overexpression of calreticulin and motor impairment in mice Behavioural Brain Research , 303, 34-43

Prolonged and sustained stimulation of the hypothalamo-pituitary-adrenal axis have adverse effects on numerous brain regions, including the cerebellum. Motor coordination and motor learning are essential for animal and require the regulation of cerebellar neurons. The G-protein-coupled cannabinoid CB1 receptor coordinates synaptic transmission throughout the CNS and is of highest abundance in the cerebellum. Accordingly, the aim of this study was to investigate the long-lasting effects of chronic psychosocial stress on motor coordination and motor learning, CB1 receptor expression, endogenous cannabinoid ligands and gene expression in the cerebellum. After chronic psychosocial stress, motor coordination and motor learning were impaired as indicated the righting reflex and the rota-rod. The amount of the endocannabinoid 2-AG increased while CB1 mRNA and protein expression were downregulated after chronic stress. Transcriptome analysis revealed 319 genes differentially expressed by chronic psychosocial stress in the cerebellum; mainly involved in synaptic transmission, transmission of nerve impulse, and cell-cell signaling. Calreticulin was validated as a stress candidate gene. The present study provides evidence that chronic stress activates calreticulin and might be one of the pathological mechanisms underlying the motor coordination and motor learning dysfunctions seen in social defeat mice.

Keywords: Psychosocial stress, Cerebellum, Calreticulin, Endocannabinoid system, Behavior, RNA seq.

Torres, M., Rojas, M., Campillo, N., Cardenes, N., Montserrat, J. M., Navajas, D., Farré, R., (2015). Parabiotic model for differentiating local and systemic effects of continuous and intermittent hypoxia Journal of Applied Physiology , 118, (1), 42-47

Hypoxia can be damaging either because cells are directly sensitive to low oxygen pressure in their local microenvironment and/or because they are exposed to circulating factors systemically secreted in response to hypoxia. The conventional hypoxia model, breathing hypoxic air, does not allow one to distinguish between these local and systemic effects. Here we propose and validate a model for differentially applying local and systemic hypoxic challenges in an animal. We used parabiosis, two mice sharing circulation by surgical union through the skin, and tested the hypothesis that when one of the parabionts breathes room air and the other one is subjected to hypoxic air, both mice share systemic circulation but remain normoxic and hypoxic, respectively. We tested two common hypoxic paradigms in 10 parabiotic pairs: continuous hypoxia (10% O2) mimicking chronic lung diseases, and intermittent hypoxia (40 s, 21% O2; 20 s, 5% O2) simulating sleep apnea. Arterial oxygen saturation and oxygen partial pressure at muscle tissue were measured in both parabionts. Effective cross-circulation was assessed by intraperitoneally injecting a dye in one of the parabionts and measuring blood dye concentration in both animals after 2 h. The results confirmed the hypothesis that tissues of the parabiont under room air were perfused with normally oxygenated blood and, at the same time, were exposed to all of the systemic mediators secreted by the other parabiont actually subjected to hypoxia. In conclusion, combination of parabiosis and hypoxic/normoxic air breathing is a novel approach to investigate the effects of local and systemic hypoxia in respiratory diseases.

Keywords: Animal model, Local hypoxia, Parabiosis, Systemic hypoxia

Aviles, A. I., Alsaleh, S. M., Sobrevilla, P., Casals, A., (2015). Force-feedback sensory substitution using supervised recurrent learning for robotic-assisted surgery Engineering in Medicine and Biology Society (EMBC) 37th Annual International Conference of the IEEE , IEEE (Milan, Italy) , 1-4

The lack of force feedback is considered one of the major limitations in Robot Assisted Minimally Invasive Surgeries. Since add-on sensors are not a practical solution for clinical environments, in this paper we present a force estimation approach that starts with the reconstruction of a 3D deformation structure of the tissue surface by minimizing an energy functional. A Recurrent Neural Network-Long Short Term Memory (RNN-LSTM) based architecture is then presented to accurately estimate the applied forces. According to the results, our solution offers long-term stability and shows a significant percentage of accuracy improvement, ranging from about 54% to 78%, over existing approaches.

