A Double-Layer Polyurethane Electrospun Membrane with Directional Sweat Transport Ability for Use as a Soft Strain Sensor.

Wearable electronics for long-term monitoring of physiological signals should be capable of removing sweat generated during daily motion, which significantly impacts signal stability, human comfort, and safety of the electronics. In this study, we developed a double-layer polyurethane (PU) membrane with sweat-directional transport ability that can be applied for monitoring strain signals. The PU membrane was composed of a hydrophilic, conductive layer and a relatively hydrophobic layer. The double-layer PU composite membrane exhibited varied pore size and opposite hydrophilicity on its two sides, enabling the spontaneous pumping of sweat from the hydrophobic side to the hydrophilic side, i.e., the directional transport of sweat. The membrane can be used as a strain sensor to monitor motion strain over a broad working range of 0% to 250% with high sensitivity (GF = 4.11). The sensor can also detect simple human movements even under sweating conditions. We believe that the strategy demonstrated here will provide new insights into the design of next-generation strain sensors.

Tracking Real-World Physical Activity in Chronic Obstructive Pulmonary Disease Over One Year: Results from a Monocentric, Prospective, Observational Cohort Study.

Introduction: Lung function constraints and comorbidities such as coronary heart disease, sarcopenia, and mood disorders make chronic obstructive pulmonary disease (COPD) patients avoid physical activity (PA). However, PA represents an important pillar of COPD management and is explicitly recommended by professional associations to enhance physical functioning and positively modulate disease progression. Methods: In this monocentric, prospective, observational feasibility study, it was our primary objective to investigate the association between PA and the evolution of the COPD assessment test (CAT) and the occurrence of acute exacerbations of COPD (AECOPD), respectively. To this end, we equipped 42 COPD patients with an activity tracking wearable and telemonitored their daily PA levels over one year using a dedicated web-based interface. Patients additionally provided weekly CAT scores using the same telehealth platform and came in for 3 study visits to assess functional parameters and biochemical markers related to nutrition and inflammation. Results: A principal study finding was that PA was inversely associated with CAT score (drop of 0.21 points associated with an increase of 1000 daily steps, p = 0.004), and that the 50% of patients with higher PA levels showed less CAT score progression over time (0.42 points per year) than the 50% of patients with lower PA levels (3.26 points per year) (p < 0.001). In addition, higher PA levels were significantly associated with a lower likelihood of experiencing a moderate-to-severe AECOPD (31% risk reduction associated with an increase of 1000 daily steps, p = 0.0097). Discussion: Our study demonstrates the relevance of PA for key COPD outcome metrics in a real-world setting and underpins the importance of PA for COPD self-management in everyday life. Our study paves the way for future intervention trials to prospectively identify medically relevant PA thresholds and establish training recommendations for different patient subgroups.

Higher Levels of Morning and Daytime Light Exposure Associated with Positive Sleep Indices in Professional Team Sport Athletes.

Objective: Light exposure techniques have been recommended to combat sleep issues caused by disruption to circadian regularity in the athletic population, although studies are lacking. Methods: A total of 17 professional male Australian Football athletes (age ± SD: 22 ± 3 years) wore a wrist actigraph to measure sleep parameters, and a wearable light sensor to measure melanopic equivalent daylight illuminance (mEDI, in lux) for 14 days. Participants completed three sleep questionnaires at the end of the data collection period and completed well-being surveys 6 times. The Sleep Regularity Index (SRI) for each player was also calculated from actigraphy data. Light exposure data were organised into three different timeframes: morning (wake time + 2 hours), daytime (end of morning to 6 pm), and evening (2 hours leading up to bedtime) for analysis. Repeated measures correlation was conducted for objective sleep measures and mEDI values per timeframe. Pearson's correlation was conducted on subjective sleep measures and well-being measures against mEDI values per timeframe. Results: Higher morning light was associated with significantly (p < 0.001) greater total sleep time (r = 0.31). Higher daytime light exposure was associated with higher subjective sleep quality (r = 0.48, p < 0.05). Higher evening light exposure was associated with higher Athlete Sleep Screening Questionnaire (ASSQ) global scores (r = 0.52, p < 0.05). There were no other significant correlations between light exposure and sleep or well-being measures (p > 0.05). Conclusion: Higher morning and daylight exposure levels were associated with various positive objective and subjective sleep measures in professional team sport athletes, supporting the need for education on optimising light exposure to improve circadian function, sleep, and health.

