Publications

We report the fabrication and characterization of a highly sensitive pressure sensor that has been successfully tested using 3D-bioprinted skeletal muscle tissue. The proposed pressure sensor consists of two assembled 3D printed specimens, which were obtained using 60/40 v/v poly(3,4-ethylenedioxythiophene):polystyrene sulfonic acid (PEDOT:PSS) / poly(ethylene glycol) diacrylate (PEGDA) mixture, placed between two indium tin oxidecoated polyethylene terephthalate (PET-ITO) films. The printed specimens were shaped with a serrated structure, improving the sensitivity of the contact when pressed against PET-ITO film. Initially, the performance of the fabricated pressure sensor was tested using light cylindrical weights, which corresponded to pressures ranging from 0.99 to 14.71 kPa, and as prove of concept, carefully pressing with the finger (from 2.91 to 6.81 kPa). As the sensitivity and fast response of sensor were compatible with detection of soft muscle contractions, 3D-bioprinted skeletal muscle bioactuators were manufactured using myoblast cells. The contractions of the bioactuators, which were induced using electrical stimulation, exerted a pressure of 1.5 kPa only that was clearly and precisely detected by the sensor. Overall, the potential application of proposed pressure sensor for wearable and biomedical devices is evidenced by demonstrating its fast response time (< 50 ms) and sensitivity.

JTD Keywords: 4-ethylenedioxythiophene), Bioactuator, Healt, Hydrogels, Poly(3, Poly(ethylene glycol) diacrylate, Raman-spectroscopy, Soft electronics, Wearable electronic

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

Breathing pattern has been shown to be different in chronic obstructive pulmonary disease (COPD) patients compared to healthy controls during rest and walking. In this study we evaluated respiratory parameters and the breathing variability of COPD patients as a function of their severity. Thoracic bioimpedance was acquired on 66 COPD patients during the performance of the six-minute walk test (6MWT), as well as 5 minutes before and after the test while the patients were seated, i.e. resting and recovery phases. The patients were classified by their level of airflow limitation into moderate and severe groups. We characterized the breathing patterns by evaluating common respiratory parameters using only wearable bioimpedance. Specifically, we computed the median and the coefficient of variation of the parameters during the three phases of the protocol, and evaluated the statistical differences between the two COPD severity groups. We observed significant differences between the COPD severity groups only during the sitting phases, whereas the behavior during the 6MWT was similar. Particularly, we observed an inverse relationship between breathing pattern variability and COPD severity, which may indicate that the most severely diseased patients had a more restricted breathing compared to the moderate patients.

JTD Keywords: 6mwt, activation, breathing pattern, burden, chronic obstructive pulmonary disease, exercise, muscles, pressure, pulmonary, signals, variability, volumes, wearables, Bioimpedance, Impedance pneumography

Chronic obstructive pulmonary disease (COPD) requires a multifactorial assessment, evaluating the airflow limitation and symptoms of the patients. The 6-min walk test (6MWT) is commonly used to evaluate the functional exercise capacity in these patients. This study aims to propose a novel predictive model of the major 6MWT outcomes for COPD assessment, without physical performance measurements.Cardiopulmonary and clinical parameters were obtained from fifty COPD patients. These parameters were used as inputs of a Bayesian network (BN), which integrated three multivariate models including the 6-min walking distance (6MWD), the maximum HR (HRmax) after the walking, and the HR decay 3 min after (HRR3). The use of BN allows the assessment of the patients' status by predicting the 6MWT outcomes, but also inferring disease severity parameters based on actual patient's 6MWT outcomes.Firstly, the correlation obtained between the estimated and actual 6MWT measures was strong (R = 0.84, MAPE = 8.10% for HRmax) and moderate (R = 0.58, MAPE = 15.43% for 6MWD and R = 0.58, MAPE = 32.49% for HRR3), improving the classical methods to estimate 6MWD. Secondly, the classification of disease severity showed an accuracy of 78.3% using three severity groups, which increased up to 84.4% for two defined severity groups.We propose a powerful two-way assessment tool for COPD patients, capable of predicting 6MWT outcomes without the need for an actual walking exercise. This model-based tool opens the way to implement a continuous monitoring system for COPD patients at home and to provide more personalized care.Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.

