Bioingeniería
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Examinando Bioingeniería por Materia "ELECTROENCEFALOGRAFIA"
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Póster Epilepsy seizure onset detection applying 1-NN classifier based on statistical parameters(2018) Zorgno, Ivanna; Blanc, María Cecilia; Oxenford, Simón; Gil Garbagnoli, Francisco; D'Giano, Carlos; Quintero-Rincón, Antonio"Epilepsy is a disease caused by an excessive discharge of a group of neurons in the cerebral cortex. Extracting this information using EEG signals is an ongoing challenge in biomedical signal processing. In this paper, a new method is proposed for onset seizure detection in epileptic EEG signals based on parameters from the t-location-scale distribution coupled with the variance and the Pearson correlation coefficient. The 1-nearest neighbor classifier achieved a 91% sensitivity (True positive rate) and 95% specificity (True Negative Rate) with a delay of 4.5 seconds (on average) in the 45 signals analyzed, which suggests that the proposed methodology is potentially useful for seizure onset detection in epileptic EEG signals."Póster 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."Póster Procesamiento de señales de electroencefalograma para detección de crisis epiléptica(2019) Girado, Sol; Rensonnet, Pablo; Volman, Uriel"Desarrollo de software de procesamiento de señales de electroencefalograma en Matlab para detección y análisis de crisis epilépticas a partir de estudios de 23 canales."