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Background:
Adherence to home-based respiratory rehabilitation is a significant challenge for cardiac surgery patients. Few studies have attempted to address this problem.
Methods:
This research introduces a digital solution to improve adherence to respiratory rehabilitation by offering virtual supervision. It leverages the YOLOv11 pose detection algorithm to track the Voldyne® 2500 incentive spirometer and monitor rehabilitation sessions. Usability and accuracy were evaluated with nine healthy volunteers, combining objective performance metrics with the System Usability Scale (SUS) survey.
Results:
The models demonstrated high accuracy in spirometer tracking and efficient inference times. The app achieved an average SUS score of 83%, indicating good usability, though refinements to the monitoring algorithms are recommended.
Conclusion:
This low-cost, non-invasive solution shows potential for clinical use. Future efforts will focus on enhancing usability and accuracy to prepare the app for clinical trials.