Innovative integration of lung ultrasound and wearable monitoring for predicting pulmonary complications in colorectal surgery: A prospective study.

BACKGROUND: Postoperative pulmonary complications (PPCs) are common in patients who undergo colorectal surgery. Studies have focused on how to accurately diagnose and reduce the incidence of PPCs. Lung ultrasound has been proven to be useful in preoperative monitoring and postoperative care after cardiopulmonary surgery. However, lung ultrasound has not been studied in abdominal surgeries and has not been used with wearable devices to evaluate the influence of postoperative ambulation on the incidence of PPCs. AIM: To investigate the relationship between lung ultrasound scores, PPCs, and postoperative physical activity levels in patients who underwent colorectal surgery. METHODS: In this prospective observational study conducted from November 1, 2019 to August 1, 2020, patients who underwent colorectal surgery underwent daily bedside ultrasonography from the day before surgery to postoperative day (POD) 5. Lung ultrasound scores and PPCs were recorded and analyzed to investigate their relationship. Pedometer bracelets measured the daily movement distance for 5 days post-surgery, and the correlation between postoperative activity levels and lung ultrasound scores was examined. RESULTS: Thirteen cases of PPCs was observed in the cohort of 101 patients. The mean (standard deviation) peak lung ultrasound score was 5.32 (2.52). Patients with a lung ultrasound score of ≥ 6 constituted the high-risk group. High-risk lung ultrasound scores were associated with an increased incidence of PPCs after colorectal surgery (logistic regression coefficient, 1.715; odds ratio, 5.556). Postoperative movement distance was negatively associated with the lung ultrasound scores [Spearman's rank correlation coefficient (r), -0.356, P < 0.05]. CONCLUSION: Lung ultrasound effectively evaluates pulmonary condition post-colorectal surgery. Early ambulation and respiratory exercises in the initial two PODs will reduce PPCs and optimize postoperative care in patients undergoing colorectal surgery.

The acceptability of wearable technology for long-term respiratory disease: A cross-sectional survey.

Few studies have investigated the acceptability of wearable technology in patients with long-term respiratory disease. We conducted a 24-item cross-sectional survey (September 2022-February 2023), developed using four common themes universal to previously described models of technology acceptance and social behavioural therapy, to explore the acceptability of wearable technology spanning the breadth of chronic respiratory disease. A total of 74 valid survey responses were analysed with 50 % aged 51-70years; 72 % female; 63 % white British ethnicity; 79 % having an income less than £50,000, and 93 % having at least obstructive airways disease. A third of participants current used wearables with 85 % using smart watches. Most of these participants used wearables to monitor their symptoms (69 %) and as a general health measurement device (85 %). Likert scale questions (ranked 1-7) showed that participants valued accuracy and approval of wearables by regulatory bodies (median (IQR) rank score 7 (Huberty et al., 2015; Preusse et al., 2016) 6-76-7 and felt that wearables would increase their confidence in managing their long-term health condition (median (IQR) rank score 6 (Huberty et al., 2015; Preusse et al., 2016) 6-76-7. Favourable product characteristics for wearables were accuracy (73 %), easy to learn (63 %) and easy to use (50 %). They were less concerned about aesthetics (23 %) and battery life (27 %). This survey will guide future developers to produce a wearable for a population with chronic respiratory disease which will improve acceptability, usability and longevity.

Feasibility of using electrodermal activity responses to assess level of crowdedness of pedestrian paths.

