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Journal Article

Single-trial evoked potential estimation using wavelets


Logothetis,  NK
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Wong, Z., Maier, A., Leopold, D., Logothetis, N., & Liang, H. (2007). Single-trial evoked potential estimation using wavelets. Computers in Biology and Medicine, 37(4), 463-473. doi:10.1016/j.compbiomed.2006.08.011.

Cite as: https://hdl.handle.net/21.11116/0000-0003-CBFD-C
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.