14 citations · 33 across the 9 of their papers we have counts for
9 papers
Epanechnikov nonparametric kernel density estimation based feature-learning in respiratory disease chest X-ray images
Veronica Marsico, Antonio Quintero-Rincon, Hadj Batatia
This study presents a novel method for diagnosing respiratory diseases using image data. It combines Epanechnikov's non-parametric kernel density estimation (EKDE) with a bimodal l…
Hybrid Pipeline SWD Detection in Long-Term EEG Signals
Antonio Quintero Rincon, Nicolas Masino, Veronica Marsico +1
Spike-and-wave discharges (SWDs) are the electroencephalographic hallmark of absence epilepsy, yet their manual identification in multi-day recordings remains labour-intensive and…
Effect sizes as a statistical feature-selector-based learning to detect breast cancer
Nicolas Masino, Antonio Quintero-Rincon
Breast cancer detection is still an open research field, despite a tremendous effort devoted to work in this area. Effect size is a statistical concept that measures the strength o…
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…
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…
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…
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…