JTD Keywords: 6mwt, bayesian networks, copd, distance, exercise capacity, physical capacity, reference equations, severity, survival, wearables, 6mwt, Heart-rate recovery, Wearables

Background: There is a pressing need for scalable healthcare solutions and a shift in the rehabilitation paradigm from hospitals to homes to tackle the increase in stroke incidence while reducing the practical and economic burden for patients, hospitals, and society. Digital health technologies can contribute to addressing this challenge; however, little is known about their effectiveness in at-home settings. In response, we have designed the RGS@home study to investigate the effectiveness, acceptance, and cost of a deep tech solution called the Rehabilitation Gaming System (RGS). RGS is a cloud-based system for delivering Al-enhanced rehabilitation using virtual reality, motion capture, and wearables that can be used in the hospital and at home. The core principles of the brain theory-based RGS intervention are to deliver rehabilitation exercises in the form of embodied, goal-oriented, and task-specific action.; Methods: The RGS@home study is a randomized longitudinal clinical trial designed to assess whether the combination of the RGS intervention with standard care is superior to standard care alone for the functional recovery of stroke patients at the hospital and at home. The study is conducted in collaboration with hospitals in Spain, Sweden, and France and includes inpatients and outpatients at subacute and chronic stages post-stroke. The intervention duration is 3 months with assessment at baseline and after 3, 6, and 12 months. The impact of RGS is evaluated in terms of quality of life measurements, usability, and acceptance using standardized clinical scales, together with health economic analysis. So far, one-third of the patients expected to participate in the study have been recruited (N = 90, mean age 60, days after stroke >= 30 days). The trial will end in July 2023.; Discussion: We predict an improvement in the patients' recovery, high acceptance, and reduced costs due to a soft landing from the clinic to home rehabilitation. In addition, the data provided will allow us to assess whether the prescription of therapy at home can counteract deterioration and improve quality of life while also identifying new standards for online and remote assessment, diagnostics, and intervention across European hospitals.

JTD Keywords: deep tech, e-health, home treatment, motor recovery, randomized clinical trial, stroke, upper extremities, virtual reality, Deep tech, E-health, Functional recovery, Home treatment, Motor recovery, Randomized clinical trial, Stroke, Upper extremities, Virtual reality, Wearables

Large doses of movement practice have been shown to restore upper extremities' motor function in a significant subset of individuals post-stroke. However, such large doses are both difficult to implement in the clinic and highly inefficient. In addition, an important reduction in upper extremity function and use is commonly seen following rehabilitation-induced gains, resulting in “rehabilitation in vain”. For those with mild to moderate sensorimotor impairment, the limited spontaneous use of the more affected limb during activities of daily living has been previously proposed to cause a decline of motor function, initiating a vicious cycle of recovery, in which non-use and poor performance reinforce each other. Here, we review computational, experimental, and clinical studies that support the view that if arm use is raised above an effective threshold, one enters a virtuous cycle in which arm use and function can reinforce each other via self-practice in the wild. If not, one enters a vicious cycle of declining arm use and function. In turn, and in line with best practice therapy recommendations, this virtuous/vicious cycle model advocates for a paradigm shift in neurorehabilitation whereby rehabilitation be embedded in activities of daily living such that self-practice with the aid of wearable technology that reminds and motivates can enhance paretic limb use of those who possess adequate residual sensorimotor capacity. Altogether, this model points to a user-centered approach to recovery post-stroke that is tailored to the participant's level of arm use and designed to motivate and engage in self-practice through progressive success in accomplishing meaningful activities in the wild. Copyright © 2022 Ballester, Winstein and Schweighofer.

