Abstract
Falls often cause bone fractures and are a typical risk factor for older people to become hospitalized or bedridden and require nursing care. Since the risk of falls increases due to a complex combination of physical and environmental factors, it is essential to examine the physical characteristics of the individuals and the characteristics of the environment in which they interact with. However, the risk of falls has not been quantified in environments where falls frequently occur, and moreover, the association of fall risk with physical factors remains unclear. Meanwhile, handrails and other devices are sometimes installed in buildings to prevent falls, but it is not easy for older adults and their caregivers to grasp the necessity and criteria for installing such devices. In this paper, our goal is to develop a smartphone application for augmented reality (AR) superimposition of fall prevention measures within the real-life environment of a house. This article reports on the current development progress of a prototype for the application.
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This work was supported by SECOM Foundation and JSPS KAKENHI Grant Numbers JP20K20494, JP21H04580, and JP21H00915.
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Miura, T. et al. (2023). Augmented Reality (AR) Application Superimposing the Falling Risks of Older Adults in Residential Settings and Coping Strategies: Building an Image-Based Scene Detection Model. 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_9
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