Examination of a muscular activity estimation model using a Bayesian network for the influence of an ankle foot orthosis

Jun Inoue, Kazuya Kawamura, Masakatsu G. Fujie

    研究成果: Conference contribution

    抜粋

    In the present paper, we examine the appropriateness of a new model to examine the activity of the foot in gait. We developed an estimation model for foot-ankle muscular activity in the design of an ankle-foot orthosis by means of a statistical method. We chose three muscles for measuring muscular activity and built a Bayesian network model [1] to confirm the appropriateness of the estimation model. We experimentally examined the normal gait of a non-disabled subject. We measured the muscular activity of the lower foot muscles using electromyography, the joint angles, and the pressure on each part of the sole. From these data, we obtained the causal relationship at every 10% level for these factors and built models for the stance phase, control term, and propulsive term. Our model has three advantages. First, it can express the influences that change during gait because we use 10% level nodes for each factor. Second, it can express the influences of factors that differ for low and high muscular-activity levels. Third, we created divided models that are able to reflect the actual features of gait. In evaluating the new model, we confirmed it is able to estimate all muscular activity level with an accuracy of over 90%.

    元の言語English
    ホスト出版物のタイトルProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
    ページ6446-6450
    ページ数5
    DOI
    出版物ステータスPublished - 2012
    イベント34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA
    継続期間: 2012 8 282012 9 1

    Other

    Other34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
    San Diego, CA
    期間12/8/2812/9/1

      フィンガープリント

    ASJC Scopus subject areas

    • Computer Vision and Pattern Recognition
    • Signal Processing
    • Biomedical Engineering
    • Health Informatics

    これを引用

    Inoue, J., Kawamura, K., & Fujie, M. G. (2012). Examination of a muscular activity estimation model using a Bayesian network for the influence of an ankle foot orthosis. : Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 6446-6450). [6347470] https://doi.org/10.1109/EMBC.2012.6347470