摘要
有研究表明,在下肢运动想象脑电信号分类中,在运动想象基础上加入稳态体感诱发电位能够得到更高的分类结果,但是研究大多都是基于双侧电刺激辅助诱发的体感电位,对于单侧电刺激辅助研究较少,本文对单侧脚踝胫后神经与双侧脚踝胫后神经分别施加电刺激,来探究何种刺激模式能够得到更好的分类结果。并设计了两组对照实验:单侧左脚电刺激模式vs单侧右脚电刺激模式以及单侧右脚电刺激模式vs双侧同时电刺激模式。综合频谱图、时频图谱、脑地形图特征分析结果得出,单侧右脚电刺激模式ERD特征最显著,激活程度最深。单侧右脚刺激模式比双脚同时刺激模式平均分类准确率高5.57%,单个受试者单侧右脚刺激模式比双脚同时刺激模式分类准确率高15%,证明了在单侧右脚电刺激辅助的情况下,更有利于下肢运动想象脑电信号的分类。
Studies have shown that in lower limb movement category, imagine eeg signals based on the motion to imagine joining steady-state somatosensory evoked potentials can get higher classification results, but most studies are based on double side auxiliary body feeling potential induced by electrical stimulation, the unilateral electrical stimulation auxiliary study is less, in this paper, the unilateral posterior tibial nerves and bilateral ankle ankle posterior tibial nerve stimulation, respectively to find out what kind of stimulus can get better classification results. Two control experiments were designed: unilateral left foot electrical stimulation mode vs unilateral right foot electrical stimulation mode and unilateral right foot electrical stimulation mode vs bilateral simultaneous electrical stimulation mode. Based on the analysis of the characteristics of spectrum, time-frequency map and brain topography, it was concluded that the ERD characteristics of the unilateral right foot electrical stimulation mode were the most significant and the activation degree was the deepest. The average classification accuracy of unilateral right foot stimulation mode was 5.57% higher than that of dual stimulation mode, and the classification accuracy of single subject′s unilateral right foot stimulation mode was 15% higher than that of dual stimulation mode, which proved that the assistance of unilateral right foot electrical stimulation is more conducive to the classification of lower limb motor imagination EEG signals.
作者
刘昭君
赵丽
边琰
万佳乐
Liu Zhaojun;Zhao Li;Bian Yan;Wan Jiale(Tianjin University of Technology and Education,Tianjin 300222,China)
出处
《电子测量技术》
北大核心
2021年第17期79-87,共9页
Electronic Measurement Technology