Keywords: Computer architecture, Estimation, Force, Microprocessors, Robot sensing systems, Surgery

Mur, O., Frigola, M., Casals, A., (2015). Modelling daily actions through hand-based spatio-temporal features ICAR 2015 International Conference on Advanced Robotics , IEEE (Istanbul, Turkey) , 478-483

In this paper, we propose a new approach to domestic action recognition based on a set of features which describe the relation between poses and movements of both hands. These features represent a set of basic actions in a kitchen in terms of the mimics of the hand movements, without needing information of the objects present in the scene. They address specifically the intra-class dissimilarity problem, which occurs when the same action is performed in different ways. The goal is to create a generic methodology that enables a robotic assistant system to recognize actions related to daily life activities and then, be endowed with a proactive behavior. The proposed system uses depth and color data acquired from a Kinect-style sensor and a hand tracking system. We analyze the relevance of the proposed hand-based features using a state-space search approach. Finally, we show the effectiveness of our action recognition approach using our own dataset.

Keywords: Histograms, Joints, Robot sensing systems, Thumb, Tracking, Human activity recognition, Disable and elderly assistance

Aviles, A. I., Alsaleh, S., Sobrevilla, P., Casals, A., (2015). Sensorless force estimation using a neuro-vision-based approach for robotic-assisted surgery NER 2015 7th International IEEE/EMBS Conference on Neural Engineering , IEEE (Montpellier, France) , 86-89

This paper addresses the issue of lack of force feedback in robotic-assisted minimally invasive surgeries. Force is an important measure for surgeons in order to prevent intra-operative complications and tissue damage. Thus, an innovative neuro-vision based force estimation approach is proposed. Tissue surface displacement is first measured via minimization of an energy functional. A neuro approach is then used to establish a geometric-visual relation and estimate the applied force. The proposed approach eliminates the need of add-on sensors, carrying out biocompatibility studies and is applicable to tissues of any shape. Moreover, we provided an improvement from 15.14% to 56.16% over other approaches which demonstrate the potential of our proposal.

Keywords: Estimation, Force, Minimally invasive surgery, Robot sensing systems, Three-dimensional displays

Fernàndez-Busquets, X., (2014). Toy kit against malaria: Magic bullets, LEGO, Trojan horses and Russian dolls Therapeutic Delivery , 5, (10), 1049-1052

Bennetts, Victor, Schaffernicht, Erik, Pomareda, Victor, Lilienthal, Achim, Marco, Santiago, Trincavelli, Marco, (2014). Combining non selective gas sensors on a mobile robot for identification and mapping of multiple chemical compounds Sensors 14, (9), 17331-17352

In this paper, we address the task of gas distribution modeling in scenarios where multiple heterogeneous compounds are present. Gas distribution modeling is particularly useful in emission monitoring applications where spatial representations of the gaseous patches can be used to identify emission hot spots. In realistic environments, the presence of multiple chemicals is expected and therefore, gas discrimination has to be incorporated in the modeling process. The approach presented in this work addresses the task of gas distribution modeling by combining different non selective gas sensors. Gas discrimination is addressed with an open sampling system, composed by an array of metal oxide sensors and a probabilistic algorithm tailored to uncontrolled environments. For each of the identified compounds, the mapping algorithm generates a calibrated gas distribution model using the classification uncertainty and the concentration readings acquired with a photo ionization detector. The meta parameters of the proposed modeling algorithm are automatically learned from the data. The approach was validated with a gas sensitive robot patrolling outdoor and indoor scenarios, where two different chemicals were released simultaneously. The experimental results show that the generated multi compound maps can be used to accurately predict the location of emitting gas sources.

