Falzon Owen, Camilleri Kenneth P, Muscat Joseph
Department of Systems and Control Engineering, Faculty of Engineering, University of Malta, Msida, Malta.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:4707-10. doi: 10.1109/IEMBS.2010.5626381.
The method of common spatial patterns (CSP) has been widely adopted for the discrimination of mental tasks using EEG data. In this paper, some limitations of the standard CSP implementation when considering data where phase relationships play a significant role are highlighted. Furthermore, a variant of the CSP method based on the analytic representation of signals is proposed to make up for these drawbacks. The advantages of the proposed method over the standard CSP implementation are demonstrated using simulated data and tests with real EEG data. Specifically, it is shown that the complex-valued spatial filters and the derived spatial patterns can improve the discrimination process and give a more adequate representation of the tasks being considered, respectively.
共同空间模式（CSP）方法已被广泛用于利用脑电图（EEG）数据区分心理任务。本文强调了标准CSP实现方法在考虑相位关系起重要作用的数据时存在的一些局限性。此外，还提出了一种基于信号解析表示的CSP方法变体，以弥补这些缺点。使用模拟数据和真实EEG数据测试证明了该方法相对于标准CSP实现方法的优势。具体而言，结果表明复值空间滤波器和导出的空间模式分别可以改善区分过程，并更充分地表示所考虑的任务。
