Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification

• Main Authors: Sobhan Sheykhivand, Tohid Yousefi Rezaii, Zohreh Mousavi, Azra Delpak, Ali Farzamnia
• Format: Article
• Language: English; English
• Published: IEEE Access 2020
• Subjects: RC346-429 Neurology. Diseases of the nervous system Including speech disorders
• Online Access: https://eprints.ums.edu.my/id/eprint/29236/1/Automatic%20identification%20of%20epileptic%20seizures%20from%20EEG%20signals%20using%20sparse%20representation-based%20classification.pdf; https://eprints.ums.edu.my/id/eprint/29236/2/Automatic%20identification%20of%20epileptic%20seizures%20from%20EEG%20signals%20using%20sparse%20representation-based%20classification1.pdf; https://eprints.ums.edu.my/id/eprint/29236/; https://ieeexplore.ieee.org/document/9149613; https://doi.org/10.1109/ACCESS.2020.3011877

Identifying seizure activities in non-stationary electroencephalography (EEG) is a challenging task since it is time-consuming, burdensome, and dependent on expensive human resources and subject to error and bias. A computerized seizure identification scheme can eradicate the above problems, assist...