Keywords: Environmental monitoring, Gas discrimination, Gas distribution mapping, Service robots, Open sampling systems, PID, Metal oxide sensors

Juanola-Feliu, E., Miribel-Català, P. L., Avilés, C. P., Colomer-Farrarons, J., González-Piñero, M., Samitier, J., (2014). Design of a customized multipurpose nano-enabled implantable system for in-vivo theranostics Sensors 14, (10), 19275-19306

The first part of this paper reviews the current development and key issues on implantable multi-sensor devices for in vivo theranostics. Afterwards, the authors propose an innovative biomedical multisensory system for in vivo biomarker monitoring that could be suitable for customized theranostics applications. At this point, findings suggest that cross-cutting Key Enabling Technologies (KETs) could improve the overall performance of the system given that the convergence of technologies in nanotechnology, biotechnology, micro&nanoelectronics and advanced materials permit the development of new medical devices of small dimensions, using biocompatible materials, and embedding reliable and targeted biosensors, high speed data communication, and even energy autonomy. Therefore, this article deals with new research and market challenges of implantable sensor devices, from the point of view of the pervasive system, and time-to-market. The remote clinical monitoring approach introduced in this paper could be based on an array of biosensors to extract information from the patient. A key contribution of the authors is that the general architecture introduced in this paper would require minor modifications for the final customized bio-implantable medical device.

Keywords: Biocompatible, Biosensor, Biotelemetry, Implantable multi-sensor, Innovation, KET, Nanomedicine, Personalized medicine, Biotelemetry, Innovation, Medical nanotechnology, Biocompatible, Implantable system, In-vivo, KET, Multi sensor, Personalized medicines, Theranostics, Biosensors

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

Marco, S., Gutiérrez-Gálvez, A., Lansner, A., Martinez, D., Rospars, J. P., Beccherelli, R., Perera, A., Pearce, T., Vershure, P., Persaud, K., (2013). Biologically inspired large scale chemical sensor arrays and embedded data processing Proceedings of SPIE - The International Society for Optical Engineering Smart Sensors, Actuators, and MEMS VI , SPIE Digital Library (Grenoble, France) 8763, 1-15

Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. EU Funded Project NEUROCHEM (Bio-ICT-FET- 216916) has developed novel computing paradigms and biologically motivated artefacts for chemical sensing taking inspiration from the biological olfactory pathway. To demonstrate this approach, a biomimetic demonstrator has been built featuring a large scale sensor array (65K elements) in conducting polymer technology mimicking the olfactory receptor neuron layer, and abstracted biomimetic algorithms have been implemented in an embedded system that interfaces the chemical sensors. The embedded system integrates computational models of the main anatomic building blocks in the olfactory pathway: The olfactory bulb, and olfactory cortex in vertebrates (alternatively, antennal lobe and mushroom bodies in the insect). For implementation in the embedded processor an abstraction phase has been carried out in which their processing capabilities are captured by algorithmic solutions. Finally, the algorithmic models are tested with an odour robot with navigation capabilities in mixed chemical plumes.

Keywords: Antennal lobes, Artificial olfaction, Computational neuroscience, Olfactory bulbs, Plume tracking, Abstracting, Actuators, Algorithms, Biomimetic processes, Chemical sensors, Conducting polymers, Data processing, Flavors, Odors, Robots, Smart sensors, Embedded systems

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

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

Hernandez Bennetts, V. M., Lilienthal, A. J., Khaliq, A. A., Pomareda Sese, V., Trincavelli, M., (2013). Towards real-world gas distribution mapping and leak localization using a mobile robot with 3d and remote gas sensing capabilities 2013 IEEE International Conference on Robotics and Automation (ICRA) (ed. Parker, Lynne E.), IEEE (Karlsruhe, Germany) , 2335-2340

