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Related Experiment Video

Updated: Jul 4, 2026

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

Published on: April 19, 2019

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

Vassiliki Koufi¹

¹Department of Digital Systems, University of Piraeus, Greece.

Studies in Health Technology and Informatics

|July 3, 2026

Summary

This study introduces a new framework to make therapeutic exercise guidelines computable for digital health systems. It enhances mobile apps to track adherence to personalized exercise protocols, improving chronic disease management.

Keywords:

adherence modeling cloud-based architecture explainable AI mHealth therapeutic exercise

Related Experiment Videos

Last Updated: Jul 4, 2026

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

Published on: April 19, 2019

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.