As urban populations grow, it's imperative to evaluate and enhance the quality of pedestrian paths from the user's perspective. Crowdedness, associated with discomfort and safety, is crucial in determining the overall walking quality and user experience. Previously utilized methods for measuring crowdedness, such as travel diaries and floating population surveys, were limited to collecting perceptual data from sporadic surveys with restricted spatial coverage. Similarly, methods based on CCTV or mobile service data have been used but present issues with blind spots and fail to consider pedestrian perspectives. Against this background, this study explores the feasibility of assessing crowdedness levels by measuring subjects' physiological responses in a laboratory setting based on visual images of real and virtual environments. This study hypothesizes that the amount of people or vehicles passing by affects the electrodermal activity (EDA) of pedestrians, indicating the comfort level of using the environment. Experimental EDA data were measured using a wearable device while the subjects were watching videos showing different pedestrian traffic flows. Representative EDA signal features (e.g., skin conductance responses) were extracted after data pre-processing. Noticeable changes in EDA responses are observed when subjects countered specific environmental variations, such as differing volumes of passing people, on pedestrian paths. The findings suggest that EDA data can be instrumental in differentiating crowdedness levels on pedestrian paths. This study contributes to the body of knowledge by demonstrating the potential of EDA data to characterize the crowdedness experienced by pedestrians. This aids in the development of a novel, quantitative method to gauge pedestrian path crowdedness and to discern contributing factors, such as path width.

A Clinician and Electronic Health Record Wearable Device Intervention to Increase Physical Activity in Patients With Obesity: Formative Qualitative Study.

BACKGROUND: The number of individuals using digital health devices has grown in recent years. A higher rate of use in patients suggests that primary care providers (PCPs) may be able to leverage these tools to effectively guide and monitor physical activity (PA) for their patients. Despite evidence that remote patient monitoring (RPM) may enhance obesity interventions, few primary care practices have implemented programs that use commercial digital health tools to promote health or reduce complications of the disease. OBJECTIVE: This formative study aimed to assess the perceptions, needs, and challenges of implementation of an electronic health record (EHR)-integrated RPM program using wearable devices to promote patient PA at a large urban primary care practice to prepare for future intervention. METHODS: Our team identified existing workflows to upload wearable data to the EHR (Epic Systems), which included direct Fitbit (Google) integration that allowed for patient PA data to be uploaded to the EHR. We identified pictorial job aids describing the clinical workflow to PCPs. We then performed semistructured interviews with PCPs (n=10) and patients with obesity (n=8) at a large urban primary care clinic regarding their preferences and barriers to the program. We presented previously developed pictorial aids with instructions for (1) providers to complete an order set, set step-count goals, and receive feedback and (2) patients to set up their wearable devices and connect them to their patient portal account. We used rapid qualitative analysis during and after the interviews to code and develop key themes for both patients and providers that addressed our research objective. RESULTS: In total, 3 themes were identified from provider interviews: (1) providers' knowledge of PA prescription is focused on general guidelines with limited knowledge on how to tailor guidance to patients, (2) providers were open to receiving PA data but were worried about being overburdened by additional patient data, and (3) providers were concerned about patients being able to equitably access and participate in digital health interventions. In addition, 3 themes were also identified from patient interviews: (1) patients received limited or nonspecific guidance regarding PA from providers and other resources, (2) patients want to share exercise metrics with the health care team and receive tailored PA guidance at regular intervals, and (3) patients need written resources to support setting up an RPM program with access to live assistance on an as-needed basis. CONCLUSIONS: Implementation of an EHR-based RPM program and associated workflow is acceptable to PCPs and patients but will require attention to provider concerns of added burdensome patient data and patient concerns of receiving tailored PA guidance. Our ongoing work will pilot the RPM program and evaluate feasibility and acceptability within a primary care setting.

Efficient Permeable Monolithic Hybrid Tribo-Piezo-Electromagnetic Nanogenerator Based on Topological-Insulator-Composite.

