運用獨立成份分析法於事件相關電位之腦波訊號比較

Comparisons of EEG signal in ERP Using Independent Component Analysis

鍾博玹(Po-Hsuan Chung)；黃元惠(Yuan-Huei Huang)；趙文鴻(Wen Hong Chao)

腦波圖 ； 事件相關腦電位 ； 伴隨性負變化 ； 專注度 ； 獨立成分分析法 ； electroencephalograph (EEG) ； event-related potential (ERP) ； contingent negative variation(CNV) ； attention ； independent component analysis (ICA)

元培學報

26期（2023 / 06 / 01）

1 - 19

繁體中文;英文

腦波圖（electroencephalograph, EEG）研究中常用事件相關腦電位（Event-related potential, ERP）之伴隨性負變化（Contingent negative variation, CNV）觀察腦部反應變化，本研究設計了四個實驗區段；第一個區段：忽略刺激（Ignore stimuli, IS），第二個區段：按鍵任務（Button mission, BM），第三個區段：計數閃光刺激任務（Number of flash stimulus mission, NM），第四個區段：按鍵任務與計數閃光刺激任務（BM and NM, BNM），進行實驗測量腦波觀察專注度對大腦的CNV反應本研究運用獨立成分分析法（Independent component analysis, ICA）分析腦波訊號觀察大腦的CNV反應變化。結果發現ICA能將位於CZ或FZ的混合訊號成功的分離取得更準確的腦波原始訊號。

In electroencephalograph (EEG) research, the contingent negative variation (CNV) of event-related potential (ERP) is often used to observe the variations of brain response. Four section were designed in this study to measure EEG signals. The first section is Ignore stimuli (IS). The second section is Button mission (BM). The third section is Number of flash stimulus mission (NM). The forth section is BM and NM (BNM). The purpose of this study is to observe the CNV of brain response in attention by using the independent component analysis (ICA). The results showed that ICA could successfully separate the mixed signals of Cz or Fz to obtain more accurate original brain wave signals.