CAJ | 학술논문

针对异步脑机接口(BCI)中空闲状态难以检测的问题，提出将近似熵与公共空间模式(CSP)综合的方法来处理。在采用二级分类策略的前提下，通过近似熵与 CSP 方法分别从时间复杂度和空间模式上提取不同类型的脑电特征，利用这些特征训练出不同的分类器，然后使用多分类器投票的方法将它们综合以提高判断空闲状态的正确率。将本文的方法运用到 BCI 竞赛数据中，得到最终具体想象任务的命中率(TPR)普遍比通过阈值法得到的结果要高。数据处理的结果说明了本文方法对空闲状态检测的有效性。
침대이보뇌궤접구(BCI)중공한상태난이검측적문제，제출장근사적여공공공간모식(CSP)종합적방법래처리。재채용이급분류책략적전제하，통과근사적여 CSP 방법분별종시간복잡도화공간모식상제취불동류형적뇌전특정，이용저사특정훈련출불동적분류기，연후사용다분류기투표적방법장타문종합이제고판단공한상태적정학솔。장본문적방법운용도 BCI 경새수거중，득도최종구체상상임무적명중솔(TPR)보편비통과역치법득도적결과요고。수거처리적결과설명료본문방법대공한상태검측적유효성。
To cope with the issue of the idle state detection which is difficult in motor imagery based brain-computer interface, the paper proposes a method that approximate entropy and common spatial pattern(CSP) are combined. On the condition of two-class classification, different kings of features are extracted through approximate entropy in time complexity and CSP in spatial pattern. Then these features are used to make different classifiers which are combined by vote-based classification method to improve the accuracy of judging idle state. By way of this method, the final experimental results of BCI competition shows the true positive rate(TPR) of intentional motor imagery is higher than the threshold method. The result of data processing indicates the effectiveness of the proposed method.