Virtual Reality Sensor-Based IoT Embedded System for Stress Diagnosis
A. Ahilan, M. Anline Rejula, S.N. Kumar, B. Muthu Kumar
Abstract
In today’s scenario, mental stress is common among people. Stress can be defined as tension arising due to daily life’s emotional, psychological, and physical pressures. It has become a serious issue in the modern world as it affects not only our physical health but also our work performance, passion for work, and general attitude in daily life. Chronic exposure to stress exhibits physical symptoms such as aches, muscle tension, and dizziness. If not treated well, it paves the way toward severe health consequences which results in depression, cardiovascular diseases, sleep disorders, degradation in the immune system, and cancer. Stress can be detected at an early stage by measuring the variability in a few parameters. The virtual reality (VR) based IoT embedded system is designed to transfer data through the cloud platform. Electromyography (EMG), galvanic skin response, oxygen saturation level, and heart rate are used to detect stress. The statistical analysis has performed on the acquired VR sensor data and MATLAB software was used for the statistical analysis of EMG signals. The VR technology was utilized in this research for stress alleviation by revealing the human subjects to happy video and prior to that stress was induced in the human subjects by using illusion video. The convolution neural network was also employed in this research work for the classification of stress and non-stress states. The results reveal that VR technology with the aid of pleasant music or video clipping minimizes the stress level in human beings.