Due to its environmental, economical and safety implications, methane leak detection is a crucial task to address in the biogas production industry. In this paper, we introduce Gasbot, a robotic platform that aims to automatize methane emission monitoring in landfills and biogas production sites. The distinctive characteristic of the Gasbot platform is the use of a Tunable Laser Absorption Spectroscopy (TDLAS) sensor. This sensor provides integral concentration measurements over the path of the laser beam. Existing gas distribution mapping algorithms can only handle local measurements obtained from traditional in-situ chemical sensors. In this paper we also describe an algorithm to generate 3D methane concentration maps from integral concentration and depth measurements. The Gasbot platform has been tested in two different scenarios: an underground corridor, where a pipeline leak was simulated and in a decommissioned landfill site, where an artificial methane emission source was introduced.

Keywords: Laser beams, Measurement by laser beam, Mobile robots, Robot kinematics, Robot sensing systems

Guamán, Ana V., Carreras, Alba, Calvo, Daniel, Agudo, Idoya, Navajas, Daniel, Pardo, Antonio, Marco, Santiago, Farré, Ramon, (2012). Rapid detection of sepsis in rats through volatile organic compounds in breath Journal of Chromatography B , 881-882, 76-82

Background: Sepsis is one of the main causes of death in adult intensive care units. The major drawbacks of the different methods used for its diagnosis and monitoring are their inability to provide fast responses and unsuitability for bedside use. In this study, performed using a rat sepsis model, we evaluate breath analysis with Ion Mobility Spectrometry (IMS) as a fast, portable and non-invasive strategy. Methods: This study was carried out on 20 Sprague-Dawley rats. Ten rats were injected with lipopolysaccharide from Escherichia coli and ten rats were IP injected with regular saline. After a 24-h period, the rats were anaesthetized and their exhaled breaths were collected and measured with IMS and SPME-gas chromatography/mass spectrometry (SPME-GC/MS) and the data were analyzed with multivariate data processing techniques. Results: The SPME-GC/MS dataset processing showed 92% accuracy in the discrimination between the two groups, with a confidence interval of between 90.9% and 92.9%. Percentages for sensitivity and specificity were 98% (97.5–98.5%) and 85% (84.6–87.6%), respectively. The IMS database processing generated an accuracy of 99.8% (99.7–99.9%), a specificity of 99.6% (99.5–99.7%) and a sensitivity of 99.9% (99.8–100%). Conclusions: IMS involving fast analysis times, minimum sample handling and portable instrumentation can be an alternative for continuous bedside monitoring. IMS spectra require data processing with proper statistical models for the technique to be used as an alternative to other methods. These animal model results suggest that exhaled breath can be used as a point-of-care tool for the diagnosis and monitoring of sepsis.

Keywords: Sepsis, Volatile organic compounds, Ion mobility spectrometer, Rat model, Bedside patient systems, Non-invasive detection

Marco, S., Gutierrez-Galvez, A., (2012). Signal and data processing for machine olfaction and chemical sensing: A review IEEE Sensors Journal , 12, (11), 3189-3214

Signal and data processing are essential elements in electronic noses as well as in most chemical sensing instruments. The multivariate responses obtained by chemical sensor arrays require signal and data processing to carry out the fundamental tasks of odor identification (classification), concentration estimation (regression), and grouping of similar odors (clustering). In the last decade, important advances have shown that proper processing can improve the robustness of the instruments against diverse perturbations, namely, environmental variables, background changes, drift, etc. This article reviews the advances made in recent years in signal and data processing for machine olfaction and chemical sensing.

