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An approach based on wavelet analysis for feature extraction in the a-wave of the electroretinogram.

Abstract：

:Most biomedical signals are non-stationary. The knowledge of their frequency content and temporal distribution is then useful in a clinical context. The wavelet analysis is appropriate to achieve this task. The present paper uses this method to reveal hidden characteristics and anomalies of the human a-wave, an important component of the electroretinogram since it is a measure of the functional integrity of the photoreceptors. We here analyse the time-frequency features of the a-wave both in normal subjects and in patients affected by Achromatopsia, a pathology disturbing the functionality of the cones. The results indicate the presence of two or three stable frequencies that, in the pathological case, shift toward lower values and change their times of occurrence. The present findings are a first step toward a deeper understanding of the features of the a-wave and possible applications to diagnostic procedures in order to recognise incipient photoreceptoral pathologies.

journal_name

Comput Methods Programs Biomed

journal_title

Computer methods and programs in biomedicine

authors

Barraco R,Persano Adorno D,Brai M

doi

10.1016/j.cmpb.2011.05.001

subject

Has Abstract

pub_date

2011-12-01 00:00:00

pages

316-24

issue

3

eissn

0169-2607

issn

1872-7565

pii

S0169-2607(11)00116-7

journal_volume

104

pub_type

杂志文章

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