Research for JYU : An AI-Driven, Fully Remote Mobile Application for Functional Exercise Testing
Abstract
As people live longer, the incidence and severity of health problems increases, placing strain on healthcare systems. There is an urgent need for resource-wise approaches to healthcare. We present a system built using open-source tools that allows health and functional capacity data to be collected remotely. The app records performance on functional tests using the phone’s built-in camera and provides users with immediate feedback. Pose estimation is used to detect the user in the video. The x, y coordinates of key body landmarks are then used to compute further metrics such as joint angles and repetition durations. In a proof-of-concept study, we collected data from 13 patients who had recently undergone knee ligament or knee replacement surgery. Patients performed the sit-to-stand test twice, with an average difference in test duration of 1.12 s (range: 1.16–3.2 s). Y-coordinate locations allowed us to automatically identify repetition start and end times, while x, y coordinates were used to compute joint angles, a common rehabilitation outcome variable. Mean difference in repetition duration was 0.1 s (range: −0.4–0.4 s) between trials 1 and 2. Bland-Altman plots confirmed general test-retest consistency within participants. We present a mobile app that enables functional tests to be performed remotely and without supervision. We also demonstrate real-world feasibility, including the ability to automate the entire process, from testing to analysis and the provision of real-time feedback. This approach is scalable, and could form part of national health strategies, allowing healthcare providers to minimise the need for in-person appointments whilst yielding cost savings.
Main Authors
Format
Conferences
Conference paper
Published
2024
Series
Subjects
Publication in research information system
Publisher
Springer
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202405233889Käytä tätä linkitykseen.
Parent publication ISBN
978-3-031-59090-0
Review status
Peer reviewed
ISSN
1865-0929
DOI
https://doi.org/10.1007/978-3-031-59091-7_18
Keywords
Conference
Nordic Conference on Digital Health and Wireless Solutions
Language
English
Published in
Communications in Computer and Information Science
Is part of publication
Digital Health and Wireless Solutions : First Nordic Conference, NCDHWS 2024, Oulu, Finland, May 7-8, 2024, Proceedings, Part I
Citation
- Cronin, N., Lehtiö, A., & Talaskivi, J. (2024). Research for JYU : An AI-Driven, Fully Remote Mobile Application for Functional Exercise Testing. In M. Särestöniemi, P. Keikhosrokiani, D. Singh, E. Harjula, A. Tiulpin, M. Jansson, M. Isomursu, M. van Gils, S. Saarakkala, & J. Reponen (Eds.), Digital Health and Wireless Solutions : First Nordic Conference, NCDHWS 2024, Oulu, Finland, May 7-8, 2024, Proceedings, Part I (2083, pp. 279-287). Springer. Communications in Computer and Information Science. https://doi.org/10.1007/978-3-031-59091-7_18
Copyright© 2024 the Authors