Parkinson’s Disease Management Via Wearable Sensors

Abstract

This study presents an innovative IoT-based system for the real-time management of Parkinson's Disease using a combination of Flex Sensor, Node MCU, SCR Sensor, and ADXL335. The Flex Sensor captures hand tremors, the ADXL335 monitors overall motion, and the SCR Sensor measures physiological stress levels. These components collectively enable continuous monitoring of Parkinson's symptoms. The data is wirelessly transmitted to a centralized server for analysis, allowing healthcare providers to remotely assess patient conditions. Machine learning algorithms offer insights into disease progression and predict potential exacerbations. The system provides timely alerts, enhancing patient care and reducing healthcare costs. This research contributes to the evolving landscape of IoT applications in healthcare for neurodegenerative disorders.