Wavelet analysis of human photoreceptoral response

R. Barraco, D. P. Adorno, M. Brai
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引用次数: 7

Abstract

Feature detection of biomedical signals is crucial for deepening our knowledge of the physiological phenomena giving rise to them. To achieve this aim, even if many analytic approaches have been suggested only few are able to deal with signals whose features are time dependent, and to provide useful clinical information. In this work we use the wavelet analysis to extract peculiarities of the early response of the photoreceptoral human system, known as a-wave ERG-component. The analysis of the a-wave features is important since this component reflects the functional integrity of the two populations of photoreceptors, rods and cones whose activation dynamics are not well known. Moreover, in incipient photoreceptoral pathologies the eventual anomalies in a-wave are not always detectable with a naked eye analysis of the traces. We here propose the possibility to discriminate the pathologic from the healthy traces throughout the differentiation of their time-frequency characteristics, revealed by the wavelet analysis. The investigated pathologies are the Achromatopsia, a cone disease and the Congenital Stationary Night Blindness, a rod trouble. The results show that the number of stable frequencies present and their times of occurrence are indicative of the status of the retinal photoreceptors. In particular, in the pathological cases, the frequency components shift toward lower values and change their times of occurrence, with respect to healthy traces.
人体光感受器反应的小波分析
生物医学信号的特征检测对于加深我们对产生这些信号的生理现象的认识至关重要。为了实现这一目标,即使已经提出了许多分析方法,但只有少数能够处理特征与时间相关的信号,并提供有用的临床信息。在这项工作中,我们使用小波分析来提取人体光感受器系统的早期反应特性,称为a波ergg成分。对a波特征的分析很重要,因为这一成分反映了两种光感受器的功能完整性,杆状体和锥状体,其激活动力学尚不清楚。此外,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的。我们在这里提出了通过小波分析揭示的病理痕迹的时频特征的区分来区分病理痕迹和健康痕迹的可能性。所调查的病理是色盲,一种锥体疾病和先天性静止性夜盲症,一种杆状疾病。结果表明,存在稳定频率的数量及其出现的次数表明视网膜光感受器的状态。特别是,在病理情况下,频率分量向较低的值移动,并改变其出现的时间,相对于健康的痕迹。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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