Research for JYU: An AI-Driven, Fully Remote Mobile Application for Functional Exercise Testing

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Cronin, N
Lehtiö, A
Talaskivi, J
Griffith University Author(s)
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Särestöniemi, Mariella

Keikhosrokiani, Pantea

Singh, Daljeet

Harjula, Erkki

Tiulpin, Aleksei

Jansson, Miia

Isomursu, Minna

van Gils, Mark

Saarakkala, Simo

Reponen, Jarmo

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Oulu, Finland


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.

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Digital Health and Wireless Solutions: First Nordic Conference​, NCDHWS 2024, Oulu, Finland, May 7–8, 2024, Proceedings, Part II

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© The Author(s) 2024. Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

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Cronin, N; Lehtiö, A; Talaskivi, J, Research for JYU: An AI-Driven, Fully Remote Mobile Application for Functional Exercise Testing, Communications in Computer and Information Science, 2024, 2084, pp. 279-287