Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Evaluation of Empirical Mode Decomposition for Event-Related Potential Analysis | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2011 Article ID 965237 11 pages doi 2011 965237 Research Article Evaluation of Empirical Mode Decomposition for Event-Related Potential Analysis N. Williams S. J. Nasuto and J. D. Saddy Centre for Integrative Neuroscience and Neurodynamics CINN University of Reading Reading RG6 6AY UK Correspondence should be addressed to N. Williams sir07nw@ Received 2 July 2010 Revised 1 December 2010 Accepted 21 January 2011 Academic Editor Patrick Flandrin Copyright 2011 N. Williams et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 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. 1. Introduction Event-related potentials ERPs are changes in the ongoing electroencephalographic EEG signal related to processing of a stimulus 1 . The amplitude of ERP is usually much lower than that of the background EEG and is hard to visualise at the level of .
