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.

BARRACO, R., PERSANO ADORNO, D., BRAI, M. (2011). An approach based on wavelet analysis for feature extraction in the electroretinogram. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 104(104), 316-324 [10.1016/j.cmpb.2011.05.001].

An approach based on wavelet analysis for feature extraction in the electroretinogram

BARRACO, Rosita Maria Luisa;PERSANO ADORNO, Dominique;BRAI, Maria
2011-01-01

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.
2011
BARRACO, R., PERSANO ADORNO, D., BRAI, M. (2011). An approach based on wavelet analysis for feature extraction in the electroretinogram. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 104(104), 316-324 [10.1016/j.cmpb.2011.05.001].
File in questo prodotto:
File Dimensione Formato  
CMPB_2011.pdf

Solo gestori archvio

Descrizione: Articolo principale
Dimensione 1.35 MB
Formato Adobe PDF
1.35 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/61919
Citazioni
  • ???jsp.display-item.citation.pmc??? 5
  • Scopus 18
  • ???jsp.display-item.citation.isi??? 18
social impact