Work

AI Enhanced Tai Chi Rehabilitation for Substance Use Disorder with Clinical Evidence and Predictive Modeling for Relapse Prevention

Year: 2025

Type: article

Abstract: Substance use disorder (SUD) remains a significant global health issue, with relapse rates exceeding 60% in some compulsory rehabilitation centers despite structured interventions. Recent research suggests that mind–body exercises, like Tai Chi, can lessen cravings and enhance psychological well-being, though their current use is often standardized, subjective, and not personalized. This study aimed to evaluate the clinical benefits of Tai Chi within a compulsory rehabilitation setting and to develop an AI-enhanced framework for individualized relapse prevention. A randomized controlled trial (RCT) involving 168 participants diagnosed with SUD compared a Tai Chi intervention group with a standard physical education control group. Psychometric outcomes were measured using validated scales, while a conceptual AI framework using a CNN-LSTM architecture was simulated with multimodal inputs that combined psychometric indicators and motion-based features. The RCT showed significant reductions in craving, depression, and anxiety, along with improved self-control in the Tai Chi group compared to controls. Mediation analysis indicated that psychological symptoms partially explained the link between craving and relapse risk. The AI simulation achieved 82% accuracy and an area under the ROC curve of 0.85, with craving and depression identified as key predictors. These results provide initial evidence that integrating Tai Chi with AI-driven monitoring can transform exercise-based rehabilitation into a closed-loop, adaptive system capable of delivering personalized feedback and early relapse warnings. This combined approach has the potential to enhance the scalability, accuracy, and effectiveness of institutional rehab programs for SUD.

Source: Journal of Machine Intelligence in Healthcare

DOI: 10.70062/jmih.v1i2.170

Authors: Nova Ariyanto, Siti Fatimah Abd Rahman

Institutions: Universitas Muhammadiyah Semarang, International Islamic University Malaysia

Language: English

Topic: Substance Abuse Treatment and Outcomes

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: bronze

Funder: Fund for Astrophysical Research