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Ambient-Stable and Resilient Glycerogel Electrolytes for Flexible Solid-State Supercapacitors.

Hydrogel electrolytes are increasingly used for flexible solid-state supercapacitors emerged as promising power sources due to their similarity to aqueous electrolytes. However, their performance is limited by evaporation or freezing in challenging weather, restricting their practical applications. This study introduces a flexible glycerogel electrolyte with antidrying and antifreezing properties, offering exceptional durability under harsh conditions. Inspired by the role of glycerol and electrolytes in electrodermal activity of biological tissue, eco-friendly NaCl and hygroscopic glycerol are incorporated into a stretchable hydrogel matrix. The resulting glycerogel electrolyte retained hydration in the open air for 180 days. It also exhibited stable conductivity under extreme temperatures (-20 to 60 °C) and low-pressure conditions (∼2.4 kPa). A fibrous solid-state supercapacitor assembled using carbon nanotube yarns delivered a maximum gravimetric capacitance of 148 F·g-1 at 0.5 A·g-1. Notably, the device maintained 94%, 86%, and 90% of its initial capacitance after 30 days of exposure to -20 °C, 60 °C, and low-pressure conditions, respectively, without encapsulation. To demonstrate practical utility, this fibrous supercapacitor was integrated into the ear loop of a facial mask, enabling heat-induced sanitization that killed 99.999% of bacterial cells. This glycerogel electrolyte provides a sustainable, versatile solution for powering future wearable electronic devices across diverse environmental conditions.

Electric Capacitance

Effectiveness of Wearable Digital Therapeutics in Improving Sleep Outcomes Among Individuals With Insomnia: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Wearable devices are increasingly used for sleep monitoring and as adjunctive treatment. Existing meta-analyses mostly pool composite digital therapies and rarely isolate stand-alone wearables or distinguish between objective and subjective end points. Whether stand-alone wearable interventions improve sleep outcomes in adults with insomnia, and which factors moderate treatment heterogeneity, remains unclear. OBJECTIVE: This study aims to evaluate the effectiveness of wearable digital interventions on sleep outcomes in adults with insomnia versus control strategies and explore moderators of effectiveness, including device-wearing position, intervention duration, and control type, using meta-regression. METHODS: This systematic review and meta-analysis was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta‑Analyses) 2020 statement and the PRISMA-S (Preferred Reporting Items for Systematic Reviews and Meta‑Analyses Literature Search Extension) guideline. Five electronic databases and clinical trial registries were searched from inception to May 18, 2026. Eligible studies were randomized controlled trials (RCTs) evaluating wearable digital interventions in adults with insomnia compared with sham, waitlist, usual care, or active control conditions and had an intervention duration of at least 1 week. Study screening, data extraction, and risk-of-bias assessment were carried out independently by 2 reviewers. Pooled estimates were calculated using a restricted maximum likelihood random-effects model with the Hartung-Knapp-Sidik-Jonkman correction. Heterogeneity was assessed using the I² statistic, and 95% prediction intervals (PIs) were calculated for the primary analyses. The certainty of evidence was rated using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) approach. RESULTS: Sixteen RCTs (N=910) were included. Wearable digital interventions were associated with a significant reduction in objective sleep-onset latency (SOL; mean difference [MD] -4.52, 95% CI -8.38 to -0.67, PI -9.52 to 0.47 min) and a significant improvement in subjective sleep efficiency (SE; MD 2.00%, 95% CI 1.90%-2.11%, PI 1.85%-2.15%). Subjective total sleep time (TST) also showed a significant increase (MD 19.11, 95% CI 2.98-35.24, PI -16.20 to 54.43 minutes). Meta-regression showed that control type, intervention duration, and device location did not explain the heterogeneity of the insomnia severity index (ISI) (R²=0). Sensitivity analysis confirmed the robustness of pooled ISI estimates, and an Egger test indicated no small-study effects (P=.07). Certainty of evidence ranged from moderate to high. CONCLUSIONS: Wearable digital interventions provide selective benefits for objective SOL, subjective SE, and subjective TST in adults with insomnia, with no improvement in overall ISI. Despite statistically significant effects on several sleep parameters, wide PIs, substantial heterogeneity, and limited study numbers indicate preliminary, nonconclusive findings. Wearables should be viewed as affordable adjunctive tools requiring further validation, not substitutes for first-line cognitive behavioral therapy for insomnia. Large-scale, long-term RCTs with standardized protocols and patient-level external validation are required to consolidate the evidence base.

