Publications

[No abstract available]

JTD Keywords: Breathing, Cost, Developed country, Developing countries, Developing country, Health care facility, Home monitoring, Human, Humans, Internet, Internet of things, Letter, Lowest income group, Lung function, Lung mechanics, Lung resistance, Mathematical model, Middle income country, Mobile applications, Non invasive procedure, Open source technology, Oscillometry, Pneumotachygraphy, Telemedicine

Surface electromyography (sEMG) can be used to measure the electrical activity of the respiratory muscles. The possible applications of sEMG span from patients suffering from acute respiratory failure to patients receiving chronic home mechanical ventilation, to evaluate muscle function, titrate ventilatory support and guide treatment. However, sEMG is mainly used as a monitoring tool for research and its use in clinical practice is still limited-in part due to a lack of standardization and transparent reporting. During this round table meeting, recommendations on data acquisition, processing, interpretation, and potential clinical applications of respiratory sEMG were discussed. This paper informs the clinical researcher interested in respiratory muscle monitoring about the current state of the art on sEMG, knowledge gaps and potential future applications for patients with respiratory failure.

JTD Keywords: Acute respiratory failure, Artificial ventilation, Asthmatic-children, Breathing muscle, Clinical monitoring, Clinical practice, Clinical research, Consensus development, Data interpretation, Disease exacerbation, Drive, Electrode positioning, Electrode removal, Electromyography, Force, Home care, Human, Human diaphragm, Humans, Information processing, Inspiratory muscle training, Inspiratory muscles, Intensive care unit, Knowledge gap, Long term care, Mechanical ventilation, Medical procedures, Muscle contraction, Muscle fatigue, Muscle function, Muscle training, Muscle, skeletal, Muscle-activity, Noninvasive ventilation, Patient monitoring, Patient-ventilator asynchrony, Physiology, Prognosis, Quality of life, Reporting and data system, Respiratory failure, Respiratory muscles, Review, Severe exacerbations, Signal processing, Skeletal muscle, Standardization, Surface electromyography, Time factor

Although multifunctional wearable devices have been widely investigated for healthcare systems, augmented/virtual realities, and telemedicines, there are few reports on multiple signal monitoring and logical signal processing by using one single nanomaterial without additional algorithms or rigid application-specific integrated circuit chips. Here, multifunctional intelligent wearable devices are developed using monolithically patterned gold nanowires for both signal monitoring and processing. Gold bulk and hollow nanowires show distinctive electrical properties with high chemical stability and high stretchability. In accordance, the monolithically patterned gold nanowires can be used to fabricate the robust interfaces, programmable sensors, on-demand heating systems, and strain-gated logical circuits. The stretchable sensors show high sensitivity for strain and temperature changes on the skin. Furthermore, the micro-wrinkle structures of gold nanowires exhibit the negative gauge factor, which can be used for strain-gated logical circuits. Taken together, this multifunctional intelligent wearable device would be harnessed as a promising platform for futuristic electronic and biomedical applications.© 2023 Wiley-VCH GmbH.

JTD Keywords: electronics, fabrication, intelligent multifunction, monolithic patterns, signal monitoring and processing, wearable devices, Gold nanowires, Intelligent multifunction, Intraocular-pressure, Monolithic patterns, Signal monitoring and processing, Wearable devices

A fundamental task of the respiratory system is to operate as a mechanical gas pump ensuring that fresh air gets in close contact with the blood circulating through the lung capillaries to achieve O2 and CO2 exchange. To ventilate the lungs, the respiratory muscles provide the pressure required to overcome the viscoelastic mechanical load of the respiratory system. From a mechanical viewpoint, the most relevant respiratory system properties are the resistance of the airways (R aw), and the compliance of the lung tissue (C L) and chest wall (C CW). Both airflow and lung volume changes in spontaneous breathing and mechanical ventilation are determined by applying the fundamental mechanical laws to the relationships between the pressures inside the respiratory system (at the airway opening, alveolar, pleural, and muscular) and R aw, C L, and C CW. These relationships also are the basis of the different methods available to measure respiratory mechanics during spontaneous and artificial ventilation. Whereas a simple mechanical model (R aw, C L, and C CW) describes the basic understanding of ventilation mechanics, more complex concepts (nonlinearity, inhomogeneous ventilation, or viscoelasticity) should be employed to better describe and measure ventilation mechanics in patients.Thieme. All rights reserved.

JTD Keywords: airway-resistance, alveolar, compliance, dilution, elastance, flow, inhomogeneous ventilation, input impedance, lung-volume, mechanical ventilation, monitoring, pendelluft, pleural pressure, respiratory-distress-syndrome, viscoelasticity, Chest-wall mechanics, Resistance

In recent years, metaplasmonic biosensors have emerged as a novel counterpart of well-established plasmonic biosensors based on thin metallic layers. Metaplasmonic biosensors offer high potential for sensor miniaturiza-tion, extreme sensitivity biosensing, and high multiplexing capabilities with detection methods free of coupling optical elements. These capabilities make metaplasmonic biosensors highly attractive for Point-of-Care and handled/portable devices or novel On-Chip devices; as a result, it has increased the number of prototypes and potential applications that emerged during the last years. One of the main challenges to achieving fully operative devices is the achievement of high-throughput biointerfaces for sensitive and selective biodetection in complex media. Despite the superior surface sensitivity achieved by metaplasmonic sensors compared to conventional plasmonic sensors based on metallic thin films, the main limitations to achieving high-throughput and multiplexed biosensing usually are associated with the sensitivity and selectivity of the bioin-terface and, as a consequence, their application to the direct analysis of real complex samples. This graphical review discusses the potential challenges and capabilities of different biofunctionalization strategies, biorecog-nition elements, and antifouling strategies to achieve scalable and high-throughput metaplasmonic biosensing for Point-of-Care devices and bioengineering applications like Organs-On-Chip.

