Artificial neural network-based estimation of the eyeball position using the magnetic contact lens sensing technique

Seung Yup Lee; Keun Young Kim; Hee Chan Kim

doi:10.1109/IEMBS.2005.1616313

Artificial neural network-based estimation of the eyeball position using the magnetic contact lens sensing technique

Conf Proc IEEE Eng Med Biol Soc. 2005:2005:7766-8. doi: 10.1109/IEMBS.2005.1616313.

Authors

Seung Yup Lee¹, Keun Young Kim, Hee Chan Kim

Affiliation

¹ Interdisciplinary Program-Biomedical Engineering Major, Graduate School.

PMID: 17282082
DOI: 10.1109/IEMBS.2005.1616313

Abstract

We have created an artificial neural network based approach for measuring eye movement using a magnetic contact lens sensing technique. The sensor array is based on using four magnetoresistive sensors. A two-layer feed-forward artificial neural network was used and an artificial eyeball model was made for the test. The neural network is trained with sample data obtained from nine spots. After training, we compared the position calculated from the developed system with the real one. The result shows that there is a good linear relationship between them. This indicates the developed system is capable of recording the position of the eyeball with a high degree of accuracy.