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Related Experiment Video

Updated: Apr 5, 2026

Mobile Game-based Virtual Reality Program for Upper Extremity Stroke Rehabilitation
05:52

Mobile Game-based Virtual Reality Program for Upper Extremity Stroke Rehabilitation

Published on: March 8, 2018

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Developing movement therapy application with Microsoft Kinect control for supporting stroke rehabilitation.

Flavian A Mintal1, Veronika Szucs2, Cecília Sik-Lanyi3

  • 1m.flavian@gmail.com, University of Pannonia, Egyetem str. 10. Veszprém, Hungary.

Studies in Health Technology and Informatics
|August 22, 2015
PubMed
Summary

This study developed a novel application for stroke patient rehabilitation, utilizing real-time gesture analysis for personalized movement therapy. The software enhances the rehabilitation process through adaptive exercises and a user-friendly interface.

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Area of Science:

  • Rehabilitation Medicine
  • Biomedical Engineering
  • Human-Computer Interaction

Background:

  • Stroke rehabilitation often requires personalized therapy to address individual patient needs.
  • Existing medical devices may lack advanced, real-time motion analysis capabilities.
  • Developing adaptive and engaging therapeutic tools is crucial for improving patient outcomes.

Purpose of the Study:

  • To create an innovative application for movement therapy to aid stroke patient rehabilitation.
  • To integrate a real-time, location-based gesture analyzing algorithm into a rehabilitation tool.
  • To design a user-friendly interface for personalized exercise delivery.

Main Methods:

  • Development of a rehabilitation application using C# and WPF technology.
  • Implementation of a real-time, location-based gesture analyzing algorithm.
  • Utilizing data from a Kinect sensor for motion tracking and analysis.

Main Results:

  • The developed software demonstrated suitability for improving the stroke rehabilitation process.
  • The real-time gesture analyzing algorithm functions effectively in the background.
  • A simple and intuitive user interface was successfully created.

Conclusions:

  • The application offers a promising approach to personalized stroke rehabilitation.
  • The integration of advanced gesture analysis in medical devices can enhance therapeutic effectiveness.
  • The developed software provides a foundation for future advancements in digital rehabilitation tools.