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Application of wavelet based denoising techniques to rTMS evoked potentials
Philip Chrapka1, Hubert de Bruin, Gary Hasey
1Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada. chrapkpk@mcmaster.ca
Abstract:
This paper presents a new method of removing noise from the EEG response signal recorded during repetitive transcranial magnetic stimulation (rTMS). This noise is principally composed of the residual stimulus artifact and mV amplitude compound muscle action potentials recorded from the scalp muscles and precludes analysis of the cortical evoked potentials, especially during the first 15 ms post stimulus. The method uses the wavelet transform with a fourth order Daubechies mother wavelet and a novel coefficient reduction algorithm based on cortical amplitude thresholds. The approach has been tested and two methods of coefficient reduction compared using data recorded during a study of cortical sensitivity to rTMS at different scalp locations.

