2018
DOI: 10.1371/journal.pone.0194964
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Empirical mode decomposition processing to improve multifocal-visual-evoked-potential signal analysis in multiple sclerosis

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 met… Show more

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Cited by 11 publications
(10 citation statements)
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“…As previously described 20 , 23 , mfVEP signals were recorded monocularly with VERIS software 5.9 (Electro-Diagnostic Imaging, Inc., Redwood City, CA). The visual stimulus was a scaled dartboard with a diameter of 44.5 degrees, containing 60 sectors, each with 16 alternating checks.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…As previously described 20 , 23 , mfVEP signals were recorded monocularly with VERIS software 5.9 (Electro-Diagnostic Imaging, Inc., Redwood City, CA). The visual stimulus was a scaled dartboard with a diameter of 44.5 degrees, containing 60 sectors, each with 16 alternating checks.…”
Section: Methodsmentioning
confidence: 99%
“…Traditional analysis of mfVEP recordings is based on the study of the recordings’ amplitudes and latencies 16 , 18 . However, it has been demonstrated that in some cases diagnosis using mfVEP signals can be improved using advanced signal filtering and extraction algorithms, such as the wavelet transform 19 , empirical mode decomposition 20 , and singular spectrum analysis 21 , among other alternatives.…”
Section: Introductionmentioning
confidence: 99%
“…The practical aspects of taking mfVEP recordings have been described in previous papers [8,32]. Briefly, VERIS software 5.9 (Electro-Diagnostic Imaging, Inc., Redwood City, CA) was used to obtain 6 channels for each of the 60 sectors into which the visual field is divided.…”
Section: Methodsmentioning
confidence: 99%
“…The latest clinical decision support systems for diagnosing MS are based on artificial intelligence analyze multifocal visual evoked potentials (mfVEP) [34], optical coherence tomography [69], EEG signals [70], functional magnetic resonance imaging (fMRI) [71], among others. Biomedical data fusion with advanced strategies for the analysis by selecting those more discriminant parameters from each exploratory test would reduce the decision error probability, increase reliability, and therefore reach an earlier and more precise diagnosis.…”
Section: Limitations and Future Workmentioning
confidence: 99%
“…In biomedical signal analysis, EMD has been used to filter multifocal visual-evoked potentials in MS diagnosis (selecting only the IMF with the highest amplitude [34]) or to analyze gamma-band activity in single-channel electroencephalography (EEG) signals [35]. EEMD was used by Naik et al [36] in single-channel electromyography (EMG) signal classification and by Chang to remove artefacts in electrocardiograms [37].…”
Section: Introductionmentioning
confidence: 99%