Suppressing interferences of EIT on synchronous recording EEG based on comb filter for seizure detection.

The purpose of this study was to eliminate the interferences of electrical impedance tomography (EIT) on synchronous recording electroencephalography (EEG) for seizure detection. The simulated EIT signal generated by COMSOL Multiphysics was superimposed on the clinical EEG signal obtained from the CHB-MIT Scalp EEG Database, and then the spectrum features of superimposed mixed signals were analyzed. According to the spectrum analysis, in addition to high-frequency interference at 51.2 kHz related to the drive current, there was also low-frequency interference caused by switching of electrode pairs, which were used to inject drive current. A low pass filter and a comb filter were used to suppress the high-frequency interference and low-frequency interference, respectively. Simulation results suggested the low-pass filter and comb filter working together effectively filtered out the interference of EIT on EEG in the process of synchronous monitoring. As a result, the normal EEG and epileptic EEG could be recognized effectively. Pearson correlation analysis further confirmed the interference of EIT on EEG was effectively suppressed. This study provides a simple and effective interference suppression method for the synchronous monitoring of EIT and EEG, which could be served as a reference for the synchronous monitoring of EEG and other medical electromagnetic devices.

本研究旨在消除电阻抗断层成像（EIT）对同步记录脑电图（EEG）用于癫痫发作检测的干扰。 由COMSOL Multiphysics生成的模拟EIT信号叠加在从CHB - MIT头皮脑电图数据库获取的临床脑电图信号上，然后分析叠加混合信号的频谱特征。根据频谱分析，除了与驱动电流相关的51.2 kHz高频干扰外，还存在由用于注入驱动电流的电极对切换引起的低频干扰。分别使用低通滤波器和梳状滤波器来抑制高频干扰和低频干扰。仿真结果表明，低通滤波器和梳状滤波器共同作用有效地滤除了同步监测过程中EIT对EEG的干扰。 因此，可以有效识别正常脑电图和癫痫脑电图。皮尔逊相关性分析进一步证实EIT对EEG的干扰得到了有效抑制。 本研究为EIT和EEG的同步监测提供了一种简单有效的干扰抑制方法，可为脑电图与其他医用电磁设备的同步监测提供参考。