An Epilepsy Detection Method Using Multiview Clustering Algorithm and Deep Features
Joint Authors
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-01
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The automatic detection of epilepsy is essentially the classification of EEG signals of seizures and nonseizures, and its purpose is to distinguish the different characteristics of seizure brain electrical signals and normal brain electrical signals.
In order to improve the effect of automatic detection, this study proposes a new classification method based on unsupervised multiview clustering results.
In addition, considering the high-dimensional characteristics of the original data samples, a deep convolutional neural network (DCNN) is introduced to extract the sample features to obtain deep features.
The deep feature reduces the sample dimension and increases the sample separability.
The main steps of our proposed novel EEG detection method contain the following three steps: first, a multiview FCM clustering algorithm is introduced, and the training samples are used to train the center and weight of each view.
Then, the class center and weight of each view obtained by training are used to calculate the view-weighted membership value of the new prediction sample.
Finally, the classification label of the new prediction sample is obtained.
Experimental results show that the proposed method can effectively detect seizures.
American Psychological Association (APA)
Zhan, Qianyi& Hu, Wei. 2020. An Epilepsy Detection Method Using Multiview Clustering Algorithm and Deep Features. Computational and Mathematical Methods in Medicine،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1139465
Modern Language Association (MLA)
Zhan, Qianyi& Hu, Wei. An Epilepsy Detection Method Using Multiview Clustering Algorithm and Deep Features. Computational and Mathematical Methods in Medicine No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1139465
American Medical Association (AMA)
Zhan, Qianyi& Hu, Wei. An Epilepsy Detection Method Using Multiview Clustering Algorithm and Deep Features. Computational and Mathematical Methods in Medicine. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1139465
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1139465