A Recognition Method of Spread and Grasp Actions Combining Motion Imagination and Action Observation

doi:10.7652/xjtuxb201910021

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A Recognition Method of Spread and Grasp Actions Combining Motion Imagination and Action Observation

更新时间：2025-07-09

- A Recognition Method of Spread and Grasp Actions Combining Motion Imagination and Action Observation
- Vol. 53, Issue 10, Pages: 151-158(2019)
- 作者机构：
  
  西安交通大学现代设计与转子轴承系统教育部重点实验室,西安,710049
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb201910021
  CLC： R318.04
- Online First：10 October 2019，
  
  Published：2019
- 稿件说明：
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A Recognition Method of Spread and Grasp Actions Combining Motion Imagination and Action Observation[J]. 2019, 53(10): 151-158.
DOI：

A Recognition Method of Spread and Grasp Actions Combining Motion Imagination and Action Observation[J]. 2019, 53(10): 151-158. DOI： 10.7652/xjtuxb201910021.

摘要

为了获取单侧手部在伸-握动作下与运动想象直接相关的脑电信号(EEG)特征并实现精细动作有效识别

提出了结合运动想象和动作观察的单侧手部伸-握动作精细识别方法。首先

设计了结合运动想象和动作观察的复合范式

增强了伸-握动作所对应大脑皮层的激活程度

并探索了在运动想象、运动观察和复合范式下大脑皮层的激活规律; 然后利用小波变换重构各个通道EEG并计算相应多尺度熵

并通过共空间模式获取伸-握动作所对应EEG特征; 最后

利用线性判别式法从EEG特征中识别“伸开”和“握拳”精细动作。实验结果表明:相比单一实验范式的运动想象或动作观察

该方法在低频(5～20 Hz)时更能有效地激活运动区和枕区的神经元; 同时

“伸开”动作对应EEG的多尺度熵明显大于“握拳”动作的熵值

实现了单侧手部伸-握动作精细意图感知

其平均正确率可达85.7%。

Abstract

A recognition method for spread and grasp actions of a hand that combines motion imagination and action observation is proposed to obtain electroencephalogram(EEG)feature that is directly relevant to motor imagery of spread and grasp movements of the hand and to effectively identify fine actions.First

a compound paradigm that combines motor imagery and action observation(short for compound paradigm)is designed to enhance activation of the human cerebral cortex associated with the spread and grasp actions of a hand.Activation rules of the cerebral cortex are investigated under motor imagery

action observation and compound paradigm.Then

EEG is reconstructed for each channel by using a wavelet reconstruction and the multiscale entropy of EEG is calculated.EEG features of spread and grasp actions of the hand are extracted through a common spatial pattern.Finally

both the -spread- and -grasp- actions are identified from EEG features based on a linear discriminant method.Experimental

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references

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