JTD Keywords: compensatory movement, computational neurorehabilitation, decision-making, individuals, learned non-use, learned nonuse, monkeys, neurorehabilitation, recovery, rehabilitation, stroke, stroke patients, wearable sensors, wrist, Arm movement, Article, Cerebrovascular accident, Clinical decision making, Clinical practice, Clinical study, Compensatory movement, Computational neurorehabilitation, Computer model, Daily life activity, Decision-making, Experimental study, Human, Induced movement therapy, Learned non-use, Musculoskeletal function, Neurorehabilitation, Paresis, Sensorimotor function, Stroke, Stroke rehabilitation, User-centered design, Vicious cycle, Virtuous cycle, Wearable sensors

Polymer nanocomposite materials based on metallic nanowires are widely investigated as transparent and flexible electrodes or as stretchable conductors and dielectrics for biosensing. Here we show that Scanning Dielectric Microscopy (SDM) can map the depth distribution of metallic nanowires within the nanocomposites in a non-destructive way. This is achieved by a quantitative analysis of sub-surface electrostatic force microscopy measurements with finite-element numerical calculations. As an application we determined the three-dimensional spatial distribution of ?50 nm diameter silver nanowires in ?100 nm-250 nm thick gelatin films. The characterization is done both under dry ambient conditions, where gelatin shows a relatively low dielectric constant, ?r ? 5, and under humid ambient conditions, where its dielectric constant increases up to ?r ? 14. The present results show that SDM can be a valuable non-destructive subsurface characterization technique for nanowire-based nanocomposite materials, which can contribute to the optimization of these materials for applications in fields such as wearable electronics, solar cell technologies or printable electronics. © The Royal Society of Chemistry.

JTD Keywords: composite, constant, electrodes, mode, nanostructures, objects, progress, subsurface, tomography, Composite materials, Dielectric materials, Electric force microscopy, Electrostatic force, Force microscopy, Low dielectric constants, Nanocomposites, Numerical calculation, Polymer nanocomposite, Printable electronics, Scanning dielectric microscopy, Silver nanowires, Solar cell technology, Stretchable conductors, Subsurface characterizations, Transparent electrodes, Wearable technology

© 1964-2012 IEEE. Chronic Obstructive Pulmonary Disease (COPD) is one of the most common chronic conditions. The current assessment of COPD requires a maximal maneuver during a spirometry test to quantify airflow limitations of patients. Other less invasive measurements such as thoracic bioimpedance and myographic signals have been studied as an alternative to classical methods as they provide information about respiration. Particularly, strong correlations have been shown between thoracic bioimpedance and respiratory volume. The main objective of this study is to investigate bioimpedance and its combination with myographic parameters in COPD patients to assess the applicability in respiratory disease monitoring. We measured bioimpedance, surface electromyography and surface mechanomyography in forty-three COPD patients during an incremental inspiratory threshold loading protocol. We introduced two novel features that can be used to assess COPD condition derived from the variation of bioimpedance and the electrical and mechanical activity during each respiratory cycle. These features demonstrate significant differences between mild and severe patients, indicating a lower inspiratory contribution of the inspiratory muscles to global respiratory ventilation in the severest COPD patients. In conclusion, the combination of bioimpedance and myographic signals provides useful indices to noninvasively assess the breathing of COPD patients.

