AI-Driven MRF Type 2 Diabetes Integrating DHT IF and Resistance Training to OM and Functional Outcomes

AI-Driven Multimodal Rehabilitation Framework for Type 2 Diabetes Integrating Digital Health Technologies, Intermittent Fasting, and Resistance Training to Optimize Metabolic and Functional Outcomes

This randomized controlled trial aims to evaluate the effectiveness of an AI-driven multimodal rehabilitation framework combining digital health technologies, intermittent fasting, and resistance training in individuals with Type 2 Diabetes Mellitus (T2DM). The study will integrate mobile-based AI monitoring for glucose trends, physical activity tracking, and dietary adherence reminders, thereby improving patient engagement and self-management.

Participants will be randomized into two groups: the intervention group receiving AI-guided resistance training alongside intermittent fasting, and the control group receiving standard diabetes care. Outcomes will include changes in HbA1c, insulin sensitivity (HOMA-IR), muscle strength, functional mobility, and quality of life. The study will also assess adherence, feasibility, and cost-effectiveness. By utilizing AI-enabled technology and lifestyle-based interventions, this study addresses the gap between clinical management and sustainable self-care in T2DM. The framework is designed to be low-cost, scalable, and adaptable, making it suitable for resource-limited healthcare systems.

Inclusion Criteria:

• Diagnosed with Type 2 Diabetes (≥1 year)
• HbA1c between 6.5% and 9.0%
• Sedentary or low physical activity levels
• BMI: 25-35 kg/m²
• Able to perform mild-to-moderate exercise

Exclusion Criteria:

• any other disability
• not willing