JTD Keywords: Biointerfaces, Biosensing, Biosensors, Cell culture monitoring, Metaplasmonic, Nanoplasmonic, Organ-on-chip, Point-of-care

Conventionally, odours emitted by different sources present in wastewater treatment plants (WWTPs) are measured by dynamic olfactometry, where a human panel sniffs and analyzes air bags collected from the plant. Although the method is considered the gold standard, the process is costly, slow, and infrequent, which does not allow operators to quickly identify and respond to problems. To better monitor and map WWTP odour emissions, here we propose a small rotary-wing drone equipped with a lightweight (1.3-kg) electronic nose. The "sniffing drone" sucks in air via a ten-meter (33-foot) tube and delivers it to a sensor chamber where it is analyzed in real-time by an array of 21 gas sensors. From the sensor signals, machine learning (ML) algorithms predict the odour concentration that a human panel using the EN13725 methodology would report. To calibrate and validate the predictive models, the drone also carries a remotely controlled sampling device (compliant with EN13725:2022) to collect sample air in bags for post-flight dynamic olfactometry. The feasibility of the proposed system is assessed in a WWTP in Spain through several measurement campaigns covering diverse operating regimes of the plant and meteorological conditions. We demonstrate that training the ML algorithms with dynamic (transient) sensor signals measured in flight conditions leads to better performance than the traditional approach of using steady-state signals measured in the lab via controlled exposures to odour bags. The comparison of the electronic nose predictions with dynamic olfactometry measurements indicates a negligible bias between the two measurement techniques and 95 % limits of agreement within a factor of four. This apparently large disagreement, partly caused by the high uncertainty of olfactometric measurements (typically a factor of two), is more than offset by the immediacy of the predictions and the practical advantages of using a drone-based system.Copyright © 2022. Published by Elsevier B.V.

JTD Keywords: calibration, chemical sensors, drone, dynamic olfactometry, electronic nose, odourquantification, olfaction, volatile organic-compounds, wwtp, Calibration, Chemical sensors, Drone, Dynamic olfactometry, Electronic nose, Environmental monitoring, Odour quantification, Olfaction, Variable selection methods, Wwtp

JTD Keywords: Diagnosis, Monitoring, Pneumonia

JTD Keywords: Monitoring, Physiological diagnostic services, Respiratory muscle

Introduction: After a stroke, a wide range of deficits can occur with varying onset latencies. As a result, assessing impairment and recovery are enormous challenges in neurorehabilitation. Although several clinical scales are generally accepted, they are time-consuming, show high inter-rater variability, have low ecological validity, and are vulnerable to biases introduced by compensatory movements and action modifications. Alternative methods need to be developed for efficient and objective assessment. In this study, we explore the potential of computer-based body tracking systems and classification tools to estimate the motor impairment of the more affected arm in stroke patients. Methods: We present a method for estimating clinical scores from movement parameters that are extracted from kinematic data recorded during unsupervised computer-based rehabilitation sessions. We identify a number of kinematic descriptors that characterise the patients' hemiparesis (e.g., movement smoothness, work area), we implement a double-noise model and perform a multivariate regression using clinical data from 98 stroke patients who completed a total of 191 sessions with RGS. Results: Our results reveal a new digital biomarker of arm function, the Total Goal-Directed Movement (TGDM), which relates to the patients work area during the execution of goal-oriented reaching movements. The model's performance to estimate FM-UE scores reaches an accuracy of R-2: 0.38 with an error (sigma: 12.8). Next, we evaluate its reliability (r = 0.89 for test-retest), longitudinal external validity (95% true positive rate), sensitivity, and generalisation to other tasks that involve planar reaching movements (R-2: 0.39). The model achieves comparable accuracy also for the Chedoke Arm and Hand Activity Inventory (R-2: 0.40) and Barthel Index (R-2: 0.35). Conclusions: Our results highlight the clinical value of kinematic data collected during unsupervised goal-oriented motor training with the RGS combined with data science techniques, and provide new insight into factors underlying recovery and its biomarkers.

JTD Keywords: interactive feedback, motion classification, motion sensing, multivariate regression, posture monitoring, rehabilitation, stroke, Adult, Aged, Analytic method, Arm movement, Article, Barthel index, Brain hemorrhage, Cerebrovascular accident, Chedoke arm and hand activity inventory, Clinical protocol, Cognitive defect, Computer analysis, Controlled study, Convergent validity, Correlation coefficient, Disease severity, External validity, Female, Fugl meyer assessment for the upper extremity, Functional assessment, Functional status assessment, General health status assessment, Hemiparesis, Human, Interactive feedback, Ischemic stroke, Kinematics, Major clinical study, Male, Mini mental state examination, Motion classification, Motion sensing, Motor analog scale, Movement, Multivariate regression, Muscle function, Posture monitoring, Probability, Recovery, Rehabilitation, Reliability, Retrospective study, Stroke, Stroke patient, Test retest reliability, Therapy, Total goal directed movement, Upper extremities, Upper limb, Upper-limb, Wolf motor function test

Under intrauterine growth restriction (IUGR), abnormal attainment of the nutrients and oxygen by the fetus restricts the normal evolution of the prenatal causing in many cases high morbidity being one of the top-ten causes of neonatal death. The current gold standards in hospitals to detect this relevant problem is the clinical observation by echography, cardiotocography and Doppler. These qualitative techniques are not conclusive and requires risky invasive fetal scalp blood testing and/or amniocentesis. We developed micro-implantable multiparametric electrochemical sensors for measuring ischemia in real time in fetal tissue and vascular. This implantable technology is designed to continuous monitoring for an early detection of ischemia to avoid potential fetal injury. Two miniaturized electrochemical sensors were developed based on oxygen and pH detection. The sensors were optimized in vitro under controlled concentration, to assess the selectivity and sensitivity required. The sensors were then validated in vivo in the ewe fetus model, by means of their insertion in the muscle leg and inside the iliac artery of the fetus. Ischemia was achieved by gradually obstructing the umbilical cord to regulate the amount of blood reaching the fetus. An important challenge in fetal monitoring is the detection of low levels of oxygen and pH changes under ischemic conditions, requiring high sensitivity sensors. Significant differences were observed in both; pH and pO(2) sensors under changes from normoxia to hypoxia states in the fetus tissue and vascular with both sensors. Herein, we demonstrate the feasibility of the developed sensors for future fetal monitoring in medical applications.

