AIMC Topic: Wearable Electronic Devices

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Simplification of Mobility Tests and Data Processing to Increase Applicability of Wearable Sensors as Diagnostic Tools for Parkinson's Disease.

Sensors (Basel, Switzerland)
Quantitative mobility analysis using wearable sensors, while promising as a diagnostic tool for Parkinson's disease (PD), is not commonly applied in clinical settings. Major obstacles include uncertainty regarding the best protocol for instrumented m...

Predicting the severity of mood and neuropsychiatric symptoms from digital biomarkers using wearable physiological data and deep learning.

Computers in biology and medicine
Neuropsychiatric symptoms (NPS) and mood disorders are common in individuals with mild cognitive impairment (MCI) and increase the risk of progression to dementia. Wearable devices collecting physiological and behavioral data can help in remote, pass...

Tai Chi Expertise Classification in Older Adults Using Wrist Wearables and Machine Learning.

Sensors (Basel, Switzerland)
Tai Chi is a Chinese martial art that provides an adaptive and accessible exercise for older adults with varying functional capacity. While Tai Chi is widely recommended for its physical benefits, wider adoption in at-home practice presents challenge...

Automated detection of tonic seizures using wearable movement sensor and artificial neural network.

Epilepsia
Although several validated wearable devices are available for detection of generalized tonic-clonic seizures, automated detection of tonic seizures is still a challenge. In this phase 1 study, we report development and validation of an artificial neu...

Using Video Technology and AI within Parkinson's Disease Free-Living Fall Risk Assessment.

Sensors (Basel, Switzerland)
Falls are a major concern for people with Parkinson's disease (PwPD), but accurately assessing real-world fall risk beyond the clinic is challenging. Contemporary technologies could enable the capture of objective and high-resolution data to better i...

Strain-Temperature Dual Sensor Based on Deep Learning Strategy for Human-Computer Interaction Systems.

ACS sensors
Thermoelectric (TE) hydrogels, mimicking human skin, possessing temperature and strain sensing capabilities, are well-suited for human-machine interaction interfaces and wearable devices. In this study, a TE hydrogel with high toughness and temperatu...

Integrating Artificial Intelligence-Driven Wearable Technology in Oncology Decision-Making: A Narrative Review.

Oncology
BACKGROUND: Clinical decision-making in oncology is a complex process influenced by numerous disease-related factors, patient demographics, and logistical considerations. With the advent of artificial intelligence (AI), precision medicine is undergoi...

Unlocking Tomorrow's Health Care: Expanding the Clinical Scope of Wearables by Applying Artificial Intelligence.

The Canadian journal of cardiology
As an integral aspect of health care, digital technology has enabled modelling of complex relationships to detect, screen, diagnose, and predict patient outcomes. With massive data sets, artificial intelligence (AI) can have marked effects on 3 level...

MXene-Based Skin-Like Hydrogel Sensor and Machine Learning-Assisted Handwriting Recognition.

ACS applied materials & interfaces
Conductive hydrogels are widely used in flexible sensors owing to their adjustable structure, good conductivity, and flexibility. The performance of excellent mechanical properties, high sensitivity, and elastic modulus compatible with human tissues ...

Compressed Deep Learning Models for Wearable Atrial Fibrillation Detection through Attention.

Sensors (Basel, Switzerland)
Deep learning (DL) models have shown promise for the accurate detection of atrial fibrillation (AF) from electrocardiogram/photoplethysmography (ECG/PPG) data, yet deploying these on resource-constrained wearable devices remains challenging. This stu...