Keywords: Chemical sensors, Electronic nose, Intelligent sensors, Measurement techniques, Sensor arrays, Sensor systems

Fazel Zarandi, M. H., Avazbeigi, M., (2012). A multi-agent solution for reduction of bullwhip effect in fuzzy supply chains Journal of Intelligent and Fuzzy Systems , 23, (5), 259-268

In this paper, we present a new Multi-Agent System for reduction of the bullwhip effect in fuzzy supply chains. First, we show that a supply chain that uses an optimal ordering policy without data sharing among echelons still suffers from the bullwhip effect. Then, we propose the multi-agent solution to manage and reduce the bullwhip effect. The proposed multi-agent system includes four different types of agents in which each agent has its own list of actions. The proposed Multi-agent System applies a new Tabu Search algorithm for fuzzy rule generation, and a new data filtering algorithm for extraction of the bullwhip-free data from supply chain data warehouse. We validate the multi-agent system under different conditions and discuss how the system responds to different factors. The results show that the proposed multi-agent system reduces the bullwhip effect significantly in a rational time.

Keywords: Bullwhip effect, Bullwhip-free data, Decentralized decision making, Fuzzy rule base, Fuzzy supply chain, Fuzzy time series, Multi-agent system, Supply chain management

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

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

Amigo, L. E., Fernandez, Q., Giralt, X., Casals, A., Amat, J., (2012). Study of patient-orthosis interaction forces in rehabilitation therapies IEEE Conference Publications 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) , IEEE (Roma, Italy) , 1098-1103

The design of mechanical joints that kinematically behave as their biological counterparts is a challenge that if not addressed properly can cause inadequate forces transmission between robot and patient. This paper studies the interaction forces in rehabilitation therapies of the elbow joint. To measure the effect of orthosis-patient misalignments, a force sensor with a novel distributed architecture has been designed and used for this study. A test-bed based on an industrial robot acting as a virtual exoskeleton that emulates the action of a therapist has been developed and the interaction forces analyzed.

Keywords: Force, Force measurement, Force sensors, Joints, Medical treatment, Robot sensing systems, Force sensors, Medical robotics, Patient rehabilitation, Biological counterparts, Distributed architecture, Elbow joint, Force sensor, Inadequate forces transmission, Industrial robot, Mechanical joints design, Orthosis-patient misalignments, Patient-orthosis interaction forces, Rehabilitation therapies, Robot, Test-bed, Virtual exoskeleton

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

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

Fernandez, L., Gutierrez-Galvez, A., Marco, S., (2010). Gas sensor array system inspired on the sensory diversity and redundancy of the olfactory epithelium Procedia Engineering Eurosensor XXIV Conference (ed. Jakoby, B., Vellekoop, M.J.), Elsevier Science BV (Linz, Austria) 5, (0), 25-28

This paper presents a chemical sensing system that takes inspiration from the combination of sensory diversity and redundancy at the olfactory epithelium to enhance the chemical information obtained from the odorants. The system is based on commercial MOS sensors and achieves, first, diversity trough different types of MOS along with modulation of their temperatures, and second redundancy including 12 MOS sensors for each type (12×8) combined with a high-speed multiplexing system that allows connecting 16 load resistors with each and every one of the 96 sensors in about two seconds. Exposition of the system to ethanol, ammonia, and acetone at different concentrations shows how the system is able to capture a large amount of information of the identity and the concentration of the odorant.

Keywords: Gas sensor array, Biologically inspired system, Redundancy, Diversity, MOX sensors, Temperature modulation

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

Amigo, L.E., Casals, A., Amat, J., (2010). Polyarticulated architecture for the emulation of an isocentric joint in orthetic applications BioRob 2010 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics , IEEE (Tokyo, Japan) , 825-830

The design of orthotic devices that tries to fit to the anthropomorphic structure of human limbs faces the problem of achieving the highest approximation to the anatomical kinematics. This paper studies the main characteristics and performances of orthotic devices, mainly focusing on the upper limbs, and proposes a solution to the problem of the superposition of rotation and displacement of some joints, as the shoulder, elbow or knee. A 3 DoF virtual joint is proposed to emulate a human joint, solving the isocentricity and size adaptation of most current orthosis.

Keywords: Prosthetics and other practical applications, Prosthetics and orthotics, Prosthetic and orthotic control systems, Robotics, Biomechanics (mechanical engineering), Robot and manipulator mechanics

Fumagalli, L., Ferrari, G., Sampietro, M., Gomila, G., (2009). Quantitative nanoscale dielectric microscopy of single-layer supported biomembranes Nano Letters , 9, (4), 1604-1608

We present the experimental demonstration of low-frequency dielectric constant imaging of single-layer supported biomembranes at the nanoscale. The dielectric constant image has been quantitatively reconstructed by combining the thickness and local capacitance obtained using a scanning force microscope equipped with a sub-attofarad low-frequency capacitance detector. This work opens new possibilities for studying bioelectric phenomena and the dielectric properties of biological membranes at the nanoscale.

Keywords: Atomic-force microscopy, Nnear-field microscopy, Purple membrane, Scanning capacitance, Biological-systems, Fluid, Spectroscopy, Resolution, Proteins, Dynamics

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

Casals, A., Frigola, M., Amat, J., (2009). Robotics, a valuable tool in surgery Revista Iberoamericana de Automatica e Informatica Industrial , 6, (1), 5-19

Continuous advances on diagnostic techniques based on medical images, as well as the incorporation of new techniques in surgical instruments are progressively changing the new surgical procedures. Also, new minimally invasive techniques, which are currently highly consolidated, have produced significant advances, both from the technological and from the surgical treatment perspectives. The limitations that the manual realization of surgical interventions implies, in what refers to precision and accessibility, can be tackled with the help of robotics. In the same way, sensor based robot control techniques are opening new possibilities for the introduction of more improvements in these procedures, either relying on teleoperation, in which the surgeon and the robot establish their best synergy to get the optimal results, or by means of the automation of some specific actions or tasks. In this article the effect of robotics in the evolution of surgical techniques is described. Starting with a review of the robotics application fields, the article continues analyzing the methods and technologies involved in the process of robotizing surgical procedures, as well as the surgeon-robot interaction systems.

Keywords: Robotics, Medical Applications, Teleoperation, Biomedical Systems, Computer Aided Surgery, Human-Machine Interaction

Hernansanz, A., Amat, J., Casals, A., (2009). Optimization criterion for safety task transfer in cooperative robotics 14th International Conference on Advanced Robotics (ICAR) , IEEE (Munich, Germany) , 254-259

This paper presents a strategy for a cooperative multirobot system, constituting a virtual robot. The virtual robot is composed of a set of robotic arms acting as only one, transferring the execution of a teleoperated task from one to another when necessary. To decide which of the robots is the most suitable to execute the task at every instant, a multiparametric decision function has been defined. This function is based on a set of intrinsic and extrinsic evaluation indexes of the robot. Since the internal operation of the virtual robot must be transparent to the user, a control architecture has been developed.

Keywords: Control engineering computing, Manipulators, Multi-robot systems, Optimsation, Telerobotics, Virtual reality

Gutierrez, A., Marco, S., (2009). Biologically inspired signal processing for chemical sensing Studies in Computational Intelligence GOSPEL Workshop on Bio-inspired Signal Processing (ed. Gutierrez, A., Marco, S.), Springer (Barcelona, Spain) -----, (188), -----

This 167-page book is volume 188 in the series 'Studies in computational intelligence.' This volume contain 9 extensive chapters written in English. This volume presents a collection of research advances in biologically inspired signal processing for chemical sensing. The olfactory system, and the gustatory system to a minor extent, has been taken in the last decades as a source of inspiration to develop artificial sensing systems. The recognition of odors by the olfactory system entails a number of signal processing functions such as preprocessing, dimensionality reduction, contrast enhancement, and classification. Using mathematical models to mimic the architecture of the olfactory system, these processing functions can be applied to chemical sensor signals. This book provides background on the olfactory system including a review on information processing in the insect olfactory system along with a proposed signal processing architecture based on the mammalian cortex. It also provides some bio-inspired approaches to process chemical sensor signals such as an olfactory mucosa to improve odor separation and a model of olfactory receptor neuron convergence to correlated sensor responses to an odor and his organoleptic properties. This book will useful to those working or studying in the areas of sensory reception and computational biology.

