CAJ | 학술논문

目的：本文通过对客观记录的受试者脑电图数据进行马氏距离判别分析，判断其能否应用于脑电数据特征提取和分类决策。为脑电图研究的其它分析做基础分析。方法：根据α波的强弱不同将21导电极分为四类，分别对63例正常状态下受试者21导联电极的脑电图数据进行马氏距离判别分析，并利用误判率回代估计法检验判别准确率。数据处理和统计分析采用独立设计的脑电图分析工具箱和马氏距离判别分析程序。结果：表明对63例正常状态下受试者的脑电图数据进行马氏距离判别分析，预测各电极分类准确率84.4豫。结论：马氏判别法预测准确率较高，脑电特征（主要为α波）提取较为准确，能较好的应用于脑电数据特征提取和分类决策中，从而辅助脑电图的检查和定量分析，为脑电图的检验提供有效的分析手段。
목적：본문통과대객관기록적수시자뇌전도수거진행마씨거리판별분석，판단기능부응용우뇌전수거특정제취화분류결책。위뇌전도연구적기타분석주기출분석。방법：근거α파적강약불동장21도전겁분위사류，분별대63례정상상태하수시자21도련전겁적뇌전도수거진행마씨거리판별분석，병이용오판솔회대고계법검험판별준학솔。수거처리화통계분석채용독립설계적뇌전도분석공구상화마씨거리판별분석정서。결과：표명대63례정상상태하수시자적뇌전도수거진행마씨거리판별분석，예측각전겁분류준학솔84.4예。결론：마씨판별법예측준학솔교고，뇌전특정（주요위α파）제취교위준학，능교호적응용우뇌전수거특정제취화분류결책중，종이보조뇌전도적검사화정량분석，위뇌전도적검험제공유효적분석수단。
Objective: In this paper, we have done mahalanobis discriminant analysis to EEG data of experiment objects which are recorded impersonally, come up with a relatively accurate method used in feature extraction and classification decisions. The present study is the groundwork analysis for other analysis in EEG study. Methods: In accordance with the strength of α wave, the head electrodes are divided into four species. In use of part of 21 electrodes EEG data of 63 people, we have done Mahalanobis discriminant analysis to EEG data of six objects. EEG data processing and statistic analysis adopted independently designed EEG analysis toolbox and the program of correlation analysis. Results: In use of part of EEG data of 63 people, we have done Mahalanobis discriminant analysis, the electrode classification accuracy rates is 84.4%. Conclusions:Mahalanobis discriminant has higher prediction accuracy, EEG features (mainlyαwave) extract more accurate. Mahalanobis discriminant would be better applied to the feature extraction and classification decisions of EEG data.