Fabien Lotte, Anatole Lécuyer, Fabrice Lamarche, Bruno Arnaldi
IRISA Rennes, F-35 042 Rennes, France.
IEEE Trans Neural Syst Rehabil Eng. 2007 Jun;15(2):322-4. doi: 10.1109/TNSRE.2007.897032.
This paper studies the use of fuzzy inference systems (FISs) for motor imagery classification in electroencephalography (EEG)-based brain-computer interfaces (BCIs). The results of the four studies achieved are promising as, on the analysed data, the used FIS was efficient, interpretable, showed good capabilities of rejecting outliers and offered the possibility of using a priori knowledge.
本文研究了模糊推理系统(FISs)在基于脑电图(EEG)的脑机接口(BCIs)中用于运动想象分类的应用。所取得的四项研究结果很有前景,因为在所分析的数据上,所使用的FIS是高效的、可解释的,具有良好的异常值剔除能力,并提供了使用先验知识的可能性。