JTD Keywords: electrochemical biosensor, implantable sensor, in vivo validation, ischemia detection, tissue and vascular monitoring, Animal experiment, Animal model, Animal tissue, Article, Blood-gases, Brain, Classification, Controlled study, Diagnosis, Doppler, Early diagnosis, Electrochemical analysis, Electrochemical biosensor, Ewe, Feasibility study, Female, Fetus, Fetus disease, Fetus monitoring, Gestational age, Hypoxemia, Iliac artery, Implantable sensor, In vivo validation, Intrauterine growth restriction, Intrauterine growth retardation, Ischemia detection, Leg muscle, Management, Nonhuman, Oxygen consumption, Ph, Ph and oxygen detection, Ph measurement, Process optimization, Sheep, Tissue and vascular monitoring, Umbilical-cord occlusion

Over the last years, optical biosensors based on plasmonic nanomaterials have gained great scientific interest due to their unquestionable advantages compared to other biosensing technologies. They can achieve sensitive, direct, and label-free analysis with exceptional potential for multiplexing and miniaturization. Recently, it has been demonstrated the potential of using optical discs as high throughput nanotemplates for the development of plasmonic biosensors in a cost-effective way. This work is a pilot study focused on the development of an integrated plasmonic biosensor for the monitoring of cell adhesion and growth of human retinal pigmented cell line (ARPE-19) under different media conditions (0 and 2% of FBS). We observed an increase of the plasmonic band displacement under 2% FBS compared to 0% conditions over time (1, 3, and 5 h). These preliminary results show that the proposed plasmonic biosensing approach is a direct, non-destructive, and real-time tool that could be employed in the study of living cells behavior and culture conditions. Furthermore, this setup could assess the viability of the cells and their growth over time with low variability between the technical replicates improving the experimental replicability.

JTD Keywords: cell confluency, cell culture, nanocrystals, optical biosensor, Adhesion monitoring, Biosensing, Biosensors, Cell adhesion, Cell confluency, Cell culture, Cells, Condition, Cost effectiveness, Disposables, Nano-structured, Nanocrystals, Optical bio-sensors, Optical biosensor, Plasmonic biosensors, Plasmonic nanostructures, Plasmonics, Polylysine

Patients with spinal cord injury (SCI) have an increased risk of sleep-disordered breathing (SDB), which can lead to serious comorbidities and impact patients’ recovery and quality of life. However, sleep tests are rarely performed on SCI patients, given their multiple health needs and the cost and complexity of diagnostic equipment. The objective of this study was to use a novel smartphone system as a simple non-invasive tool to monitor SDB in SCI patients. We recorded pulse oximetry, acoustic, and accelerometer data using a smartphone during overnight tests in 19 SCI patients and 19 able-bodied controls. Then, we analyzed these signals with automatic algorithms to detect desaturation, apnea, and hypopnea events and monitor sleep position. The apnea–hypopnea index (AHI) was significantly higher in SCI patients than controls (25 ± 15 vs. 9 ± 7, p < 0.001). We found that 63% of SCI patients had moderate-to-severe SDB (AHI ? 15) in contrast to 21% of control subjects. Most SCI patients slept predominantly in supine position, but an increased occurrence of events in supine position was only observed for eight patients. This study highlights the problem of SDB in SCI and provides simple cost-effective sleep monitoring tools to facilitate the detection, understanding, and management of SDB in SCI patients.

JTD Keywords: apnea syndrome, biomedical signal processing, individuals, mhealth, monitoring, nasal resistance, people, position, prevalence, questionnaire, sample, sleep apnea, sleep position, sleep-disordered breathing, smartphone, time, Apnea-hypopnea indices, Biomedical signal processing, Biomedical signals processing, Cost effectiveness, Diagnosis, Mhealth, Monitoring, Noninvasive medical procedures, Oximeters, Oxygen-saturation, Patient rehabilitation, Simple++, Sleep apnea, Sleep position, Sleep research, Sleep-disordered breathing, Smart phones, Smartphone, Smartphones, Spinal cord injury, Spinal cord injury patients

Perinatal asphyxia is a major cause of severe brain damage and death. For its prenatal identification, Doppler ultrasound has been used as a surrogate marker of fetal hypoxia. However, Doppler evaluation cannot be performed continuously. We have evaluated the performance of a miniaturized multiparametric sensor aiming to evaluate tissular oxygen and pH changes continuously in an umbilical cord occlusion (UCO) sheep model. The electrochemical sensors were inserted in fetal hindlimb skeletal muscle and electrochemical signals were recorded. Fetal hemodynamic changes and metabolic status were also monitored during the experiment. Additionally, histological assessment of the tissue surrounding the sensors was performed. Both electrochemical sensors detected the pO2 and pH changes induced by the UCO and these changes were correlated with hemodynamic parameters as well as with pH and oxygen content in the blood. Finally, histological assessment revealed no signs of alteration on the same day of insertion. This study provides the first evidence showing the application of miniaturized multiparametric electrochemical sensors detecting changes in oxygen and pH in skeletal muscular tissue in a fetal sheep model.

JTD Keywords: continuous monitoring of acid-base status, diagnosis, doppler, electrochemical sensors, growth restriction, high-risk pregnancies, human-fetus, management, responses, tissue ph, Continuous monitoring of acid-base status, Electrochemical sensors, High-risk pregnancies, Umbilical cord occlusion, Umbilical-cord occlusion

JTD Keywords: Experimental approaches, Monitoring, Pneumonia

Poor sleep quality or disturbed sleep is associated with multiple health conditions. Sleep position affects the severity and occurrence of these complications, and positional therapy is one of the less invasive treatments to deal with them. Sleep positions can be self-reported, which is unreliable, or determined by using specific devices, such as polysomnography, polygraphy or cameras, that can be expensive and difficult to employ at home. The aim of this study is to determine how smartphones could be used to monitor and treat sleep position at home. We divided our research into three tasks: (1) develop an Android smartphone application (‘SleepPos’ app) which monitors angle-based high-resolution sleep position and allows to simultaneously apply positional treatment; (2) test the smartphone application at home coupled with a pulse oximeter; and (3) explore the potential of this tool to detect the positional occurrence of desaturation events. The results show how the ‘SleepPos’ app successfully determined the sleep position and revealed positional patterns of occurrence of desaturation events. The ‘SleepPos’ app also succeeded in applying positional therapy and preventing the subjects from sleeping in the supine sleep position. This study demonstrates how smartphones are capable of reliably monitoring high-resolution sleep position and provide useful clinical information about the positional occurrence of desaturation events.

