Locomotion mode recognition method based on inertial measurement units in exoskeleton robot

Binfeng Wang; Jianbin Zheng; Yifan Gao; Yu Wang; Guanghai Wu

doi:10.1117/12.2659268

23 November 2022 Locomotion mode recognition method based on inertial measurement units in exoskeleton robot

Binfeng Wang, Jianbin Zheng, Yifan Gao, Yu Wang, Guanghai Wu

Proceedings Volume 12454, International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022); 1245411 (2022) https://doi.org/10.1117/12.2659268
Event: International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022), 2022, Hohhot, China

Abstract

The lower limb exoskeleton robot is a wearable device that enhances the movement ability of human lower extremities. Locomotion mode recognition is an important prerequisite for controlling the lower limb exoskeleton robot. This proposed paper demonstrates a method of locomotion mode recognition of the lower limb exoskeleton robot based on residual networks. This article studies five common locomotion modes, including level ground walking, stair ascending, stair descending, ramp ascending and ramp descending. We collect locomotion data from 5 subjects using a set of 4 inertial sensors for 5 lower limb locomotion modes of different specificities. The residual network based hierarchical classifier is trained to classify the modes into a specified label hierarchy. The residual network can automatically learn mixed features without the participation of experts, avoiding manual feature extraction. It is noticeable to solve the degradation question and alleviate the problem of gradient disappearance. Some comparative experiments carried out on the selection of hyperparameters applied to optimize the residual network structure proposed. The results show that the average recognition rate reaches 96.95%, which has a prominent recognition effect on locomotion mode recognition.

Citation Download Citation

Binfeng Wang, Jianbin Zheng, Yifan Gao, Yu Wang, and Guanghai Wu "Locomotion mode recognition method based on inertial measurement units in exoskeleton robot", Proc. SPIE 12454, International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022), 1245411 (23 November 2022); https://doi.org/10.1117/12.2659268

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