Deep Learning for Epilepsy monitoring: A survey

Diagnosis of epilepsy can be expensive, time-consuming, and often inaccurate. The gold standard diagnostic monitoring is continuous video-electroencephalography (EEG), which ideally captures all epileptic events dis-charges. Automated seizures activity from EEG would save time resources, it the focus much EEG-based research. purpose this paper to provide a survey in order understand, classify benchmark key parameters deep learning-based approaches that were applied processing signals for monitoring. This identifies availability data black-box nature DL as main challenges hindering clinical acceptance analysis systems based on Deep Learning suggests use Explainable Artificial Intelligence (XAI) Transfer overcome these issues. It also underlines need more research recognize full potential big data, Computing Edge, IoT implement wearable devices assist patients improve their quality life.