most citedEpileptic seizure prediction using Pearson's product-moment correlation coefficient of a linear classifier from generalized Gaussian modeling

5 citations · 5 across the 2 of their papers we have counts for

collaborators

5 papers

stat.AP20205 cited

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…

eess.SP2020

Mu-suppression detection in motor imagery electroencephalographic signals using the generalized extreme value distribution

Antonio Quintero-Rincón, Carlos D'Giano, Hadj Batatia

This paper deals with the detection of mu-suppression from electroencephalographic (EEG) signals in brain-computer interface (BCI). For this purpose, an efficient algorithm is prop…

eess.SP2020

Hand bone conduction sound study by using the DSP Logger MX 300

Melanie Adler, Mariana Fiala Sanchez, Constanza Martini +3

Bone conduction is the transmission of acoustic energy to the inner ear by different paths involving the bones of the skull. In this work, we use the path the hand provides in orde…

stat.AP2019

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…

stat.AP2019

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…