Humans

Use of Wearable Sensors in Angelman Syndrome: A Systematic Review.

BACKGROUND: Wearable sensors are a promising method for collecting clinical trial outcome data for people with Angelman syndrome (AS). However, there has yet to be a systematic probe into the ways in which wearable sensors have been successfully used in AS. The current study aims to provide a quantitative summary of wearable sensors used in AS, including contexts of use and psychometric properties, and to present key narrative highlights. METHOD: Literature searches were performed in three electronic databases: APA PsycInfo, PubMed and Web of Science Core Collection. Data items were categorized into four categories: sample characteristics, study methodological details, wearable sensor characteristics and psychometric properties assessed. Sample characteristics included sample size, age, biological sex, race/ethnicity and cognitive/developmental functioning. Study methodological details were subdivided into study design and setting. Wearable sensor characteristics included sensor type, placement site, means of attachment, assessed construct and sensor-related data loss. Psychometric properties assessed included reliability and validity of sensor-derived data. RESULTS: We identified 16 articles through our systematic review. Wearable sensors were used to study sleep (n = 10, 62.5%), language (n = 2, 12.5%), gait (n = 2, 12.5%), caregiver proximity (n = 1, 6.3%), EEG power (n = 1, 6.3%), and arousal (n = 1, 6.3%) in AS through actigraphs, vocalization recorders, inertial sensors, radio-frequency identification watches, wireless EEG caps, and functional near-infrared spectroscopy caps, respectively. Findings from these studies broadly indicate that wearable sensors are feasible, reliable and valid for assessing a range of behaviours relevant to AS. CONCLUSIONS: Wearable sensors are a promising solution to enhance assessments in AS. However, with the small extant literature characterized by small sample sizes and restricted focus on a few relevant features in AS, there remains ample opportunities to explore the use of wearable sensors in people with AS. Additional studies will better inform clinical decision-making and ultimately improve the lives of people with AS and their families.

Humans

Wearable wrist-watch type cuff oscillometric blood pressure monitors: consensus statement by the European Society of Hypertension Working Group on blood pressure monitoring.

Wearable wristwatch-type cuff oscillometric blood pressure (BP) monitors represent a new category of BP devices and are the first wearable monitors to use established cuff-oscillometric BP measurement technology. This consensus statement by the European Society of Hypertension Working Group on BP Monitoring reviews the published evidence on their design, accuracy, validation, clinical application, and remaining research questions. Of 281 articles identified through a systematic PubMed search, 26 were relevant. Several devices are currently available; however, only two have published validation studies performed according to established standards (Omron HeartGuide and Huawei Watch D/D2). Static validation studies generally showed acceptable accuracy, whereas data on 24-h ambulatory use, in special populations, and clinical applications remain limited. Potential advantages include self-initiated measurement at home, at work, and in other settings and conditions; more convenient and repeatable 24-h ambulatory monitoring; more convenient and accurate assessment of asleep BP; capture of stress-related and other BP-related episodes. However, proper wrist position, user adherence, ambulatory performance, and clinical applications require further investigation. More research is needed to establish the accuracy and clinical utility of these novel devices and their role in improving the diagnosis and management of hypertension.

Humans

Evaluating Wearable Devices for Remote Monitoring in Psychosis: Pilot Study Nested Within the CONNECT Cohort Study.

