摘要
要对下肢外骨骼机器人进行有效地控制,不仅需要设计一个有效的控制系统,而且需要准确的捕捉下肢的运动并进行精准的步态识别。为此设计了一种基于脑电、肌电、光纤于一体的多信息感知融合控制系统,可以实现多动作间的高随意性切换。并采用分形理论,着重针对光纤感知系统测得的下肢角度数据进行特征提取。结果表明,提取到的人体下肢运动信息特征值效果明显,可以适用于分辨人体的平走、跑步、上坡、下坡、下蹲和起立等六种运动模式。
As for effective control of the lower extremity exoskeleton robot, design of an effective control system, as well as the important system to accurately capture the movement of the lower limbs and precise gait recognition are needed. So, in this paper, the EEG, EMG and fiber optical multi-information perception based control system is proposed, it can achieve high random switching between multiple operation, in which the fractal theory is used. This paper focuses on the fiber optic sensing system for lower limb angles measuring and feature extraction. The results shows that the extracted eigenvalues of the human lower limb motion information are obviously effective, which can be applied to distinguish between the human level of walking, jogging, uphill, downhill, squat and stand of six motion mode.
出处
《计算机仿真》
CSCD
北大核心
2016年第7期314-317,387,共5页
Computer Simulation
关键词
外骨骼机器人
多信息
感知融合
光纤感知
分形理论
特征提取
Exoskeleton robot
Multi-information
Perception fusion
Fiber optical sensing
Fractal theory
Feature extraction