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Design and Evaluation of an Augmented Reality-Based Exergame System to Reduce Fall Risk in the Elderly

Author

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  • Meiling Chen

    (School of Health Management, Hangzhou Normal University, Hangzhou 310036, China
    School of Humanity and Management, Zhejiang Chinese Medical University, Hangzhou 310053, China)

  • Qingfeng Tang

    (School of Health Management, Hangzhou Normal University, Hangzhou 310036, China
    The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, Anqing 246011, China)

  • Shoujiang Xu

    (School of Health Management, Hangzhou Normal University, Hangzhou 310036, China)

  • Pengfei Leng

    (School of Health Management, Hangzhou Normal University, Hangzhou 310036, China)

  • Zhigeng Pan

    (Institute of VR and Intelligent System, Hangzhou Normal University, Hangzhou 310036, China)

Abstract

Falls are a major public health concern in today’s aging society. Virtual reality (VR) technology is a promising method for reducing fall risk. However, the absence of representations of the user’s body in a VR environment lessens the spatial sense of presence. In terms of user experience, augmented reality (AR) can provide a higher degree of presence and embodiment than VR. We developed an AR-based exergame system that is specifically designed for the elderly to reduce fall risk. Kinect2.0 was used to capture and generate 3D models of the elderly and immerse them in an interactive virtual environment. The software included three functional modules: fall risk assessment, cognitive–motor intervention (CMI) training, and training feedback. The User Experience Questionnaire (UEQ-S) was used to evaluate user experience. Twenty-five elders were enrolled in the study. It was shown that the average scores for each aspect were: pragmatic quality score (1.652 ± 0.868); hedonic quality score (1.880 ± 0.962); and overall score was 1.776 ± 0.819. The overall score was higher than 0.8, which means that the system exhibited a positive user experience. After comparing the average score in a dataset product of UEQ-S Data Analysis Tool, it was found that the pragmatic quality aspect was categorized as good, while the hedonic quality aspect was categorized as excellent. It revealed a positive evaluation from users.

Suggested Citation

  • Meiling Chen & Qingfeng Tang & Shoujiang Xu & Pengfei Leng & Zhigeng Pan, 2020. "Design and Evaluation of an Augmented Reality-Based Exergame System to Reduce Fall Risk in the Elderly," IJERPH, MDPI, vol. 17(19), pages 1-10, October.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:19:p:7208-:d:422817
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    Cited by:

    1. Chen-Yi Song & Jau-Yih Tsauo & Pei-Hsin Fang & I-Yao Fang & Shao-Hsi Chang, 2021. "Physical Fitness among Community-Dwelling Older Women with and without Risk of Falling—The Taipei Study, Taiwan," IJERPH, MDPI, vol. 18(14), pages 1-8, July.

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