Feature Selection in Classification of Eye Movements Using Electrooculography for Activity Recognition
Joint Authors
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-12-09
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Activity recognition is needed in different requisition, for example, reconnaissance system, patient monitoring, and human-computer interfaces.
Feature selection plays an important role in activity recognition, data mining, and machine learning.
In selecting subset of features, an efficient evolutionary algorithm Differential Evolution (DE), a very efficient optimizer, is used for finding informative features from eye movements using electrooculography (EOG).
Many researchers use EOG signals in human-computer interactions with various computational intelligence methods to analyze eye movements.
The proposed system involves analysis of EOG signals using clearness based features, minimum redundancy maximum relevance features, and Differential Evolution based features.
This work concentrates more on the feature selection algorithm based on DE in order to improve the classification for faultless activity recognition.
American Psychological Association (APA)
Mala, S.& Latha, K.. 2014. Feature Selection in Classification of Eye Movements Using Electrooculography for Activity Recognition. Computational and Mathematical Methods in Medicine،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1016828
Modern Language Association (MLA)
Mala, S.& Latha, K.. Feature Selection in Classification of Eye Movements Using Electrooculography for Activity Recognition. Computational and Mathematical Methods in Medicine No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1016828
American Medical Association (AMA)
Mala, S.& Latha, K.. Feature Selection in Classification of Eye Movements Using Electrooculography for Activity Recognition. Computational and Mathematical Methods in Medicine. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1016828
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1016828