Karimi Fatemeh, Kofman Jonathan, Mrachacz-Kersting Natalie, Farina Dario, Jiang Ning
Department of Systems Design Engineering, Faculty of Engineering, University of WaterlooWaterloo, ON, Canada.
Department of Health Science and Technology, Aalborg UniversityAalborg, Denmark.
Front Neurosci. 2017 Jun 30;11:356. doi: 10.3389/fnins.2017.00356. eCollection 2017.
The movement related cortical potential (MRCP), a slow cortical potential from the scalp electroencephalogram (EEG), has been used in real-time brain-computer-interface (BCI) systems designed for neurorehabilitation. Detecting MPCPs in real time with high accuracy and low latency is essential in these applications. In this study, we propose a new MRCP detection method based on constrained independent component analysis (cICA). The method was tested for MRCP detection during executed and imagined ankle dorsiflexion of 24 healthy participants, and compared with four commonly used spatial filters for MRCP detection in an offline experiment. The effect of cICA and the compared spatial filters on the morphology of the extracted MRCP was evaluated by two indices quantifying the signal-to-noise ratio and variability of the extracted MRCP. The performance of the filters for detection was then directly compared for accuracy and latency. The latency obtained with cICA (-34 ± 29 ms motor execution (ME) and 28 ± 16 ms for motor imagery (MI) dataset) was significantly smaller than with all other spatial filters. Moreover, cICA resulted in greater true positive rates (87.11 ± 11.73 for ME and 86.66 ± 6.96 for MI dataset) and lower false positive rates (20.69 ± 13.68 for ME and 19.31 ± 12.60 for MI dataset) compared to the other methods. These results confirm the superiority of cICA in MRCP detection with respect to previously proposed EEG filtering approaches.
运动相关皮层电位（MRCP）是头皮脑电图（EEG）中的一种慢皮层电位，已被用于为神经康复设计的实时脑机接口（BCI）系统。在这些应用中，以高精度和低延迟实时检测MPCP至关重要。在本研究中，我们提出了一种基于约束独立成分分析（cICA）的新型MRCP检测方法。该方法在24名健康参与者执行和想象踝关节背屈期间进行了MRCP检测测试，并在离线实验中与四种常用的用于MRCP检测的空间滤波器进行了比较。通过量化提取的MRCP的信噪比和变异性的两个指标，评估了cICA和比较的空间滤波器对提取的MRCP形态的影响。然后直接比较滤波器的检测性能，以评估准确性和延迟。使用cICA获得的延迟（运动执行（ME）数据集为-34±29毫秒，运动想象（MI）数据集为28±16毫秒）明显小于所有其他空间滤波器。此外，与其他方法相比，cICA产生了更高的真阳性率（ME数据集为87.11±11.73，MI数据集为86.66±6.96）和更低的假阳性率（ME数据集为20.69±13.68，MI数据集为19.31±12.60）。这些结果证实了cICA在MRCP检测方面相对于先前提出的EEG滤波方法的优越性。
