The objective of this study is to develop an estimation model of foot-ankle muscular activity for designing an ankle-foot orthosis with a training function. We built a Bayesian network model  and chose three muscles to confirm its effectiveness. Such a model needs to include all factors affecting the gait, for example, speed reflex movements, joint angles and so forth. In an experiment, we examined the normal gait of a non-disabled subject. We measured the muscular activity of the lower foot muscles by electromyography, the joint angles by using statistical methods, and the sole pressure on each part of the sole. From this data, we obtained the causal relationship at every 10% level of these factors. Our model has three advantages. First, it can express the influences, which change throughout the gait, because we use 10% level nodes of each factor. Second, it can express the influences of factors, which are different for low and high muscular activity levels. Last, the model can compensate the missed estimations by estimating every 10% level muscle activity. In an evaluation of this model, we confirmed that this model can estimate all muscular activity level with an accuracy rate greater than 90%.
|ホスト出版物のタイトル||Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics|
|出版ステータス||Published - 2012|
|イベント||2012 4th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2012 - Rome|
継続期間: 2012 6月 24 → 2012 6月 27
|Other||2012 4th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2012|
|Period||12/6/24 → 12/6/27|
ASJC Scopus subject areas