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Improving patient rehabilitation performance in exercise games using collaborative filtering approach.

Waidah Ismail1,2, Ismail Ahmed Al-Qasem Al-Hadi1,3, Crina Grosan4

  • 1Faculty of Science and Technology, Universiti Sains Islam Malaysia, Nilai, Negeri Sembilan, Malaysia.

Peerj. Computer Science
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Summary

A new recommender system, ReComS++, accurately suggests virtual reality exergame settings to optimize rehabilitation for patients with disabilities. This system improves movement performance by personalizing game difficulty based on patient history.

Keywords:
Collaborative filteringExercise gamesRehabilitation

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Area of Science:

  • Rehabilitation medicine
  • Human-computer interaction
  • Artificial intelligence

Background:

  • Virtual reality (VR) exergames aid patients with disabilities in improving limb movement.
  • Exergame settings significantly impact rehabilitation outcomes and data accuracy.
  • Suboptimal settings can hinder expected improvements in patient performance.

Purpose of the Study:

  • To develop and evaluate a recommender system (ResComS) for personalized exergame settings.
  • To optimize patient rehabilitation by suggesting the most suitable movement settings.
  • To enhance the accuracy of rehabilitation results through tailored game parameters.

Main Methods:

  • Proposed three recommender system methods: ReComS, ReComS+, and ReComS++.
  • Employed K-nearest neighbours, collaborative filtering, k-means, and bacterial foraging optimisation algorithms.
  • Utilized the Medical Interactive Recovery Assistant (MIRA) software platform for data collection.

Main Results:

  • The ReComS++ approach demonstrated superior performance in predicting optimal exergame settings.
  • The system achieved an accuracy of 85.76% in predicting the best settings for patients.
  • Patient exergame performances validated the effectiveness of the recommended settings.

Conclusions:

  • The developed recommender system, particularly ReComS++, effectively personalizes VR exergame settings.
  • Accurate setting recommendations can significantly improve rehabilitation outcomes for patients with disabilities.
  • This approach offers a promising method for enhancing the efficacy of VR-based physical therapy.