Published on in Vol 9, No 3 (2022): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37229, first published .
Automated Assessment of Balance Rehabilitation Exercises With a Data-Driven Scoring Model: Algorithm Development and Validation Study

Automated Assessment of Balance Rehabilitation Exercises With a Data-Driven Scoring Model: Algorithm Development and Validation Study

Automated Assessment of Balance Rehabilitation Exercises With a Data-Driven Scoring Model: Algorithm Development and Validation Study

Journals

  1. Modlin D, Kuo Y. The effects of using augmented reality in rehabilitation and recovery exercise on patients’ outcomes and experiences: a systematic review. Frontiers in Virtual Reality 2025;6 View
  2. Jabri S, Hauth J, DiCesare C, Carender W, Ojeda L, Wiens J, Stirling L, Huan X, Sienko K. Automatic multi-IMU-based deep learning evaluation of intensity during static standing balance training exercises. Journal of NeuroEngineering and Rehabilitation 2025 View

Conference Proceedings

  1. Karapintzou E, Tsakanikas V, Kikidis D, Nikitas C, Nairn B, Pavlou M, Bamiou D, Exarchos T, Fotiadis D. 2024 IEEE 24th International Conference on Bioinformatics and Bioengineering (BIBE). AI-Enhanced Tele-Rehabilitation: Predictive Modeling for Fall Risk and Treatment Efficacy in Balance Disorders View
  2. Boucharas D, Georgoula M, Karapintzou E, Pardalis A, Maglaras K, Tsakanikas V, Pimenta A, Agostinho C, Jardim-Goncalves R, Nikitas C, Iliadou E, Kikidis D, Fotiadis D. 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Advancing Telerehabilitation with AI: Predicting Balance Scores from Early Sessions View