Single-trial evoked potential estimation using wavelets

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• 作者：Zhisong Wang ; Alex ; er Maier ; David A. Leopold ; Nikos K. Logothetis ; Hualou Liang
• 关键词：Wavelet ; Single-trial ; Evoked potential ; Local field potential (LFP) ; Multiunit activity (MUA) ; Translation-invariant ; Structure-from-motion (SFM) ; LMS ; RLS ; Wiener
• 刊名：Computers in Biology and Medicine
• 出版年：2007
• 出版时间：April 2007
• 年：2007
• 卷：37
• 期：4
• 页码：463-473
• 全文大小：605 K

文摘

In this paper we present conventional and translation-invariant (TI) wavelet-based approaches for single-trial evoked potential estimation based on intracortical recordings. We demonstrate that the wavelet-based approaches outperform several existing methods including the Wiener filter, least mean square (LMS), and recursive least squares (RLS), and that the TI wavelet-based estimates have higher SNR and lower RMSE than the conventional wavelet-based estimates. We also show that multichannel averaging significantly improves the evoked potential estimation, especially for the wavelet-based approaches. The excellent performances of the wavelet-based approaches for extracting evoked potentials are demonstrated via examples using simulated and experimental data.