Statistical based analysis of electrooculogram (EOG) signals

A pilot study

Sandra D'Souza, N. Sriraam

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The use of Electrooculogram (EOG) signals for developing Human-Computer Interfaces is increasing in the recent times. Several advantages including ease and flexibility in acquiring EOG signals have encouraged insight into EOG based research. In order to identify optimal features for EOG signals for rehabilitation applications, it is necessary to apply the statistical basis to decide the selection of best feature. This paper suggests a pilot study on non-parametric statistical based approach for analyzing EOG signals. This paper considers the detailed statistical analysis of Electrooculogram (EOG) signals. The EOG signals are acquired by considering the horizontal and vertical movements of the eye. The recording includes subjects with identified age groups with different activities. Power spectral densities based on Welch, Yule-Walker, Burg methods are estimated from the acquired EOG signals. Then non-parametric based statistical analysis is performed to show whether the gender or age of the subject influences the EOG signal obtained for different activities. The experimental results based on statistical analysis show that the raw data did not hold any significance to categorize male-female or age wise grouping. However, some features extracted set from the raw data provides useful statistical information which will be of great importance when used for selective rehabilitation.

Original languageEnglish
Title of host publicationResearch Methods
Subtitle of host publicationConcepts, Methodologies, Tools, and Applications
PublisherIGI Global Publishing
Pages1153-1167
Number of pages15
Volume3-4
ISBN (Electronic)9781466674578
ISBN (Print)1466674563, 9781466674561
DOIs
Publication statusPublished - 31-01-2015

Fingerprint

statistical analysis
Statistical methods
Patient rehabilitation
rehabilitation
Power spectral density
grouping
Interfaces (computer)
recording
age group
flexibility
gender
time

All Science Journal Classification (ASJC) codes

  • Social Sciences(all)
  • Engineering(all)

Cite this

D'Souza, S., & Sriraam, N. (2015). Statistical based analysis of electrooculogram (EOG) signals: A pilot study. In Research Methods: Concepts, Methodologies, Tools, and Applications (Vol. 3-4, pp. 1153-1167). IGI Global Publishing. https://doi.org/10.4018/978-1-4666-7456-1ch050, https://doi.org/10.4018/978-1-4666-7456-1.ch050
D'Souza, Sandra ; Sriraam, N. / Statistical based analysis of electrooculogram (EOG) signals : A pilot study. Research Methods: Concepts, Methodologies, Tools, and Applications. Vol. 3-4 IGI Global Publishing, 2015. pp. 1153-1167
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D'Souza, S & Sriraam, N 2015, Statistical based analysis of electrooculogram (EOG) signals: A pilot study. in Research Methods: Concepts, Methodologies, Tools, and Applications. vol. 3-4, IGI Global Publishing, pp. 1153-1167. https://doi.org/10.4018/978-1-4666-7456-1ch050, https://doi.org/10.4018/978-1-4666-7456-1.ch050

Statistical based analysis of electrooculogram (EOG) signals : A pilot study. / D'Souza, Sandra; Sriraam, N.

Research Methods: Concepts, Methodologies, Tools, and Applications. Vol. 3-4 IGI Global Publishing, 2015. p. 1153-1167.

Research output: Chapter in Book/Report/Conference proceedingChapter

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D'Souza S, Sriraam N. Statistical based analysis of electrooculogram (EOG) signals: A pilot study. In Research Methods: Concepts, Methodologies, Tools, and Applications. Vol. 3-4. IGI Global Publishing. 2015. p. 1153-1167 https://doi.org/10.4018/978-1-4666-7456-1ch050, https://doi.org/10.4018/978-1-4666-7456-1.ch050