Filtering multifocal VEP signals using Prony's method. (1st January 2015) - Fernández, A.; de Santiago, L.; Blanco, R.; Pérez-Rico, C.; Rodríguez-Ascariz, J.M.; Barea, R.; Miguel-Jiménez, J.M.; García-Luque, J.R.; Ortiz del Castillo, M.; Sánchez-Morla, E.M.; Boquete, L.
Abstract: Background: This paper describes use of Prony's method as a filter applied to multifocal visual-evoked-potential (mfVEP) signals. Prony's method can be viewed as an extension of Fourier analysis that allows a signal to be decomposed into a linear combination of functions with different amplitudes, damping factors, frequencies and phase angles. Method: By selecting Prony method parameters, a frequency filter has been developed which improves signal-to-noise ratio (SNR). Three different criteria were applied to data recorded from control subjects to produce three separate datasets: unfiltered raw data, data filtered using the traditional method (fast Fourier transform: FFT), and data filtered using Prony's method. Results: Filtering using Prony's method improved the signals' original SNR by 44.52%, while the FFT filter improved the SNR by 33.56%. The extent to which signal can be separated from noise was analysed using receiver–operating–characteristic (ROC) curves. The area under the curve (AUC) was greater in the signals filtered using Prony's method than in the original signals or in those filtered using the FFT. Conclusion: filtering using Prony's method improves the quality of mfVEP signal pre-processing when compared with the original signals, or with those filtered using the FFT. Highlights: A new filter method based on Prony's method has been proposed. Main parameters of Prony's method have been adjusted to obtain maximum gain. Quality of signals filtered with three different methods have been compared. Prony's method improves the quality of mfVEP signals. A great number of analysable visual-field sectors has been obtained