Effects of Artificial Intelligence Recognition-Based Telerehabilitation on Exercise Capacity in Patients With...

Area of Science:

• Cardiovascular Medicine
• Digital Health
• Rehabilitation Science

Background:

• Hypertension poses significant global mortality risks, with conventional exercise therapy facing adherence challenges.
• Artificial intelligence (AI)-assisted remote rehabilitation offers personalized monitoring and guidance, but requires validation.
• This study systematically evaluated the clinical benefits of AI-assisted telerehabilitation for hypertension.

Purpose of the Study:

• To assess the efficacy of an 8-week AI-assisted telerehabilitation program in improving exercise capacity and health outcomes for hypertension patients.
• To compare AI-assisted telerehabilitation with conventional offline exercise guidance.

Main Methods:

• A prospective, randomized controlled trial involving 62 adult hypertension patients (aged 18-75).
• Participants were randomized to AI-assisted telerehabilitation or conventional exercise guidance for 8 weeks.
• Primary outcome was the change in 6-minute walk distance (6MWD); secondary outcomes included blood pressure, exercise capacity (peak VO2), and self-efficacy.

Main Results:

• No serious adverse events were reported with AI-assisted telerehabilitation.
• The AI group showed significantly greater improvements in 6MWD, systolic blood pressure reduction, and exercise self-efficacy.
• Significant improvements were also observed in physical activity levels (IPAQ), total exercise time, and peak oxygen uptake (peak VO2).

Conclusions:

• AI-assisted remote rehabilitation enhances exercise capacity, physical activity, and self-efficacy in hypertension patients.
• It demonstrates effectiveness in systolic blood pressure control compared to conventional methods.
• AI rehabilitation presents a scalable, effective strategy for home-based hypertension management.