MLLGSPAPNov 29, 2019

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

arXiv:1911.13018v16 citations
Originality Synthesis-oriented
AI Analysis

This addresses epilepsy detection for biomedical applications, but appears incremental as it applies a statistical coefficient to a known problem.

The paper tackled the problem of detecting spike-and-wave epileptiform discharge patterns in biomedical engineering by proposing a new method based on Kendall's Tau-b coefficient, achieving 94% specificity for patient-specific detection and 83% for general detection on a real dataset.

Epilepsy is an important public health issue. An appropriate epileptiform discharge pattern detection 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 detection based on Kendall's Tau-b coefficient. The proposed approach is demonstrated on a real dataset 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.

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