Improving the quality of multifocal visual evoked potential results by calculating multiple virtual channels

Mazinani, Babac; Waberski, Till Dino; Weinberger, A; Walter, Peter; Roessler, Gernot

doi:10.1007/s10384-011-0040-4

Cited by 4 publications

(3 citation statements)

References 10 publications

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“…In this context, various studies have attempted to improve the diagnostic capacity of the mfVEP technique either by enhancing the visual stimulus parameters [ 10 ], by altering the number of electrodes used and their localization, by adding virtual channels [ 11 ], by investigating offline signal processing methods such as principal component analysis [ 12 ], by using wavelets [ 13 ] or by applying Prony’s method as a filter [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

Empirical mode decomposition processing to improve multifocal-visual-evoked-potential signal analysis in multiple sclerosis

et al. 2018

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ObjectiveTo study the performance of multifocal-visual-evoked-potential (mfVEP) signals filtered using empirical mode decomposition (EMD) in discriminating, based on amplitude, between control and multiple sclerosis (MS) patient groups, and to reduce variability in interocular latency in control subjects.MethodsMfVEP signals were obtained from controls, clinically definitive MS and MS-risk progression patients (radiologically isolated syndrome (RIS) and clinically isolated syndrome (CIS)). The conventional method of processing mfVEPs consists of using a 1–35 Hz bandpass frequency filter (XDFT).The EMD algorithm was used to decompose the XDFT signals into several intrinsic mode functions (IMFs). This signal processing was assessed by computing the amplitudes and latencies of the XDFT and IMF signals (XEMD). The amplitudes from the full visual field and from ring 5 (9.8–15° eccentricity) were studied. The discrimination index was calculated between controls and patients. Interocular latency values were computed from the XDFT and XEMD signals in a control database to study variability.ResultsUsing the amplitude of the mfVEP signals filtered with EMD (XEMD) obtains higher discrimination index values than the conventional method when control, MS-risk progression (RIS and CIS) and MS subjects are studied. The lowest variability in interocular latency computations from the control patient database was obtained by comparing the XEMD signals with the XDFT signals. Even better results (amplitude discrimination and latency variability) were obtained in ring 5 (9.8–15° eccentricity of the visual field).ConclusionsFiltering mfVEP signals using the EMD algorithm will result in better identification of subjects at risk of developing MS and better accuracy in latency studies. This could be applied to assess visual cortex activity in MS diagnosis and evolution studies.

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Section: Introductionmentioning

confidence: 99%

Empirical mode decomposition processing to improve multifocal-visual-evoked-potential signal analysis in multiple sclerosis

et al. 2018

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“…In [33] research the advantages of a prediction method based on 40 virtual electrodes. Using a database of 15 healthy participants, the standard method (bandwidth of 1 Hz-2 kHz) obtains an SNR S of 3.877 1.08, while with the prediction method the SNR S is 4.36 71.03, representing a gain of þ12.66%.…”

Section: Discussionmentioning

confidence: 99%

Filtering multifocal VEP signals using Prony’s method

Fernández

Santiago

Blanco

et al. 2015

Computers in Biology and Medicine

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“…The monocular response amplitude, defined as SNR, is used to analyse mfVEP signals in multiple sclerosis patients [24]. The type of analysis could be use to evaluate the advantages of using an mfVEP-signal prediction method on various points on the skull [25]; to compare various multifocal visual stimulation methods [4]; or to evaluate the effects of eccentricity on contrast response characteristics [21].…”

Section: Introductionmentioning

confidence: 99%

A new method for quantifying mfVEP signal intensity in multiple sclerosis

Castillo

Santiago

Fernández

et al. 2015

Biomedical Signal Processing and Control

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Improving the quality of multifocal visual evoked potential results by calculating multiple virtual channels

Abstract: 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.

Cited by 4 publications

References 10 publications

Empirical mode decomposition processing to improve multifocal-visual-evoked-potential signal analysis in multiple sclerosis

Empirical mode decomposition processing to improve multifocal-visual-evoked-potential signal analysis in multiple sclerosis

Filtering multifocal VEP signals using Prony’s method

A new method for quantifying mfVEP signal intensity in multiple sclerosis

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