Exploring Sampling in the Detection of Multicategory EEG Signals
Joint Authors
Siuly, Siuly
Kabir, Enamul
Wang, Hua
Zhang, Yanchun
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-04-21
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The paper presents a structure based on samplings and machine leaning techniques for the detection of multicategory EEG signals where random sampling (RS) and optimal allocation sampling (OS) are explored.
In the proposed framework, before using the RS and OS scheme, the entire EEG signals of each class are partitioned into several groups based on a particular time period.
The RS and OS schemes are used in order to have representative observations from each group of each category of EEG data.
Then all of the selected samples by the RS from the groups of each category are combined in a one set named RS set.
In the similar way, for the OS scheme, an OS set is obtained.
Then eleven statistical features are extracted from the RS and OS set, separately.
Finally this study employs three well-known classifiers: k-nearest neighbor (k-NN), multinomial logistic regression with a ridge estimator (MLR), and support vector machine (SVM) to evaluate the performance for the RS and OS feature set.
The experimental outcomes demonstrate that the RS scheme well represents the EEG signals and the k-NN with the RS is the optimum choice for detection of multicategory EEG signals.
American Psychological Association (APA)
Siuly, Siuly& Kabir, Enamul& Wang, Hua& Zhang, Yanchun. 2015. Exploring Sampling in the Detection of Multicategory EEG Signals. Computational and Mathematical Methods in Medicine،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1057943
Modern Language Association (MLA)
Siuly, Siuly…[et al.]. Exploring Sampling in the Detection of Multicategory EEG Signals. Computational and Mathematical Methods in Medicine No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1057943
American Medical Association (AMA)
Siuly, Siuly& Kabir, Enamul& Wang, Hua& Zhang, Yanchun. Exploring Sampling in the Detection of Multicategory EEG Signals. Computational and Mathematical Methods in Medicine. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1057943
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057943