Vidaurre C, Schlögl A, Cabeza R, Scherer R, Pfurtscheller G
Department of Electrical Engineering and Electronics, State University of Navarra, Pamplona, Spain.
IEEE Trans Biomed Eng. 2006 Jun;53(6):1214-9. doi: 10.1109/TBME.2006.873542.
A viable fully on-line adaptive brain computer interface (BCI) is introduced. On-line experiments with nine naive and able-bodied subjects were carried out using a continuously adaptive BCI system. The data were analyzed and the viability of the system was studied. The BCI was based on motor imagery, the feature extraction was performed with an adaptive autoregressive model and the classifier used was an adaptive quadratic discriminant analysis. The classifier was on-line updated by an adaptive estimation of the information matrix (ADIM). The system was also able to provide continuous feedback to the subject. The success of the feedback was studied analyzing the error rate and mutual information of each session and this analysis showed a clear improvement of the subject's control of the BCI from session to session.
介绍了一种可行的全在线自适应脑机接口(BCI)。使用连续自适应BCI系统对九名未经过训练的健全受试者进行了在线实验。对数据进行了分析,并研究了该系统的可行性。该BCI基于运动想象,特征提取采用自适应自回归模型,使用的分类器是自适应二次判别分析。分类器通过信息矩阵的自适应估计(ADIM)进行在线更新。该系统还能够向受试者提供连续反馈。通过分析每个会话的错误率和互信息来研究反馈的成功情况,该分析表明受试者对BCI的控制在各会话之间有明显改善。