Browsing by Author "Muro, Valeria"
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póster.listelement.badge A new algorithm for automatic identification of spike-wave EEG signals in epileptic patient-specific(2018) Racca, Dora María; Quintero-Rincón, Antonio; Muro, Valeria; D'Giano, Carlos"Appropriate diagnosis and treatment of epilepsy is a main public health issue. Patients suffering from this disease often exhibit different physical characterizations, which results from the synchronous and excessive discharge of a group of neurons in the cerebral cortex. Extracting this information using EEG signals is an important problem in biomedical processing. In this work we propose a new method to indentify and characterize patient specific spike-and-wave EEG epileptic signals. The method is based on the use of trained neuronal networks on probability density function parameters of the translation and rescaling of the Student'st-distribution (location: µ,scale: σ and shape: ν) of pure spike-and-wave-signals. The neuronal network was trained with both normal and epileptic signals. The study resulted in 100% specificity and sensitivity on the studied signals."artículo de publicación periódica.listelement.badge Spike-and-wave detection in epileptic signals using cross-correlation and decision trees(2018) Quintero-Rincón, Antonio; Alanis, Manuela; Muro, Valeria; D'Giano, Carlos"Identify spike-and-waves patterns in epileptic signals is a typical problem in electroencephalographic (EEG) signal processing. In this paper we propose cross-correlation coupled with decision tree model as new method in order to assess and detect spike-and-wave discharges (SWD) in long-term epileptic signals. The proposed approach is demonstrated in terms of accuracy, sensitivity and specificity classification on real EEG signals using a database developed with medical annotations."póster.listelement.badge Spike-and-wave epileptiform discharge pattern detection based on Kendall’s Tau-b Coefficient(2019) Ems, Joaquín; Hirschson Álvarez Prado, Lourdes; Carenzo, Catalina; Muro, Valeria; D'Giano, Carlos; Quintero-Rincón, Antonio"Epilepsy is a main public health issue. An appropriate epileptiform discharges 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 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."ponencia en congreso.listelement.badge Study on spike-and-wave detection in epileptic signals using T-location-scale distribution and the K-nearest neighbors classifier(2017-12) Quintero-Rincón, Antonio; Prendes, Jorge; D'Giano, Carlos; Muro, Valeria"Pattern classification in electroencephalography (EEG) signals is an important problem in biomedical engineering since it enables the detection of brain activity, in particular the early detection of epileptic seizures. In this paper we propose a k-nearest neighbors classification for epileptic EEG signals based on an t-location-scale statistical representation to detect spike-and-waves. The proposed approach is demonstrated on a real dataset containing both spike-and-wave events and normal brain function signals, where our performance is evaluated in terms of classification accuracy, sensitivity and specificity."