JTD Keywords: accelerometry, android, apnea patients, app, association, biomedical signal processing, management, mhealth, monitoring, pathophysiology, pilot mhealth, questionnaire, sleep position, smartphone, supine position, time, Accelerometry, Android, App, Biomedical signal processing, Mhealth, Monitoring, Sleep position, Smart-phone, Smartphone, Tennis ball technique

The human olfactory system remains one of the most challenging biological systems to replicate. Humans use it without thinking, where it can equally offer protection from harm and bring enjoyment in equal measure. It is the system’s ability to detect and analyze complex odors, without the need for specialized infra-structure, that is the envy of many scientists. The field of artificial olfaction has recruited and stimulated interdisciplinary research and commercial development for several applications that include malodor measurement, medical diagnostics, food and beverage quality, environment and security. Over the last century, innovative engineers and scientists have been focused on solving a range of problems associated with measurement and control of odor. The IEEE Sensors Journal has published Special Issues on olfaction in 2002 and 2012. Here we continue that coverage. In this article, we summarize early work in the 20th Century that served as the foundation upon which we have been building our odor-monitoring instrumental and measurement systems. We then examine the current state of the art that has been achieved over the last two decades as we have transitioned into the 21st Century. Much has been accomplished, but great progress is needed in sensor technology, system design, product manufacture and performance standards. In the final section, we predict levels of performance and ubiquitous applications that will be realized during in the mid to late 21st Century.

JTD Keywords: air-quality, breath analysis, calibration transfer, chemical sensor arrays, chemosensor arrays, drift compensation, electronic nose, gas sensors, headspace sampling, machine learning, machine olfaction, odor detection, plume structure, voc analysis, Artificial olfaction, Electrodes, Electronic nose, Electronic nose technology, Headspace sampling, Instruments, Machine learning, Machine olfaction, Monitoring, Odor detection, Olfactory, Sensor phenomena and characterization, Sensors, Temperature sensors, Voc analysis

Poor sleep quality is a risk factor for multiple mental, cardiovascular, and cerebrovascular diseases. Certain sleep positions or excessive position changes can be related to some diseases and poor sleep quality. Nevertheless, sleep position is usually classified into four discrete values: supine, prone, left and right. An increase in sleep position resolution is necessary to better assess sleep position dynamics and to interpret more accurately intermediate sleep positions. This research aims to study the feasibility of smartphones as sleep position monitors by (1) developing algorithms to retrieve the sleep position angle from smartphone accelerometry; (2) monitoring the sleep position angle in patients with obstructive sleep apnea (OSA); (3) comparing the discretized sleep angle versus the four classic sleep positions obtained by the video-validated polysomnography (PSG); and (4) analyzing the presence of positional OSA (pOSA) related to its sleep angle of occurrence. Results from 19 OSA patients reveal that a higher resolution sleep position would help to better diagnose and treat patients with position-dependent diseases such as pOSA. They also show that smartphones are promising mHealth tools for enhanced position monitoring at hospitals and home, as they can provide sleep position with higher resolution than the gold-standard video-validated PSG.

JTD Keywords: accelerometry, actigraphy, association, biomedical signal processing, index, latency, mhealth, monitoring, pathophysiology, quality, questionnaire, score, sleep apnea, sleep position, smartphone, time, Accelerometry, Biomedical signal processing, Mhealth, Monitoring, Sleep apnea, Sleep position, Smartphone, Supine position

© 2020 Elsevier B.V. Hypoxia is a common medical problem, sometimes difficult to detect and caused by different situations. Control of hypoxia is of great medical importance and early detection is essential to prevent life threatening complications. However, the few current methods are invasive, expensive, and risky. Thus, the development of reliable and accurate sensors for the continuous monitoring of hypoxia is of vital importance for clinical monitoring. Herein, we report an implantable sensor to address these needs. The developed device is a low-cost, miniaturised implantable electrochemical sensor for monitoring hypoxia in tissue by means of pH detection. This technology is based on protonation/deprotonation of polypyrrole conductive polymer. The sensor was optimized in vitro and tested in vivo intramuscularly and ex vivo in blood in adult rabbits with respiration-induced hypoxia and correlated with the standard device ePOCTM. The sensor demonstrated excellent sensitivity and reproducibility; 46.4 ± 0.4 mV/pH in the pH range of 4–9 and the selectivity coefficient exhibited low interference activity in vitro. The device was linear (R2 = 0.925) with a low dispersion of the values (n = 11) with a cut-off of 7.1 for hypoxia in vivo and ex vivo. Statistics with one-way ANOVA (α = 0.05), shows statistical differences between hypoxia and normoxia states and the good performance of the pH sensor, which demonstrated good agreement with the standard device. The sensor was stable and functional after 18 months. The excellent results demonstrated the feasibility of the sensors in real-time monitoring of intramuscular tissue and blood for medical applications.

JTD Keywords: biocompatibility, blood-flow, clinical monitoring, electrochemical biosensor, electrodes, hypoxia, implantable sensor, in vivo tissue monitoring, ischemia, lactate, ph, ph sensor, rabbits, responses, vitro, Clinical monitoring, Dual signal outputs, Hypoxia, Implantable sensor, In vivo tissue monitoring, Ischemia, Ph sensor

© 2021 Elsevier B.V. The blood-brain barrier (BBB) is a dynamic cellular barrier that regulates brain nutrient supply, waste efflux, and paracellular diffusion through specialized junctional complexes. Finding a system to mimic and monitor BBB integrity (i.e., to be able to assess the effect of certain compounds on opening or closing the barrier) is of vital importance in several pathologies. This work aims to overcome some limitations of current barrier integrity measuring techniques thanks to a multi-layer microfluidic platform with integrated electrodes and Multi-frequency Trans-Endothelial Electrical Resistance (MTEER) in synergy with machine learning algorithms. MTEER measurements are performed across the barrier in a range of frequencies up to 10 MHz highlighting the presence of information on different frequency ranges. Results show that the proposed platform can detect barrier formation, opening, and regeneration afterwards, correlating with the results obtained from immunostaining of junctional complexes. This model presents novel techniques for a future biological barrier in-vitro studies that could potentially help on elucidating barrier opening or sealing on treatments with different drugs.

