單通道腦電信號(hào)中眼電干擾的自動(dòng)分離方法
doi: 10.11999/JEIT140602
基金項(xiàng)目:
國(guó)家自然科學(xué)基金(61171186, 61271345)，語(yǔ)言語(yǔ)音教育部-微軟重點(diǎn)實(shí)驗(yàn)室開(kāi)放基金(HIT.KLOF.2011XXX)和中央高?；究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)資金(HIT.NSRIF.2012047)資助課題
Automatic Electrooculogram Separation Method for Single Channel Electroencephalogram Signals
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摘要: 當(dāng)前主流的眼電(EOG)去除方法需要利用多通道腦電的相關(guān)性，難以在單通道的便攜式腦機(jī)接口(BCI)中應(yīng)用。該文提出一種基于長(zhǎng)時(shí)差分振幅包絡(luò)與小波變換的眼電干擾自動(dòng)分離方法。首先在原腦電信號(hào)的長(zhǎng)時(shí)差分振幅包絡(luò)上實(shí)施雙門(mén)限法來(lái)精確檢測(cè)眼電的起止點(diǎn)，然后利用sym5小波對(duì)腦電進(jìn)行分解并引進(jìn)Birg_Massart策略來(lái)自適應(yīng)地確定小波重構(gòu)系數(shù)閾值，最后通過(guò)小波重構(gòu)精確地估計(jì)眼電，實(shí)現(xiàn)單通道上眼電與腦電的自動(dòng)分離。大量實(shí)驗(yàn)證明，該方法與主流的平均偽跡回歸分析和基于獨(dú)立成分分析(ICA)的方法相比，能夠獲得更好的估計(jì)眼電與原眼電的相關(guān)性，保證更高的校正信噪比和較強(qiáng)的實(shí)時(shí)性，能夠滿足腦機(jī)接口多方面的需要。
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關(guān)鍵詞:
- 單通道腦電信號(hào) /
- 眼電分離 /
- 小波變換 /
- 長(zhǎng)時(shí)差分振幅包絡(luò)
Abstract: The traditional ElectroOculoGram (EOG) correction methods usually use the correlation information of multi-channel ElectroEncephaloGram (EEG), and are difficult to apply to portable Brain-Computer Interface (BCI) in single channel. An automatic EOG separation method is proposed based on the long term difference amplitude envelope and the wavelet transformation in the paper. Firstly, the accurate EOG beginning and ending points are detected on the long term difference amplitude envelope of the original EEG through a dual thresholds method. Secondly, the sym5 wavelet is applied to decompose the original EEG signal, and the Birg_Massart strategy is introduced to adaptively determine the thresholds of wavelet coefficients. Finally, the EOG is accurately reconstructed and separated from the EEG in this channel. Compared with the popular regression analysis of averaging artifact and the Independent Component Analysis (ICA) based methods, the proposed method is proved to achieve a better correlation measure between the separated EOG and the original EOG, a higher signal-to-noise ratio of the corrected EEG, and a good real-time operating speed for most BCI application requirements. -
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