JTD Keywords: Bioimpedance, Chronic obstructive pulmonary disease, Inspiratory threshold protocol, Myographic signals, Wearables

After a stroke, a great number of patients experience persistent motor impairments such as hemiparesis or weakness in one entire side of the body. As a result, the lack of use of the paretic limb might be one of the main contributors to functional loss after clinical discharge. We aim to reverse this cycle by promoting the use of the paretic limb during activities of daily living (ADLs). To do so, we describe the key components of a system composed of a wearable bracelet (i.e., a smartwatch) and a mobile phone, designed to bring a set of neurorehabilitation principles that promote acquisition, retention and generalization of skills to the home of the patient. A fundamental question is whether the loss in motor function derived from learned–non–use may emerge as a consequence of decision–making processes for motor optimization. Our system is based on well-established rehabilitation strategies that aim to reverse this behaviour by increasing the reward associated with action execution and implicitly reducing the expected cost of using the paretic limb, following the notion of reinforcement–induced movement therapy (RIMT). Here we validate an accelerometer-based measure of arm use and its capacity to discriminate different activities that require increasing movement of the arm. The usability and acceptance of the device as a rehabilitation tool is tested using a battery of self–reported and objective measurements obtained from acute/subacute patients and healthy controls. We believe that an extension of these technologies will allow for the deployment of unsupervised rehabilitation paradigms during and beyond hospitalization time. © 2021, Springer Nature Switzerland AG.

JTD Keywords: adls, hemiparesis, learned non-use, wearables, Activities of daily living, Adls, Functional loss, Generalisation, Hemiparesis, Learned non-use, Motor impairments, Neurorehabilitation [], Patient experiences, Stroke, Wearable devices, Wearable technology, Wearables

Many studies have focused on novel noninvasive techniques to monitor respiratory rate such as bioimpedance. We propose an algorithm to detect respiratory phases using wearable bioimpedance to compute time parameters like respiratory rate, inspiratory and expiratory times, and duty cycle. The proposed algorithm was compared with two other algorithms from literature designed to estimate the respiratory rate using physiological signals like bioimpedance. We acquired bioimpedance and airflow from 50 chronic obstructive pulmonary disease (COPD) patients during an inspiratory loading protocol. We compared performance of the algorithms by computing accuracy and mean average percentage error (MAPE) between the bioimpedance parameters and the reference parameters from airflow. We found similar performance for the three algorithms in terms of accuracy (>0.96) and respiratory time and rate errors (<3.42 %). However, the proposed algorithm showed lower MAPE in duty cycle (10.18 %), inspiratory time (10.65 %) and expiratory time (8.61 %). Furthermore, only the proposed algorithm kept the statistical differences in duty cycle between COPD severity levels that were observed using airflow. Accordingly, we suggest bioimpedance to monitor breathing pattern parameters in home situations.Clinical relevance - This study exhibits the suitability of wearable thoracic bioimpedance to detect respiratory phases and to compute accurate breathing pattern parameters. © 2021 IEEE.

JTD Keywords: algorithms, copd, signals, Algorithm, Algorithms, Bioimpedance, Breathing rate, Chronic obstructive lung disease, Electronic device, Human, Humans, Lung, Pulmonary disease, chronic obstructive, Respiratory rate, Wearable electronic devices

The utilization of hydrogels derived from biopolymers as solid electrolyte (SE) of electrochemical supercapacitors (ESCs) is a topic of increasing interest because of their promising applications in biomedicine (e.g. for energy storage in autonomous implantable devices). In this work an unsaturated polyesteramide that contains phenylalanine, butenediol and fumarate as building blocks has been photo-crosslinked to obtain a hydrogel (UPEA-h). The structure of UPEA-h, which is characterized by a network of open interconnected pores surrounded by regions with compact morphology, favors ion transport, while the biodegradability and biocompatibility conferred by the α-amino acid unit and the ester group are appropriated for its usage in the biomedical field. Voltammetric and galvanostatic assays have been conducted to evaluate the behavior of UPEA-h when used as SE in ESCs with poly(3,4-ethylenedioxythiophene) (PEDOT) electrodes. Hence, PEDOT/UPEA-h devices displayed supercapacitor response of up 179 F/g and capacitance retention higher than 90%. Moreover, the long-term stability, leakage-current, and self-discharging response of PEDOT/UPEA-h ESCs reflect the great potential of UPEA-h as ion-conductive electrolyte. Indeed, the performance of PEDOT/UPEA-h is higher than found in analogous devices constructed using other biohydrogels as SE (e.g. κ-carrageenan, poly-γ-glutamic acid and cellulose hydrogels).

