Monitoring Respiratory Rehabilitation with YOLO Pose: Usability and Accuracy Assessment of a Mobile App for Spirometer Tracking
Year: 2025
Type: book-chapter
Abstract: 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.
DOI: 10.3233/shti250189
Authors: Davide Ferrari, Pietro Belotti, Andrea Forcella, Lorenzo Lecchi, Nicola Sana, Silvia Mariani, Giovanni Marchetto, Andrea Vitali
Institution: University of Bergamo
Language: English
Subfield: General Health Professions
Field: Health Professions
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4409773140