ANC SCHEMES FOR THE ENHANCEMENT OF EEG SIGNALS IN THE PRESENCE OF EOGARTIFACTS

One of the most important applications of adaptive systems is in noise cancellation using adaptive filters. Ln this paper, we propose adapti ve noise cancellation schemes for the enhancement of EEG signals in th e presence of EOG artifacts. The effect of two reference inputs is stu died on simulated as well as recorded EEG signals and it is found that one reference input is enough to get sufficient minimization of EOG a rtifacts. This has been verified through correlation analysis also. We use signal to noise ratio and linear prediction spectra, along with t ime plots, for comparing the performance of the proposed schemes for m inimizing EOG artifacts from contaminated EEG signals. Results show th at the proposed schemes are very effective (especially the one which e mploys Newton's method) in minimizing the EOG artifacts from contamina ted EEG signals. (C) 1996 Academic Press, Inc.