Promoting continuous rehabilitation with AI-based motion capture and biomechanical analysis: objective feedback as a...

Area of Science:

• Rehabilitation Medicine
• Biomedical Engineering
• Gerontology

Background:

• Exercise therapy is crucial for rehabilitation but faces challenges with patient adherence and motivation.
• Objective tracking of motor skill changes and providing feedback may improve rehabilitation continuity.

Purpose of the Study:

• To investigate the effect of AI-based markerless motion capture feedback on exercise motivation in elderly patients undergoing rehabilitation.
• To assess if visualizing motor function changes enhances understanding and motivation for continued exercise participation.

Main Methods:

• Utilized AI-based markerless motion capture to estimate upper limb joint moments.
• Assessed motivation using the Motivation in Exercise Questionnaire (MEQ) in elderly patients (n=31) with diverse conditions.
• Employed a non-randomized design with an 8-week intervention, providing feedback at 4 weeks and follow-up.

Main Results:

• Feedback group showed a tendency for improved motivation and willingness to continue exercising, though not statistically significant (p=0.09).
• Understanding of athletic ability changes also showed a positive trend with feedback (p=0.13).
• Parkinsonism participants exhibited significantly negative changes in questionnaire scores compared to other groups (p=0.022).

Conclusions:

• Visualizing motor function changes via feedback can temporarily boost exercise motivation in elderly rehabilitation patients.
• The positive effects of feedback on motivation were not sustained one month post-intervention.
• Continuous, more frequent feedback (e.g., monthly) is likely necessary to maintain long-term exercise adherence.