Peak component latency-corrected average method for evoked potential waveform estimation.
A peak component latency-corrected average (PC-LCA) method consisting of three steps is presented for estimating the evoked potentials (EP) in the human brain. The present PC-LCA is essentially an alternative version of the original LCA method developed by McGillem et al. It first uses a time-varying adaptive filter as a preprocessor to suppress the ongoing EEG and to enhance the EP. Then, the statistics of mean latencies and amplitudes of the EP peak components are estimated by a peak detection and alignment procedure. The final waveform estimate is obtained by superimposing the estimated mean peak components on background information and subsequently fitting a truncated Fourier series using the fast Fourier transform (FFT). Consistent estimates of the EP peak component information are established based on asymptotic analysis of the PC-LCA. Finally, real-time implementation of the PC-LCA is considered, and the superior performance of the PC-LCA method is confirmed by detailed numerical results.
Yu
X H
XH
Department of Radio Engineering, Southeast University, Nanjing, P. R. China.
Zhang
Y S
YS
He
Z Y
ZY
D004569:Electroencephalography; D005071:Evoked Potentials; D016057:Evoked Potentials, Auditory, Brain Stem / Q000502:physiology*; D005583:Fourier Analysis; D006801:Humans; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation