In this paper, the direction of eye movement is detected from Electro-oculographic signal using different types of support vector machine classifier. Here, a data acquisition system is designed to collect stimulated Electrooculo-graphic signal. Discrete wavelet transform features of the signal are taken for classification. Eye movement in left and right direction is classified by support vector machine classifier with different kernels. Linear, quadratic, polynomial, radial basis function and multilayer perceptron kernels have been used. In com-parison, all of them shown good results but multilayer perceptron performs the best. These classified signals may further be used for control application.
CITATION STYLE
Banerjee, A., Konar, A., Janarthana, R., & Tibarewala, D. N. (2013). Electro-oculogram based classification of eye movement direction. In Advances in Intelligent Systems and Computing (Vol. 178, pp. 151–159). Springer Verlag. https://doi.org/10.1007/978-3-642-31600-5_15
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