Babac A E Mazinani1, Till D Waberski2, Andreas W A Weinberger3, Peter Walter3, Gernot F Roessler3. 1. Department of Ophthalmology, University Hospital RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Germany. bmazinani@gmx.de. 2. Department of Neurology, University Hospital RWTH Aachen, Aachen, Germany. 3. Department of Ophthalmology, University Hospital RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Germany.
Abstract
PURPOSE: To introduce a method for improvement of multifocal VEP (mfVEP) recordings by prediction of waveforms at multiple positions on the surface of the skull. METHODS: Fifteen healthy participants (mean age 24 ± 3.8 years) underwent mfVEP recordings from 3 surface positions. Two methods of a best-of-mfVEP approach were used and compared. In the first, a standard procedure, further data from 3 calculated channels were used. In the second approach, mfVEPs were obtained by using data derived from 40 virtual electrode positions on the basis of predictions from dipole source calculations. RESULTS: The mean signal-to-noise ratios (SNRs) of the best-of-mfVEPs of both methods were compared. The SNR was significantly higher for mfVEP data using additional virtual recordings revealed by dipole source determination (2.87 vs. 3.36; P < 0.035). CONCLUSION: We conclude that multichannel prediction of mfVEP responses based on dipole source calculation significantly improves the quality of the examination results compared with the currently prevalent standard method.
PURPOSE: To introduce a method for improvement of multifocal VEP (mfVEP) recordings by prediction of waveforms at multiple positions on the surface of the skull. METHODS: Fifteen healthy participants (mean age 24 ± 3.8 years) underwent mfVEP recordings from 3 surface positions. Two methods of a best-of-mfVEP approach were used and compared. In the first, a standard procedure, further data from 3 calculated channels were used. In the second approach, mfVEPs were obtained by using data derived from 40 virtual electrode positions on the basis of predictions from dipole source calculations. RESULTS: The mean signal-to-noise ratios (SNRs) of the best-of-mfVEPs of both methods were compared. The SNR was significantly higher for mfVEP data using additional virtual recordings revealed by dipole source determination (2.87 vs. 3.36; P < 0.035). CONCLUSION: We conclude that multichannel prediction of mfVEP responses based on dipole source calculation significantly improves the quality of the examination results compared with the currently prevalent standard method.
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