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Hui Wu,1– 4,* Meiyan Zhou,2,* Songtao Liu,2,* Yu Qi,2 Fan Zhou,1– 4 Liwei Wang,1,2 Conghai Fan1,3,4 1College of Anesthesiology, Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic ...

Abstract High-throughput analysis of EEG data has significantly contributed to understanding neural dynamics in Alzheimer’s disease diagnosis. However, the complexity and high dimensionality of EEG signals pose challen...

"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...

Implicit learning is a fundamental cognitive process whose identification is critical for understanding human cognition and developing innovative training methodologies. We propose a generalizable feature selection and s...

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...

La alineacion temporal de señales de electroencefalograma (EEG) constituye un problema relevante en el analisis de potenciales relacionados con eventos (ERP) debido a la variabilidad en la latencia con la que aparecen e...

"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...

This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete...

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 ...

Materias / palabras clave: Nonparametric statistics; Statistical hypothesis testing; Null hypothesis; Test statistic; Computer science; Statistic; Statistical power; Null (SQL); Sensitivity (control systems); Statistics; Statistical model; Artific...

Abstract Epilepsy is a chronic neurological disease that profoundly impacts patients’ daily lives. Electroencephalography (EEG) serves as a crucial tool for the clinical diagnosis of epilepsy and other brain disorders....

BackgroundCaffeine is one of the most frequently administered medicines in neonatology—prescribed for the management of apnoea of prematurity, to aid extubation and increasingly for conditions such as bronchopulmonary ...

BackgroundBuilt environments shape navigation, attention, and motor control through continuous brain–body-environment coupling, yet architecture, rehabilitation, and clinical mobility practice still lack a shared quant...

Abstract Background In the neurorehabilitation framework of treadmill-based robot-assisted gait training (t-RAGT), a threefold relationship among physiotherapist (Pht), patient (Pt), and the selected robotic device shoul...

This study presents a novel machine learning approach to assess human well-being through the analysis of brain wave activities. We developed a Random Forest classifier to categorize brain wave patterns into three states ...