Automated epileptic seizures detection using multi-features and multilayer perceptron neural network-Reference-Cited by-同舟云学术

Automated epileptic seizures detection using multi-features and multilayer perceptron neural network

Published:2018-09-03 Issue:2 Volume:5 Page:
ISSN:2198-4018
Container-title:Brain Informatics
language:en
Short-container-title:Brain Inf.

Author:

Sriraam N.^ORCID,Raghu S.,Tamanna Kadeeja,Narayan Leena,Khanum Mehraj,Hegde A. S.,Kumar Anjani Bhushan

Publisher

Springer Science and Business Media LLC

Subject

Cognitive Neuroscience,Computer Science Applications,Neurology

Link

http://link.springer.com/article/10.1186/s40708-018-0088-8/fulltext.html

Reference38 articles.

1. Dabye AS, Issaka M, Gueye L (2015) Localization of epileptic seizure with an approach based on the PSD with an auto-regressive model. arXiv:1506.00947

2. Kamath C (2013) A new approach to detect epileptic seizures in Electroencephalograms using Teager energy. ISRN Biomedical Engineering, Hindawi. https://doi.org/10.1155/2013/358108

3. Kamath C (2013) Teager energy based filter-Bank Cepstra in EEG classification for seizure detection using radial basis function neural network. ISRN Biomedical Engineering, Hindawi. https://doi.org/10.1155/2013/498754

4. Abbasi R, Esmaeilpour M (2017) Selecting statistical characteristics of brain signals to detect epileptic seizures using discrete wavelet transform and perceptron neural network. IJIMAI 4(5):33–38

5. Zhou W, Liu Y, Yuan Q, Li X (2013) Epileptic seizure detection using lacunarity and Bayesian linear discriminant analysis in intracranial EEG. IEEE Trans Biomed Eng 60(12):3375–3381

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