人机交互问题中基于MSI算法的P300诱发电位检测方法

Y. Turovsky, A. Vakhtin, S. Borzunov, E. Martynenko
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引用次数: 0

摘要

本文提出了一种基于对刺激过程的脑电活动的一次迭代来检测背景脑电图诱发电位的方法。该方法的基础是研究人员感兴趣的诱发电位(EP)成分的准周期序列的形成,由于增加了具有给定时移的EP参考片段。将得到的序列与相干积累方法框架内积累的参考电位进行比较,并进行适当变换,使期望分量的周期与所研究信号的周期一致。采用多变量同步指数(MSI)方法进行比较,该方法是典型相关方法的进一步发展。所得结果可应用于基于P300电位的脑机接口任务。此外,该解决方案适用于任何包含单个或非周期成分的生物医学信号的隔离。
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P300 Evoked Potential Detection Method Using the MSI Algorithm in the Problem of Human-Computer Interaction
The paper presents a method for detecting evoked potentials from a background electroencephalogram based on one iteration of brain electrical activity in response to the stimulation process. The basis of the method is the formation of a quasi-periodic sequence of the component of the evoked potential (EP) of interest to the researcher, due to the addition of reference fragments of the EP with a given time shift. The resulting sequence is compared with the reference EP accumulated within the framework of the coherent accumulation approach and appropriately transformed so that the period of the desired component coincides with that in the signal under study. The comparison is carried out taking into account the Multivariate Synchronization Index (MSI) method, which is a further development of the canonical correlation method. The results obtained can be applied to the tasks of brain-computer interfaces (BCI) based on the P300 potential. In addition, this solution is applicable to the isolation of any biomedical signal containing single or non-periodic components.
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