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Epilepsy

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Novel Automatic Epilepsy Detection Method Multi-weight Transition Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The automatic diagnosis of epilepsy using Electroencephalogram (EEG) signals had always been an important research direction. A novel automatic epilepsy detection method based on multi-weight transition network was proposed in this paper. The epilept...

A convolutional neural network based framework for classification of seizure types.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Epileptic seizures are caused by a disturbance in the electrical activity of the brain and classified as many different types of epileptic seizures based on the characteristics of EEG and other parameters. Till now research has been conducted to clas...

Epileptic States Recognition Using Transfer Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic recognition of electroencephalogram (EEG) signals plays a major role in epilepsy diagnosis and assessment. However, the recognition accuracy of conventional methods is usually not satisfactory because of the inconsistent distribution of tra...

Detection of Epileptic Seizures using Unsupervised Learning Techniques for Feature Extraction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic epileptic seizure prediction from EEG (electroencephalogram) data is a challenging problem. This is due to the complex nature of the signal itself and of the generated abnormalities. In this paper, we investigate several deep network archit...

Implementation of Bagged SVM Ensemble Model for Classification of Epileptic States Using EEG.

Current pharmaceutical biotechnology
BACKGROUND: To decipher EEG (Electroencephalography), intending to locate inter-ictal and ictal discharges for supporting the diagnoses of epilepsy and locating the seizure focus, is a critical task. The aim of this work was to find how the ensemble ...

A Multi-View Deep Learning Framework for EEG Seizure Detection.

IEEE journal of biomedical and health informatics
The recent advances in pervasive sensing technologies have enabled us to monitor and analyze the multi-channel electroencephalogram (EEG) signals of epilepsy patients to prevent serious outcomes caused by epileptic seizures. To avoid manual visual in...

Deep Learning Enabled Automatic Abnormal EEG Identification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In hospitals, physicians diagnose brain-related disorders such as epilepsy by analyzing electroencephalograms (EEG). However, manual analysis of EEG data requires highly trained clinicians or neurophysiologists and is a procedure that is known to hav...

Classification of single-channel EEG signals for epileptic seizures detection based on hybrid features.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Epilepsy is a common chronic neurological disorder of the brain. Clinically, epileptic seizures are usually detected via the continuous monitoring of electroencephalogram (EEG) signals by experienced neurophysiologists.

Robotic-Assisted and Image-Guided MRI-Compatible Stereoelectroencephalography.

The Canadian journal of neurological sciences. Le journal canadien des sciences neurologiques
BACKGROUND: Stereoelectroencephalography has been in regular use at the Montreal Neurological Institute since 1972. The technique has been in constant evolution to incorporate advances in materials, imaging, and robotics technology. MRI-compatible el...