The ability to pick up objects off the floor can degrade over time with elderly individuals, leading to a reduced quality of life and an increase in the risk of falling. Healthcare professionals have expressed an interest in monitoring the decline in pickup ability of a subject over extended periods of time and intervening when it becomes hazardous to the subject\'s health. The current means of evaluating pickup ability involving in-clinic patient visits is both time and financially expensive. There is a clear need for a cost-effective, remote means of pickup evaluation to ease the burden on both patients and physicians. To address these challenges, we introduce a Time-of-Pickup (ToP) solution, called ToPick, designed for the automatic assessment of pickup ability over time. The practical performance of ToPick is evident, demonstrated by a minimal median error of approximately 100 milliseconds in evaluating 20 pickup events among 10 elderly individuals. Furthermore, ToPick exhibits a high level of reliability, achieving perfect accuracy, precision, and recall scores for pickup event detection. We actualize our research findings by designing an application intended for adoption by both healthcare practitioners and elderly individuals. The app aims to reduce both time and financial costs while enabling mobile treatment for users.

Textile-based surface electromyography (sEMG) electrodes have emerged as a prominent tool in muscle fatigue assessment, marking a significant shift toward innovative, noninvasive methods. This review examines the transition from metallic fibers to novel conductive polymers, elastomers, and advanced material-based electrodes, reflecting on the rapid evolution of materials in sEMG sensor technology. It highlights the pivotal role of materials science in enhancing sensor adaptability, signal accuracy, and longevity, crucial for practical applications in health monitoring, while examining the balance of clinical precision with user comfort. Additionally, it maps the global sEMG research landscape of diverse regional contributors and their impact on technological progress, focusing on the integration of Eastern manufacturing prowess with Western technological innovations and exploring both the opportunities and challenges in this global synergy. The integration of such textile-based sEMG innovations with artificial intelligence, nanotechnology, energy harvesting, and IoT connectivity is also anticipated as future prospects. Such advancements are poised to revolutionize personalized preventive healthcare. As the exploration of textile-based sEMG electrodes continues, the transformative potential not only promises to revolutionize integrated wellness and preventive healthcare but also signifies a seamless transition from laboratory innovations to real-world applications in sports medicine, envisioning the future of truly wearable material technologies.

Depression is a prevalent and debilitating mental health disorder that significantly impacts individuals, families, and societies worldwide. Despite advancements in treatment, challenges remain in effectively managing and monitoring depressive symptoms. Wearable technology, which encompasses devices that can monitor physiological and behavioral parameters in real time, offers promising new avenues for enhancing depression treatment. This comprehensive review explores the potential of wearable technology in managing and treating depression. It examines how wearables can monitor depressive symptoms, improve patient engagement and adherence to treatment plans, and provide valuable data for personalized treatment strategies. The review covers the integration of wearable technology in clinical settings, the role of wearables in remote monitoring and telemedicine, and the ethical and privacy considerations associated with their use. Additionally, it highlights case studies and pilot programs demonstrating the practical applications and outcomes of wearable technology interventions. Future directions and innovations are discussed, identifying potential advancements and challenges in this emerging field. This review aims to inform healthcare professionals, researchers, and policymakers about the opportunities and challenges of integrating wearable technology into depression treatment, ultimately contributing to improved mental healthcare outcomes.

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.

BACKGROUND: Previous research has suggested that spatiotemporal step parameters differ between settings; however, it remains unclear how different settings influence walking balance control.
OBJECTIVE: How do settings and sex influence walking balance control during walking at different speeds for young adults?
METHODS: Forty-two adults (21 male (23 ± 4 years), 21 female (24 ± 5 years)) completed overground walking trials in four settings: laboratory (10 m), hallway, indoor open, and outdoor pathway (all 20 m) at three self-selected speeds (slow, preferred, fast) following verbal instructions. Participants wore 17 inertial sensors (Xsens Awinda, Movella, Henderson, NV) to capture total body kinematics. The number of included strides was matched across all conditions, with six strides included in each condition for all participants. Medial-lateral and anterior-posterior total body angular momentum range over each stride was calculated (HML range and HAP range). Setting × speed × sex mixed factorial analysis of variance with repeated measures on setting and speed were used for statistical analysis (α =.05).
RESULTS: Significant setting × speed interactions (p <.001) were present for both outcomes. HML range was greater in the laboratory and hallway compared to the indoor open and outdoor pathway settings for slow walking speed only. HAP range was lower in the outdoor pathway compared to all indoor settings at slow and preferred walking speeds. Differences in HAP range between settings was more pronounced at the slow speed condition. Across setting and speed conditions, HML range was greater for males compared to females.
CONCLUSIONS: Young adults may alter their balance control strategy depending on the setting (laboratory, indoor open and outdoor pathway), particularly at slow speeds. Researchers and clinicians are cautioned not to assume walking in laboratory settings reflects walking in all settings nor that males and females can be examined as a single group.

