Abstract
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.
Highlights
Using the amplitude of the Multifocal visual evoked potentials (mfVEPs) signals filtered with empirical mode decomposition (EMD) (XEMD) obtains higher discrimination index values than the conventional method when control, multiple sclerosis (MS)-risk progression (RIS and clinically isolated syndrome (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
Filtering mfVEP signals using the EMD algorithm will result in better identification of subjects at risk of developing MS and better accuracy in latency studies
Summary
MfVEPThe visual-evoked-potentials (VEP) test is a diagnostic tool that allows an objective assessment of the visual pathway. The conventional visual evoked potential (cVEP) measures the electrophysiological signals obtained by stimulating the full visual field using flash or checkerboard stimuli. The cVEP produces an overall response in the primary visual cortex [1], but it does not provide specific topographical information about the retina and visual cortex [2]. The multifocal-visual-evoked-potentials (mfVEP) technique permits analysis of the topographical features of different sectors of the visual field represented in the visual cortex [3,4]. Several studies [5,6,7] have shown how the mfVEP technique overcomes most of the limitations of conventional VEPs because it allows for the simultaneous recording of local responses from many visual field sectors (up to 120). The mfVEP technique has already been shown to be more sensitive than standard automated perimetry for the early detection of visual field defects in multiple sclerosis (MS) [8,9] and other optic neuropathies, such as glaucoma [2]
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