BACKGROUND: Digital remote monitoring technologies, including smartphones and wearables, offer promising avenues for early detection of psychosis relapse. However, selecting devices that are acceptable to participants and produce high-quality data remains challenging. OBJECTIVE: The aim of this nested pilot study was to assess the acceptability and data quality of 3 commercially available wearable devices in people with psychosis recruited to the CONNECT cohort study. METHODS: Participants recruited to the CONNECT study before July 31, 2024, were included in the pilot study and selected 1 of 3 wearable devices: a Fitbit Charge 5, Samsung Galaxy Watch 5, or Apple Watch SE. Baseline demographics were compared between device groups. Acceptability of devices to participants was assessed through a Wearable Device Satisfaction Questionnaire after 3 months of use, with the proportion of positive responses to each question calculated and compared. Data completeness was also assessed by calculating the number (and percentage) of valid days of step count, heart rate, and sleep data, and comparing between groups. Data quality was assessed through summarizing the amount of troubleshooting required, additional metrics available from the wearables, and continuity of data completeness by calculating the proportion of participants with at least 3 days of heart rate data per week for the first 20 weeks of follow-up. Predefined criteria were used to determine the next steps for the wider CONNECT study: if one device was superior, this would be selected; if none were found to be superior and the Fitbit was found to be noninferior, then Fitbit would be retained. RESULTS: Of the first 107 participants recruited to CONNECT, 105 were included in the pilot study evaluation. The Samsung Galaxy Watch was selected most frequently by participants (46/105, 43.8%), followed by the Apple Watch (27/105, 25.7%), and Fitbit Charge (23/105, 21.9%). Differences in participant demographics were observed across device groups. Self-reported acceptability after use did not differ substantially between devices. However, in terms of data completeness, the median proportion of valid heart rate data days was significantly lower for Samsung Galaxy (median 31.2%, IQR 8.5%-46.0%) compared to Fitbit (median 80.1%, IQR 26.7%-95.0%; P=.003) and Apple Watch (median 49.3%, IQR 21.5%-86.0%; P=.02). There was no significant difference between Fitbit and Apple Watch. Similar patterns were observed for step count and sleep data. The Samsung Galaxy Watch required more frequent troubleshooting for data flow issues and lacked additional physiological metrics, available from the other devices. CONCLUSIONS: Due to comparatively lower data quality and technical performance, the Samsung Galaxy Watch was discontinued for use in the subsequent phase of the CONNECT study. The study highlights the importance of incorporating nested evaluations of devices in long-term research.

Humans

Use of wearable technologies for physical activity promotion in older adults: A systematic review.

This systematic review, conducted according to PRISMA guidelines and registered in PROSPERO (CRD420251055299), examined the use of wearable technologies for promoting physical activity (PA) in adults aged 60 years and older. Searches across five databases (PubMed, Scopus, Web of Science, CINAHL, Cochrane) identified 2438 records, of which only six randomized controlled trials published between 2021 and 2025 met inclusion criteria, with sample sizes ranging from 36 to 551 participants and mean ages between 65 and 79 years. Given the small number of included studies, findings should be interpreted as preliminary. The studies ranged from the standalone use of commercial trackers (Fitbit, Polar, ActiGraph) to multicomponent interventions combining wearables with physiotherapist feedback, telephone counseling, web-based platforms, or interactive cognitive-motor training. Wearables used alone, as in the REACT trial, produced small or non-significant PA effects. In contrast, interventions integrating devices with personalized feedback, professional support, or digital platforms, such as PROMOTE and TASMANIA, were associated with more consistent improvements in PA, physical function, and cognitive outcomes. Multicomponent programs, such as PEER and ICMT, reported broader benefits, including cognition, balance, and reductions in sedentary behavior, though these findings derive from individual trials and require replication. Risk of bias, assessed with the Cochrane Risk of Bias tool version 2 (RoB 2.0), was rated as "some concerns" for five studies and low for only one, mainly due to gaps in randomization reporting, missing data, and lack of preregistration. Tentatively, and based on a very limited evidence base, wearables may have greater impact when embedded within broader behavioral systems, incorporating feedback, coaching, or interactive components, rather than when used in isolation as passive monitoring tools. Adherence and psychosocial outcomes appeared related to comfort and perceived usefulness among older adults, though larger and more robust trials are needed to confirm these patterns.

Humans

Detection of cytokine release syndrome using wearables and cytokine profiling following CAR-T therapy for myeloma.

