Deep learning epileptic seizure detection based on the matching pursuit algorithm and its time-frequency graphical representation - Kunik, Mateusz M.; Gramacki, Artur (Zielona Góra: Uniwersytet Zielonogórski)
Electroencephalography (EEG) is the primary diagnostic and an important prognostic clinical tool for epilepsy. The detection of epileptic activity is usually performed by a human expert and is based on finding specific patterns in the multi-channel electroencephalogram. However, the manual inspection of EEG signals is a time-consuming procedure for neurologists. Therefore, various attempts are made to automate it using both conventional and deep learning techniques.
Keywords: EEG signals; epileptic seizure detection; matching pursuit algorithm; time-frequency representation; deep learning