语言脑机接口康复系统中的参数优化研究

Research on Parameter Optimization in Speech Rehabilitation System Based on Brain Computer Interface

脑机接口可为失语症及运动障碍患者提供新的康复途径。本文设计了基于汉字默读的语言脑机接口实验,将9位被试脑电信号从时域、频域和空间域三方面进行特征选择和优化,用于汉字识别。采用事件相关谱扰动算法进行时频分析,以获取特征显著的时频区间,利用共空间模式进行空域分析,选择出最佳导联组并结合分类结果对电极优化选择。结果表明:默读汉字所引起的脑电信号时频能量变化主要分布在α波和β波,且随默读时间动态变化。特征选择时,改进时间与频率区间较固定时间与频率区间均能有效提高汉字的平均匹配准确率,若同时改进时间与滤波范围,匹配准确率提高范围达到3.37%。本文有助于语言脑机接口的理论研究,同时为语言康复训练提供新思路。

Brain-computer interface(BCI)system provides a new way of rehabilitation for patients with aphasia.9 healthy subjects were selected to take part in this study.And EEG signals were acquired synchronously while the subjects reading Chinese characters silently.To distinguish four characters better,the EEG signal feature were selected and optimized from time-frequency domain and spatial domain.The significant time and frequency range for signal feature were selected by event related spectral perturbation(ERSP)at first.Common spatial pattern(CSP)was used to represent the spatial distribution.Different channel groups are classified by Fisher classifier to obtain the optimal channel group.The results show that spectral energy was dynamic changed in alpha and beta bands while all characters were read silently.Averaged matching accuracy of Chinese characters were improved by used the modified time and frequency range.And the matching accuracy was increased by 3.37%than used the feature from unified time and frequency range.This study contributes to the development of speech brain-computer interface,which provide new ideas for speech rehabilitation.