Raspberry Pi-Enabled Wearable Sensors for Personal Health Tracking and Analysis

Proactive healthcare management has made personal health tracking and analysis commonplace. Raspberry Pi-enabled wearable sensors assess health in this study. Wearable sensors with the inexpensive Raspberry Pi give a flexible platform for real-time physiological and environmental data collection and analysis. Raspberry Pi's computing, connectivity, and expandability enable personal health tracking. The Raspberry Pi platform readily integrates wearable sensors like heart rate monitor, accelerometer, temperature sensor, and GPS module to detect physical activity, environmental variables, and vital signs. Machine learning algorithms and statistical methods analyze data to reveal a person's health status, trends, and risks. Consumers can receive threshold-based alerts and feedback via the Raspberry Pi platform. This article covers Raspberry Pi-enabled wearable sensor system design, sensor selection, data collection, processing, and UI development. The article describes the system's fitness monitoring, chronic illness management, and early health anomaly detection purposes. Experiments show the system's personal health tracking and analysis. The findings demonstrate the system's data processing and actionable insights. This research study offers a Raspberry Pi-enabled wearable sensor system for health monitoring and analysis. Raspberry Pi with wearable sensors collects, processes, and analyzes real-time data. This study suggests that the low-cost and adaptable phases improve individual well-being monitoring.