Multi-distance fluctuation based dispersion fractal for epileptic seizure detection in EEG signal

2021 ◽  
Vol 69 ◽  
pp. 102938
Author(s):  
Inung Wijayanto ◽  
Rudy Hartanto ◽  
Hanung Adi Nugroho
2018 ◽  
Vol 17 (4) ◽  
pp. 526-531
Author(s):  
K Baskar ◽  
C Karthikeyan

Epileptic seizure detection is a common diagnosis practiced by the expert clinicians through direct visual observation from the electroencephalography (EEG) signal. This detection by the expert clinicians is considered sensitive to bias and time consuming. Further, it suffers from various problems like unsustainability in larger dataset processing and low power detection. Hence, many computerized detection approaches are highly preferred to eliminate the aforementioned problems and to expedite the research in epilepsy seizure detection for aiding the medical professionals. Many such automated epilepsy diagnosis framework has been designed by various researches, which is made to operate in a single or in a combined manner with other domains. This study reviews different approaches, which is been designed to aid the human diagnosis using new avenues that explains the causes of epilepsy and seizures. Further, this study summarizes various methods used previously to analyze the epilepsy and seizures based on its state of art approach. Also, investigations are carried out in terms of performance evaluation to find the best suitable epileptic seizure detection technique in the application of Neuro-informatics.Bangladesh Journal of Medical Science Vol.17(4) 2018 p.526-531


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