JTD Keywords: blood-brain barrier, cellular barrier integrity monitoring, impedance sensors, machine learning, microelectrodes, mteer, rapid prototyping, Blood-brain barrier, Cellular barrier integrity monitoring, Electrical impedance spectroscopy, Impedance sensors, Machine learning, Microelectrodes, Mteer, Rapid prototyping

Organ-on-a-chip (OOC) devices offer new approaches for metabolic disease modeling and drug discovery by providing biologically relevant models of tissues and organs in vitro with a high degree of control over experimental variables for high-content screening applications. Yet, to fully exploit the potential of these platforms, there is a need to interface them with integrated non-labeled sensing modules, capable of monitoring, in situ, their biochemical response to external stimuli, such as stress or drugs. In order to meet this need, we aim here to develop an integrated technology based on coupling a localized surface plasmon resonance (LSPR) sensing module to an OOC device to monitor the insulin in situ secretion in pancreatic islets, a key physiological event that is usually perturbed in metabolic diseases such as type 2 diabetes (T2D). As a proof of concept, we developed a biomimetic islet-on-a-chip (IOC) device composed of mouse pancreatic islets hosted in a cellulose-based scaffold as a novel approach. The IOC was interfaced with a state-of-the-art on-chip LSPR sensing platform to monitor the in situ insulin secretion. The developed platform offers a powerful tool to enable the in situ response study of microtissues to external stimuli for applications such as a drug-screening platform for human models, bypassing animal testing.

JTD Keywords: biosensor, cytoarchitecture, dna hybridization, gelatin, in situ insulin monitoring, langerhans, lspr sensors, microfluidic device, organ-on-a-chip, parallel, platform, scaffold, Human pancreatic-islets, In situ insulin monitoring, Lspr sensors, Organ-on-a-chip

Wastewater treatment plants (WWTPs) are sources of greenhouse gases, hazardous air pollutants and offensive odors. These emissions can have negative repercussions in and around the plant, degrading the quality of life of surrounding neighborhoods, damaging the environment, and reducing employee’s overall job satisfaction. Current monitoring methodologies based on fixed gas detectors and sporadic olfactometric measurements (human panels) do not allow for an accurate spatial representation of such emissions. In this paper we use a small drone equipped with an array of electrochemical and metal oxide (MOX) sensors for mapping odorous gases in a mid-sized WWTP. An innovative sampling system based on two (10 m long) flexible tubes hanging from the drone allowed near-source sampling from a safe distance with negligible influence from the downwash of the drone’s propellers. The proposed platform is very convenient for monitoring hard-toreach emission sources, such as the plant’s deodorization chimney, which turned out to be responsible for the strongest odor emissions. The geo-localized measurements visualized in the form of a two-dimensional (2D) gas concentration map revealed the main emission hotspots where abatement solutions were needed. A principal component analysis (PCA) of the multivariate sensor signals suggests that the proposed system can also be used to trace which emission source is responsible for a certain measurement.

JTD Keywords: air pollution, environmental monitoring, gas sensors, industrial emissions, mapping, odour, uav, Air pollution, Drone, Environmental monitoring, Gas sensors, Industrial emissions, Mapping, Odour, Sensors, Uav

© 1964-2012 IEEE. Surface electromyography (sEMG) can be used for the evaluation of respiratory muscle activity. Recording sEMG involves the use of surface electrodes in a bipolar configuration. However, electrocardiographic (ECG) interference and electrode orientation represent considerable drawbacks to bipolar acquisition. As an alternative, concentric ring electrodes (CREs) can be used for sEMG acquisition and offer great potential for the evaluation of respiratory muscle activity due to their enhanced spatial resolution and simple placement protocol, which does not depend on muscle fiber orientation. The aim of this work was to analyze the performance of CREs during respiratory sEMG acquisitions. Respiratory muscle sEMG was applied to the diaphragm and sternocleidomastoid muscles using a bipolar and a CRE configuration. Thirty-two subjects underwent four inspiratory load spontaneous breathing tests which was repeated after interchanging the electrode positions. We calculated parameters such as (1) spectral power and (2) median frequency during inspiration, and power ratios of inspiratory sEMG without ECG in relation to (3) basal sEMG without ECG (Rins/noise), (4) basal sEMG with ECG (Rins/cardio) and (5) expiratory sEMG without ECG (Rins/exp). Spectral power, Rins/noise and Rins/cardio increased with the inspiratory load. Significantly higher values (p < 0.05) of Rins/cardio and significantly higher median frequencies were obtained for CREs. Rins/noise and Rins/exp were higher for the bipolar configuration only in diaphragm sEMG recordings, whereas no significant differences were found in the sternocleidomastoid recordings. Our results suggest that the evaluation of respiratory muscle activity by means of sEMG can benefit from the remarkably reduced influence of cardiac activity, the enhanced detection of the shift in frequency content and the axial isotropy of CREs which facilitates its placement.

JTD Keywords: atmospheric measurements, concentric ring electrodes, electrocardiography, electrodes, electromyography, laplacian potential, non-invasive respiratory monitoring, particle measurements, respiratory muscles, surface electromyography, Concentric ring electrodes, Laplacian potential, Muscles, Non-invasive respiratory monitoring, Respiratory muscles, Surface electromyography

© 2021, The Author(s). Background: One of the most prevalent causes of fetal hypoxia leading to stillbirth is placental insufficiency. Hemodynamic changes evaluated with Doppler ultrasound have been used as a surrogate marker of fetal hypoxia. However, Doppler evaluation cannot be performed continuously. As a first step, the present work aimed to evaluate the performance of miniaturized electrochemical sensors in the continuous monitoring of oxygen and pH changes in a model of acute hypoxia-acidosis. Methods: pH and oxygen electrochemical sensors were evaluated in a ventilatory hypoxia rabbit model. The ventilator hypoxia protocol included 3 differential phases: basal (100% FiO2), the hypoxia-acidosis period (10% FiO2) and recovery (100% FiO2). Sensors were tested in blood tissue (ex vivo sensing) and in muscular tissue (in vivo sensing). pH electrochemical and oxygen sensors were evaluated on the day of insertion (short-term evaluation) and pH electrochemical sensors were also tested after 5 days of insertion (long-term evaluation). pH and oxygen sensing were registered throughout the ventilatory hypoxia protocol (basal, hypoxia-acidosis, and recovery) and were compared with blood gas metabolites results from carotid artery catheterization (obtained with the EPOC blood analyzer). Finally, histological assessment was performed on the sensor insertion site. One-way ANOVA was used for the analysis of the evolution of acid-based metabolites and electrochemical sensor signaling results; a t-test was used for pre- and post-calibration analyses; and chi-square analyses for categorical variables. Results: At the short-term evaluation, both the pH and oxygen electrochemical sensors distinguished the basal and hypoxia-acidosis periods in both the in vivo and ex vivo sensing. However, only the ex vivo sensing detected the recovery period. In the long-term evaluation, the pH electrochemical sensor signal seemed to lose sensibility. Finally, histological assessment revealed no signs of alteration on the day of evaluation (short-term), whereas in the long-term evaluation a sub-acute inflammatory reaction adjacent to the implantation site was detected. Conclusions: Miniaturized electrochemical sensors represent a new generation of tools for the continuous monitoring of hypoxia-acidosis, which is especially indicated in high-risk pregnancies. Further studies including more tissue-compatible material would be required in order to improve long-term electrochemical sensing.

