A Health Monitoring System Based on Flexible Triboelectric Sensors for Intelligence Medical Internet of Things and its Applications in Virtual Reality
Junqi Mao, Puen Zhou, Xiaoyao Wang, Hongbo Yao, Liuyang Liang, Yiqiao, Zhao, Jiawei Zhang, Dayan Ban, Haiwu Zheng

TL;DR
This paper presents a flexible triboelectric sensor-based IoMT system for intelligent health monitoring, specifically targeting Parkinson's Disease patients, integrating deep learning for movement analysis, and enabling comprehensive, cost-effective patient assessment.
Contribution
It introduces a novel wearable triboelectric sensor system combined with deep learning analytics for precise health monitoring in IoMT applications, especially for neurological conditions.
Findings
Accurately detects limb movements and fine motor skills in PD patients.
Provides comprehensive health assessment including location, heart rate, and identity.
Demonstrates cost-effective and highly sensitive wearable sensor technology.
Abstract
The Internet of Medical Things (IoMT) is a platform that combines Internet of Things (IoT) technology with medical applications, enabling the realization of precision medicine, intelligent healthcare, and telemedicine in the era of digitalization and intelligence. However, the IoMT faces various challenges, including sustainable power supply, human adaptability of sensors and the intelligence of sensors. In this study, we designed a robust and intelligent IoMT system through the synergistic integration of flexible wearable triboelectric sensors and deep learning-assisted data analytics. We embedded four triboelectric sensors into a wristband to detect and analyze limb movements in patients suffering from Parkinson's Disease (PD). By further integrating deep learning-assisted data analytics, we actualized an intelligent healthcare monitoring system for the surveillance and interaction of…
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Taxonomy
TopicsAdvanced Sensor and Energy Harvesting Materials