Escalating energy demands of self-independent on-skin/wearable electronics impose challenges on corresponding power sources to offer greater power density, permeability, and stretchability. Here, a high-efficient breathable and stretchable monolithic hybrid triboelectric-piezoelectric-electromagnetic nanogenerator-based electronic skin (TPEG-skin) is reported via sandwiching a liquid metal mesh with two-layer topological insulator-piezoelectric polymer composite nanofibers. TPEG-skin concurrently extracts biomechanical energy (from body motions) and electromagnetic radiations (from adjacent appliances), operating as epidermal power sources and whole-body self-powered sensors. Topological insulators with conductive surface states supply notably enhanced triboelectric and piezoelectric effects, endowing TPEG-skin with a 288 V output voltage (10 N, 4 Hz), ∼3 times that of state-of-the-art devices. Liquid metal meshes serve as breathable electrodes and extract ambient electromagnetic pollution (±60 V, ±1.6 µA cm-2). TPEG-skin implements self-powered physiological and body motion monitoring and system-level human-machine interactions. This study provides compatible energy strategies for on-skin/wearable electronics with high power density, monolithic device integration, and multifunctionality.

Reliability of Wearable Technology to Monitor Core Temperature Among Helicopter-Based EMS Crews.

BACKGROUND: Excessive heat stress led to more than 400 deaths in the United States from 2011 to 2021. Common methods for heat injury prevention revolve around measurements of the environment and fail to account for the unique individual response to stressors. METHODS: An observational approach was utilized with nine helicopter-based emergency medical services personnel during emergency flights to compare core temperature readings obtained from an ingestible temperature monitoring pill and the estimated core temperature reading of the Slate Safety Band V2 wearable device. Comparison of data was conducted within Microsoft Excel programming to determine the mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), mean biased error (MBE), and Bland-Altman plot development. FINDINGS: A significant bias (t = 17.58, p < .001) toward the Slate Safety device reading higher with an average difference of -0.48°C (-0.86°F) was found, meaning the average temperature reading is 0.48°C (-0.86°F) higher with the Slate Safety device. A significant correlation of .26 (p < .001) was noted between the ingestible pill and the wearable device with a 95% confidence interval of 0.23 to 0.29. Aggregate core temperature data demonstrated an MSE of 0.43, an RMSE of 0.65, an MAE of 0.54, and an MBE of -0.48. CONCLUSIONS/APPLICATION TO PRACTICE: The ability to monitor the physiological parameters of a worker remotely adds safety tools relative to the risks of heat stress. The slightly higher reading associated with the Slate Safety wearable device provides an added safety margin to protect our workers.

An Integrated All-Natural Conductive Supramolecular Hydrogel Wearable Biosensor with Enhanced Biocompatibility and Antibacterial Properties.

Conductive hydrogels exhibit tremendous potential for wearable bioelectronics, biosensing, and health monitoring applications, yet concurrently enhancing their biocompatibility and antimicrobial properties remains a long-standing challenge. Herein, we report an all-natural conductive supramolecular hydrogel (GT5-DACD2-B) prepared via the Schiff base reaction between the biofriendly dialdehyde cyclodextrin and gelatin. The potent antibacterial agent fusidic acid (FA) is incorporated through host-guest inclusion, enabling 100% inhibition of Staphylococcus aureus proliferation. The biocompatibility of our hydrogel is bolstered with tannic acid (TA) facilitating antibacterial effects through interactions with gelatin, while borax augments conductivity. This supramolecular hydrogel not only exhibits stable conductivity and rapid response characteristics but also functions as a flexible sensor for monitoring human movement, facial expressions, and speech recognition. Innovatively integrating biocompatibility, antimicrobial activity, and conductivity into a single system, our work pioneers a paradigm for developing multifunctional biosensors with integrated antibacterial functionalities, paving the way for advanced wearable bioelectronics with enhanced safety and multifunctionality.

Data Analytics in Physical Activity Studies With Accelerometers: Scoping Review.

