Application of prewhitening to AR spectral estimation of EEG

Conventional fast Fourier transform (FFT) and autoregressive (AR) spectral estimation techniques do not always perform well when applied to short segments of single trial EEG. On this class of EEG signal, the conventional FFT-based methods can suffer from significant leakage problems while conventional AR methods can suffer from problems related to model order selection and retention of spectral information in the residuals. An established alternative to the conventional AR estimation scheme called prewhitened AR spectral estimation, which theoretically addresses these drawbacks, was applied to EEG signals. Relative comparisons of the performance of a conventional FFT-based estimate, the conventional AR estimate, and the prewhitened AR estimate on three different examples of real, short-segment, single-trial EEGs are presented. These comparisons demonstrate that the prewhitened AR method overcomes the inherent drawbacks of the conventional methods.