Keywords: Nervous System (Neural Coordination), Computer Applications (Computational Biology), Sense Organs (Sensory Reception)

Lopez, M. J., Caballero, D., Campo, E. M., Perez-Castillejos, R., Errachid, A., Esteve, J., Plaza, J. A., (2008). Focused ion beam-assisted technology in sub-picolitre micro-dispenser fabrication Journal of Micromechanics and Microengineering , 18, (7), 8

Novel medical and biological applications are driving increased interest in the fabrication of micropipette or micro-dispensers. Reduced volume samples and drug dosages are prime motivators in this effort. We have combined microfabrication technology with ion beam milling techniques to successfully produce cantilever-type polysilicon micro-dispensers with 3D enclosed microchannels. The microfabrication technology described here allows for the designing of nozzles with multiple shapes. The contribution of ion beam milling has had a large impact on the fabrication process and on further customizing shapes of nozzles and inlet ports. Functionalization tests were conducted to prove the viability of ion beam-fabricated micro-dispensers. Self-assembled monolayers were successfully formed when a gold surface was patterned with a thiol solution dispensed by the fabricated micro-dispensers.

Keywords: Dip-pen nanolithography, Silicon, Deposition, Microneedles, Delivery, Arrays, Polysilicon, Capillary, Systems, Gene

Cho, S., Castellarnau, M., Samitier, J., Thielecke, H., (2008). Dependence of impedance of embedded single cells on cellular behaviour Sensors 8, (2), 1198-1211

Non-invasive single cell analyses are increasingly required for the medical diagnostics of test substances or the development of drugs and therapies on the single cell level. For the non-invasive characterisation of cells, impedance spectroscopy which provides the frequency dependent electrical properties has been used. Recently, microfludic systems have been investigated to manipulate the single cells and to characterise the electrical properties of embedded cells. In this article, the impedance of partially embedded single cells dependent on the cellular behaviour was investigated by using the microcapillary. An analytical equation was derived to relate the impedance of embedded cells with respect to the morphological and physiological change of extracellular interface. The capillary system with impedance measurement showed a feasibility to monitor the impedance change of embedded single cells caused by morphological and physiological change of cell during the addition of DMSO. By fitting the derived equation to the measured impedance of cell embedded at different negative pressure levels, it was able to extrapolate the equivalent gap and gap conductivity between the cell and capillary wall representing the cellular behaviour.

Keywords: Frequency-domain, Spectroscopy, Erythrocytes, Biosensor, Membrane, System

Castellarnau, M., Zine, N., Bausells, J., Madrid, C., Juarez, A., Samitier, J., Errachid, A., (2008). ISFET-based biosensor to monitor sugar metabolism in bacteria Materials Science & Engineering C 5th Maghreb-Europe Meeting on Materials and their Applicatons for Devices and Physical, Chemical and Biological Sensors (ed. -----), Elsevier Science (Mahdia, Tunisia) 28, (5-6), 680-685

We report the use of ion-selective field effect transistor devices (ISFETs) with an integrated pseudo-reference electrode for on-line monitoring of bacterial metabolism by monitoring of the pH variation. As a model we tested the ability of Lactobacillus strains to ferment sugars, producing lactic acid, which results in a decrease in pH in the suspension medium. We have tested and compared sugar uptake by L. sakei and a L. curvatus strains. The results obtained show that it is possible to distinguish between both types of Lactobacillus strains through their pattern of ribose uptake. The use of ISFETs represents a non-invasive methodology that can be used to monitor biological activity in a wide variety of systems.

Keywords: Lactobacillus-sakei, Technology, Sensors, System, Growth, Cells, State, Meat