Single-trial evoked potential estimation using wavelets

Wong, Z; Maier, A; Leopold, DA; Logothetis, NK; Liang, H

doi:10.1016/j.compbiomed.2006.08.011

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

Single-trial evoked potential estimation using wavelets

MPS-Authors

/persons/resource/persons84063

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;

External Resource

https://www.sciencedirect.com/science/article/pii/S0010482506001284
(Publisher version)

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

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

Abstract

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.