A comparison among different techniques for human ERG signals processing and classification
A comparison among different techniques for human ERG signals processing and classification
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DOI：
10.1016/j.ejmp.2013.03.006
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发表时间：
2014-02-01
影响因子：
3.4
通讯作者：
Tranchina, L.
中科院分区：
文献类型：
--
作者：
Barraco, R.;Adorno, D. Persano;Tranchina, L.
生物医学信号的特征检测对于加深我们对相关生理过程的认识至关重要。为了实现这一目标，可以应用许多分析方法，但只有少数能够处理具有时间相关特征的信号，这些信号可以提供有用的临床信息。在生物医学信号中，视网膜电图（ERG）记录了视网膜对闪光灯的反应，可以提高我们对复杂的光感受器活动的理解。本研究的重点是分析人体光感受器系统的早期反应，即a波ergg成分。这种波反映了光感受器，视杆细胞和视锥细胞的功能完整性，其激活动力学尚未完全了解。此外，由于在早期的光感受器病理中，最终的a波异常并不总是用“肉眼”分析痕迹来检测到，因此，通过适当的分析技术区分病理痕迹和健康痕迹的可能性可能有助于临床诊断。在本文中，我们讨论并比较了各种信号处理技术，如傅里叶分析（FA），主成分分析（PCA），小波分析（WA）在识别病理痕迹和健康痕迹方面的效率。研究的视网膜病变有色盲、视锥疾病和先天性静止性夜盲症，它们影响光感受器信号的传递。我们的研究结果证明，传统ERGs的PCA和FA都不能为眼部病变的诊断提供有用的临床信息，而基于小波变换的更复杂的分析为患者的常规临床检查提供了有力的工具。(C) 2013年意大利医药工业协会。Elsevier Ltd.出版。版权所有。
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. (C) 2013 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.