Gait Phase Estimation Based on User–Walker Interaction Force

Applied Sciences

Mayu Yokoya¹  Kazunori Yamada¹  Yasuhiro Akiyama²  Pengcheng Li²  Yoji Yamada²  Xianglong Wan³ 

[1] Business Innovation Division, Panasonic Corp., Oaza Kadoma, Kadoma-shi, Osaka 571-8501, Japan;Department of Mechanical System Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan;School of Automation and Electrical Engineering, University of Science and Technology Beijing, 30 Xueyuan Road, Haidian District, Beijing 100083, China;

关键词: smart walker;    gait phase estimation;    adaptive control;    switching mechanism;   

DOI  :  10.3390/app11177888

来源: DOAJ

【 摘 要 】

Smart walkers have been developed for assistance and rehabilitation of elderly people and patients with physical health conditions. A force sensor mounted under the handle is widely used in smart walkers to establish a human–machine interface. The interaction force can be used to control the walker and estimate gait parameters using methods such as the Kalman filter for real-time estimation. However, the estimation performance decreases when the peaks of the interaction force are not captured. To improve the stability and accuracy of gait parameter estimation, we propose an online estimation method to continuously estimate the gait phase and cadence. A multiple model switching mechanism is introduced to improve the estimation performance when gait is asymmetric, and an adaptive rule is proposed to improve the estimation robustness and accuracy. Simulations and experiments demonstrate the effectiveness and accuracy of the proposed gait parameter estimation method. Here, the average estimation error for the gait phase is 0.691 rad when the gait is symmetric and 0.722 rad when it is asymmetric.

【 授权许可】

Unknown