EEG is a valuable tool for evaluation of brain maturation in preterm babies. Preterm EEG constitutes of high voltage burst activities and more suppressed episodes, called interburst intervals (IBIs). Evolution of background characteristics provides information on brain maturation and helps in prediction of neurological outcome. The aim is to develop a method for automated burst detection.status: publishe
Background: The electroencephalographic (EEG) background pattern of preterm infants changes with pos...
The goal of this study is to develop an automated algorithm to quantify background electroencephalog...
BACKGROUND: The electroencephalographic (EEG) background pattern of preterm infants changes with pos...
To extract useful information from preterm electroencephalogram (EEG) for diagnosis and long-term pr...
To aid with prognosis and stratification of clinical treatment for preterm infants, a method for aut...
Objective: To describe the characteristics of activity bursts in the early preterm EEG, to assess in...
Aim: To develop a method that segments preterm EEG into bursts and inter-bursts by extracting and co...
\u3cp\u3eElectroencephalographic characteristics are useful in assessment of the functional status o...
Release for paper: JM O' Toole, GB Boylan, RO Lloyd, RM Goulding, S Vanhatalo, and NJ Stevenson, "D...
International audienceObjective: The study of electroencephalographic (EEG) bursts in preterm infant...
EEG inter-burst interval (IBI) and its evolution is a robust parameter for grading hypoxic encephalo...
Essential information about early brain maturation can be retrieved from the preterm human electroen...
This PhD project aims to define specific EEG maturational features in premature infants and to devel...
Around 10 percent of all human births is premature, which means about 15 million babies are born bef...
In this paper, we study machine learning techniques and features of electroencephalography activity ...
Background: The electroencephalographic (EEG) background pattern of preterm infants changes with pos...
The goal of this study is to develop an automated algorithm to quantify background electroencephalog...
BACKGROUND: The electroencephalographic (EEG) background pattern of preterm infants changes with pos...
To extract useful information from preterm electroencephalogram (EEG) for diagnosis and long-term pr...
To aid with prognosis and stratification of clinical treatment for preterm infants, a method for aut...
Objective: To describe the characteristics of activity bursts in the early preterm EEG, to assess in...
Aim: To develop a method that segments preterm EEG into bursts and inter-bursts by extracting and co...
\u3cp\u3eElectroencephalographic characteristics are useful in assessment of the functional status o...
Release for paper: JM O' Toole, GB Boylan, RO Lloyd, RM Goulding, S Vanhatalo, and NJ Stevenson, "D...
International audienceObjective: The study of electroencephalographic (EEG) bursts in preterm infant...
EEG inter-burst interval (IBI) and its evolution is a robust parameter for grading hypoxic encephalo...
Essential information about early brain maturation can be retrieved from the preterm human electroen...
This PhD project aims to define specific EEG maturational features in premature infants and to devel...
Around 10 percent of all human births is premature, which means about 15 million babies are born bef...
In this paper, we study machine learning techniques and features of electroencephalography activity ...
Background: The electroencephalographic (EEG) background pattern of preterm infants changes with pos...
The goal of this study is to develop an automated algorithm to quantify background electroencephalog...
BACKGROUND: The electroencephalographic (EEG) background pattern of preterm infants changes with pos...