Spike-and-wave epileptiform discharge pattern detection based on Kendall's Tau-b coefficient

Quintero-Rincón, Antonio, Carenzo, Catalina, Ems, Joaquín, Hirschson, Lourdes, Muro, Valeria, D'Giano, Carlos

arXiv.org Machine Learning 

Epilepsy is a n important public health issue. An appropriate epileptiform discharge pattern detectio n of this neurological disease is a typical problem in biomedical engineering. In this paper, a new method is proposed for spike - and - wave discharge pattern dete ction based on Kendall's Tau - b c oefficient. The proposed approach is demonstrated on a real data set containing spike - and - wave discharge signals, where our performance is evaluated in terms of high Specificity, rule in (SpPIn) with 94% for patient - specific spike - and - wave discharge detection and 83% for a general spike - and - wave discharge detection. Key words: Spike - and - wave discharge; Kendall's Tau - b c oefficient; Electroencephalography ( EEG); Epilepsy; high Specificity, rule in ( SpPIn) Introduction Electroencephalography (EEG) is widely used to record the electrical activity of the brain in neurological health centers.

Duplicate Docs Excel Report

Title
None found

Similar Docs  Excel Report  more

TitleSimilaritySource
None found