Convolutional Neural Networks for Early Seizure Alert System
A general framework of a system for early seizure detection and alert is presented. Many studies have shown high potential of electroencephalograms (EEG) when there are used together with machine learning algorithms for seizure/non-seizure classification task. In this paper, mainly guidelines will be presented on how to use convolutional neural networks for the purpose of highly accurate classification of non-invasive EEG for patients with epilepsy. Convolutional neural networks can be pre-trained on a sample data as described in this paper and then implemented into an application or a device, which readjusts its parameters according to the patient-specific EEG patterns and thus can be further used as a seizure monitoring and alert system. The paper also demonstrated how transfer learning can be applied to create a patient-specific classifier with high accuracy.
KeywordsEEG Epilepsy Convolutional neural networks Deep learning Classification
T. Iesmantas was supported by the postdoctoral fellowship grant, provided by the Kaunas University of Technology, Faculty of Mathematics and Natural Sciences.
T. Iesmantas was partially supported by the postdoctoral fellowship grant, provided by the Kaunas University of Technology, Faculty of Mathematics and Natural Sciences. In addition, part of the research presented in this paper was based upon work from COST Action (ENJECT TD 1405), supported by COST (European Cooperation in Science and Technology).
Conflict of Interest
The authors declare that they have no conflict of interest.
- 2.Shoeb A, Guttag J (2010) Application of machine learning to epileptic seizure detection. In: Proceedings of the 27th international conference on machine learning, Haifa, Israel, pp 975– 982Google Scholar
- 3.Mirowski P, Madhavan D, LeCun Y, Kuzniecky R (2009) Classification of patterns of EEG synchronization for seizure prediction. Electroencephalogr Clin Neurophysiol 120(11):1927–1940Google Scholar
- 4.Mirowski P, Le Cun Y, Madhavan D, Kuzniecky R (2008) Comparing SVM and convolutional networks for epileptic seizure prediction from intracranial EEG. IEEE Workshop on Machine Learning for Signal ProcessingGoogle Scholar
- 8.LeCun Y, Boser B, Denker JS, Henderson D, Howard RE, Hubbard W, Jackel LD (1990) Handwritten digit recognition with a back-propagation network. In: Touretzky David (ed) Advances in neural information processing systems 2 (NIPS*89). Denver, COGoogle Scholar
- 9.LeCun Y, Bottou L, Bengio Y, Haffner P (1998) Gradient-based learning applied to document recognition. In: Proceedings of the IEEE, Nov 1998Google Scholar
- 10.Myers M, Padmanabha A, Hossain G, de Jongh Curry AL, Blaha CD (2016) Seizure prediction and detection via phase and amplitude lock values. Front Hum Neurosci 10(80)Google Scholar