시선 추적 센서 데이터를 활용한 뇌파 잡파제거 방법에 관한 연구
A Study on EEG Artifact Removal Method using Eye tracking Sensor Data
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초록
뇌파(Electroencephalogram, EEG)는 외부 자극 때문에 발생하는 뇌 활동을 연구하기 위해 사용되는 도구로 두피에 전극을부착하여 기록한다. 이 과정에서 잡파(artifact)가 혼입되어 신호를 왜곡시키기 쉬워 이를 제거하기 위한 후처리가 필수적이다. 잡파 제거를 위해 널리 사용되는 방법으로 독립성분분석(Independent Component Analysis, ICA)이 존재한다. 이 방법은성능은 우수하나 뇌파 정보를 일부 손실시키는 단점이 있다. 본 논문에서는 이러한 문제점을 보완하기 위해 시선 추적 센서(Eyetracker)를 통해 얻은 눈 깜빡임 정보를 이용하여 필터 적용 범위를 제한함으로써 뇌파 정보 손실을 줄이는 방법을 제안한다. 이후 신호 대 잡음 비(Signal to Noise Ratio, SNR), 스펙트럼 일관성(Spectral Coherence, SC) 등의 정량화 방법을 이용하여 기존의 방법과 제안하는 방법의 결과를 비교하였다
Abstract
Electroencephalogram (EEG) is a tool used to study brain activity caused by external stimuli. In this process, artifactsare mixed and it is easy to distort the signal, so post-processing is necessary to remove it. Independent ComponentAnalysis (ICA) is a widely used method for removing artifact. This method has a disadvantage in that it has excellentperformance but some loss of brain wave information. In this paper, we propose a method to reduce EEG informationloss by restricting the filter coverage using eye blink information obtained from Eyetracker. We then compared theresults of the proposed method with the conventional method using quantization methods such as Signal to Noise Ratio(SNR) and Spectral Coherence (SC).
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