Title :
Artificial neural network-based estimation of the eyeball position using the magnetic contact lens sensing technique
Author :
Lee, Seung Yup ; Kim, Keun Young ; Kim, Hee Chan
Author_Institution :
Seoul Nat. Univ.
fDate :
6/27/1905 12:00:00 AM
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
Keywords :
biomagnetism; biomechanics; contact lenses; eye; feedforward neural nets; magnetic sensors; magnetoresistive devices; medical signal processing; eye movement; eyeball position estimation; magnetic contact lens sensing technique; magnetoresistive sensors; sensor array; two-layer feedforward artificial neural network; Artificial neural networks; Biomedical engineering; Biomedical measurements; Biosensors; Lenses; Magnetic field measurement; Magnetic sensors; Magnetoresistance; Sensor arrays; Testing;
Conference_Titel :
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location :
Shanghai
Print_ISBN :
0-7803-8741-4
DOI :
10.1109/IEMBS.2005.1616313