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Researchers at the University of Helsinki and the Helsinki University Hospital in Finland developed a software based on machine learning, which can independently interpret EEG signals from a premature infant and generate an estimate of the brain’s functional maturity.
In the study, published in the journal Scientific Reports, a large amount of EEG data on preterm infants was fed into a computer, and the software calculated hundreds of computational features from each measurement without intervention from a doctor.
With the help of a support vector machine algorithm, these features were combined to generate a reliable estimate of the EEG maturational age of the infant, researchers said.
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“We currently track the development of an infant’s weight, height and head circumference with growth charts,” said Sampsa Vanhatalo from the University of Helsinki.
EEG monitoring combined with automatic analysis provides a practical tool for the monitoring of the neurological development of preterm infants and generates information which will help plan the best possible care for the individual child, Vanhatalo said.
“This method gives us a first-time opportunity to track the most crucial development of a preterm infant, the functional maturation of the brain, both during and after intensive care,” researchers said.