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Personalized health services are of paramount importance for the treatment and prevention of cardiorespiratory diseases, such as hypertension. The assessment of cardiorespiratory function and biometric identification (ID...

Falls among older adults pose a major healthcare and social burden, making early identification of high-risk individuals essential for prevention. This study presents a portable, non-invasive AI-based wearable system tha...

Abstract Wearable sensor–based human activity recognition (HAR) is central to smart sport and health-monitoring applications, yet existing deep learning models often rely on ad hoc multimodal fusion and offer limited i...

With the increasing aging population, the health management of older people has become an increasingly important issue. The author aims to meet the health needs of older people by designing a wearable device and a vital ...

Abstract BackgroundAtrial fibrillation (AF) and atrial flutter (AFL) are common arrhythmias associated with the risk of ischemic stroke, which can be reduced with anticoagulation therapy. Thus, early diagnosi...

Reliable beat-level arrhythmia detection from electrocardiogram (ECG) signals is essential for continuous patient monitoring. However, many existing deep learning models remain computationally expensive and are sensitive...

ABSTRACT Monitoring the movements of ruminant animals is one of the most challenging tasks. In animals that act according to their habits, it is difficult to label such movements and transfer them to farmers. Monitoring ...

Embodied therapies such as movement therapy have shown promise in enhancing emotional regulation, cognitive engagement, and physical rehabilitation. However, scalable and personalized delivery of such interventions remai...

ABSTRACT Invoking high‐performance bio‐based fibres (e.g., Bacterial cellulose) contributes to the sustainability and functionality of wearable electronic devices at the material level. However, the fabrication of se...

Achieving high-efficient and low-power communication is pivotal yet very challenging in the emerging technologies. Unlike conventional backscatter communication system, we propose and demonstrate an amplitude-reconfigura...

Goal: To enable comfortable and non-invasive heart rhythm monitoring, this work aims to reconstruct electrocardiogram (ECG) signals from photoplethysmogram (PPG) signals, eliminating the need for multiple electrode attac...

Abstract The reflex arc is fundamental to the physiology of posture and robust locomotion. Mimicking biological reflexes in engineered systems has, therefore, high potential to improve robustness and learning performance...

This dataset comprises physiological signals recorded via a wearable device (Empatica E4) during structured acute stress induction and both aerobic and anaerobic exercise sessions. Collected metrics include blood volume ...

"El estrés es un fenómeno que afecta a toda la población y que puede tener un impacto negativo en la salud si no es gestionado adecuadamente. Un monitoreo continuo del estrés implementado en sistemas portátiles podr...

Lifting is a common task. This work typically requires muscle strength, especially the back muscles. However, this work carries a risk of back injury if performed incorrectly or inappropriately. Using a back muscle injur...

This study presents a comparative evaluation of three hybrid deep learning models for human activity recognition (HAR) in free-living and highly imbalanced conditions: 1DCNN-ResBLSTM-Attention (Model A), Attention-Mechan...