Psychological Perceptual Analysis Based on Dance Therapy Using Artificial Intelligence Techniques

Abstract

Dance is an embodied activity when applied therapeutically, and it can have numerous specific and unspecific health assistances. Dance Movement Therapy (DMT) is a psychotherapeutic process used for the individual’s emotional, cognitive, and physical integration. To automatically synthesize dance movements according to the music, it needs to solve some computational challenges. This paper proposes the Artificial Intelligence assisted Dance Movement Therapy (AIDMT) to predict an individual’s psychological condition. The complete aim of this paper is to analyze the effects of recreational/general dance and dance movement therapy (DMT) on well-being, anxiety, and depression by a convolution neural network (CNN). The research results support the potential usefulness of DMT as a multi-faceted intervention for enhancing different facets of functioning in adolescence with diminishing cognitive abilities. The absence of advantageous effects for our long-term DMT and exercise intervention effects discover the requirement to preserve persistent activity levels with sufficient duration and intensity. Conclusion — The experimental result suggests that AIDMT achieves the highest classification accuracy of 98.03%.