Wireless acquisition system of autonomic response signals for personal early detection of psychological stress applications

Detecting psychological stress is crucial for mental well-being and for preventing stress-related health issues. This research presents a wireless system designed to monitor autonomic responses for stress detection and classification. The system integrates wearable photoplethysmography (PPG) and galvanic skin response (GSR) sensors to capture stress-related physiological indicators. The collected signals are transmitted wirelessly for real- time visualization and analysis. Experimental results demonstrated that the system effectively recorded stable PPG and GSR signals with minimal interference, validating its feasibility for stress detection. The PPG signal monitored heart rate fluctuations, while the GSR signal tracked variations in skin conductivity. The integration of machine learning techniques in future work could further improve the accuracy of stress classification. This research lays the foundation for developing accessible, non-invasive, and personalized stress monitoring solutions.