Epilepsia

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Development of an online calculator for the prediction of seizure freedom following pediatric hemispherectomy using the Hemispherectomy Outcome Prediction Scale (HOPS)

Weil, Alexander G.; Dimentberg, Evan; Lewis, Evan C.; Ibrahim, George M.; Kola, Olivia; Tseng, Chi-Hong; Chen, Jia-Shu; Lin, Kao-Min; Cai, Li-Xin; Liu, Qing-Zhu; Lin, Jiu-Luan; Zhou, Wen-Jing; Mathern, Gary W.; Smyth, Matthew D.; O'Neill, Brent R.; Dudley, Roy; Ragheb, John; Pociecha, Juan; Chamorro, Noelia; Muro, Valeria L. (Wiley, 2023-06-22)

Objectives: Although hemispheric surgeries are among the most effective procedures for drug-resistant epilepsy (DRE) in the pediatric population, there is a large variability in seizure outcomes at the group level. A ...
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 ...
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 ...
Artifacts Detection in EEG Signals

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

Resumen no disponible
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 ...
Cytotoxic lesion of the corpus callosum in a patient with aphasic status epilepticus

Castiglione, Juan Ignacio; Ricciardi, Mario Emiliano; Bensi, Catalina (Universidad de la Costa, 2020-12-07)

A 47-year-old man with a history of aphasic seizures presented to the emergency room with a 12-hour global aphasia. Upon admission, brain MRI did not reveal acute lesions, and EEG showed sharp waves in the left frontal-temporal ...
Hemispherectomy Outcome Prediction Scale: Development and validation of a seizure freedom prediction tool

Weil, Alexander G.; Lewis, Evan C.; Ibrahim, George M.; Kola, Olivia; Tseng, Chi-Hong; Zhou, Xinkai; Lin, Kao-Min; Cai, Li-Xin; Liu, Qing-Zhu; Lin, Jiu-Luan; Zhou, Wen-Jing; Mathern, Gary W.; Smyth, Matthew D.; O'Neill, Brent R.; Dudley, Roy; Ragheb, John; Bhatia, Sanjiv; Pociecha, Juan; Chamorro, Noelia; Muro, Valeria L. (Wiley, 2021-03-13)

Objective To develop and validate a model to predict seizure freedom in children undergoing cerebral hemispheric surgery for the treatment of drug‐resistant epilepsy. Methods We analyzed 1267 hemispheric surgeries ...
Developmental and epileptic encephalopathy due to SZT2 genomic variants: Emerging features of a syndromic condition

Trivisano, Marina; Rivera, Manuel; Terracciano, Alessandra; Ciolfi, Andrea; Napolitano, Antonio; Pepi, Chiara; Calabrese, Costanza; Digilio, Maria Cristina; Tartaglia, Marco; Curatolo, Paolo; Vigevano, Federico; Specchio, Nicola (Academic Press, 2020-07)

Seizure threshold 2 (SZT2) gene mutations have been associated with developmental and epileptic encephalopathies (DEEs). Following a literature review, we collected 22 patients and identified the main clinical features ...
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 ...
Postencephalitic Epilepsy and Acute Symptomatic Seizures, in Infectious, Undetermined Etiology and Autoimmune Encephalitis (P4.5-028)

Marone, Abril; Alessandro, Lucas; Ugarnes, Gabriela; Farez, Mauricio Franco (AAN, 2019-05-08)

Objective: To describe the encephalitis that have more frequently acute symptomatic seizures (ASS), type of seizures and development of postencephalitic epilepsy (PE). Background: Encephalitis is a frequent cause of ...
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 ...
Importance of Understanding the Real Cause of Death in Status Epilepticus

Hawkes, Maximiliano Alberto; Hocker, Sara (Academic Press, 2019-12-24)

Resumen no disponible
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 ...
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 ...

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