Transform domain adaptive enhancement filter for evoked potential

This paper is to present the use of transform domain adaptive filter (TDADF) to process evoked potential (EP). The use of adaptive filter (ADF) in processing EP is effective than traditional averaging method. However to design an ADF with normalized LMS with good convergence performance is not an easy task. Thus, we proposed the TDADF method to improve the convergence performance of processing EP. Simulations were conducted to obtain the SNR of visual evoked potential. Moreover, collected data from somatosensory evoked potential was used in the testing. We observed that TDADF method has better performance than ADF with normalized LMS algorithm.