โก Quick Summary
A recent study evaluated the impact of an 8-week AI-assisted telerehabilitation program on exercise capacity in patients with hypertension. The results indicated significant improvements in 6-minute walk distance and other health metrics, showcasing the potential of AI in enhancing rehabilitation strategies.
๐ Key Details
- ๐ Participants: 62 adults aged 18-75 with hypertension
- ๐งฉ Intervention: AI-assisted remote rehabilitation plus routine health education
- โ๏ธ Control: Conventional offline exercise guidance with health education
- ๐ Duration: 8 weeks, with sessions lasting 30-50 minutes, 3 times weekly
- ๐ Primary Outcome: Change in 6-minute walk distance (6MWD)
๐ Key Takeaways
- ๐ AI-assisted telerehabilitation significantly improved exercise capacity in patients with hypertension.
- ๐ 6-minute walk distance (6MWD) increased by an adjusted mean difference of 62.77 meters (P=.002).
- ๐ช Systolic blood pressure saw a reduction of 4.11 mmHg (P=.046).
- ๐ International Physical Activity Questionnaire (IPAQ) scores improved by 658.96 (P=.011).
- ๐ก Exercise self-efficacy increased by 21.71 (P<.001).
- โฑ๏ธ Total exercise time increased by 98.24 minutes (P=.001).
- ๐ฌ๏ธ Peak oxygen uptake (peak VO2) improved by 3.39 mL/kg/min (P=.026).
- ๐ก๏ธ No serious adverse events were reported during the study.
๐ Background
Hypertension is a significant global health issue, contributing to increased risks of cardiovascular diseases and mortality. Traditional exercise therapies often lack accessibility and personalization, which can hinder patient adherence. The integration of artificial intelligence (AI) in rehabilitation offers a novel approach to address these challenges, providing real-time monitoring and tailored guidance for patients.
๐๏ธ Study
This randomized controlled trial involved 62 patients diagnosed with hypertension, who were divided into two groups: one receiving AI-assisted telerehabilitation and the other receiving conventional exercise guidance. The study aimed to assess the effectiveness of the AI program over an 8-week period, focusing on various health outcomes, including exercise capacity and psychological well-being.
๐ Results
The findings revealed that the intervention group experienced substantial improvements across multiple metrics. The 6-minute walk distance increased significantly, alongside reductions in systolic blood pressure and enhancements in physical activity levels and exercise self-efficacy. These results underscore the effectiveness of AI-assisted rehabilitation in managing hypertension.
๐ Impact and Implications
The implications of this study are profound, suggesting that AI-assisted telerehabilitation could serve as a scalable and effective strategy for managing hypertension in real-world settings. By enhancing exercise capacity and promoting regular physical activity, this approach could lead to better health outcomes and improved quality of life for patients with hypertension.
๐ฎ Conclusion
This study highlights the transformative potential of AI-assisted rehabilitation in improving health outcomes for patients with hypertension. By providing personalized and accessible exercise programs, we can enhance patient adherence and overall health. Future research should continue to explore the integration of AI in rehabilitation strategies to further optimize hypertension management.
๐ฌ Your comments
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Effects of Artificial Intelligence Recognition-Based Telerehabilitation on Exercise Capacity in Patients With Hypertension: Randomized Controlled Trial.
Abstract
BACKGROUND: Hypertension remains a major global health challenge, significantly increasing cardiovascular and all-cause mortality risks. While exercise therapy is effective, conventional approaches face limitations in accessibility and personalization, compromising adherence. Artificial intelligence (AI)-assisted remote rehabilitation enables real-time monitoring and personalized guidance, offering a promising alternative. Nevertheless, its clinical benefits and applicability require further systematic validation.
OBJECTIVE: This study aimed to evaluate the efficacy of an 8-week AI-assisted telerehabilitation program on improving exercise capacity and related health outcomes in patients with hypertension.
METHODS: This prospective, dual-arm, parallel, open-label, randomized controlled trial enrolled 62 patients with hypertension recruited via convenience sampling. Participants were adults aged between 18 and 75 years with a confirmed hypertension diagnosis who were excluded for severe cardiac complications, recent myocardial infarction, unstable angina, or physical disabilities preventing exercise. The participants were randomly assigned (1:1) to an intervention group that received AI-assisted remote rehabilitation plus routine health education, or a control group that received health education and conventional offline exercise guidance. The supervised exercise program included warm-up, cardiorespiratory endurance, strength resistance, balance, and flexibility training, followed by a cooldown. Sessions lasted between 30 and 50 minutes and were performed at least 3 times weekly for 8 weeks. Assessments at baseline and 8 weeks included the 6-minute walk test (6MWT), cardiopulmonary exercise testing (CPET), International Physical Activity Questionnaire (IPAQ), Short-Form Health Survey 12 (SF-12), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), exercise self-efficacy, blood pressure (BP), body weight, handgrip strength, and other health-related indicators. The primary outcome was the change in 6-minute walk distance (6MWD). Data were analyzed according to the intention-to-treat principle.
RESULTS: Throughout the 8-week intervention period, no serious adverse events related to the AI-assisted telerehabilitation intervention occurred. After 8 weeks, the intervention group demonstrated significantly greater improvements than the control group in 6-minute walk distance (6MWD; adjusted mean difference 62.77, 95% CI 26.33-99.22; P=.002), systolic BP reduction (adjusted mean difference 4.11, 95% CI 0.11-8.28; P=.046), IPAQ score (adjusted mean difference 658.96, 95% CI 159.23-1158.69; P=.011), exercise self-efficacy score (adjusted mean difference 21.71, 95% CI 13.59-29.82; P<.001), total exercise time (adjusted mean difference 98.24, 95% CI 49.39-147.08; P=.001) peak oxygen uptake (peak VO2) (adjusted mean difference 3.39, 95% CI 0.49-6.29; P=.026), and peak oxygen uptake percent predicted (peak VO2%pred) (adjusted mean difference 11.58, 95% CI 2.06-21.10; P=.021).
CONCLUSIONS: Compared with conventional exercise rehabilitation, AI-assisted remote rehabilitation was found to improve exercise capacity, boost regular physical activity and exercise self-efficacy, and aid in systolic BP control among patients with hypertension. This study positioned AI-assisted rehabilitation as a scalable and effective strategy for real-world hypertension management. It further contributes actionable guidance for developing effective home-based exercise strategies tailored to populations with hypertension.
TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2300076451; https://www.chictr.org.cn/showproj.html?proj=208353.
Author: [‘Yao Q’, ‘Qiu B’, ‘He L’, ‘Wang Q’, ‘Zou J’, ‘Liang D’, ‘Wen S’, ‘Liu Y’, ‘Li G’, ‘Hu J’, ‘Ma H’, ‘Huang G’, ‘Zeng Q’]
Journal: J Med Internet Res
Citation: Yao Q, et al. Effects of Artificial Intelligence Recognition-Based Telerehabilitation on Exercise Capacity in Patients With Hypertension: Randomized Controlled Trial. Effects of Artificial Intelligence Recognition-Based Telerehabilitation on Exercise Capacity in Patients With Hypertension: Randomized Controlled Trial. 2026; 28:e81400. doi: 10.2196/81400