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Wiers, Reinout W., Verschure, Paul, (2021). Curing the broken brain model of addiction: Neurorehabilitation from a systems perspective Addictive Behaviors 112, 106602

The dominant biomedical perspective on addictions has been that they are chronic brain diseases. While we acknowledge that the brains of people with addictions differ from those without, we argue that the “broken brain” model of addiction has important limitations. We propose that a systems-level perspective more effectively captures the integrated architecture of the embodied and situated human mind and brain in relation to the development of addictions. This more dynamic conceptualization places addiction in the broader context of the addicted brain that drives behavior, where the addicted brain is the substrate of the addicted mind, that in turn is situated in a physical and socio-cultural environment. From this perspective, neurorehabilitation should shift from a “broken-brain” to a systems theoretical framework, which includes high-level concepts related to the physical and social environment, motivation, self-image, and the meaning of alternative activities, which in turn will dynamically influence subsequent brain adaptations. We call this integrated approach system-oriented neurorehabilitation. We illustrate our proposal by showing the link between addiction and the architecture of the embodied brain, including a systems-level perspective on classical conditioning, which has been successfully translated into neurorehabilitation. Central to this example is the notion that the human brain makes predictions on future states as well as expected (or counterfactual) errors, in the context of its goals. We advocate system-oriented neurorehabilitation of addiction where the patients' goals are central in targeted, personalized assessment and intervention.

Keywords: Addiction, Brain disease model, Neurorehabilitation, Systems approach

Burgués, Javier, Marco, Santiago, (2020). Environmental chemical sensing using small drones: A review Science of The Total Environment 748, 141172

Recent advances in miniaturization of chemical instrumentation and in low-cost small drones are catalyzing exponential growth in the use of such platforms for environmental chemical sensing applications. The versatility of chemically sensitive drones is reflected by their rapid adoption in scientific, industrial, and regulatory domains, such as in atmospheric research studies, industrial emission monitoring, and in enforcement of environmental regulations. As a result of this interdisciplinarity, progress to date has been reported across a broad spread of scientific and non-scientific databases, including scientific journals, press releases, company websites, and field reports. The aim of this paper is to assemble all of these pieces of information into a comprehensive, structured and updated review of the field of chemical sensing using small drones. We exhaustively review current and emerging applications of this technology, as well as sensing platforms and algorithms developed by research groups and companies for tasks such as gas concentration mapping, source localization, and flux estimation. We conclude with a discussion of the most pressing technological and regulatory limitations in current practice, and how these could be addressed by future research.

Keywords: Unmanned aircraft systems, Remotely piloted aircraft systems, Chemical sensors, Gas sensors, Environmental monitoring, Industrial emission monitoring

Palacio, F., Fonollosa, J., Burgués, J., Gomez, J. M., Marco, S., (2020). Pulsed-temperature metal oxide gas sensors for microwatt power consumption IEEE Access 8, 70938-70946

Metal Oxide (MOX) gas sensors rely on chemical reactions that occur efficiently at high temperatures, resulting in too-demanding power requirements for certain applications. Operating the sensor under a Pulsed-Temperature Operation (PTO), by which the sensor heater is switched ON and OFF periodically, is a common practice to reduce the power consumption. However, the sensor performance is degraded as the OFF periods become larger. Other research works studied, generally, PTO schemes applying waveforms to the heater with time periods of seconds and duty cycles above 20%. Here, instead, we explore the behaviour of PTO sensors working under aggressive schemes, reaching power savings of 99% and beyond with respect to continuous heater stimulation. Using sensor sensitivity and the limit of detection, we evaluated four Ultra Low Power (ULP) sensors under different PTO schemes exposed to ammonia, ethylene, and acetaldehyde. Results show that it is possible to operate the sensors with total power consumption in the range of microwatts. Despite the aggressive power reduction, sensor sensitivity suffers only a moderate decline and the limit of detection may degrade up to a factor five. This is, however, gas-dependent and should be explored on a case-by-case basis since, for example, the same degradation has not been observed for ammonia. Finally, the run-in time, i.e., the time required to get a stable response immediately after switching on the sensor, increases when reducing the power consumption, from 10 minutes to values in the range of 10–20 hours for power consumptions smaller than 200 microwatts.

Keywords: Robot sensing systems, Temperature sensors, Heating systems, Gas detectors, Power demand, Sensitivity, Electronic nose, gas sensors, low-power operation, machine olfaction, pulsed-temperature operation, temperature modulation

Wang, S., Hu, Y., Burgués, J., Marco, S., Liu, S.-L., (2020). Prediction of gas concentration using gated recurrent neural networks 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS) , IEEE (Genova, Italy) , 178-182

Low-cost gas sensors allow for large-scale spatial monitoring of air quality in the environment. However they require calibration before deployment. Methods such as multivariate regression techniques have been applied towards sensor calibration. In this work, we propose instead, the use of deep learning methods, particularly, recurrent neural networks for predicting the gas concentrations based on the outputs of these sensors. This paper presents a first study of using Gated Recurrent Unit (GRU) neural network models for gas concentration prediction. The GRU networks achieve on average, a 44.69% and a 25.17% RMSE improvement in concentration prediction on a gas dataset when compared with Support Vector Regression (SVR) and Multilayer Perceptron (MLP) models respectively. With the current advances in deep network hardware accelerators, these networks can be combined with the sensors for a compact embedded system suitable for edge applications.

