AIMC Topic: Wearable Electronic Devices

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Multimodal Detection of Agitation in People With Dementia in Clinical Settings: Observational Pilot Study.

JMIR aging
BACKGROUND: Dementia is a progressive neurodegenerative condition that affects millions worldwide, often accompanied by agitation and aggression (AA), which contribute to patient distress and increased health care burden. Existing assessment methods ...

Synergizing Nanosensor-Enhanced Wearable Devices with Machine Learning for Precision Health Management Benefiting Older Adult Populations.

ACS nano
Population aging presents significant health challenges and socioeconomic burdens globally, driving an increased demand for precision health management. In the era of big data, the exponential growth of health information is accelerating advances in ...

Self-Assembly MXene/PDA@Cotton Fabric Pressure Sensor Integrated with Deep Learning for Sign Language Recognition.

ACS applied materials & interfaces
In recent years, smart textiles and flexible wearable products have garnered significant attention in fields such as human-computer interaction, medical rehabilitation training, and motion monitoring. Flexible pressure sensors have attracted signific...

Exploiting heart rate variability for driver drowsiness detection using wearable sensors and machine learning.

Scientific reports
Driver drowsiness is a critical issue in transportation systems and a leading cause of traffic accidents. Common factors contributing to accidents include intoxicated driving, fatigue, and sleep deprivation. Drowsiness significantly impairs a driver'...

PREACT-digital: study protocol for a longitudinal, observational multicentre study on digital phenotypes of non-response to cognitive behavioural therapy for internalising disorders.

BMJ open
INTRODUCTION: Cognitive behavioural therapy (CBT) serves as a first-line treatment for internalising disorders (ID), encompassing depressive, anxiety or obsessive-compulsive disorders. Nonetheless, a substantial proportion of patients do not experien...

Integrating deep learning in stride-to-stride muscle activity estimation of young and old adults with wearable inertial measurement units.

Scientific reports
Deep learning has become powerful and yet versatile tool that allows for the extraction of complex patterns from rich datasets. One field that can benefits from this advancement is human gait analysis. Conventional gait analysis requires a specialize...

Electrical grid-independent machine learning-assisted wearable gait analysis device with triboelectric-electromagnetic hybrid energy harvester.

Biosensors & bioelectronics
In this study, an Electrical grid-independent Machine learning-assisted Wearable device for Gait analysis (EMWG) with a ground reaction force sensor is presented. For gait analysis, a multi-layer perceptron is identified as the optimal model among va...

GPS-based street-view greenspace exposure and wearable assessed physical activity in a prospective cohort of US women.

The international journal of behavioral nutrition and physical activity
BACKGROUND: Increasing evidence positively links greenspace and physical activity (PA). However, most studies use measures of greenspace, such as satellite-based vegetation indices around the residence, which fail to capture ground-level views and da...

Self-Healing Triboelectric Sensors with Enhanced Durability for Gesture Recognition and Human-Machine Interaction.

Nano letters
The emergence of triboelectric nanogenerators (TENGs) has significantly developed the landscape of wearable electronics. However, the durability and self-healing capabilities of TENGs remain challenging. Herein, a self-healing triboelectric nanogener...

A novel feature extractor based on constrained cross network for detecting sleep state.

Scientific reports
With increasing awareness of healthy living and social pressure, more and more people have begun to pay attention to their sleep state. Most existing methods that utilize wrist-worn devices data for detection rely on heuristic algorithms or tradition...