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This paper is in the following e-collection/theme issue:

Technology in Physiotherapy (211) Emerging Technologies for Rehabilitation (380) Innovations in Exercise Rehabilitation (310)

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

Authors of this article:

Vassilios Tsakanikas1 Author Orcid Image ;   Dimitris Gatsios1 Author Orcid Image ;   Athanasios Pardalis1 Author Orcid Image ;   Kostas M Tsiouris1 Author Orcid Image ;   Eleni Georga1 Author Orcid Image ;   Doris-Eva Bamiou2, 3 Author Orcid Image ;   Marousa Pavlou4 Author Orcid Image ;   Christos Nikitas5 Author Orcid Image ;   Dimitrios Kikidis5 Author Orcid Image ;   Isabelle Walz6 Author Orcid Image ;   Christoph Maurer6 Author Orcid Image ;   Dimitrios Fotiadis1, 7 Author Orcid Image
Article Authors Cited by (7) Tweetations (4) Metrics

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;23(1) View
  3. Peng X, Mao X, Fang X. Human pose recognition and automated scoring detection for sports rehabilitation. Scientific Reports 2026 View
  4. Qiao Y, Wang Z. Real-time rehabilitation assessment and corrective guidance driven by dual regulation pose analysis. Applied Intelligence 2026;56(5) 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
  3. Boucharas D, Kotoulas G, Nikitas C, Tassi S, Karapintzou E, Pardalis A, Maglaras K, Tsakanikas V, Iliadou E, Tsoukatos M, Papadopoulou S, Rentoumis A, Arkoumanis I, Fostiropoulos I, Fotiadis D. 2025 IEEE 25th International Conference on Bioinformatics and Bioengineering (BIBE). From Falls to Confidence: Assessing HOLOBALANCE's Impact and Predictive AI Models on Fear of Falling View