Automatic Seizure Detection and Prediction Based on Brain Connectivity Features and a CNNs Meet Transformers Classifier

• Published in: Brain sciences Vol. 13; no. 5; p. 820
• Main Authors: Tian, Ziwei, Hu, Bingliang, Si, Yang, Wang, Quan
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 18.05.2023; MDPI
• Subjects: Accuracy; brain connectivity; Classification; CNNs meet transformers; Computational linguistics; Convulsions & seizures; EEG; Efficiency; Electric transformers; Electroencephalography; Epilepsy; epileptic state classification; Language processing; Natural language interfaces; Nervous system diseases; Neural networks; Physiology; Predictions; Seizures; Seizures (Medicine); support vector machine; China; brain connectivity; CNNs meet transformers; support vector machine; EEG; epileptic state classification

(1) Background: Epilepsy is a neurological disorder that causes repeated seizures. Since electroencephalogram (EEG) patterns differ in different states (inter-ictal, pre-ictal, and ictal), a seizure can be detected and predicted by extracting various features. However, the brain connectivity network...