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IoT-Enabled Wearable Device for Stroke Rehabilitation at Home
Abstract
This article presents a LoRa-based health monitoring device designed for rehabilitation patients. The system combines body surface EMG sensing with inertial motion tracking to record muscle activation, joint angle, and repetition count. A wearable unit transmits processed features over LoRa (Long Range network) to a cloud server. The cloud is a place where data is stored. The cloud provides the endpoint for visualization. Patients and clinicians access the data via web and mobile dashboards that display real-time EMG graphs, angle observations, session history, and feedback. Signal preprocessing includes bandpass filtering, rectification, RMS calculation, and normalization. Experiments showed EMG error < 6%, angle error < 3°, and rep detection F1 ≈ 0.96. LoRa communication achieved > 90% packet delivery indoors and outdoors with latency < 500 ms. Battery life exceeded 30 hours of continuous use. Case studies confirmed utility in hospitals, homes, clinics, and rural centers.
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