AI-Driven Health Monitoring using Wearable Devices for Physical and Mental Well-Being

This research investigates a health monitoring system that will cater to the physical and mental well-being using wearable devices, Internet of Things (IoT), AI-driven analytics and machine learning. While traditional wearable health applications focus on individual health indicators (e.g., heart rate, step count), this study integrates those with other indicators of mental and physical wellness and provides a more expansive evaluation. Implementing multiple machine learning models including Random Forest and Long Short-Term Memory (LSTM) for predicting stress levels, calorie requirements, and blood pressures. The technology will inform lifestyle choices for the user through personalized health insights. The system allows tracking both mood and stress markers, as well as providing recommendations to the users based on their health metrics. This encourages users to grasp the dynamic connection between their mental and physical well-being by developing a proactive and comprehensive approach to health.