机械工程学报 ›› 2019, Vol. 55 ›› Issue (11): 19-27.doi: 10.3901/JME.2019.11.019
王启宁1,2, 郑恩昊3, 许东方1, 麦金耿1
收稿日期:
2018-03-31
修回日期:
2018-11-21
出版日期:
2019-06-05
发布日期:
2019-06-05
通讯作者:
王启宁(通信作者),男,1981年出生,博士,研究员,博士研究生导师。主要研究方向为智能机器人和康复工程。E-mail:qiningwang@pku.edu.cn
作者简介:
郑恩昊,男,1987年出生,博士,副研究员。主要研究方向为神经接口、人机交互。E-mail:enhao.zheng@ia.ac.cn;许东方,男,1990年出生,博士研究生。主要研究方向为人机接口、仿生材料。E-mail:dongfangxu@pku.edu.cn;麦金耿,男,1982年出生,博士。主要研究方向为并行计算、神经接口。E-mail:jingengmai@pku.edu.cn
基金资助:
WANG Qining1,2, ZHENG Enhao3, XU Dongfang1, MAI Jingeng1
Received:
2018-03-31
Revised:
2018-11-21
Online:
2019-06-05
Published:
2019-06-05
摘要: 人体运动意图的准确可靠识别是人机共融中的关键问题之一。针对现有研究中的局限和不足,提出了全新的非接触式电容传感方法。该方法以金属电极不接触皮肤的方式测量肌肉收缩信号。介绍了电容传感的原理,分析了基于该方法测量肌肉收缩形状变化的机理。分别介绍了非接触式电容传感方法在小腿智能动力假肢控制和上肢运动识别中的应用。针对下肢智能假肢控制,提出了基于非接触式电容传感的运动模态以及模态切换的识别。为了进一步提高系统的可穿戴性,提出了基于柔性可延展液态金属电极的电容传感系统并进行了初步的试验验证;针对上肢运动识别,首先介绍了用于腕关节离散运动模式的识别研究,其次介绍了基于电容传感对连续握力的识别和估计,证实了电容传感这一全新方法在上肢运动识别中的可行性。未来会在穿戴式机器人控制以及协作性机器人模仿学习中对电容传感方法进行更深入的研究。
中图分类号:
王启宁, 郑恩昊, 许东方, 麦金耿. 基于非接触式电容传感的人体运动意图识别[J]. 机械工程学报, 2019, 55(11): 19-27.
WANG Qining, ZHENG Enhao, XU Dongfang, MAI Jingeng. Noncontact Capacitive Sensing Based Human Motion Intent Recognition[J]. Journal of Mechanical Engineering, 2019, 55(11): 19-27.
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