A comparison among different techniques for human ERG signals processing and classification

Abstract

Feature detection in biomedical signals is crucial for deepening our knowledge about the involved physiological processes. To achieve this aim, many analytic approaches can be applied but only few are able to deal with signals whose time dependent features provide useful clinical information. Among the biomedical signals, the electroretinogram (ERG), that records the retinal response to a light flash, can improve our comprehension of the complex photoreceptoral activities. The present study is focused on the analysis of the early response of the photoreceptoral human system, known as a-wave ERG-component. This wave reflects the functional integrity of the photoreceptors, rods and cones, whose activation dynamics are not yet completely understood. Moreover, since in incipient photoreceptoral pathologies eventual anomalies in a-wave are not always detectable with a "naked eye" analysis of the traces, the possibility to discriminate pathologic from healthy traces, by means of appropriate analytical techniques, could help in clinical diagnosis. In the present paper, we discuss and compare the efficiency of various techniques of signal processing, such as Fourier analysis (FA), Principal Component Analysis (PCA), Wavelet Analysis (WA) in recognising pathological traces from the healthy ones. The investigated retinal pathologies are Achromatopsia, a cone disease and Congenital Stationary Night Blindness, affecting the photoreceptoral signal transmission. Our findings prove that both PCA and FA of conventional ERGs, don't add clinical information useful for the diagnosis of ocular pathologies, whereas the use of a more sophisticated analysis, based on the wavelet transform, provides a powerful tool for routine clinical examinations of patients.

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

“…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.…”

“…It has been used to analyze the photopic negative response in the full-field ERG of healthy subjects [ 22 ]. Barraco et al [ 23 ] compared different analytical approaches (including application of the continuous wavelet transform, CWT) to analyze the a -wave of the full-field ERG, demonstrating consistently altered photoreceptor behavior in various diseases. Nair and Joseph [ 24 ] could differentiate patients with congenital stationary night blindness, rod–cone dystrophy and central retinal occlusion from healthy controls using wavelet analysis of the full-field ERG.…”

Active learning in a real‐world bioengineering problem: A pilot‐study on ophthalmologic data processing

“…The students had attended a previous focus session lasting 8 hr, covering the features of the ERG and the different techniques of data processing, such as the Fourier Transform, the Wavelet Analysis, the Principal Component Analysis, etc. . In particular, for improving and speeding up the clinical analysis and classification of the ERGs, during the regular lectures, a procedure based on the Empirical Mode Decomposition (EMD) coupled with an Artificial Neural Network (ANN), has been explicated to the students; this method turned out to be very effective and adequate for processing ophthalmologic data .…”

“…In clinical routine, the widespread method used to analyze the ERGs is based on the visual examination of the morphology of the waveforms. However, this analysis often fails to detect or to recognize an eventual pathology or its degree of seriousness; consequently, more sophisticated clinical ophthalmologic investigations are required [6,8]. These are time‐consuming, expensive, and may imply patient displacements.…”

Comparison among Short Time Fourier Transform and Continuous Wavelet Transform Techniques in Flash Erg Signals Processing

“…2014 yılında yapılan başka bir çalışmada herhangi bir göz rahatsızlığı bulunmayan sağlıklı bireylerden ve akromatopsi ile doğuştan sabit gece körlüğü bulunan bireylerden alınan fERG sinyallerinin 'a' bileşenlerinin analizinde farklı sinyal işleme tekniklerinin (PCA, FA ve DA) başarımlarını karşılaştırmışlardır. Yöntemlerin içerisinde Meksika şapka dalgacığın kullanıldığı DA yönteminin diğer yöntemlere kıyasla daha başarılı olduğu tespit edilmiştir [19]. Mathieu Gauvin ve ark.…”