Listar por autor "Quintero Rincón, Antonio"

Mostrando ítems 1-9 de 9

A quadratic linear-parabolic model-based EEG classification to detect epileptic seizures

Quintero Rincón, Antonio; D'Giano, Carlos; Batatia, Hadj (Editorial Department of the Journals of Nanjing Medical University, 2019-08-28)

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 model-based classification method to detect ...
Artifacts Detection in EEG Signals

Quintero Rincón, Antonio; D'Giano, Carlos; Batatia, Hadj (International Frequency Sensor Association, 2021)

Resumen no disponible
Epilepsy seizure onset detection applying 1-NN classifier based on statistical parameters

Zorgno, Ivanna; Blanc, María Cecilia; Oxenford, Simon; Gil Garbagnoli, Francisco; D’Giano, Carlos; Quintero Rincón, Antonio (IEEE, 2019-02-21)

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

Adler, Melanie Victoria; Fialá Sánchez, Mariana; Martini, Constanza; Vartabedian, Luciana Mariam; Zazzali, Matías Nicolás; Quintero Rincón, Antonio (Sociedad Argentina de Bioingeniería, 2020)

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 order to transmit the sound coming from the ...
Mu-suppression detection in motor imagery electroencephalographic signals using the generalized extreme value distribution

Quintero Rincón, Antonio; D’Giano, Carlos; Batatia, Hadj (IEEE, 2020-06-19)

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 proposed based on a statistical model and a ...
Seizure Onset Detection in EEG Signals Based on Entropy from Generalized Gaussian PDF Modeling and Ensemble Bagging Classifier

Quintero Rincón, Antonio; D'Giano, Carlos; Batatia, Hadj (Springer, 2019-07-11)

This paper proposes a new algorithm for epileptic seizure onset detection in EEG signals. The algorithm relies on the measure of the entropy of observed data sequences. Precisely, the data is decomposed into different brain ...
Spike-and-wave epileptiform discharge pattern detection based on Kendall's Tau-b coefficient

Quintero Rincón, Antonio; Carenzo, Catalina; Ems, Joaquín; Hirschson, Lourdes; Muro, Valeria L.; D'Giano, Carlos ("Iuliu Haţieganu" Publishing House, 2019-03-30)

Epilepsy is an important public health issue. An appropriate epileptiform discharge pattern detection of this neurological disease is a typical problem in biomedical engineering. In this paper, a new method is proposed for ...
Statistical Model-Based Classification to Detect Patient-Specific Spike-and-Wave in EEG Signals

Quintero Rincón, Antonio; Muro, Valeria L.; D'Giano, Carlos; Prendes, Jorge; Batatia, Hadj (MDPI, 2020-10-29)

Spike-and-wave discharge (SWD) pattern detection in electroencephalography (EEG) is a crucial signal processing problem in epilepsy applications. It is particularly important for overcoming time-consuming, difficult, and ...
Study on epileptic seizure detection in EEG signals using largest Lyapunov exponents and logistic regression

Quintero Rincón, Antonio; Flugelman, Máximo; Prendes, Jorge; D'Giano, Carlos (Sociedad Argentina de Bioingeniería, 2019)

Seizure detection plays a central role in most aspects of epilepsy care. Understanding the complex epileptic signals system is a typical problem in electroencephalographic (EEG) signal processing. This problem requires different ...

Listar por autor "Quintero Rincón, Antonio"

Listar por autor "Quintero Rincón, Antonio"

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