BACKGROUND: Monitoring free-living physical activity (PA) through wearable devices enables the real-time assessment of activity features associated with health outcomes and provision of treatment recommendations and adjustments. The conclusions of studies on PA and health depend crucially on reliable statistical analyses of digital data. Data analytics, however, are challenging due to the various metrics adopted for measuring PA, different aims of studies, and complex temporal variations within variables. The application, interpretation, and appropriateness of these analytical tools have yet to be summarized. OBJECTIVE: This research aimed to review studies that used analytical methods for analyzing PA monitored by accelerometers. Specifically, this review addressed three questions: (1) What metrics are used to describe an individual's free-living daily PA? (2) What are the current analytical tools for analyzing PA data, particularly under the aims of classification, association with health outcomes, and prediction of health events? and (3) What challenges exist in the analyses, and what recommendations for future research are suggested regarding the use of statistical methods in various research tasks? METHODS: This scoping review was conducted following an existing framework to map research studies by exploring the information about PA. Three databases, PubMed, IEEE Xplore, and the ACM Digital Library, were searched in February 2024 to identify related publications. Eligible articles were classification, association, or prediction studies involving human PA monitored through wearable accelerometers. RESULTS: After screening 1312 articles, 428 (32.62%) eligible studies were identified and categorized into at least 1 of the following 3 thematic categories: classification (75/428, 17.5%), association (342/428, 79.9%), and prediction (32/428, 7.5%). Most articles (414/428, 96.7%) derived PA variables from 3D acceleration, rather than 1D acceleration. All eligible articles (428/428, 100%) considered PA metrics represented in the time domain, while a small fraction (16/428, 3.7%) also considered PA metrics in the frequency domain. The number of studies evaluating the influence of PA on health conditions has increased greatly. Among the studies in our review, regression-type models were the most prevalent (373/428, 87.1%). The machine learning approach for classification research is also gaining popularity (32/75, 43%). In addition to summary statistics of PA, several recent studies used tools to incorporate PA trajectories and account for temporal patterns, including longitudinal data analysis with repeated PA measurements and functional data analysis with PA as a continuum for time-varying association (68/428, 15.9%). CONCLUSIONS: Summary metrics can quickly provide descriptions of the strength, frequency, and duration of individuals' overall PA. When the distribution and profile of PA need to be evaluated or detected, considering PA metrics as longitudinal or functional data can provide detailed information and improve the understanding of the role PA plays in health. Depending on the research goal, appropriate analytical tools can ensure the reliability of the scientific findings.

Dynamic monitoring of a 3D-printed airway tissue model using an organic electrochemical transistor.

Assessing the transepithelial resistance to ion flow in the presence of an electric field enables the evaluation of the integrity of the epithelial cell layer. In this study, we introduce an organic electrochemical transistor (OECT) interfaced with a 3D living tissue, designed to monitor the electrical resistance of cellular barriers in real-time. We have developed a non-invasive, tissue-sensing platform by integrating an inkjet-printed large-area OECT with a 3D-bioprinted multilayered airway tissue. This unique configuration enables the evaluation of epithelial barrier integrity through the dynamic response capabilities of the OECT. Our system effectively tracks the formation and integrity of 3D-printed airway tissues in both liquid-liquid and air-liquid interface culture environments. Furthermore, we successfully quantified the degradation of barrier function due to influenza A (H1N1) viral infection and the dose-dependent efficacy of oseltamivir (Tamiflu®) in mitigating this degradation. The tissue-electronic platform offers a non-invasive and label-free method for real-time monitoring of 3D artificial tissue barriers, without disturbing the cellular biology. It holds the potential for further applications in monitoring the structures and functions of 3D tissues and organs, significantly contributing to the advancement of personalized medicine.

Calibration-free and ready-to-use wearable electroanalytical reporting system (r-WEAR) for long-term remote monitoring of electrolytes markers.

A major bottleneck in the development of wearable ion-selective sensors is the inherent conditioning and calibration procedures at the user's end due to the signal's instability and non-uniformity. To address this challenge, we developed a strategy that integrates three interdependent materials and device engineering approaches to realize a Ready-to-use Wearable ElectroAnalytical Reporting system (r-WEAR) for reliable electrolytes monitoring. The strategy collectively utilized (1) finely-configured diffusion-limiting polymers to stabilize the electromotive force in the electrodes, (2) a uniform electrical induction in electrochemical cells to normalize the open-circuit potential (OCP), and (3) an electrical shunt to maintain the OCP across the entire sensor in the r-WEAR. The approaches jointly enable fabrication of homogeneously stable and uniform ion-selective sensors, eliminating common conditioning and calibration practices. As a result, the r-WEAR demonstrated a signal's variation down to ±1.99 mV with a signal drift of 0.5 % per hour (0.12 mV h-1) during a 12-h continuous measurement of 10 sensors and a signal drift as low as 13.3 µV h-1 during storage. On-body evaluations of the r-WEAR for four days without conditioning and re-/calibration further validated the sensor's performance in realistic settings, indicating its remarkable potential for practical usage in a user operation-free manner in wearable healthcare applications.