The goal of this study is to determine the feasibility of a wearable multi-sensor positioning prototype to be used as a training tool to evaluate rowing technique and to determine the positioning accuracy using multiple mathematical models and estimation methods. The wearable device consists of an inertial measurement unit (IMU), an ultra-wideband (UWB) transceiver, and a global navigation satellite system (GNSS) receiver. An experiment on a rowing shell was conducted to evaluate the performance of the system on a rower\'s wrist, against a centimeter-level GNSS reference trajectory. This experiment analyzed the rowing motion in multiple navigation frames and with various positioning methods. The results show that the wearable device prototype is a viable option for rowing technique analysis; the system was able to provide the position, velocity, and attitude of a rower\'s wrist, with a positioning accuracy ranging between ±0.185 m and ±1.656 m depending on the estimation method.

(1) Background: Heart rate variability (HRV) has been investigated in the context of ST-segment elevation myocardial infarction (STEMI). This study contributes to the field by assessing short-term HRV during primary percutaneous coronary intervention (PCI) using wearable technology, providing real-time insights into autonomic function. (2) Methods: This single-center, observational cohort study included 104 STEMI patients undergoing primary percutaneous coronary intervention (PCI). HRV parameters (including SDNN, RMSSD, pNN50, HF, SD1, and SD2/SD1 ratio) were measured using a wearable device (Empatica E4 wristband, CE certified). Measurements were taken throughout the entire duration of the primary PCI, as well as specifically during the initial 5 min and the final 5 min of the procedure. The association between HRV parameters and adverse outcomes, including in-hospital mortality and in-hospital major adverse cardiovascular events (MACE), were assessed. (3) Results: HRV parameters significantly decreased after myocardial revascularization, particularly SDNN, RMSSD, pNN50, HF, SD1, and SD2/SD1 ratio. Significant associations were found between reduced SD2/SD1 ratio, approximate entropy, and adverse outcomes, including increased in-hospital mortality and in-hospital MACE (respectively, p = 0.007, p = 0.017 and p = 0.006 and p = 0.005). The SD2/SD1 ratio was significantly lower in patients who died during the hospital stay (p = 0.008) compared to survivors. Approximate entropy was also significantly lower in deceased patients (p = 0.019). (4) Conclusions: Real-time HRV monitoring using wearable technology offers valuable data regarding dynamic physiological changes during primary PCI. Further studies are required to validate these preliminary results and to explore their potential implications for clinical practice.

BACKGROUND: Physical activity (PA) plays a crucial role in health care, providing benefits in the prevention and management of many noncommunicable diseases. Wearable activity trackers (WATs) provide an opportunity to monitor and promote PA in various health care settings.
OBJECTIVE: This study aimed to develop a consensus-based framework for the optimal use of WATs in health care.
METHODS: A 4-round Delphi survey was conducted, involving a panel (n=58) of health care professionals, health service managers, and researchers. Round 1 used open-response questions to identify overarching themes. Rounds 2 and 3 used 9-point Likert scales to refine participants\' opinions and establish consensus on key factors related to WAT use in health care, including metrics, device characteristics, clinical populations and settings, and software considerations. Round 3 also explored barriers and mitigating strategies to WAT use in clinical settings. Insights from Rounds 1-3 informed a draft checklist designed to guide a systematic approach to WAT adoption in health care. In Round 4, participants evaluated the draft checklist\'s clarity, utility, and appropriateness.
RESULTS: Participation rates for rounds 1 to 4 were 76% (n=44), 74% (n=43), 74% (n=43), and 66% (n=38), respectively. The study found a strong interest in using WATs across diverse clinical populations and settings. Key metrics (step count, minutes of PA, and sedentary time), device characteristics (eg, easy to charge, comfortable, waterproof, simple data access, and easy to navigate and interpret data), and software characteristics (eg, remote and wireless data access, access to multiple patients\' data) were identified. Various barriers to WAT adoption were highlighted, including device-related, patient-related, clinician-related, and system-level issues. The findings culminated in a 12-item draft checklist for using WATs in health care, with all 12 items endorsed for their utility, clarity, and appropriateness in Round 4.
CONCLUSIONS: This study underscores the potential of WATs in enhancing patient care across a broad spectrum of health care settings. While the benefits of WATs are evident, successful integration requires addressing several challenges, from technological developments to patient education and clinician training. Collaboration between WAT manufacturers, researchers, and health care professionals will be pivotal for implementing WATs in the health care sector.

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This paper presents the generation of a Q-set for two Q studies investigating the perspectives of (1) patients with multiple sclerosis and (2) their healthcare professionals on the use of wearable technology. It describes the adopted Q methodology and how it was applied in different phases. The concourse is derived from the relevant literature, based on the unified theory of acceptance and use of technology (UTAUT2) model, with privacy as a moderator, and Hofstede\'s \"Cultural Dimensions\" framework, incorporates statements drawn from the concourse following review by experts This is followed by a pilot study involving 4 stakeholders to improve the relevance and quality of the research. A 43-statement Q-sample was developed for the first Q study, and a 32-statement Q-sample was developed for the second Q study. This preliminary study reported the development of a legitimate and reliable concourse in a transparent and comprehensive manner. The lessons learnt from developing the concourse in this study could be beneficial for future research when conducted in a similar digital healthcare context and in the context of MS where individuals often experience symptoms related to vision, sensation, coordination, and movement.