Qigong Master: A Qigong-Based Attention Training Game Using Action Recognition and Balance Analysis

Abstract

Baduanjin is a type of martial art that is aimed at the development and health of the physical, emotional and spiritual aspects. It emphasizes on gentle movements, relaxed yet disciplined, and training of mental concentration through relaxation. In order to make Baduanjin attention training more effective and easier, we proposed a novel Baduanjin-based attention training game that instructs the subject to practice Baduanjin using virtual reality (VR) and motion analysis. Through a virtual instructor who demonstrates a series of Baduanjin actions, the subject is asked to follow the instructor's movement at any time. Meanwhile, the 3D position of the subject's body joints is collected by a motion capture device for further analysis using a deep learning model to evaluate the order correctness and precision of the Baduanjin actions. In addition, transfer learning technique is used to solve the problem of small size of Baduanjin data. Preliminary tests with 20 normal individuals showed that the recognition accuracy of the Baduanjin actions reached nearly 97%, and the balance analysis reflected the position change of the body center of mass to a certain extent. We also compared the performance of the model with and without pre-training to demonstrate the importance of transfer learning. The result of these explorations shows the feasibility of this prototype system as an attention training system and its potential as an assistive treatment option. In conclusion, we not only created the virtual instructor that could provide accurate movement demonstration, but also collected objective action data for more accurate balance analysis to provide appropriate feedback.