A hybrid unsupervised approach toward EEG epileptic spikes detection

• Main Authors: Khosropanah, Pegah, Ramli, Abdul Rahman, Abbasi, Mohammad Reza, Marhaban, Mohammad Hamiruce, Ahmedov, Anvarjon
• Format: Article
• Language: English; English
• Published: Springer Verlag (Germany) 2018
• Subjects: QA75 Electronic computers. Computer science; QM Human anatomy; QP Physiology; R Medicine (General); RZ Other systems of medicine; TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.um.edu.my/19662/1/10.1007%40s00521-018-3797-2.pdf; http://eprints.um.edu.my/19662/2/10.1007%40s00521-018-3797-2.pdf; http://eprints.um.edu.my/19662/; http://dx.doi.org/10.1007/s00521-018-3797-2

Epileptic spikes are complementary sources of information in EEG to diagnose and localize the origin of epilepsy. However, not only is visual inspection of EEG labor intensive, time consuming, and prone to human error, but it also needs long-term training to acquire the level of skill required for i...