'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
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
