Mental Health Monitoring and Relaxation Companion

In today's fast-paced world, mental health has become increasingly critical yet often overlooked. Stress, anxiety, and depression affect millions globally, and early detection can preventserious health complications. This paper presentsMindEase, an innovative IoT-based system thatmonitors mental health in real-time using physiologicalbiosensors and provides intelligent relaxation feedback.ThesystemintegratesECG(Electrocardiogram),four pulse,biosensors— temperature, and GSR (Galvanic Skin Response)— connected to a NodeMCU (ESP8266) microcontroller for data acquisition. The collected data is transmitted to ThingSpeak, an IoT cloud platform, for real-time visualization and storage. A Python-based software interface processes the sensor data, classifies stress levels, and automatically triggers personalized relaxation interventions such as soothing music, meditation videos, and medical consultation alerts. The multi-modal sensor approach demonstrates high accuracy in stress detection compared to single-sensor systems, making it a practical solution for students, professionals, and individuals managing daily stress. Testing confirmed reliable operation across various physiological conditions, establishing MindEase as a comprehensive mental wellness companion combining hardware, IoT connectivity, and intelligent softwareanalysis. Keywords: Mental Health Monitoring, IoT, Biosensors, Stress Detection, ECG, GSR, NodeMCU, ThingSpeak, Python, Cloud Computing, Wearable Health Systems, Biofeedback.