Design and Evaluation of the Mental Relaxation VR Scenes Using Forehead EEG Features

With the acceleration of social rhythm and the exacerbation of psychological problems caused by stress, psychological relief and adjuvant therapy based on relaxation and decompression have become the focus of research. Different from the traditional psychological relaxation therapy methods that using images, audios and videos, VR-based relaxation therapy is a promising way as the interaction of the VR system and dynamics of virtual environment affect the effectiveness of relax through more immersive and authentic audio-visual scenes. It makes the patient's emotion adjust to the normal state by generating a simulated environment in a VR system to comfort the subject and relieve subject mental stress. This paper presents a novel VR relaxation scenes design and evaluation framework where subject sensitive tourism VR videos were selected and combined with alpha wave induced background music. The relaxation effectiveness of VR scenes were evaluated by SAM scale, relaxation questionnaire and frontal EEG signals. A number of frontal EEG features from various analysis domains were explored to obtain the best stress-relevant features and to establish a stress-frontal EEG correlation model for stress evaluation, including time, frequency, entropy, geometric analysis, subband spectra, multiscale entropy, etc. 13 students aged between 20 and 30 were recruited in the evaluation experiment of 6 newly designed VR relaxation scenes. During which subjects frontal EEG signals were recorded as well as the SAM scale and questionnaire, the features that demonstrate an significant difference before and after watching VR scenes were identified, such as Energy, Energy ratio, the mean square root of frequency, frequency domain symmetry, Energy entropy and Shannon entropywhere frequency bands of delta, theta, low alpha and high alpha were considered. Finally, the features that demonstrate an significant difference before and after watching VR scenes were identified. The best stress-relevant features were selected to establish a stress-frontal EEG correlation model for stress evaluation which could be used to validate the effectiveness of VR relaxation scenes.