AIMC Topic: Wearable Electronic Devices

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Multimodal Wearable Sensing for Biomechanics and Biomolecules Enabled by the M-MPM/VCFs@Ag Interface with Machine Learning Pipeline.

ACS sensors
The addition sensing device of sweat to wearable biostress sensors would eliminate the need for using multiple gadgets for healthcare analysis. Due to the distinct package fashion of sensor interface for biostress and biomolecule, achieving permeabil...

A skin-interfaced wireless wearable device and data analytics approach for sleep-stage and disorder detection.

Proceedings of the National Academy of Sciences of the United States of America
Accurate identification of sleep stages and disorders is crucial for maintaining health, preventing chronic conditions, and improving diagnosis and treatment. Direct respiratory measurements, as key biomarkers, are missing in traditional wrist- or fi...

Effects of the lumbar support function of wearable robot (Bot Fit) on sitting position.

Biomedical engineering online
BACKGROUND: Sedentary lifestyles can lead to musculoskeletal disorders, but proper sitting posture, particularly maintaining a slight anterior pelvic tilt, helps prevent issues like lower back pain and spinal misalignment. Samsung Electronics wearabl...

Using machine learning to identify Parkinson's disease severity subtypes with multimodal data.

Journal of neuroengineering and rehabilitation
BACKGROUND: Classifying and predicting Parkinson's disease (PD) is challenging because of its diverse subtypes based on severity levels. Currently, identifying objective biomarkers associated with disease severity that can distinguish PD subtypes in ...

Airbag-like Comb Flexible Pressure Sensor and Its Wearable Applications.

ACS applied materials & interfaces
Flexible wearable devices demonstrate immense potential in healthcare and human-computer interaction, yet the development of high-performance flexible pressure sensors for these applications remains a pressing technical challenge. Inspired by the str...

Estimating motor symptom presence and severity in Parkinson's disease from wrist accelerometer time series using ROCKET and InceptionTime.

Scientific reports
Parkinson's disease (PD) is a neurodegenerative condition characterized by frequently changing motor symptoms, necessitating continuous symptom monitoring for more targeted treatment. Classical time series classification and deep learning techniques ...

Relapse prediction using wearable data through convolutional autoencoders and clustering for patients with psychotic disorders.

Scientific reports
Relapse of psychotic disorders occurs commonly even after appropriate treatment. Digital phenotyping becomes essential to achieve remote monitoring for mental conditions. We applied a personalized approach using neural-network-based anomaly detection...

Characterising physical activity patterns in community-dwelling older adults using digital phenotyping: a 2-week observational study protocol.

BMJ open
INTRODUCTION: Physical activity (PA) is crucial for older adults' well-being and mitigating health risks. Encouraging active lifestyles requires a deeper understanding of the factors influencing PA, which conventional approaches often overlook by ass...

IoT-enabled real-time health monitoring system for adolescent physical rehabilitation.

Scientific reports
This study aims to develop an intelligent system leveraging Internet of Thing (IoT) technology to enhance the precision of youth physical training monitoring and improve training outcomes. A wearable device incorporating Micro Electro Mechanical Syst...

Unlocking the Potential of Wear Time of a Wearable Device to Enhance Postpartum Depression Screening and Detection: Cross-Sectional Study.

JMIR formative research
BACKGROUND: Postpartum depression (PPD) is a mood disorder affecting 1 in 7 women after childbirth that is often underscreened and underdetected. If not diagnosed and treated, PPD is associated with long-term developmental challenges in the child and...