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Virtual reality system based on Kinect for the elderly in fall prevention.

W-M Hsieh1, C-C Chen2, S-C Wang3

  • 1Department of Electronic Engineering and Graduate Institute of Computer and Communication Engineering, National Taipei University of Technology, Taipei, Taiwan Department of Electronic Engineering, Hwa Hsia Institute of Technology, Taipei, Taiwan.

Technology and Health Care : Official Journal of the European Society for Engineering and Medicine
|December 24, 2013
PubMed
Summary

This study introduces an interactive platform using Kinect and virtual reality for balance training. The system effectively improved balance and prevented falls in the elderly through engaging, game-like exercises.

Keywords:
BalanceKinectfallinformation platformvirtual reality

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Area of Science:

  • Gerontology and Rehabilitation Engineering
  • Human-Computer Interaction
  • Biomedical Signal Processing

Background:

  • Balance ability is crucial for daily movements, body stability, and overall physical function.
  • Effective balance training is essential across all age groups, particularly for the elderly.
  • Traditional balance training can be tedious, potentially limiting engagement and results.

Purpose of the Study:

  • To develop an interactive information platform combining Kinect and virtual reality for balance training and evaluation.
  • To integrate real-time monitoring of physiological data (SpO2, pulse rate) and performance metrics (velocity, reaction time) during training.
  • To enhance elderly physical function through engaging and effective balance exercises.

Main Methods:

  • Designed a platform with interactive scenarios based on balance ability indicators.
  • Incorporated game-like exercises to increase user engagement and motivation.
  • Utilized Kinect and virtual reality for immersive and dynamic training experiences.

Main Results:

  • The platform successfully collected and analyzed real-time data (SpO2, pulse rate, velocity, reaction time) for performance evaluation.
  • Balance assessment scale testing (BBS, TUG) showed significant improvement in the experimental group compared to the control group (P < 0.01).
  • Demonstrated a noninvasive, unconstrained method for monitoring physiological responses during exercise.

Conclusions:

  • The developed information platform effectively enhances balance ability and meets practical needs for elderly physical function training.
  • Game-like exercises significantly improve balance and contribute to fall prevention.
  • The platform provides valuable data for evaluating training effectiveness and planning future interventions.