A novel method for separating the components of the clinical electroretinogram

Varadharajan, Srinivasa; Fitzgerald, Kathleen; Lakshminarayanan, Vasudevan

doi:10.1080/09500340600855122

Cited by 11 publications

(8 citation statements)

References 22 publications

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“…Review of the literature showed that several mother wavelets have been applied in DWT of the ERG response, such as the “Daubechies” wavelets [ 20 , 21 , 25 ], the “Haar” wavelet [ 24 , 35 ] and the “Mexican hat” [ 23 , 36 , 37 ]. For glaucoma, Miguel-Jiménez et al have successfully applied DWT to the global flash mfERG response in advanced glaucoma.…”

Section: Methodsmentioning

confidence: 99%

“…Its use has been increasingly studied and applied either to improve the interpretation of the biosignal itself (ECG [ 17 ], EMG [ 18 ]) or to exclude interference between signals [ 19 ]. In electrophysiology of vision, this method has been introduced a decade ago [ 20 , 21 ]. It has been used to analyze the photopic negative response in the full-field ERG of healthy subjects [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

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Wavelet decomposition analysis in the two-flash multifocal ERG in early glaucoma: a comparison to ganglion cell analysis and visual field

Monhart¹,

Schötzau

Ledolter

et al. 2017

Doc Ophthalmol

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PurposeTo further improve analysis of the two-flash multifocal electroretinogram (2F-mfERG) in glaucoma in regard to structure–function analysis, using discrete wavelet transform (DWT) analysis.MethodsSixty subjects [35 controls and 25 primary open-angle glaucoma (POAG)] underwent 2F-mfERG. Responses were analyzed with the DWT. The DWT level that could best separate POAG from controls was compared to the root-mean-square (RMS) calculations previously used in the analysis of the 2F-mfERG. In a subgroup analysis, structure–function correlation was assessed between DWT, optical coherence tomography and automated perimetry (mf103 customized pattern) for the central 15°.ResultsFrequency level 4 of the wavelet variance analysis (144 Hz, WVA-144) was most sensitive (p < 0.003). It correlated positively with RMS but had a better AUC. Positive relations were found between visual field, WVA-144 and GCIPL thickness. The highest predictive factor for glaucoma diagnostic was seen in the GCIPL, but this improved further by adding the mean sensitivity and WVA-144.ConclusionsmfERG using WVA analysis improves glaucoma diagnosis, especially when combined with GCIPL and MS.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Wavelet decomposition analysis in the two-flash multifocal ERG in early glaucoma: a comparison to ganglion cell analysis and visual field

Monhart¹,

Schötzau

Ledolter

et al. 2017

Doc Ophthalmol

View full text Add to dashboard Cite

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“…Up to now, wavelet techniques have been applied in electrophysiology to separate the components of the clinical ERG (Varadharajan et al 2007) and to analyze the dynamics of the oscillatory potentials in the rat retinal response (Forte et al 2008). …”

Section: Introductionmentioning

confidence: 99%

ERG signal analysis using wavelet transform

2011

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The wavelet analysis is a powerful tool for analyzing and detecting features of signals characterized by time-dependent statistical properties, as biomedical signals. The identification and the analysis of the components of these signals in the time-frequency domain, give meaningful information about the physiological mechanisms that govern them. This article presents the results of the wavelet analysis applied to the a-wave component of the human electroretinogram. In order to deepen and improve our knowledge about the behavior of the early photoreceptoral response, including the possible activation of interactions and correlations among the photoreceptors, we have detected and identified the stable time-frequency components of the a-wave, using six representative values of luminance. The results indicate the occurrence of three frequencies lying in the range 20-200 Hz. The lowest one is attributed to the summed activities of the photoreceptors. The others are weaker and at low luminance one of them does not occur. We relate them to the response of the rods and the cones whose aggregate activities are non-linear and typically exhibit self-organization under selective stimuli. The identification of the stable frequency components and of their times of occurrence helps us to shine light about the complex mechanisms governing the a-wave. The present results are promising toward the assessment of more refined model concerning the photoreceptoral activities.

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“…Moreover, DWT coefficients were shown to be superior to traditional TD measures in segregating normal and pathological PERG waveforms using principal components analysis (Rogala & Brykalski, 2005). It was also shown that it is possible to approximate the TD a-wave, b-wave, and at least one OP using the inverse DWT of the scotopic ERG waveform (Varadharajan, Fitzgerald, & Lakshminarayanan, 2007). Similarly, Miguel-Jiménez, Boquete, Ortega, Rodriguez-Ascariz, and Blanco (2010) used the DWT decomposition to reconstruct mfERG waveforms into different frequency bands and suggested that this approach could potentially be more sensitive to detect changes in glaucoma patients, compared to Humphrey visual field tests.…”

Section: Introductionmentioning

confidence: 99%

Functional decomposition of the human ERG based on the discrete wavelet transform

et al. 2015

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The morphology of the electroretinogram (ERG) can be altered as a result of normal and pathological processes of the retina. However, given that the ERG is almost solely assessed in terms of its amplitude and timing, defining the shape of the ERG waveform so that subtle, physiologically driven, morphological changes can be systematically and reproducibly detected remains a challenging problem. We examined if the discrete wavelet transform (DWT) could meet this challenge. Normal human photopic ERGs evoked to a broad range of luminance intensities (to yield waveforms of various shapes, amplitudes, and timings) were analyzed using DWT descriptors of the ERG. Luminance-response curves that were generated using the various DWT descriptors revealed distinct (p < 0.05) luminance-dependence patterns, indicating that the stimulus luminance differently modulates the various time-frequency components of the ERG and thus its morphology. The latter represents the first attempt to study the luminance-dependence of ERG descriptors obtained with the DWT. Analyses of ERGs obtained from patients affected with ON or OFF retinal pathway anomalies were also presented. We show here for the first time that distinct time-frequency descriptors can be specifically associated to the function of the ON and OFF cone pathway. Therefore, in this study, the DWT revealed reproducible, physiologically meaningful and diagnostically relevant descriptors of the ERG over a wide range of signal amplitudes and morphologies. The DWT analysis thus represents a valuable addition to the electrophysiologist's armamentarium that will improve the quantification and interpretation of normal and pathological ERG responses.

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A novel method for separating the components of the clinical electroretinogram

Cited by 11 publications

References 22 publications

Wavelet decomposition analysis in the two-flash multifocal ERG in early glaucoma: a comparison to ganglion cell analysis and visual field

Wavelet decomposition analysis in the two-flash multifocal ERG in early glaucoma: a comparison to ganglion cell analysis and visual field

ERG signal analysis using wavelet transform

Functional decomposition of the human ERG based on the discrete wavelet transform

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