东南大学学报(自然科学版)
東南大學學報(自然科學版)
동남대학학보(자연과학판)
JOURNAL OF SOUTHEAST UNIVERSITY
2014年
6期
1126-1130
,共5页
王力%张雄%仲雪飞%樊兆雯%张玉%孙瀚
王力%張雄%仲雪飛%樊兆雯%張玉%孫瀚
왕력%장웅%중설비%번조문%장옥%손한
语言想像%脑电信号%时频分析%脑机接口
語言想像%腦電信號%時頻分析%腦機接口
어언상상%뇌전신호%시빈분석%뇌궤접구
speech imagery%electroencephalography%time-frequency analysis%brain-computer interfaces
为了分析语言想像所诱导的脑电信号的时间和频率特性,利用事件相关谱扰动(ERSP)对信号进行时频分析.首先,经ERSP确定能量波动的频率范围;然后,根据该频率范围计算信号的事件相关(去)同步(ERD/ERS ),并利用共空间模式和支持向量机分别对单次实验数据的特征值进行提取和分类.对8位被试的试验结果分析表明,被试间的频率范围具有显著的差异,其中4位被试的频率范围含有α波,3位被试含有α波和β波,1位被试的脑电信号在默读汉字时无明显变化.2个汉字默读时的脑电信号可产生相似的ERD/ERS .优化频率范围后针对这2个汉字的平均分类正确率分别提高了2.25%和1.39%.时频分析能更好地显示脑电信号的能量变化率,并能改善语言想像脑机接口的性能.
為瞭分析語言想像所誘導的腦電信號的時間和頻率特性,利用事件相關譜擾動(ERSP)對信號進行時頻分析.首先,經ERSP確定能量波動的頻率範圍;然後,根據該頻率範圍計算信號的事件相關(去)同步(ERD/ERS ),併利用共空間模式和支持嚮量機分彆對單次實驗數據的特徵值進行提取和分類.對8位被試的試驗結果分析錶明,被試間的頻率範圍具有顯著的差異,其中4位被試的頻率範圍含有α波,3位被試含有α波和β波,1位被試的腦電信號在默讀漢字時無明顯變化.2箇漢字默讀時的腦電信號可產生相似的ERD/ERS .優化頻率範圍後針對這2箇漢字的平均分類正確率分彆提高瞭2.25%和1.39%.時頻分析能更好地顯示腦電信號的能量變化率,併能改善語言想像腦機接口的性能.
위료분석어언상상소유도적뇌전신호적시간화빈솔특성,이용사건상관보우동(ERSP)대신호진행시빈분석.수선,경ERSP학정능량파동적빈솔범위;연후,근거해빈솔범위계산신호적사건상관(거)동보(ERD/ERS ),병이용공공간모식화지지향량궤분별대단차실험수거적특정치진행제취화분류.대8위피시적시험결과분석표명,피시간적빈솔범위구유현저적차이,기중4위피시적빈솔범위함유α파,3위피시함유α파화β파,1위피시적뇌전신호재묵독한자시무명현변화.2개한자묵독시적뇌전신호가산생상사적ERD/ERS .우화빈솔범위후침대저2개한자적평균분류정학솔분별제고료2.25%화1.39%.시빈분석능경호지현시뇌전신호적능량변화솔,병능개선어언상상뇌궤접구적성능.
To analyze time and frequency characteristics of electroencephalography signals induced by speech imagery,event-related spectral perturbation (ERSP)is used in the time-frequency analy-sis of signals.First,the frequency range of the energy fluctuation can be determined by ERSP. Then,according to the frequency range,event-related (de)synchronization (ERD/ERS)of the sig-nals is calculated,and the eigenvalues of each experimental data are extracted and classified by com-mon spatial pattern and support vector machine,respectively.The results of eight subjects show that the frequency ranges are obviously different among subjects.The ranges of four subjects include αrhythm and those of three subjects include αand βrhythms.The electroencephalography signals of one subject do not evidently change when he reads a Chinese character in mind.The similar ERD/ERS of electroencephalography signals may produce while reading two Chinese characters in mind. After optimizing the frequency ranges,the average classification accuracy for the two characters are improved by 2. 25% and 1. 39%,respectively.The energy gradient of electroencephalography sig-nals can be exhibited better by time-frequency analysis,and the performance of speech imagery based brain-computer interfaces can be also improved.