Recognition of EOG based reading task using AR features

Sandra D'Souza, Sriraam Natarajan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Eye movements play an important role in evaluating the process of reading. By visual inspection of the eye movements, it is possible to differentiate the reading process of different persons. The eye movements can be considered as objective tools for understanding the reading process. However, most of the eye movements are involuntary and out of our conscious control. Hence the reading process is better understood when the analysis of eye movements is automated. This research work presents a pilot study conducted in process of automating eye movement analysis to get an insight into the reading process. Electrooculogram (EOG) has been used for recording the eye movements from a group of 40 volunteers. Several autoregressive (AR) features based on Yule walker's method, Burg's method, modified covariance method and Linear Predictor Coefficients obtained using Levinson-Durbin recursion methods have been extracted from the raw EOG. The horizontal and vertical modes were then recognized by employing a recurrent Elm an neural network. Simulation results show a classification accuracy of 99.95% which indicates the suitability of proposed scheme for human-computer interface applications.

Original languageEnglish
Title of host publicationProceedings of International Conference on Circuits, Communication, Control and Computing, I4C 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages113-117
Number of pages5
ISBN (Electronic)9781479965465
DOIs
Publication statusPublished - 10-03-2014
Event2014 International Conference on Circuits, Communication, Control and Computing, I4C 2014 - Bangalore, India
Duration: 21-11-201422-11-2014

Conference

Conference2014 International Conference on Circuits, Communication, Control and Computing, I4C 2014
CountryIndia
CityBangalore
Period21-11-1422-11-14

Fingerprint

Eye movements
Interfaces (computer)
Inspection
Neural networks

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Cite this

D'Souza, S., & Natarajan, S. (2014). Recognition of EOG based reading task using AR features. In Proceedings of International Conference on Circuits, Communication, Control and Computing, I4C 2014 (pp. 113-117). [7057770] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIMCA.2014.7057770
D'Souza, Sandra ; Natarajan, Sriraam. / Recognition of EOG based reading task using AR features. Proceedings of International Conference on Circuits, Communication, Control and Computing, I4C 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 113-117
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D'Souza, S & Natarajan, S 2014, Recognition of EOG based reading task using AR features. in Proceedings of International Conference on Circuits, Communication, Control and Computing, I4C 2014., 7057770, Institute of Electrical and Electronics Engineers Inc., pp. 113-117, 2014 International Conference on Circuits, Communication, Control and Computing, I4C 2014, Bangalore, India, 21-11-14. https://doi.org/10.1109/CIMCA.2014.7057770

Recognition of EOG based reading task using AR features. / D'Souza, Sandra; Natarajan, Sriraam.

Proceedings of International Conference on Circuits, Communication, Control and Computing, I4C 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 113-117 7057770.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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D'Souza S, Natarajan S. Recognition of EOG based reading task using AR features. In Proceedings of International Conference on Circuits, Communication, Control and Computing, I4C 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 113-117. 7057770 https://doi.org/10.1109/CIMCA.2014.7057770