title: Filtering mfVEP signals using Wiener filter.
abstract: The multifocal visual-evoked-potential (mfVEP) signals are filtered using the Wiener filter combined with a Fast Fourier Transform and their signal-to-noise ratios are compared against those of unfiltered signals (RAW data) and those of signals filtered using the traditional method (FFT data). The Wiener filter improves the original signals' SNR by 37.49%, while the FFT improves the SNR by 20.41%. This gain is achieved by selecting the best channel in each sector of the visual field. In conclusion, filtering using the Wienerś method improves the quality of mfVEP signal pre-processing when compared against the original signals, or against filtering using the FFT.
authors.affiliation: Department of Electronics, University of Alcalá, Alcalá de Henares, Spain.
authors.forename: M
authors.initials: M
authors.lastname: Ortiz Del Castillo
authors.affiliation: Department of Electronics, University of Alcalá, Alcalá de Henares, Spain.
authors.forename: L
authors.initials: L
authors.lastname: de Santiago
authors.affiliation: Department of Electronics, University of Alcalá, Alcalá de Henares, Spain.
authors.forename: A
authors.initials: A
authors.lastname: Fernández
authors.affiliation: Department of Electronics, University of Alcalá, Alcalá de Henares, Spain.
authors.forename: J R
authors.initials: JR
authors.lastname: García-Luque
authors.affiliation: Department of Psychiatry, University Hospital of Guadalajara, Spain.
authors.forename: E M
authors.initials: EM
authors.lastname: Sánchez-Morla
authors.affiliation: Department of Electronics, University of Alcalá, Alcalá de Henares, Spain.
authors.forename: L
authors.initials: L
authors.lastname: Boquete
mesh_terms: D003941:Diagnostic Techniques, Ophthalmological; D005074:Evoked Potentials, Visual / Q000502:physiology*; D005901:Glaucoma / Q000000981:diagnostic imaging*; D006801:Humans; D012815:Signal Processing, Computer-Assisted