Modelling human postural stability and muscle activation augmented by a supernumerary robotic tail.

Wearable robots have promising characteristics for human augmentation; however, the the design and specification stage needs to consider biomechanical impact. In this work, musculoskeletal software is used to assess the biomechanical implications of having a two-degrees-of-freedom supernumerary robotic tail mounted posterior to the human trunk. Forward and backward tilting motions were assessed to determine the optimal design specification. Specifically; the key criteria utilised included the centre of pressure, the dynamic wrench exerted by the tail onto the human body and a global muscle activation index. Overall, it was found that use of a supernumerary tail reduced lower limb muscle activation in quiet stance. Furthermore, the optimal design specification required a trade-off between the geometric and inertial characteristics, and the amount of muscle assistance provided by the tail to facilitate safe physical Human-Robot interaction. .

Mealtime prediction using wearable insulin pump data to support diabetes management.

Many patients with diabetes struggle with post-meal high blood glucose due to missed or untimely meal-related insulin doses. To address this challenge, our research aims to: (1) study mealtime patterns in patients with type 1 diabetes using wearable insulin pump data, and (2) develop personalized models for predicting future mealtimes to support timely insulin dose administration. Using two independent datasets with over 45,000 meal logs from 82 patients with diabetes, we find that the majority of people ( ∼ 60%) have irregular and inconsistent mealtime patterns that change notably through the course of each day and across months in their own historical data. We also show the feasibility of predicting future mealtimes with personalized LSTM-based models that achieve an average F1 score of > 95% with less than 0.25 false positives per day. Our research lays the groundwork for developing a meal prediction system that can nudge patients with diabetes to administer bolus insulin doses before meal consumption to reduce the occurrence of post-meal high blood glucose.

Evidence of spontaneous cardiac-locomotor coupling during daily activities in healthy adults.

Introduction: One way to improve exercise performance and protect heart health is the extended synchronization of the stepping with the diastolic phase of the cardiac cycle. Cardiac-locomotor coupling (CLC) happens when the step rate (SR) equals the heart rate (HR). The extent of CLC in daily life is unknown. This study aims to analyze spontaneous occurrences of CLC during daily activities. Methods: A retrospective analysis of daily life recordings from a wrist-worn sensor was undertaken (PMData, N = 16, 5 months duration). The deviation between HR and SR was used to define CLC (deviation ≤ 1%) and weak CLC (1%< deviation ≤ 10%). The occurrence and the probability of CLC during everyday life were computed from the recordings. The CLC occurrences were stratified depending on the duration and intensity of the physical activity. Finally, a Monte Carlo simulation was run to evaluate the probability of random occurrences of CLC vs. the observed recordings. Results: Participants couple for 5% and weakly couple for 35% of the observational period. The ratio of 1:1 between HR and SR is the dominating occurrence across the study population and this overrepresentation is significant. CLC occurs mostly for long activities. The extent of CLC for various intensities of activity is subject-dependent. The results suggest that CLC is feasible for most people. Conclusions: CLC occurs spontaneously during unsupervised daily activity in everyone in our cohort, which suggests a mechanistic interaction between the cardiac and the locomotor systems. This interaction should be investigated for medical rehabilitation and sports applications in the future.

Effects of low-frequency pulsed electrical stimulation at the common peroneal nerve on chronic refractory wounds of the lower limb: A randomized controlled trial.

