Electro-oculogram Based Classification of Eye Movement Direction

  • Anwesha Banerjee
  • Amit Konar
  • R. Janarthana
  • D. N. Tibarewala
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 178)


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 Electrooculographic 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 comparison, all of them shown good results but multilayer perceptron performs the best. These classified signals may further be used for control application.


Support Vector Machine Discrete Wavelet Transform Linear Support Vector Machine Kernel Support Vector Machine Human Computer Interface 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Anwesha Banerjee
    • 1
  • Amit Konar
    • 2
  • R. Janarthana
    • 3
  • D. N. Tibarewala
    • 1
  1. 1.School of Bioscience & EngineeringJadavpur UniversityKolkataIndia
  2. 2.Department of Electronics & Tele CommunicationJadavpur UniversityKolkataIndia
  3. 3.Department of Information TechnologyJaya College of EngineeringChennaiIndia

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