L de Santiago1, A Klistorner2, M Ortiz1, A J Fernández-Rodríguez1, J M Rodríguez Ascariz1, R Barea1, J M Miguel-Jiménez1, L Boquete3. 1. Department of Electronics, University of Alcalá, Plaza de S. Diego, s/n, 28801 Alcalá de Henares, Spain. 2. Department of Ophthalmology Sydney EYE Hospital, 8 Macquarie St, Sydney, NSW 2000, Australia. 3. Department of Electronics, University of Alcalá, Plaza de S. Diego, s/n, 28801 Alcalá de Henares, Spain. Electronic address: luciano.boquete@uah.es.
Abstract
BACKGROUND: This paper describes a new non-commercial software application (mfVEP(2)) developed to process multifocal visual-evoked-potential (mfVEP) signals in latency (monocular and interocular) progression studies. METHOD: The software performs analysis by cross-correlating signals from the same patients. The criteria applied by the software include best channels, signal window, cross-correlation limits and signal-to-noise ratio (SNR). Software features include signal display comparing different tests and groups of sectors (quadrants, rings and hemispheres). RESULTS: The software's performance and capabilities are demonstrated on the results obtained from a patient with acute optic neuritis who underwent 9 follow-up mfVEP tests. Numerical values and graphics are presented and discussed for this case. CONCLUSIONS: The authors present a software application used to study progression in mfVEP signals. It is also useful in research projects designed to improve mfVEP techniques. This software makes it easier for users to manage the signals and allows them to choose various ways of selecting signals and representing results.
BACKGROUND: This paper describes a new non-commercial software application (mfVEP(2)) developed to process multifocal visual-evoked-potential (mfVEP) signals in latency (monocular and interocular) progression studies. METHOD: The software performs analysis by cross-correlating signals from the same patients. The criteria applied by the software include best channels, signal window, cross-correlation limits and signal-to-noise ratio (SNR). Software features include signal display comparing different tests and groups of sectors (quadrants, rings and hemispheres). RESULTS: The software's performance and capabilities are demonstrated on the results obtained from a patient with acute optic neuritis who underwent 9 follow-up mfVEP tests. Numerical values and graphics are presented and discussed for this case. CONCLUSIONS: The authors present a software application used to study progression in mfVEP signals. It is also useful in research projects designed to improve mfVEP techniques. This software makes it easier for users to manage the signals and allows them to choose various ways of selecting signals and representing results.
Authors: Luis de Santiago; Eva Sánchez-Morla; Román Blanco; Juan Manuel Miguel; Carlos Amo; Miguel Ortiz Del Castillo; Almudena López; Luciano Boquete Journal: PLoS One Date: 2018-04-20 Impact factor: 3.240