Interaction Design of Fall Detection Camera in Smart Home Care Scenario

被引：0
|
作者：
Zhang W. [1 ,2 ]
Jin T. [3 ]
Sun T. [1 ,2 ]
Huang Y. [4 ]
Gao X. [5 ]
Jeung J. [2 ]
机构：
[1] Academy of Arts & Design, Tsinghua University, Beijing
[2] The Future Laboratory, Tsinghua University, Beijing
[3] School of Mechanical Engineering and Automation, Beihang University, Beijing
[4] Information Hub, The Hong Kong University of Science and Technology (GZ), Guangzhou
[5] School of Innovation Design, Guangzhou Academy of Fine Arts, Guangzhou
来源：
Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics | 2023年 / 35卷 / 02期
关键词：
fall detection; interaction design; older adults; smart home camera;
D O I：
10.3724/SP.J.1089.2023.20050
中图分类号：
学科分类号：
摘要：
Indoor falls and related injuries have been major health threats for older adults. To better support seniors living independently at home, the study proposed an interaction design solution for fall detection cameras in smart homecare scenarios. In this paper, we conducted an offline survey of older adults (n=422) in six cities across China and a scenario-based participatory design workshop (n=6), in order to explore their needs and preferences for fall detection camera functionality and interaction. The research concluded that older adults prefer multi-modal interaction design combining voice and GUI through the thematic analysis method. Based on optimization suggestions for the rescue process and functional demands from older participants, we enriched the features of smart home cameras, such as preset basic disease information and data sharing with doctors. Finally, according to the research results, we designed the interaction process and GUI interface of the camera based on the platform of the WeChat mini program, to provide reference for related studies. © 2023 Institute of Computing Technology. All rights reserved.
引用
收藏
页码：238 / 247
页数：9
相关论文
共 32 条
  • [1] Liu Xia, Construction of healthy elderly care service system from the perspective of smart community elderly care, Chinese Journal of Gerontology, 38, 7, pp. 1743-1745, (2018)
  • [2] Jaschinski C, Ben Allouch S, Peters O, Et al., The influence of privacy on the acceptance of technologies for assisted living, International Conference on Human-Computer Interaction, pp. 463-473, (2020)
  • [3] Ye P P, Er Y L, Wang H D, Et al., Burden of falls among people aged 60 years and older in mainland China, 1990-2019: findings from the Global Burden of Disease Study 2019, The Lancet Public Health, 6, 12, pp. e907-e918, (2021)
  • [4] The action plan for development of the smart health and elderly care industry(2021-2025), Ministry of Industry and Information Technology Electronic Letter, (2021)
  • [5] Hu Lisha, Wang Suzhen, Chen Yiqiang, Et al., Fall detection algorithms based on wearable device: a review, Journal of Zhejiang University: Engineering Science, 52, 9, pp. 1717-1728, (2018)
  • [6] Shi Xin, Xiong Qingyu, Lei Luning, Research on fall detection system based on pressure sensor, Chinese Journal of Scientific Instrument, 31, 3, pp. 715-720, (2010)
  • [7] Shen Bingqian, Wu Zhiyong, He Qianhua, Et al., Falling detection method based on human body posture judgment, Journal of Computer Applications, 34, pp. 223-227, (2014)
  • [8] Yuan Zhian, Zhou Xiaoyu, Liu Xinpu, Et al., Human fall detection method using millimeter-wave radar based on RDSNet, Journal of Radars, 10, 4, pp. 656-664, (2021)
  • [9] Wust K L, Carayon P, Werner N E, Et al., Older adult patients and care partners as knowledge brokers in fragmented health care, Human Factors, (2022)
  • [10] Sui Dangchen, Peng Qingchao, Constructing basic analysis about the “Internet + community home-based care” service model in China’s city, Social Security Studies, 3, pp. 18-26, (2017)
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