完全预测下肢步行运动想象意图的可行性研究
Feasibility Study for Fully Prediction of the Movement Imagery Intention of Lower Limb Ambulation
周斌 1王宏 1李坦 1兰钦1
作者信息
- 1. 东北大学 机械工程与自动化学院,辽宁 沈阳 110819
- 折叠
摘要
在下肢运动想象发生之前获取想象意图是为下肢神经康复系统提供精准控制策略的关键.为此,研究利用运动想象前的脑电图(electroencephalogram,EEG)信号完全预测下肢步行运动启停想象意图及其类型的可行性.对EEG信号进行预处理并提取运动相关皮质电位(movement-related cortical potential,MRCP).基于MRCP挑选出具有明显可辨别性的15个通道.利用时间卷积网络模型从被选取的MRCP通道特征中解码出下肢步行运动想象意图和意图类型.结果表明,通过MRCP形态选取的EEG通道信号在启停意图和类别上均具有明显可分离差异,验证了只使用运动想象前EEG信号能够完全预测人类下肢运动启停意图和意图类型.
Abstract
Acquiring intentions before the start of lower limb movement imagery is the key issue in providing precise control strategies for the lower limb neurorehabilitation system.To this end,the feasibility of using electroencephalogram(EEG)signals prior to movement imagery to fully predict the movement imagery start-stop intention and intention types of lower limb ambulation is investigated.The EEG signal is pre-processed and the movement-related cortical potential(MRCP)is extracted.15 channels with significant discriminability are selected based on MRCP.The temporal convolutional network models are used to decode the movement imagery intention and intention types of lower limb ambulation from the selected MRCP channel features.The results show that the EEG channel signals selected by MRCP morphology are with significant separable differences in both start-stop intention and intention types,verifying that using only pre-movement imagery EEG signals is capable of fully prediction the movement imagery start-stop intention and intention types of lower limb ambulation movement in humans.
关键词
脑电图/运动相关皮质电位/时间卷积网络/下肢步行运动想象意图/完全预测Key words
electroencephalogram(EEG)/movement-related cortical potential(MRCP)/temporal convolutional network/movement imagery intention of lower limb ambulation/fully prediction引用本文复制引用
基金项目
国家重点研发计划项目(2021YFF0306405)
出版年
2024
NETL
NSTL
万方数据