MENTAL STRESS EARLY WARNING WEARABLE

Abstract

The increasing pace of modern life has led to a rise in stress-related mental health issues, highlighting the need for continuous and objective stress monitoring. Conventional assessment methods rely on self-reporting or periodic clinical evaluations, which lack real-time capability and reliability. This paper presents the design and implementation of a low-cost mental stress early-warning wearable system for real-time monitoring and alert generation. The proposed system uses an ESP32 microcontroller integrated with multiple physiological sensors, including heart rate variability (HRV), galvanic skin response (GSR), skin temperature, and an accelerometer to analyze stress-related indicators. Sensor data are processed locally and displayed on an LCD, while simultaneously transmitted to a cloud platform for remote monitoring and data analysis. When detected stress levels exceed predefined thresholds, the system generates immediate alerts through buzzer, vibration, or notification mechanisms. Powered by a regulated 5V DC supply, the wearable ensures stable performance and low power consumption, making it suitable for continuous use. The proposed system enables early stress detection and proactive management, with potential applications in healthcare monitoring, workplace wellness, personal fitness, and telemedicine environments.