Continuous Human Gait Phase Estimation Considering Individual Diversity | |
Zhang, Xingxuan1,2; Zhang, Haojian2; Hu, Jianhua2; Wang, Yunkuan2 | |
2023-09-29 | |
会议日期 | 26-27 August 2023 |
会议地点 | Hangzhou, China |
关键词 | Gait phase estimation hip exoskeleton dynamic time warping neural network |
英文摘要 | Accurate identification of human motion state is of great significance for exoskeleton robots to provide appropriate auxiliary torque. Previous work generated exoskeleton assist torque by recognizing the phase of the human gait. However, they set the gait phase to increase linearity throughout the gait cycle and then reset to 0 at the end, without taking into account the diversity of human gait. Different individuals exhibit varying gait characteristics, even the same person may walk with different gaits under distinct situations, such as speed and slope. To address this issue, we propose a novel gait phase coding method based on dynamic time warping (DTW), which can generate differentiated phases according to different gaits. Additionally, we introduce a long short-term memory (LSTM)-based gait phase estimation method. Our experimental results demonstrate that the proposed method achieves satisfactory performance. |
语种 | 英语 |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/54519] |
专题 | 中科院工业视觉智能装备工程实验室 |
通讯作者 | Wang, Yunkuan |
作者单位 | 1.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China 2.Institute of Automation, Chinese Academy of Sciences, Beijing, China |
推荐引用方式 GB/T 7714 | Zhang, Xingxuan,Zhang, Haojian,Hu, Jianhua,et al. Continuous Human Gait Phase Estimation Considering Individual Diversity[C]. 见:. Hangzhou, China. 26-27 August 2023. |
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