Analysis of body pressure distribution on car seats by using deep learning

Reiko Mitsuya, Kazuhito Kato, Nei Kou, Takeshi Nakamura, Kohei Sugawara, Hiroki Dobashi, Takuro Sugita, Takashi Kawai

    Research output: Contribution to journalArticle

    Abstract

    This study aimed to extract information from body pressure distribution, including comfort, participant body size, and seat characteristics by using supervised deep learning, and body pressure characteristics corresponding to sensory evaluation by using unsupervised deep learning. Body pressure data of 18 participants and 19 kinds of car seats were used for the analysis. Sensory evaluation of 9 items concerning cushion characteristics and seat comfort was conducted. From the analysis, we determined that body size and car seats could be classified with high precision by using body pressure distribution data. For the sensory evaluation items, the correct answer rate was high. By examining the importance of the cells of the mat, the features of the body pressure mat at the seat cushion and backrest, body size, car seat, and parts related to sensory evaluation could be determined in detail. The study findings can be applied in the development of car seats.

    Original languageEnglish
    Pages (from-to)283-287
    Number of pages5
    JournalApplied Ergonomics
    Volume75
    DOIs
    Publication statusPublished - 2019 Feb 1

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    Keywords

    • Body pressure distribution
    • Car seat
    • Characteristics extraction
    • Deep learning
    • Machine learning
    • Support vector machine

    ASJC Scopus subject areas

    • Human Factors and Ergonomics
    • Physical Therapy, Sports Therapy and Rehabilitation
    • Safety, Risk, Reliability and Quality
    • Engineering (miscellaneous)

    Cite this

    Mitsuya, R., Kato, K., Kou, N., Nakamura, T., Sugawara, K., Dobashi, H., Sugita, T., & Kawai, T. (2019). Analysis of body pressure distribution on car seats by using deep learning. Applied Ergonomics, 75, 283-287. https://doi.org/10.1016/j.apergo.2018.08.023