From Therapeutic Exercise Guidelines to Adherence-Aware mHealth Systems: A Modeling Framework with Cloud and...

Area of Science:

• Digital Health
• Exercise Science
• Health Informatics

Background:

• World Health Organization emphasizes physical activity for noncommunicable disease prevention and management.
• Therapeutic exercise guidelines offer structured recommendations but lack digital integration.
• Current mobile health apps offer generic tracking, not formalizing exercise prescriptions or adherence.

Purpose of the Study:

• To propose a modeling framework for translating Frequency-Intensity-Time-Type (FITT)-based therapeutic exercise guidelines into computable protocols.
• To develop measurable adherence indicators for personalized exercise prescriptions.
• To create an explainability module for interpretable feedback on exercise adherence.

Main Methods:

• Developed a protocol formalization layer to encode guideline parameters as structured data.
• Introduced an adherence modeling mechanism to define compliance metrics.
• Integrated an AI-assisted natural language generation module for user feedback.

Main Results:

• Successfully translated FITT-based guidelines into computable protocol structures.
• Enabled quantification of adherence beyond simple activity completion.
• Demonstrated a functional mobile application prototype operationalizing the framework.

Conclusions:

• The proposed framework effectively integrates therapeutic exercise guidelines into digital health systems.
• This approach enhances personalized exercise prescription and adherence monitoring.
• It paves the way for more effective digital interventions in chronic disease management.