Author:
Pendyala Tulasi,Mohammad Anisa Fathima,Arumalla Anitha
Publisher
Springer Nature Singapore
Reference8 articles.
1. Adeli H, Ghosh-Dastidar S, Dadmehr N (2007) A wavelet-chaos methodology for analysis of EEGs and EEG subbands to detect seizure and epilepsy. IEEE Trans Biomed Eng 54(2):205–211
2. Runarsson TP, Sigurdsson S (2005) On-line detection of patient specific neonatal seizures using support vector machines and half-wave attribute histograms. In: International conference on computational intelligence for modelling, control and automation and International conference on intelligent agents, web technologies and internet commerce (CIMCA-IAWTIC'06), vol 2. IEEE, pp 673–677
3. Subasi A, Kemal Kiymik M, Alkan A, Koklukaya E (2005) Neural network classification of EEG signals by using AR with MLE preprocessing for epileptic seizure detection. Math Comput Appl 10(1):57–70
4. Panda R, Khobragade PS, Jambhule PD, Jengthe SN, Pal PR, Gandhi TK (2010) Classification of EEG signal using wavelet transform and support vector machine for epileptic seizure diction. In: 2010 International conference on systems in medicine and biology. IEEE, pp 405–408
5. Baldominos A, Ramón-Lozano C (2017) Optimizing EEG energy-based seizure detection using genetic algorithms. In: 2017 IEEE congress on evolutionary computation (CEC). IEEE, pp 2338–2345