RT info:eu-repo/semantics/article
T1 Continuous‑wavelet‑transform analysis of the multifocal ERG  waveform in glaucoma diagnosis
A1 Miguel Jiménez, Juan Manuel
A1 Blanco, R.
A1 Santiago Rodrigo, Luis de
A1 Fernández Rodríguez, Alfredo José
A1 Rodríguez Ascariz, José Manuel
A1 Barea Navarro, Rafael
A1 Martín Sánchez, José Luis
A1 Amo, C.
A1 Sánchez Morla, Eva María
A1 Boquete Vázquez, Luciano
K1 Glaucoma
K1 Multifocal ERG
K1 Continuous wavelet transform
K1 Neural network
K1 Electrónica
K1 Electronics
AB The vast majority of multifocal electroretinogram (mfERG) signal analyses to detect glaucoma study the signals’ amplitudes and latencies. The purpose of this paper is to investigate application of wavelet analysis of mfERG signals in diagnosis of glaucoma. This analysis method applies the continuous wavelet transform (CWT) to the signals, using the real Morlet wavelet. CWT coefficients resulting from the scale of maximum correlation are used as inputs to a neural network, which acts as a classifier. mfERG recordings are taken from the eyes of 47 subjects diagnosed with chronic open-angle glaucoma and from those of 24 healthy subjects. The high sensitivity in the classification (0.894) provides reliable detection of glaucomatous sectors, while the specificity achieved (0.844) reflects accurate detection of healthy sectors. The results obtained in this paper improve on the previous findings reported by the authors using the same visual stimuli and database.
PB Springer
YR 2015
FD 2015-04-08
LK http://hdl.handle.net/10017/49179
UL http://hdl.handle.net/10017/49179
LA eng
NO Ministerio de Ciencia e Innovación
DS MINDS@UW
RD 23-abr-2024