JTD Keywords: acute hypoxia-acidosis, continuous monitoring of acid-base status, continuous monitoring of acid–base status, electrochemical sensors, high-risk pregnancies, Acute hypoxia-acidosis, Continuous monitoring of acid–base status, Electrochemical sensors, High-risk pregnancies

Obstructive sleep apnea (OSA) is a sleep disorder in which repetitive upper airway obstructive events occur during sleep. These events can induce hypoxia, which is a risk factor for multiple cardiovascular and cerebrovascular diseases. OSA is also known to be position-dependent in some patients, which is referred to as positional OSA (pOSA). Screening for pOSA is necessary in order to design more personalized and effective treatment strategies. In this article, we propose analyzing accelerometry signals, recorded with a smartphone, to detect and monitor OSA at home. Our objectives were to: (1) develop an algorithm for detecting thoracic movement associated with disordered breathing events; (2) compare the performance of smartphones as OSA monitoring tools with a type 3 portable sleep monitor; and (3) explore the feasibility of using smartphone accelerometry to retrieve reliable patient sleep position data and assess pOSA. Accelerometry signals were collected through simultaneous overnight acquisition using both devices with 13 subjects. The smartphone tool showed a high degree of concordance compared to the portable device and succeeded in estimating the apnea-hypopnea index (AHI) and classifying the severity level in most subjects. To assess the agreement between the two systems, an event-by-event comparison was performed, which found a sensitivity of 90% and a positive predictive value of 80%. It was also possible to identify pOSA by determining the ratio of events occurring in a specific position versus the time spent in that position during the night. These novel results suggest that smartphones are promising mHealth tools for OSA and pOSA monitoring at home.

JTD Keywords: Accelerometry, Biomedical signal processing, mHealth, Monitoring, Sleep apnea, Sleep position, Smartphone

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.

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

In this work, we present a successful strategy to convert recycled LDPE films, which usually end up in landfills or leak into the environment, into an advanced biomedical product. More specifically, LDPE films for food packaging have been treated with atmosphere corona discharge plasma for electrochemical detection of glucose. Enzyme-functionalized sensors manufactured using such recycled materials, which act as a mediator capable of electrocommunicating with the glucose oxidase (GOx) enzyme, are able to detect glucose concentrations in sweat and are fully compatible with the levels of such bioanalytes in both healthy and diabetic patients. Covalent immobilization of the GOx enzyme on the plasma-treated LDPE films has been successfully performed using the carbodiimide method, as proved by X-ray photoelectron spectroscopy. Then, the electronic communication between the deeply buried active site of the GOx and the reactive excited species formed at the surface of the plasma-treated LDPE has been demonstrated by linear sweep voltammetry. Finally, cyclic voltammetry in artificial sweat has been used to show that the LDPE-functionalized sensor has a linear response in the concentration of range of 50 μM to 1 mM with a limit of detection of 375 μA·μM–1·cm–2. Comparison of the performance of sensors prepared using recycled (i.e. with additives) and pristine (i.e. without additives) LDPE indicates that the utilization of the former does not require any pretreatment to eliminate additives. The present strategy demonstrates a facile approach for recycling LDPE waste into a high value-added product, which will potentially pave the way for the treatment of plastic waste in the future. Noninvasive glucose sensors based on recycled LDPE may play a crucial role in monitoring diabetes in underdeveloped regions.

JTD Keywords: Biosensors, Diabetes monitoring, High-value recycling, Plasma treatment, Sweat sensors

Lipid membranes are involved in many physiological processes like recognition, signaling, fusion or remodeling of the cell membrane or some of its internal compartments. Within the cell, they are the ultimate barrier, while maintaining the fluidity or flexibility required for a myriad of processes, including membrane protein assembly. The physical properties of in vitro model membranes as model cell membranes have been extensively studied with a variety of techniques, from classical thermodynamics to advanced modern microscopies. Here we review the nanomechanics of solid-supported lipid membranes with a focus in their phase behavior. Relevant information obtained by quartz crystal microbalance with dissipation monitoring (QCM-D) and atomic force microscopy (AFM) as complementary techniques in the nano/mesoscale interface is presented. Membrane morphological and mechanical characterization will be discussed in the framework of its phase behavior, phase transitions and coexistence, in simple and complex models, and upon the presence of cholesterol.

JTD Keywords: Lipid phase behavior, Phase transition, Phase coexistence, Nanomechanics, Thermodynamics, Atomic force microscopy (AFM), Quartz crystal microbalance with dissipation monitoring (QCM-D)

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

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

Obstructive sleep apnea (OSA) is a prevalent disease, but most patients remain undiagnosed and untreated. Here we propose analyzing smartphone audio signals for screening OSA patients at home. Our objectives were to: (1) develop an algorithm for detecting silence events and classifying them into apneas or hypopneas; (2) evaluate the performance of this system; and (3) compare the information provided with a type 3 portable sleep monitor, based mainly on nasal airflow. Overnight signals were acquired simultaneously by both systems in 13 subjects (3 healthy subjects and 10 OSA patients). The sample entropy of audio signals was used to identify apnea/hypopnea events. The apnea-hypopnea indices predicted by the two systems presented a very high degree of concordance and the smartphone correctly detected and stratified all the OSA patients. An event-by-event comparison demonstrated good agreement between silence events and apnea/hypopnea events in the reference system (Sensitivity = 76%, Positive Predictive Value = 82%). Most apneas were detected (89%), but not so many hypopneas (61%). We observed that many hypopneas were accompanied by snoring, so there was no sound reduction. The apnea/hypopnea classification accuracy was 70%, but most discrepancies resulted from the inability of the nasal cannula of the reference device to record oral breathing. We provided a spectral characterization of oral and nasal breathing to correct this effect, and the classification accuracy increased to 82%. This novel knowledge from acoustic signals may be of great interest for clinical practice to develop new non-invasive techniques for screening and monitoring OSA patients at home.

