Advertisement

Object Shape Recognition from EEG Signals during Tactile and Visual Exploration

  • Anwesha Khasnobish
  • Amit Konar
  • D. N. Tibarewala
  • Saugat Bhattacharyya
  • R. Janarthanan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8251)

Abstract

Humans understand the world around us by visual and tactile exploration of the objects. The objective of this paper is to recognize the object-shapes from EEG signals while the subjects are exploring the same by visual and tactile means. The various object shapes are classified from electroencephalogram (EEG) signals that are stimulated by only tactile, only visual and by both means. EEG signals were acquired and analyzed from six electrodes, namely F3,F4,FC5,FC6,O1 and O2, where each pair of electrodes are located on frontal, somato-sensory and occipital region of the brain responsible for cognitive processing, tactile and visual perception. Mu-desynchronization in alpha and beta bands is used as the EEG modality for this purpose. Power spectral density (PSD) features are extracted and classified using support vector machine (SVM) classifiers in their corresponding object-shape classes. The results showed that object-shapes are best classified from EEG signals during only tactile exploration. The object shapes classified from EEG signals during only tactile exploration yielded highest mean classification accuracy of 88.34%. The average classification accuracy over all three object exploration modalities is 83.89%.

Keywords

Tactile perception visual perception object-shape recognition electroencephalogram power spectral density support vector machine 

References

  1. 1.
    Cristino, F., Colan, L.I., Leek, C.E.: The appearance of shape in visula perception: eye movement patterns during recognition and reaching. In: 3rd International Conference on Appearance, UK, pp. 125–127 (2012)Google Scholar
  2. 2.
    Hoosiang, H.: Differential surface models for tactile perception of shape and online tracking of features. IEEE Trans System, Man and Cybernetics 18(2), 312–316 (1988)CrossRefGoogle Scholar
  3. 3.
    Szubielsca, M.: Prior visual experience, and perception and memory of shape in people with total blindness. British J. Visual Impairment 29, 60–81 (2011)CrossRefGoogle Scholar
  4. 4.
    Santhian, K.: Visual cortical activity during during tactile perception in sighted and visually deprived. J. Developmental Psychobiology 46(3), 279–286 (2005)CrossRefGoogle Scholar
  5. 5.
    Mustafa, M., Lindemann, L., Magnor, M.: EEG Analysis of Implicit Human Visual Perception. In: ACM Human Factors in Computing Systems, CHI (2012)Google Scholar
  6. 6.
    Christopher, P., Taylor, J., Thut, G.: Brain activity underlying visual perception and attention as inferred from TMS-EEG: A review. J. Brain Stimulation 5(2), 125–129 (2012)Google Scholar
  7. 7.
    Grunwald, M., et al.: Theta power in the EEG of humans during ongoing processing in a haptic object recognition task. J. Cog. Brain Research 11, 33–37 (2001)CrossRefGoogle Scholar
  8. 8.
    Teplan, M.: Fundamentals of EEG Measurement. J. Measurement Sc. Review 2(2) (2002)Google Scholar
  9. 9.
    Herman, P., Prasad, G., McGinnity, T.M., Coyle, D.: Comparative analysis of spectral approaches to feature extraction for EEG-based motor imagery classification. IEEE Trans. Neural Sys. Rehab Eng. 16(4), 317–326 (2008)CrossRefGoogle Scholar
  10. 10.
    Gunn Steve, R.: Support Vector Machines For Classification and Regression. Technical report, University of Southampton (1998)Google Scholar
  11. 11.
    Burges Christopher, J.C.: A Tutorial on Support Vector Machines for Pattern Recognition. Kluwer Academic Publishers, BostonGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Anwesha Khasnobish
    • 1
  • Amit Konar
    • 2
  • D. N. Tibarewala
    • 1
  • Saugat Bhattacharyya
    • 2
  • R. Janarthanan
    • 3
  1. 1.School of Bioscience and EngineeringJadavpur UniversityKolkataIndia
  2. 2.Department of Electronics and Telecommunication EngineeringJadavpur UniversityKolkataIndia
  3. 3.Department of Computer ScienceTJS Engineering CollegeChennaiIndia

Personalised recommendations