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

Meiling Chen, Qingfeng Tang, Shoujiang Xu, Pengfei Leng and Zhigeng Pan
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Meiling Chen: School of Health Management, Hangzhou Normal University, Hangzhou 310036, China
Qingfeng Tang: School of Health Management, Hangzhou Normal University, Hangzhou 310036, 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

IJERPH, 2020, vol. 17, issue 19, 1-10

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.

Keywords: fall risk; augmented reality; exergame; cognitive–motor intervention; UEQ-S; user experience (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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