Keywords: Robot sensing systems, Predictive models, Logic gates, Gas detectors, Training, Temperature measurement, Support vector machines

Vouloutsi, Vasiliki, Mura, Anna, Tauber, F., Speck, T., Prescott, T. J., Verschure, P., (2020). Biomimetic and Biohybrid Systems 9th International Conference, Living Machines 2020, Freiburg, Germany, July 28–30, 2020, Proceedings , Springer, Cham (Lausanne, Switzerland) 12413, 1-428

This book constitutes the proceedings of the )th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2020, held in Freiburg, Germany, in July 2020. Due to COVID-19 pandemic the conference was held virtually. The 32 full and 7 short papers presented in this volume were carefully reviewed and selected from 45 submissions. They deal with 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 intelligence, Soft robotics, Biomimetics, Insect navigation, Synthetic nervous system, Computer vision, Bio-inspired materials, Visual homing, Locomotion+, Image processing, Intelligent robots, Human-robot interaction, Machine learning, Snake robot, Mobile robots, Robotic systems, Drosophila, Robots, Sensors, Signal processing

Bolognesi, Benedetta, Faure, Andre J., Seuma, Mireia, Schmiedel, Jörrn M., Tartaglia, Gian Gaetano, Lehner, Ben, (2019). The mutational landscape of a prion-like domain Nature Communications 10, (1), 4162

Insoluble protein aggregates are the hallmarks of many neurodegenerative diseases. For example, aggregates of TDP-43 occur in nearly all cases of amyotrophic lateral sclerosis (ALS). However, whether aggregates cause cellular toxicity is still not clear, even in simpler cellular systems. We reasoned that deep mutagenesis might be a powerful approach to disentangle the relationship between aggregation and toxicity. We generated >50,000 mutations in the prion-like domain (PRD) of TDP-43 and quantified their toxicity in yeast cells. Surprisingly, mutations that increase hydrophobicity and aggregation strongly decrease toxicity. In contrast, toxic variants promote the formation of dynamic liquid-like condensates. Mutations have their strongest effects in a hotspot that genetic interactions reveal to be structured in vivo, illustrating how mutagenesis can probe the in vivo structures of unstructured proteins. Our results show that aggregation of TDP-43 is not harmful but protects cells, most likely by titrating the protein away from a toxic liquid-like phase.

Keywords: Computational biology and bioinformatics, Genomics, Mechanisms of disease, Neurodegeneration, Systems biology

Moles, E., Kavallaris, M., Fernàndez-Busquets, X., (2019). Modeling the distribution of diprotic basic drugs in liposomal systems: Perspectives on malaria nanotherapy Frontiers in Pharmacology 10, 1064

Understanding how polyprotic compounds distribute within liposome (LP) suspensions is of major importance to design effective drug delivery strategies. Advances in this research field led to the definition of LP-based active drug encapsulation methods driven by transmembrane pH gradients with evidenced efficacy in the management of cancer and infectious diseases. An accurate modeling of membrane-solution drug partitioning is also fundamental when designing drug delivery systems for poorly endocytic cells, such as red blood cells (RBCs), in which the delivered payloads rely mostly on the passive diffusion of drug molecules across the cell membrane. Several experimental models have been proposed so far to predict the partitioning of polyprotic basic/acid drugs in artificial membranes. Nevertheless, the definition of a model in which the membrane-solution partitioning of each individual drug microspecies is studied relative to each other is still a topic of ongoing research. We present here a novel experimental approach based on mathematical modeling of drug encapsulation efficiency (EE) data in liposomal systems by which microspecies-specific partition coefficients are reported as a function of pH and phospholipid compositions replicating the RBC membrane in a simple and highly translatable manner. This approach has been applied to the study of several diprotic basic antimalarials of major clinical importance (quinine, primaquine, tafenoquine, quinacrine, and chloroquine) describing their respective microspecies distribution in phosphatidylcholine-LP suspensions. Estimated EE data according to the model described here closely fitted experimental values with no significant differences obtained in 75% of all pH/lipid composition-dependent conditions assayed. Additional applications studied include modeling drug EE in LPs in response to transmembrane pH gradients and lipid bilayer asymmetric charge, conditions of potential interest reflected in our previously reported RBC-targeted antimalarial nanotherapeutics.

