Wavelet-Based Muscle Artefact Noise Reduction for Short Latency rTMS Evoked Potentials.

This paper presents a new method of reducing the noise in the EEG response signal recorded during repetitive transcranial magnetic stimulation (rTMS). This noise is principally composed of the residual stimulus artefact and millivolt amplitude compound muscle action potentials (CMAP) recorded from the scalp muscles and precludes analysis of the cortical evoked potentials, especially during the first 20-ms post stimulus. The proposed method uses the wavelet transform with a fourth-order Daubechies mother wavelet and a novel coefficient reduction algorithm based on cortical amplitude thresholds. Four other mother wavelets as well as digital filtering have been tested, and the Coiflets 2 and 3 also found to be effective with Coiflet 3 results marginally better than Daubechies 4. The approach has been tested using data recorded from 16 normal subjects during a study of cortical sensitivity to rTMS at different cortical locations using stimulation amplitudes, frequencies, and sites typically used in clinical practice to treat major depressive disorder.

Application of wavelet based denoising techniques to rTMS evoked potentials.

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.