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"The use of Brain-Computer Interfaces can provide substantial improvements to the quality of life of patients with diseases such as severe Amyotrophic lateral sclerosis that cause Locked-in syndrome, by creating new aven...

"This paper presents a statistical signal processing method for the characterization of EEG of patients suffering from epilepsy. A statistical model is proposed for the signals and the Kullback-Leibler divergence is used...

"This paper presents a supervised classification method to accurately detect epileptic brain activity in real-time from electroencephalography (EEG) data. The proposed method has three main strengths: it has low computat...

This document provides some basic guidance to start working with the EPOC Emotiv neuroheadset device and describes how to use it to perform basic Brain-Computer Interface (BCI) research. A brief tutorial on how to set up...

"Appropriate diagnosis and treatment of epilepsy is a main public health issue. Patients suffering from this disease often exhibit different physical characterizations, which results from the synchronous and excessive di...

"Brain Computer Interface (BCI) or Brain Machine Interfaces (BMI), has proved the feasibility of a distinct non-biological communication channel to transmit information from the Central Nervous System (CNS) to a computer...

"Identificar la actividad cerebral epiléptica utilizando señales de electroencefalografía (EEG) en tiempo real es un problema difícil. Los métodos modernos de detección basados en técnicas avanzadas de aprendizaje...

Electrophysiological impairments of alcoholism have been researched extensively. However, there is none or few reported research on screening methods for chronic alcoholic subjects. Since chronic alcoholics have serious ...

"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, ...

"This work proposes a methodological approach to the insertion of a particular artifact produced by eyes blinking, in EEG data, in order to create a pseudo-real dataset, which in turn provides an experimental setup to te...

"Electroencephalography (EEG) system validation faces a fundamental challenge: the absence of ground truth when measuring human subjects. Physical head phantoms provide controlled testing environments with known signals;...

"Identify spike-and-waves patterns in epileptic signals is a typical problem in electroencephalographic (EEG) signal processing. In this paper we propose cross-correlation coupled with decision tree model as new method ...

"Error-related potential (ErrP) are a particular type of Event-Related Potential (ERP) elicited by a person attending a recognizable error. These Electroencephalographic (EEG) signals can be used to train a gaming agent ...