Background and aims: Electrical stimulation (ES) has been shown to substantially enhance the quality of life by alleviating pain in patients with chronic wounds. This study aimed to observe the effects of low-frequency pulsed wearable ES at the common peroneal nerve on chronic refractory wounds of the lower limb. Methods: Forty-eight participants were randomly divided into control group (n = 24) and treatment group (n = 24) in this study. The control group received standard wound care (SWC) exclusively, whereas the treatment group was administered both SWC and the wearable low-frequency ES targeting the common peroneal nerve. Measurements of wound area, pain intensity, wound status, and quality of life scores were systematically recorded both before and after 4 weeks treatment. Results: After 4 weeks of intervention, the percentage area reduction was significantly higher in the treatment group compared to the control group (Z = -3.9, p < 0.001), and the healing rate of the treatment group was significantly higher than that of the control group (33% vs. 4%). Moreover, the visual Analog Scale for Pain score (ß = -0.65, p = 0.019), the Bates-Jensen Wound Assessment Tool score (p < 0.05), and the questionnaire on quality of life with chronic wounds (Wound-Qol) score (ß = -4.23, p = 0.003) were significantly decreased in the patients in the treatment group compared to the control group. Conclusion: The wearable low-frequency pulsed ES at the common peroneal nerve for the treatment of chronic refractory wounds showed significant improvement and were far superior compared to SWC. Future research should broaden its scope to include a diverse range of wound types and benefit from collaboration across multiple research centers.

Triboelectric Nanogenerator Made with Stretchable, Antibacterial Hydrogel Electrodes for Biomechanical Sensing.

Triboelectric nanogenerators (TENGs) have attracted widespread attention as a promising candidate for energy harvesting due to their flexibility and high power density. To meet diverse application scenarios, a highly stretchable (349%), conductive (1.87 S m-1), and antibacterial electrode composed of carbon quantum dots/LiCl/agar-polyacrylamide (CQDs/LiCl/agar-PAAm) dual-network (DN) hydrogel is developed for wearable TENGs. Notably, the concentration of agar alters the pore spacing and pore size of the DN hydrogel, thereby impacting the network cross-linking density and the migration of conductive ions (Li+ and Cl-). This variation further affects the mechanical strength and conductivity of the hydrogel electrode, thus modulating the mechanical stability and electrical output performance of the TENGs. With the optimal agar content, the tensile strength and conductivity of the hydrogel electrode increase by 211 and 719%, respectively. This enhancement ensures the stable output of TENGs during continuous operation (6000 cycles), with open-circuit voltage, short-circuit current, and transferred charge increasing by 200, 530, and 155%, respectively. Additionally, doping with CQDs enables the hydrogel electrode to effectively inhibit the Gram-negative bacterium Escherichia coli. Finally, the TENGs are utilized as a self-power smart ring for efficient and concise information transmission via Morse code. Consequently, this study introduces a creative approach for designing and implementing multifunctional, flexible wearable devices.

A Passive Perspiration Inspired Wearable Platform for Continuous Glucose Monitoring.

The demand for glucose monitoring devices has witnessed continuous growth from the rising diabetic population. The traditional approach of blood glucose (BG) sensor strip testing generates only intermittent glucose readings. Interstitial fluid-based devices measure glucose dynamically, but their sensing approaches remain either minimally invasive or prone to skin irritation. Here, a sweat glucose monitoring system is presented, which completely operates under rest with no sweat stimulation and can generate real-time BG dynamics. Osmotically driven hydrogels, capillary action with paper microfluidics, and self-powered enzymatic biochemical sensor are used for simultaneous sweat extraction, transport, and glucose monitoring, respectively. The osmotic forces facilitate greater flux inflow and minimize sweat rate fluctuations compared to natural perspiration-based sampling. The epidermal platform is tested on fingertip and forearm under varying physiological conditions. Personalized calibration models are developed and validated to obtain real-time BG information from sweat. The estimated BG concentration showed a good correlation with measured BG concentration, with all values lying in the A+B region of consensus error grid (MARD = 10.56% (fingertip) and 13.17% (forearm)). Overall, the successful execution of such osmotically driven continuous BG monitoring system from passive sweat can be a useful addition to the next-generation continuous sweat glucose monitors.