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Use of wearables, which can be considered as devices worn on the body that capture dimensions of health, are common in research. Wearables are useful as they can be employed in a number of environments for a variety of populations and can record over short or long time periods. Recent advancements in technology have significantly improved the accuracy of sensors and the algorithms used to interpret their data. Commercial wearables, such as fitness trackers, smartwatches, and smart rings have seen parallel advancements. Perhaps the most common application of wearables in research is for the assessment of sleep and rest-activity rhythms as most wearables include accelerometers, a sensor commonly used to infer sleep and activity from movement patterns. Commercial wearables are appealing for use in research due to their widespread use in the general population, real-time data syncing capabilities, affordability, and their user-friendly, consumer-oriented design and interfaces. There are, however, several important factors to consider when selecting a commercial wearable for use in research. These include device specifications (durability, price, unique features, etc.), data accessibility, and participant factors. Keeping these considerations in mind can assist in the collection of high-quality data that can ultimately be used to improve population outcomes. The purpose of this methodological review is to describe considerations for the use of commercially available wearables in research for the purposes of assessing sleep and rest-activity patterns.
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http://dx.doi.org/10.1177/10998004251337065 | DOI Listing |
Front Rehabil Sci
August 2025
Department of Physical Therapy, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
Introduction: Online community-based exercise (CBE) is a rehabilitation strategy that can promote health outcomes among people living with HIV. We aimed to describe experiences implementing a community-based exercise (CBE) intervention with adults living with HIV.
Methods: We conducted a longitudinal qualitative descriptive study involving interviews with adults living with HIV and persons implementing an online tele-coaching CBE intervention.
IEEE Trans Biomed Circuits Syst
September 2025
Neuroprostheses capable of providing Somatotopic Sensory Feedback (SSF) enables the restoration of tactile sensations in amputees, thereby enhancing prosthesis embodiment, object manipulation, balance and walking stability. Transcutaneous Electrical Nerve Stimulation (TENS) represents a primary noninvasive technique for eliciting somatotopic sensations. Devices commonly used to evaluate the effectiveness of TENS stimulation are often bulky and main powered.
View Article and Find Full Text PDFProg Mol Biol Transl Sci
September 2025
School of Applied Sciences and Technology, Gujarat Technological University, Gujarat, India. Electronic address:
This chapter examines advancements and future trajectories in wearable biosensing technologies, a multidisciplinary field encompassing healthcare, materials science, and information technology. Wearable biosensors are revolutionizing real-time physiological and biochemical monitoring with applications in personalized health monitoring, disease diagnosis, fitness, and therapeutic interventions. In addition to Internet of Things (IoT) and wireless connectivity technologies such as Bluetooth Low Energy (BLE) and 5G, which facilitate transparent remote monitoring and data exchange, other notable innovations such as machine learning and artificial intelligence enhance real-time processing of data, predictive analytics, and personalized healthcare solutions.
View Article and Find Full Text PDFFront Artif Intell
August 2025
Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada.
Precision livestock farming increasingly relies on non-invasive, high-fidelity systems capable of monitoring cattle with minimal disruption to behavior or welfare. Conventional identification methods, such as ear tags and wearable sensors, often compromise animal comfort and produce inconsistent data under real-world farm conditions. This study introduces Dairy DigiD, a deep learning-based biometric classification framework that categorizes dairy cattle into four physiologically defineda groups-young, mature milking, pregnant, and dry cows-using high-resolution facial images.
View Article and Find Full Text PDFAdv Mater
September 2025
School of Electrical Engineering, Korea University, Seoul, 02841, Republic of Korea.
Bifunctional integration of indoor organic photovoltaics (OPVs) and photodetectors (OPDs) faces fundamental challenges because of incompatible interfacial thermodynamics: indoor OPVs require unimpeded charge extraction under low-light conditions (200-1000 lx), whereas OPDs require stringent suppression of noise current. Conventional hole transport layers (HTLs) fail to satisfy these opposing charge-dynamic requirements concurrently with commercial practicality (large-area uniformity, photostability, and cost-effective manufacturability). This study introduces benzene-phosphonic acid (BPA)-a minimalist self-assembled monolayer (SAM)-based HTL with a benzene core and phosphonic acid anchoring group-enabling cost-effective synthesis and excellent ITO interfacial properties such as energy alignment, uniform monolayer, and stability.
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