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Recognition and Analysis of an Age-Friendly Intelligent Sofa Design Based on Skeletal Key-Points

Author

Listed:
  • Chengmin Zhou

    (College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, China
    Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, Nanjing 210037, China)

  • Ting Huang

    (College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, China
    Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, Nanjing 210037, China)

  • Xin Luo

    (College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, China)

  • Jake Kaner

    (School of Art and Design, Nottingham Trent University, Nottingham NG1 4FQ, UK)

  • Xiaoman Fu

    (College of Art and Design, Nanjing Audit University Jinshen College, Nanjing 210023, China)

Abstract

The aging population has a higher level of consumption willingness, higher quality of life demands, and more diversified spiritual pursuits. In recent years, age-friendly industries have entered a ‘blue ocean of development’; intelligent recreation and age-friendly industries have become new growth points in the double-cycle situation; however, the current generalized design of the market is not enough to meet the needs of its elderly users. Through an extensive research and demand analysis focused on the highly-frequent use of sofas by elderly individuals, an AHP analysis showed that smart sofa design guidelines are among the most important functional indicators; user ‘pain points’ focused on low seat surfaces caused by the difficulty in getting up. To further refine this action behavior, a Kinect-based experimental device was used to capture the behavior of the elderly user during the sit-to-stand transition. The experimental data were collected from 25 key skeletal points in the human body and further investigated by converting the skeletal points into 12 key joint angles to refine the joint transition threshold risk during the sit-to-stand transition for the elderly user. The test results show that the most important joint angle affecting the sit-to-stand transition process is the trunk thigh angle was θ 5-2, with an important value of 0.122. The two-dimensional body data of the elderly user was mapped to the joint angles under the three-dimensional activity threshold to build a comfort model of the elderly user’s sofa, providing a theoretical basis for the design parameters of the aging sofa. In response to the research results, an intelligent age-friendly sofa with three forms was designed and prototyped independently, meeting the universal size of elderly users in terms of dimensional parameters, and iterating leisure and assisted standing transformation in terms of function (to reduce the risk levels of the sitting and standing transformations of elderly users).

Suggested Citation

  • Chengmin Zhou & Ting Huang & Xin Luo & Jake Kaner & Xiaoman Fu, 2022. "Recognition and Analysis of an Age-Friendly Intelligent Sofa Design Based on Skeletal Key-Points," IJERPH, MDPI, vol. 19(18), pages 1-21, September.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:18:p:11522-:d:913734
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    References listed on IDEAS

    as
    1. Yuan Chen & Ahmed Bouferguene & Yinghua Shen & Mohamed Al-Hussein, 2019. "Difference analysis of regional population ageing from temporal and spatial perspectives: a case study in China," Regional Studies, Taylor & Francis Journals, vol. 53(6), pages 849-860, June.
    2. Yang Cheng, Siyao Gao, Shuai Li, Yuchao Zhang and Mark Rosenberg, 2019. "Understanding the spatial disparities and vulnerability of population aging in China," Asia and the Pacific Policy Studies 201905, Crawford School of Public Policy, The Australian National University.
    3. Sonja Pedell & Ann Borda & Alen Keirnan & Nicole Aimers, 2021. "Combining the Digital, Social and Physical Layer to Create Age-Friendly Cities and Communities," IJERPH, MDPI, vol. 18(1), pages 1-14, January.
    4. Taoyuan Wei & Qin Zhu & Solveig Glomsrød, 2018. "Ageing Impact on the Economy and Emissions in China: A Global Computable General Equilibrium Analysis," Energies, MDPI, vol. 11(4), pages 1-13, April.
    5. Yang Cheng & Siyao Gao & Shuai Li & Yuchao Zhang & Mark Rosenberg, 2019. "Understanding the spatial disparities and vulnerability of population aging in China," Asia and the Pacific Policy Studies, Wiley Blackwell, vol. 6(1), pages 73-89, January.
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    Cited by:

    1. Ling Zhu & Yuqi Yan & Jiufang Lv, 2023. "A Bibliometric Analysis of Current Knowledge Structure and Research Progress Related to Sustainable Furniture Design Systems," Sustainability, MDPI, vol. 15(11), pages 1-27, May.

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