Keywords: Distribution coefficient, Liposomal systems, Malaria therapy, Nanomedicine, Partition coefficient, PH-controlled drug encapsulation, Polyprotic drug, Targeted drug delivery

Arsiwalla, X. D., Freire, I. T., Vouloutsi, V., Verschure, P., (2019). Latent morality in algorithms and machines Biomimetic and Biohybrid Systems 8th International Conference, Living Machines 2019 (Lecture Notes in Computer Science) , Springer, Cham (Nara, Japan) 11556, 309-315

Can machines be endowed with morality? We argue that morality in the descriptive or epistemic sense can be extended to artificial systems. Following arguments from evolutionary game-theory, we identify two main ingredients required to operationalize this notion of morality in machines. The first, being a group theory of mind, and the second, being an assignment of valence. We make the case for the plausibility of these operations in machines without reference to any form of intentionality or consciousness. The only systems requirements needed to support the above two operations are autonomous goal-directed action and the ability to interact and learn from the environment. Following this we have outlined a theoretical framework based on conceptual spaces and valence assignments to gauge latent morality in autonomous machines and algorithms.

Keywords: Autonomous systems, Ethics of algorithms, Goal-directed action, Philosophy of morality, Qualia, Theory of mind

Solà-Soler, J., Giraldo, B. F., Jané, R., (2019). Linear mixed effects modelling of oxygen desaturation after sleep apneas and hypopneas: A pilot study Engineering in Medicine and Biology Society (EMBC) 41st Annual International Conference of the IEEE , IEEE (Berlín, Germany) , 5731-5734

Obstructive Sleep Apnea severity is commonly determined after a sleep polysomnographic study by the Apnea-Hypopnea Index (AHI). This index does not contain information about the duration of events, and weights apneas and hypopneas alike. Significant differences in disease severity have been reported in patients with the same AHI. The aim of this work was to study the effect of obstructive event type and duration on the subsequent oxygen desaturation (SaO2) by mixed-effects models. These models allow continuous and categorical independent variables and can model within-subject variability through random effects. The desaturation depth dSaO2, desaturation duration dtSaO2 and desaturation area dSaO2A were analyzed in the 2022 apneas and hypopneas of eight severe patients. A mixed-effects model was defined to account for the influence of event duration (AD), event type, and their interaction on SaO2 parameters. A two-step backward model reduction process was applied for random and fixed effects optimization. The optimum model obtained for dtSaO2 suggests an almost subject-independent proportion increase with AD, which did not significantly change in apneas as compared to hypopneas. The optimum model for dSaO2 reveals a significantly higher increase as a function of AD in apneas than hypopneas. Dependence of on event type and duration was different in every subject, and a subject-specific model could be obtained. The optimum model for SaO2A combines the effects of the other two. In conclusion, the proposed mixed-effects models for SaO2 parameters allow to study the effect of respiratory event duration and type, and to include repeated events within each subject. This simple model can be easily extended to include the contribution of other important factors such as patient severity, sleep stage, sleeping position, or the presence of arousals.

Keywords: Biological system modeling, Sleep apnea, Mathematical model, Indexes, Reduced order systems, Optimization

Samitier, Josep, Correia, A., (2019). Biomimetic Nanotechnology for Biomedical Applications (NanoBio&Med 2018) Biomimetics MDPI

Emerging nanobiotechnologies can offer solutions to the current and future challenges in medicine. By covering topics from regenerative medicine, tissue engineering, drug delivery, bionanofabrication, and molecular biorecognition, this Special Issue aims to provide an update on the trends in nanomedicine and drug delivery using biomimetic approaches, and the development of novel biologically inspired devices for the safe and effective diagnosis, prevention, and treatment of disease.

Keywords: Bioinspired nanotechnologies, Bionanofabrication, Bio-nano measurement and microscopy, Nanomaterials for biological and medical applications, Nanoassemblies, Nanostructured surfaces, Drug delivery, Nanobioelectronics, Integrated systems/nanobiosensors, Nanotoxicology, Graphene-based applications

Muro, Silvia, (2018). Alterations in cellular processes involving vesicular trafficking and implications in drug delivery Biomimetics 3, (3), 19

Endocytosis and vesicular trafficking are cellular processes that regulate numerous functions required to sustain life. From a translational perspective, they offer avenues to improve the access of therapeutic drugs across cellular barriers that separate body compartments and into diseased cells. However, the fact that many factors have the potential to alter these routes, impacting our ability to effectively exploit them, is often overlooked. Altered vesicular transport may arise from the molecular defects underlying the pathological syndrome which we aim to treat, the activity of the drugs being used, or side effects derived from the drug carriers employed. In addition, most cellular models currently available do not properly reflect key physiological parameters of the biological environment in the body, hindering translational progress. This article offers a critical overview of these topics, discussing current achievements, limitations and future perspectives on the use of vesicular transport for drug delivery applications.

Keywords: Cellular vesicles, Vesicle fusion, Fission and intracellular trafficking, Drug delivery systems and nanomedicines, Transcytosis and endocytosis of drugs carriers, Disease effects on vesicular trafficking, Drug effects on vesicular trafficking, Role of the biological environment

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

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

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

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

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

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

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

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

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

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

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