Steady-state sweep visual evoked potential processing denoised by wavelet transform

Heinar A. Weiderpass; Jorge F. Yamamoto; Solange R. Salomão; Adriana Berezovsky; Josenilson M. Pereira; Paula Y. Sacai; José Pedro de Oliveira; Marcio A. Costa; Marcelo N. Burattini

doi:10.1117/12.770371

6 March 2008 Steady-state sweep visual evoked potential processing denoised by wavelet transform

Heinar A. Weiderpass, Jorge F. Yamamoto, Solange R. Salomão, Adriana Berezovsky, Josenilson M. Pereira, Paula Y. Sacai, José Pedro de Oliveira, Marcio A. Costa, Marcelo N. Burattini

Author Affiliations +

Proceedings Volume 6917, Medical Imaging 2008: Image Perception, Observer Performance, and Technology Assessment; 69171A (2008) https://doi.org/10.1117/12.770371
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

Visually evoked potential (VEP) is a very small electrical signal originated in the visual cortex in response to periodic visual stimulation. Sweep-VEP is a modified VEP procedure used to measure grating visual acuity in non-verbal and preverbal patients. This biopotential is buried in a large amount of electroencephalographic (EEG) noise and movement related artifact. The signal-to-noise ratio (SNR) plays a dominant role in determining both systematic and statistic errors. The purpose of this study is to present a method based on wavelet transform technique for filtering and extracting steady-state sweep-VEP. Counter-phase sine-wave luminance gratings modulated at 6 Hz were used as stimuli to determine sweep-VEP grating acuity thresholds. The amplitude and phase of the second-harmonic (12 Hz) pattern reversal response were analyzed using the fast Fourier transform after the wavelet filtering. The wavelet transform method was used to decompose the VEP signal into wavelet coefficients by a discrete wavelet analysis to determine which coefficients yield significant activity at the corresponding frequency. In a subsequent step only significant coefficients were considered and the remaining was set to zero allowing a reconstruction of the VEP signal. This procedure resulted in filtering out other frequencies that were considered noise. Numerical simulations and analyses of human VEP data showed that this method has provided higher SNR when compared with the classical recursive least squares (RLS) method. An additional advantage was a more appropriate phase analysis showing more realistic second-harmonic amplitude value during phase brake.

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Heinar A. Weiderpass, Jorge F. Yamamoto, Solange R. Salomão, Adriana Berezovsky, Josenilson M. Pereira, Paula Y. Sacai, José Pedro de Oliveira, Marcio A. Costa, and Marcelo N. Burattini "Steady-state sweep visual evoked potential processing denoised by wavelet transform", Proc. SPIE 6917, Medical Imaging 2008: Image Perception, Observer Performance, and Technology Assessment, 69171A (6 March 2008); https://doi.org/10.1117/12.770371

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