Author: Yuze Zhang1,2, Haojie Li1, Rui Huang1
Affiliation: <sup>1</sup> School of Exercise and Health, Shanghai University of Sport, Shanghai 200438, China.
<sup>2</sup> Chinese WuShu Academy, Beijing Sport University, Beijing 100084, China.
Conference/Journal: Sensors (Basel)
Date published: 2024 Oct 9
Other:
Volume ID: 24 , Issue ID: 19 , Pages: 6485 , Special Notes: doi: 10.3390/s24196485. , Word Count: 198
(1) Background: This study aims to compare the effects of AI-based exercise feedback and standard training on the physical and mental health outcomes of older adults participating in a 4-week tai chi training program. (2) Methods: Participants were divided into three groups: an AI feedback group received real-time movement accuracy feedback based on AI and inertial measurement units (IMUs), a conventional feedback group received verbal feedback from supervisors, and a control group received no feedback. All groups trained three times per week for 8 weeks. Outcome measures, including movement accuracy, balance, grip strength, quality of life, and depression, were assessed before and after the training period. (3) Results: Compared to pre-training, all three groups showed significant improvements in movement accuracy, grip strength, quality of life, and depression. Only the AI feedback group showed significant improvements in balance. In terms of movement accuracy and balance, the AI feedback group showed significantly greater improvement compared to the conventional feedback group and the control group. (4) Conclusions: Providing real-time AI-based movement feedback during tai chi training offers greater health benefits for older adults compared to standard training without feedback.
Keywords: elderly intervention; inertial measurement units; movement recognition; tai chi; temporal convolutional neural networks.
PMID: 39409525 DOI: 10.3390/s24196485