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Detection of movement-related cortical potentials associated with emergency and non-emergency tasks

机译:检测与紧急和非紧急任务相关的与运动有关的皮质电位

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This study focuses on a demonstration of differences between movement-related cortical potentials (MRCPs) during emergency and non-emergency situations. Two paradigms were designed for emergency and non-emergency situations. The necessary pre-processing and Laplacian spatial filter were used in the collected data. Then initial negative phase of MRCPs was extracted from scalp electroencephalogram (EEG) in non-emergency situation and compared with that in emergency situation. Based on the data of non-emergency, a matched filter (MF) algorithm was designed and was used to detect the motor intention in two paradigms. The result shows a significant difference of the initial negative phase of the MRCP in two cases. In addition, if the MF algorithm based on non-emergency situation was used for emergency situations directly, there was a large difference in accuracy. The true positive rate was 60.57±14.79% in nonemergency while 44.29±5.73% in emergency. The result indicates that additional consideration should be given to emergency situation when designing algorithms or collecting data. So, we designed a new algorithm to solve this problem, which works better compared to simple MF. The algorithm effectively improves the true positive rate and reduces the false positive per minute.
机译:这项研究的重点是演示在紧急情况和非紧急情况下与运动有关的皮质电位(MRCP)之间的差异。针对紧急情况和非紧急情况设计了两种范例。在收集的数据中使用了必要的预处理和Laplacian空间滤波器。然后在非紧急情况下从头皮脑电图(EEG)中提取MRCP的初始负相,并与紧急情况下的相比较。基于非紧急情况的数据,设计了一种匹配滤波器(MF)算法,该算法用于检测两种模式下的电机意图。结果表明,在两种情况下,MRCP的初始负相存在显着差异。此外,如果将基于非紧急情况的MF算法直接用于紧急情况,则准确性会有很大差异。非紧急情况下的真实阳性率为60.57±14.79%,紧急情况下为44.29±5.73%。结果表明,在设计算法或收集数据时应进一步考虑紧急情况。因此,我们设计了一种新算法来解决此问题,与简单MF相比,该算法效果更好。该算法有效地提高了真阳性率,减少了每分钟的假阳性率。

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