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

Content Provider	IEEE Xplore Digital Library
Author	Seung Yup Lee Keun Young Kim Hee Chan Kim
Copyright Year	2005
Description	Author affiliation: Seoul Nat. Univ. (Seung Yup Lee; Keun Young Kim)
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
Starting Page	7766
Ending Page	7768
File Size	270438
Page Count	3
File Format	PDF
ISBN	0780387414
DOI	10.1109/IEMBS.2005.1616313
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-01-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Artificial neural networks Lenses Sensor arrays Magnetic sensors Biomedical engineering Biomedical measurements Biosensors Magnetoresistance Testing Magnetic field measurement
Content Type	Text
Resource Type	Article

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