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The Effect of Fashion Model Walking Program Using Kinect on the Movement Activity of the Elderly

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HCI International 2023 – Late Breaking Papers (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14055))

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Abstract

The purpose of this study is to implement a walking program for the elderly by applying fashion model walking using Kinect. The skeleton through the avatar of the model walking that appears on the screen is given as feedback to the participant. The given information is implemented using Kinect, and the game proceeds with accurate gait balance control and the angle of the spine, which is the center of the body, in the walking program according to the body balance. Joint Value Using Unity 3D’s human pose library, Kinect modeling where 21 values ​​out of a total of 95 joint values ​​are presented. It is a game-type program in which the score of the spine angle and joint value is also lowered if the center of gravity of the body is not accurately displayed in the gait motion. Walking (right, left), turn (half, full turn, right, left respectively), pose (right center pose, left center pose) motion animations were filmed in real time. The walking motion appeared at normal speed only up to the step divided into two steps. When working with turns, full turns tended to be much more difficult than half turns. However, as the number of exercises increased, the degree of agreement between the angle of the spinal axis and the angle of the joints improved. In other words, the higher score that appears through the game format improves the control of walking balance and body balance, and the lower the accuracy of the body balance, the lower the score. This research program can be used as rehabilitation exercise for people with developmental disabilities, elderly people with dementia, and patients with Alzheimer’s disease.

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Correspondence to SungHee Hong .

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Hong, S., Park, S., Jung, S. (2023). The Effect of Fashion Model Walking Program Using Kinect on the Movement Activity of the Elderly. In: Gao, Q., Zhou, J., Duffy, V.G., Antona, M., Stephanidis, C. (eds) HCI International 2023 – Late Breaking Papers. HCII 2023. Lecture Notes in Computer Science, vol 14055. Springer, Cham. https://doi.org/10.1007/978-3-031-48041-6_5

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  • DOI: https://doi.org/10.1007/978-3-031-48041-6_5

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