The common spatial pattern (CSP) approach is known as one of the most popular spatial filtering techniques for EEG classification in motor imagery (MI) based brain-computer interfaces (BCIs). However, it still suffers some drawbacks such as sensitivity to noise, non-stationarity, and limitation to binary classification.Therefore, we propose a novel spatial filtering framework called scaCSP based on the scatter matrices of spatial covariances of EEG signals, which works generally in both binary and multi-class problems whereas CSP can be cast into our framework as a special case when only the range space of the between-class scatter matrix is used in binary cases.We further propose subspace enhanced scaCSP algorithms which easily permit incorporating more discriminative information contained in other range spaces and null spaces of the between-class and within-class scatter matrices in two scenarios: a nullspace components reduction scenario and an additional spatial filter learning scenario.The proposed algorithms are evaluated on two data sets including 4 MI tasks. The classification performance is compared against state-of-the-art competing algorithms: CSP, Tikhonov regularized CSP (TRCSP), stationary CSP (sCSP) and stationary TRCSP (sTRCSP) in the binary problems whilst multi-class extensions of CSP based on pair-wise and one-versus-rest techniques in the multi-class problems. The results show that the proposed framework outperforms all the competing algorithms in terms of average classification accuracy and computational efficiency in both binary and multi-class problems.The proposed scsCSP works as a unified framework for general multi-class problems and is promising for improving the performance of MI-BCIs.
翻译:通用空间模式(CSP)方法被称为机动图像(MI)基于大脑-计算机界面(BCIS)中最受欢迎的EEEG分类空间过滤技术之一。然而,它仍然有一些缺点,例如对噪音的敏感度、非静态性和对二进制分类的限制。 因此,我们提议基于空间共变信号分布矩阵的ScaCSP新颖的空间过滤框架,它一般在二进制和多级之间起作用,而CSP则可以作为特例纳入我们的框架中。 我们进一步提议子空间增强的SCSP算法可以很容易地将其他范围空间空间空间、非静态和对二进制分类的空格分布矩阵包含更多的歧视性信息。 无效空间构件减少假设和额外的空间过滤学习假。 拟议的算法在两种数据组合中,包括4个MI任务。 将分类的性能与每组的竞争性算法进行比较:CSP、 Tikhonov Exlicalalalal-silable 以及 CSAL-Sal-Sal-Sal-Sal-Sal-Sal-Serviolal Serviews 和C Scial-Scial-Scial-Sal-Smarlupal-S-Smarlal-S-S-Smarl)中, C 和C的S-S-SP-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-Slal-SL-S-SL-SL-SLisal-S-S-SL-S-S-S-S-S-S-S-SL-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-SL-SL-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S</s>