BACKGROUNDChimeric antigen receptor T-cell (CAR-T) therapies have revolutionized treatment for relapsed/refractory multiple myeloma (RRMM). However, cytokine release syndrome (CRS), a common and potentially severe complication, requires inpatient monitoring, limiting access and increasing costs. Wearable devices could support outpatient CAR-T delivery, but feasibility for CRS detection versus standard care remains unproven.METHODSWe conducted a prospective, single-center observational pilot study to assess the feasibility of using wearable devices for monitoring vital signs and detecting CRS. Thirty patients receiving idecabtagene vicleucel (ide-cel) or ciltacabtagene autoleucel (cilta-cel) were enrolled; 25 with sufficient monitoring data were evaluable. Sensors collected skin and axillary temperature, oxygen saturation, respiratory and heart rate, and motion. Peripheral blood cytokines were analyzed pre- and postinfusion using a multiplex proteomic platform. The primary outcome was feasibility, assessed by CRS detection sensitivity and specificity; secondary outcomes included adherence, lead time, and performance of models integrating wearable and cytokine data.RESULTSCRS occurred in 20 of 25 patients. The best-performing wearable model detected 18 or 20 CRS episodes with a sensitivity of 0.72 (mean 0.75; 95% CI 0.60-0.91) and a specificity of 0.80 (mean 0.76; 95% CI 0.68-0.84), and a median lead time of 7:00 hours before nursing recognition. Median adherence during high-risk periods was 71%. Cytokine changes paralleled temperature elevations, and IFN-γ emerged as a consistent biomarker.CONCLUSIONWearable devices are feasible for early CRS detection and may support outpatient CAR-T care. Larger outpatient studies are warranted.TRIAL REGISTRATIONThis study did not meet the criteria for ClinicalTrials.gov registration.

Humans

Wearable Sleep Monitoring in Pediatric Acute Lymphoblastic Leukemia: Associations With Subjective Sleep Ratings and Neurocognitive Functioning.

BACKGROUND: Sleep disturbances are associated with increased fatigue, reduced quality of life, and neurocognitive dysfunction and have emerged as a common complication among pediatric cancer survivors. Sleep disturbances are particularly concerning given their potential to exacerbate existing neurocognitive impacts of cancer treatments. This pilot study examined the feasibility and acceptability of a home-wearable EEG-based sleep device (Sleep ProfilerTM) for acute lymphoblastic leukemia (ALL) survivors as well as associations between specific sleep parameters and neurocognitive functioning. PROCEDURE: Children (ages 8-12; M = 10 years, SD = 1.6; N = 23) >6 months post-treatment for ALL were enrolled at clinical visits and wore the Sleep ProfilerTM for two consecutive nights at home, followed by neurocognitive testing of attention, inhibitory control, working memory, and processing speed. Parents completed subjective measures of child sleep, anxiety, depression, and acceptability. Feasibility reflected the percentage of children wearing the device at least one night and the percentage of nights with good EEG quality data. RESULTS: All participants wore the device both nights, with 84% meeting the threshold for good quality measurement. Few children met recommended quantity and quality sleep thresholds based on objective measurement, including 5 patients with elevated snoring levels; 43.5% of subjective ratings fell above the threshold for sleep disturbance. Greater sleep latency was associated with worse inhibitory control (r = -0.42, p = 0.046), and total sleep time was positively associated with inhibitory control and attention. CONCLUSIONS: Findings confirm the feasibility and acceptability of home EEG sleep monitoring in school-age survivors, and associations of sleep latency and snoring with reduced neurocognitive functioning may offer modifiable risk factors for aspects of neuropsychological dysfunction common in pediatric survivorship. CLINICAL TRIAL REGISTRATION: At the time this study was conducted, we were not required to register the study on ClinicalTrials.gov. It was a single-institution feasibility study without intervention, which was not considered a clinical trial.

Humans

Instrumented Walkway Gait Analysis Predicts Fallers in Neurological Disorders: Identifying Digital Biomarkers for Balance Monitoring.

Assessing balance is crucial in neurological rehabilitation, yet while wearable sensors enable real-world monitoring, identifying reliable digital biomarkers remains challenging. This study utilized a high-fidelity instrumented walkway to determine which gait parameters best predict balance impairment, providing robust targets for future wearable applications. We analyzed 49 steady-state gait metrics from 140 individuals with diverse neurological conditions. Using statistical analysis and machine learning, we evaluated these parameters against objective force plate sway scores and clinical fall-history labels. Group analysis identified 16 parameters significantly distinguishing fallers from non-fallers, and a neural network classified fallers with an area under the curve of 0.75. Across all analytical approaches, overall gait variability, e.g., Stride Width S.D. and the Gait Variability Index, emerged as a universal predictor of balance impairment and fall risk. Furthermore, while traditional linear models emphasized spatial postural control, machine learning classification uniquely identified inter-limb asymmetry as a premier driver of fall prediction. These findings indicate that instrumented gait analysis effectively identifies digital biomarkers for balance deficits. Isolating these specific metrics provides a clear blueprint for meaningful metrics required for continuous objective monitoring and future development of personalized, adaptive rehabilitation strategies.

Humans

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence