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Prediction of visual perceptions with artificial neural networks in a visual prosthesis for the blind.

Abstract：

:Within the framework of the OPTIVIP project, an optic nerve based visual prosthesis is developed in order to restore partial vision to the blind. One of the main challenges is to understand, decode and model the physiological process linking the stimulating parameters to the visual sensations produced in the visual field of a blind volunteer. We propose to use adaptive neural techniques. Two prediction models are investigated. The first one is a grey-box model exploiting the neurophysiological knowledge available up to now. It combines a neurophysiological model with artificial neural networks, such as multi-layer perceptrons and radial basis function networks, in order to predict the features of the visual perceptions. The second model is entirely of the black-box type. We show that both models provide satisfactory prediction tools and achieve similar prediction accuracies. Moreover, we demonstrate that significant improvement (25%) was gained with respect to linear statistical methods, suggesting that the biological process is strongly non-linear.

journal_name

Artif Intell Med

journal_title

Artificial intelligence in medicine

authors

Archambeau C,Delbeke J,Veraart C,Verleysen M

doi

10.1016/j.artmed.2004.02.004

subject

Has Abstract

pub_date

2004-11-01 00:00:00

pages

183-94

issue

3

eissn

0933-3657

issn

1873-2860

pii

S0933365704000442

journal_volume

32

pub_type

杂志文章

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