JTD Keywords: Sleep apnea, Acoustics, Monitoring, Entropy, Sensors, Microphones, Acoustics, Biomedical signal processing, mHealth, Monitoring, Sleep apnea, Smartphone

Diaphragm neuromechanical coupling (NMC), which reflects the efficiency of conversion of neural activation to transdiaphragmatic pressure (Pdi), is increasingly recognized to be a useful clinical index of diaphragm function and respiratory mechanics in neuromuscular weakness and cardiorespiratory disease. However, the current gold standard assessment of diaphragm NMC requires invasive measurements of Pdi and crural diaphragm electromyography (oesEMGdi), which complicates the measurement of diaphragm NMC in clinical practice. This is the first study to compare invasive measurements of diaphragm NMC (iNMC) using the relationship between Pdi and oesEMGdi, with noninvasive assessment of NMC (nNMC) using surface mechanomyography (sMMGlic) and electromyography (sEMGlic) of lower chest wall inspiratory muscles. Both invasive and noninvasive measurements were recorded in twelve healthy adult subjects during an inspiratory threshold loading protocol. A linear relationship between noninvasive sMMGlic and sEMGlic measurements was found, resulting in little change in nNMC with increasing inspiratory load. By contrast, a curvilinear relationship between invasive Pdi and oesEMGdi measurements was observed, such that there was a progressive increase in iNMC with increasing inspiratory threshold load. Progressive recruitment of lower ribcage muscles, serving to enhance the mechanical advantage of the diaphragm, may explain the more linear relationship between sMMGlic and sEMGlic (both representing lower intercostal plus costal diaphragm activity) than between Pdi and crural oesEMGdi. Noninvasive indices of NMC derived from sEMGlic and sMMGlic may prove to be useful indices of lower chest wall inspiratory muscle NMC, particularly in settings that do not have access to invasive measures of diaphragm function.

JTD Keywords: Cardiovascular system, Diaphragms, Diseases, Electromyography, Medical signal processing, Neurophysiology, Patient monitoring, Pneumodynamics, Inspiratory muscle neuromechanical coupling, Diaphragm neuromechanical coupling, Neural activation, Transdiaphragmatic pressure, Diaphragm function, Respiratory mechanics, Diaphragm NMC, Invasive measurements, Crural diaphragm electromyography, iNMC, Noninvasive assessment, nNMC, Lower chest wall inspiratory muscles, Inspiratory threshold loading protocol, Noninvasive sMMGlic measurements, sEMGlic measurements, oesEMGdi measurements, Inspiratory threshold load, Lower ribcage muscles, Lower intercostal plus costal diaphragm activity, Crural oesEMGdi, Noninvasive indices, sEMGlic sMMGlic, Lower chest wall inspiratory muscle NMC, Surface mechanomyography, Electromyography, Inspiratory threshold loading, Mechanomyography, Neuromechanical coupling, Respiratory muscles

Obstructive sleep apnea (OSA) is a common disorder with a low diagnosis ratio, leaving many patients undiagnosed and untreated. In the last decades, accelerometry has been found to be a feasible solution to obtain respiratory activity and a potential tool to monitor OSA. On the other hand, many smartphone-based systems have already been developed to propose solutions for OSA monitoring and treatment. The objective of this work was to develop an automatic event detector based on smartphone accelerometry and pulse oximetry, and to assess its ability to detect thoracic movements. It was validated with a commercial OSA monitoring system at home. Results of this preliminary pilot study showed that the proposed event detector for accelerometry signals is a feasible tool to detect abnormal respiratory events, such as apneas and hypopneas, and has potential to be included in smartphone-based systems for OSA assessment.

JTD Keywords: Sleep apnea, Detectors, Pulse oximetry, Monitoring, Manuals, Band-pass filters, Pulse oximeter

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

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

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

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

Obstructive Sleep Apnea (OSA) is a sleep disorder that affects mainly the adult and elderly population. Due to the high percentage of patients who remain undiagnosed and untreated because of limitations of current diagnosis methods, the management of OSA is an important social, scientific and economic problem that will be difficult to be assumed by health systems. On the other hand, smartphone platforms (mHealth systems) are being considered as an innovative solution, thanks to the integration of the essential sensors to obtain clinically relevant parameters in the same device or in combination with wireless wearable devices.

JTD Keywords: Sleep apnea, Microphones, Monitoring, Sensors, Accelerometers, Biomedical monitoring, Band-pass filters

A method for online decorrelation of chemical sensor signals from the effects of environmental humidity and temperature variations is proposed. The goal is to improve the accuracy of electronic nose measurements for continuous monitoring by processing data from simultaneous readings of environmental humidity and temperature. The electronic nose setup built for this study included eight metal-oxide sensors, temperature and humidity sensors with a wireless communication link to external computer. This wireless electronic nose was used to monitor the air for two years in the residence of one of the authors and it collected data continuously during 537 days with a sampling rate of 1 sample per second. To estimate the effects of variations in air humidity and temperature on the chemical sensors' signals, we used a standard energy band model for an n-type metal-oxide (MOX) gas sensor. The main assumption of the model is that variations in sensor conductivity can be expressed as a nonlinear function of changes in the semiconductor energy bands in the presence of external humidity and temperature variations. Fitting this model to the collected data, we confirmed that the most statistically significant factors are humidity changes and correlated changes of temperature and humidity. This simple model achieves excellent accuracy with a coefficient of determination R2 close to 1. To show how the humidity–temperature correction model works for gas discrimination, we constructed a model for online discrimination among banana, wine and baseline response. This shows that pattern recognition algorithms improve performance and reliability by including the filtered signal of the chemical sensors.

