Epilepsy/Seizure Detection Using Machine Learning Through IOT

1. “A Low Power System With EEG Data Reduction for Long-Term Epileptic Seizures Monitoring” by Syed Anas Imtiaz, Saam Iranmanesh
,Esther Rodriguez-Villegas.Paper Published by IEEE in 2019 .
2. “Highly efficient and accurate seizure prediction on constrained IOT devices” by Farad Sammie, Lars Bauer, Jorge Helen. Paper
Published by IEEE in 2018.
3. “An Automated System for Epilepsy Detection using EEG Brain Signals based on Deep Learning Approach” by Ihsan Ullah 1,
Muhammad Hussein, Edam-ul-Haq Qazi and Hatim Aboalsamh. Paper Published by IEEE in 2018.
4. “A Multi-view Deep Learning Framework for EEG Seizure Detection” by Ye Yuan, Guangxu Xun, Kebin Jia, Aidong Zhang. Paper
Published by IEEE in 2018.
5. “Diagnosis of epilepsy — A systematic review” by R. Vetrikani , T Christy Bobby.Paper Published by IEEE paper in 2017 .
6. “Epileptic seizure auto-detection using deep learning method” by Yuzhen Cao, Yixiang Guo, Hui Yu, Xuyao Yu. Paper Published by
IEEE in 2017.
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2003
8. B. Litt and J. Echauz, “Prediction of epileptic seizures,” The LancetNeurology, vol. 1, no. 1, pp. 22–30, 2002.
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50,no. 5, pp. 537–539, 2003.
10. S. A. Imtiaz, L. Logesparan, and E. Rodriguez-Villegas, “Performancepowerconsumption tradeoff in wearable epilepsy monitoring
systems,”IEEE Journal of Biomedical and Health Informatics, vol. 19, no. 3, pp.1019–1028, 2015.
11. A. S. Zandi, M. Javidan, G. A. Dumont, and R. Tafreshi, “Automatedreal-time epileptic seizure detection in scalp EEG recordings using
analgorithm based on wavelet packet transform,” IEEE Transactions onBiomedical Engineering, vol. 57, no. 7, pp. 1639–1651, 2010.