Evaluation of empirical mode decomposition for event-related potential analysis
Williams, N., Nasuto, S. and Saddy, D. (2011) Evaluation of empirical mode decomposition for event-related potential analysis. EURASIP Journal on Advances in Signal Processing, 2011. pp. 1-11. ISSN 1687-6180
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To link to this article DOI: 10.1155/2011/965237
Current methods for estimating event-related potentials (ERPs) assume stationarity of the signal. Empirical Mode Decomposition (EMD) is a data-driven decomposition technique that does not assume stationarity. We evaluated an EMD-based method for estimating the ERP. On simulated data, EMD substantially reduced background EEG while retaining the ERP. EMD-denoised single trials also estimated shape, amplitude, and latency of the ERP better than raw single trials. On experimental data, EMD-denoised trials revealed event-related differences between two conditions (condition A and B) more effectively than trials lowpass filtered at 40 Hz. EMD also revealed event-related differences on both condition A and condition B that were clearer and of longer duration than those revealed by low-pass filtering at 40 Hz. Thus, EMD-based denoising is a promising data-driven, nonstationary method for estimating ERPs and should be investigated further.