JTD Keywords: Electronic nose, Chemical sensors, Humidity, Temperature, Decorrelation, Wireless e-nose, MOX sensors, Energy band model, Home monitoring

Wireless sensors are an emerging technology that allows to assist physicians in the monitoring of patients health status. This approach can be used for the non-invasive recording of the electrical respiratory muscle activity of the diaphragm (EMGdi). In this work, we acquired the EMGdi signal of a healthy subject performing an inspiratory load test. To this end, the EMGdi activity was captured from a single channel of electromyography using a wireless platform which was compared with the EMGdi and the inspiratory mouth pressure (Pmouth) recorded with a conventional lab equipment. From the EMGdi signal we were able to evaluate the neural respiratory drive, a biomarker used for assessing the respiratory muscle function. In addition, we evaluated the breathing movement and the cardiac activity, estimating two cardio-respiratory parameters: the respiratory rate and the heart rate. The correlation between the two EMGdi signals and the Pmouth improved with increasing the respiratory load (Pearson's correlation coefficient ranges from 0.33 to 0.85). The neural respiratory drive estimated from both EMGdi signals showed a positive trend with an increase of the inspiratory load and being higher in the conventional EMGdi recording. The respiratory rate comparison between measurements revealed similar values of around 16 breaths per minute. The heart rate comparison showed a root mean error of less than 0.2 beats per minute which increased when incrementing the inspiratory load. In summary, this preliminary work explores the use of wireless devices to record the muscle respiratory activity to derive several physiological parameters. Its use can be an alternative to conventional measuring systems with the advantage of being portable, lightweight, flexible and operating at low energy. This technology can be attractive for medical staff and may have a positive impact in the way healthcare is being delivered.

JTD Keywords: Biomedical monitoring, Electrodes, Medical services, Monitoring, Muscles, Wireless communication, Wireless sensor networks

An automatic gait initialization strategy based on user intention sensing in the context of rehabilitation with a lower-limb wearable robot is proposed and evaluated. The proposed strategy involves monitoring the human-orthosis interaction torques and initial position deviation to determine the gait initiation instant and to modify orthosis operation for gait assistance, when needed. During gait, the compliant control algorithm relies on the adaptation of the joints' stiffness in function of their interaction torques and their deviation from the desired trajectories, while maintaining the dynamic stability. As a reference input, the average of a set of recorded gaits obtained from healthy subjects is used. The algorithm has been tested with five healthy subjects showing its efficient behavior in initiating the gait and maintaining the equilibrium while walking in presence of external forces. The work is performed as a preliminary study to assist patients suffering from incomplete Spinal cord injury and Stroke.

JTD Keywords: Biomedical monitoring, Exoskeletons, Joints, Knee, Legged locomotion, Trajectory, Exoskeleton, adaptive control, gait assistance, gait initiation, rehabilitation, wearable robot

The use of an autonomous mobile robot to locate gas-leaks and air quality monitoring in indoor environments are promising tasks that will avoid risky human operations. However, these are challenging tasks due to the chaotic gas profile propagation originated by uncontrolled air flows. This paper proposes the localization of an acetone gas-leak in a 44 m-length indoor corridor with a mobile robot equipped with a PID sensor. This paper assesses the influence of the mobile robot velocity and the relative height of the PID sensor in the profile of the measurements. The results show weak influence of the robot velocity and strong influence of the relative height of the PID sensor. An estimate of the gas-leak location is also performed by computing the center of mass of the highest gas concentrations.

JTD Keywords: Gas source detection, LIDAR sensor, Mobile robot, PID sensor, SLAM, Acetone, Air quality, Gases, Indoor air pollution, Mobile robots, Robots, Air quality monitoring, Autonomous Mobile Robot, Gas sources, Indoor environment, Leak localization, LIDAR sensors, Profile propagation, SLAM, Ionization of gases

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.

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

Among the most common sleep disorders are those related to disruptions in airflow (apnea) or reductions in the breath amplitude (hypopnea) with or without obstruction of the upper airway (UA). One of the most important sleep disorders is obstructive sleep apnea (OSA). This sleep-disordered breathing, quantified by the apnea-hypopnea index (AHI), can produce a significant reduction of oxygen saturation and an abnormal elevation of carbon dioxide levels in the blood. Apnea and hypopnea episodes are associated with arousals and sleep fragmentation during the night and compensatory response of the autonomic nervous system.

JTD Keywords: Biomedical engineering, Biomedical measurements, Biomedical monitoring, Breathing disorders, Medical conditions, Medical treatment, Sleep, Sleep apnea

JTD Keywords: Optogenetics, Genetically encoded biosensors, Chloride imaging, pH monitoring, Intracellular Ca, Optopharmacology, Photochromic ligands, Photoswitchable tethered ligands

Background: The identification of obstructive and central hypopneas is considered challenging in clinical practice. Presently, obstructive and central hypopneas are usually not differentiated or scores lack reliability due to the technical limitations of standard polysomnography. Esophageal pressure measurement is the gold-standard for identifying these events but its invasiveness deters its usage in daily practice. Objectives: To determine the feasibility and efficacy of an automatic noninvasive analysis method for the differentiation of obstructive and central hypopneas based solely on a single-channel nasal airflow signal. The obtained results are compared with gold-standard esophageal pressure scores. Methods: A total of 41 patients underwent full night polysomnography with systematic esophageal pressure recording. Two experts in sleep medicine independently differentiated hypopneas with the gold-standard esophageal pressure signal. Features were automatically extracted from the nasal airflow signal of each annotated hypopnea to train and test the automatic analysis method. Interscorer agreement between automatic and visual scorers was measured with Cohen's kappa statistic (κ). Results: A total of 1,237 hypopneas were visually differentiated. The automatic analysis achieved an interscorer agreement of κ = 0.37 and an accuracy of 69% for scorer A, κ = 0.40 and 70% for scorer B and κ = 0.41 and 71% for the agreed scores of scorers A and B. Conclusions: The promising results obtained in this pilot study demonstrate the feasibility of noninvasive single-channel hypopnea differentiation. Further development of this method may help improving initial diagnosis with home screening devices and offering a means of therapy selection and/or control.

JTD Keywords: Central sleep hypopnea, Esophageal pressure, Home monitoring, Obstructive sleep hypopnea, Sleep disordered breathing

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

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

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.

JTD 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

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.

JTD 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