5 citations · 6 across the 3 of their papers we have counts for
4 papers · 1 filter
Study on spike-and-wave detection in epileptic signals using t-location-scale distribution and the K-nearest neighbors classifier
Antonio Quintero-Rincón, Jorge Prendes, Valeria Muro +1
Pattern classification in electroencephalography (EEG) signals is an important problem in biomedical engineering since it enables the detection of brain activity, particularly the…
Epileptic seizure prediction using Pearson's product-moment correlation coefficient of a linear classifier from generalized Gaussian modeling
Antonio Quintero-Rincon, Carlos D'Giano, Marcelo Risk
To predict an epileptic event means the ability to determine in advance the time of the seizure with the highest possible accuracy. A correct prediction benchmark for epilepsy even…
Driver fatigue EEG signals detection by using robust univariate analysis
Antonio Quintero-Rincon, Maria Eugenia Fontecha, Carlos D'Giano
Driver fatigue is a major cause of traffic accidents and the electroencephalogram (EEG) is considered one of the most reliable predictors of fatigue. This paper proposes a novel, s…
A quadratic linear-parabolic model-based classification to detect epileptic EEG seizures
Antonio Quintero-Rincon, Carlos D'Giano, Hadj Batatia
The two-point central difference is a common algorithm in biological signal processing and is particularly useful in analyzing physiological signals. In this paper, we develop a mo…