JTD Keywords: Energy storage, Hydrogel electronics, Ion conductivity, Photo-crosslinking, Wearable electronics

Chronic obstructive pulmonary disease (COPD) patients exhibit impaired autonomic control which can be assessed by heart rate variability analysis. The study aims to evaluate the cardiac autonomic responses of COPD patients after completing a conventional six-minute walk test (6MWT). Fifty COPD patients were included in the study, for which an ECG signal (lead II) was acquired by a wearable device, before, during, and after the test. We used the heart rate (HR) time-series to assess the heart rate dynamic during recovery. The heart rate recovery (HRR) marker was evaluated every 5 s after the 6MWT and showed different dynamic trends among severity groups. We compared the HRR among patient groups classified according to the GOLD standard. Significantly larger normalized HRR values (nHRR) were found in mild COPD patients (n=23, GOLD={1,2}; nHRR 1 =14.B±7.5 %, nHRR 2 =18.6±8.1 %) compared to those with more disease severity (n=23, GOLD={3,4}; nHRR 1 =9.3±5.8 %, p=0.002; and nHRR 2 = 13.7±6.7%, p=0.041). The largest differences were observed around the first 30 s of the recovery phase (nHRR=10.8±6.6 % vs. nHRR=5.6±4 % p=0.001). Our results showed a slower recovery for the severest patients, suggesting that cardiac parameters like the ones we propose here, may provide valuable information for a better characterization of COPD severity.

JTD Keywords: Pulmonary diseases, Wearable computers, Electrocardiography, Market research, Cardiology, Heart rate variability

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

Cellulose-based supercapacitors display important advantages in comparison with devices fabricated with other materials, regarding environmental friendliness, flexibility, cost and versatility. Recent progress in the field has been mainly focused on the utilization of cellulose fibres as: structural mechanical reinforcement of electrodes; precursors of electrically active carbon-based materials; or primary electrolytes that act as reservoirs of secondary electrolytes. In this work, a flexible, lightweight, robust, portable and manageable all-carboxymethyl cellulose symmetric supercapacitor has been obtained by assembling two electrodes based on carboxymethyl cellulose hydrogels to a solid electrolytic medium formulated with the same material. Hydrogels, which were made by cross-linking carboxymethyl cellulose paste with citric acid in water, rendered not only effective solid electrolytic media by simply loading NaCl but also electroactive electrodes. For the latter, conducting polymer microparticles, which were loaded into the hydrogel network during the physical cross-linking step, were appropriately connected through the in situ anodic polymerization of a similar conducting polymer in aqueous medium, thus creating conduction paths. The performance of the assembled supercapacitors has been proved by cyclic voltammetry, galvanostatic charge-discharge and electrochemical impedance spectroscopy. This design opens a new window for the green and mass production of flexible cellulose-based supercapacitors.

JTD Keywords: Conducting polymer, Energy storage, Flexible electrodes, In situ polymerization, Wearable electronics

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

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

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

A user intention based rehabilitation strategy for a lower-limb wearable robot is proposed and evaluated. The control strategy, which involves monitoring the human-orthosis interaction torques, determines the gait initiation instant and modifies orthosis operation for gait assistance, when needed. Orthosis operation is classified as assistive or resistive in function of its evolution with respect to a normal gait pattern. The control algorithm relies on the adaptation of the joints’ stiffness in function of their interaction torques and their deviation from the desired trajectories. An average of recorded gaits obtained from healthy subjects is used as reference input. The objective of this work is to develop a control strategy that can trigger the gait initiation from the user’s intention and maintain the dynamic stability, using an efficient real-time stiffness adaptation for multiple joints, simultaneously maintaining their synchronization. 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: Adaptive control, Exoskeleton, Gait assistance, Gait initiation, Wearable robot