基于sEMG信号的人体下肢空间运动意图识别
Research on the Method of Human Lower Limb Spatial Movement Intention Recognition Based on sEMG Signals
邹锋 1胡庆龙 2赵祥欣 1张敏 1冯永飞2
作者信息
- 1. 浙江药科职业大学 医疗器械学院,浙江宁波 315500
- 2. 宁波大学 机械工程与力学学院,浙江宁波 315211
- 折叠
摘要
在目前的下肢康复机器人研究领域中,绝大多数研究集中在矢状面内的运动康复,而缺乏有效识别人体下肢在多维空间中运动意图识别方法.首先设计并研制了一种能够模拟多维空间运动的新型下肢康复训练机构.在此基础上,对下肢肌肉分布与运动模式进行了深入的分析,结合sEMG信号与创新的非洲秃鹫优化算法进行运动意图的分类,开发了一种新型的下肢空间运动意图识别算法.最后,通过实验验证了该算法在识别多维空间运动意图方面的有效性.本研究的成果不仅为未来下肢康复机器人的主动控制策略提供了坚实的理论基础,同时也开辟了康复机器人在多维空间运动控制方面的新视野.
Abstract
In the current field of research on lower limb rehabilitation robots,the majority of studies focus on the rehabilitation of movements within the sagittal plane,with a lack of effective methods for recognizing the intentions of human lower limb movements in multi-dimensional space.This paper first designs and develops a new type of lower limb rehabilitation training mechanism capable of simulating movements in multi-dimensional space.Based on this,an in-depth analysis of the distribution of lower limb muscles and movement pattems is conducted.By combining sEMG signals with the innovative African vulture optimization algorithm,a new type of spatial movement intention recognition algorithm for lower limbs is developed.Finally,the effectiveness of this algorithm in recognizing multi-dimensional spatial movement intentions is validated by experiments.The results of this study not only provide a solid theoretical foundation for future active control strategies of lower limb rehabilitation robots but also open up new perspectives in the control of multi-dimensional spatial movements for rehabilitation robots.
关键词
康复机器人/下肢空间运动/运动意图识别/主动控制策略Key words
rehabilitation robot/lower limb spatial movement/movement intention recognition/active control strategy引用本文复制引用
出版年
2024
NETL
NSTL
万方数据