Author:

Keywords:

Science & Technology, Technology, Life Sciences & Biomedicine, Engineering, Biomedical, Neurosciences, Engineering, Neurosciences & Neurology, neonatal sleep stage classification, quiet sleep detection, convolutional neural networks, NEONATAL EEG, CLASSIFICATION, Algorithms, Brain, Databases, Factual, Electroencephalography, Humans, Infant, Newborn, Infant, Premature, Markov Chains, Neural Networks, Computer, Normal Distribution, Sleep Stages, Convolutional neural networks, Neonatal sleep stage classification, Quiet sleep detection, STADIUS-19-65, 0903 Biomedical Engineering, 1103 Clinical Sciences, 1109 Neurosciences, Biomedical Engineering, 3209 Neurosciences, 4003 Biomedical engineering

Abstract:

OBJECTIVE: To classify sleep states using electroencephalogram (EEG) that reliably works over a wide range of preterm ages, as well as term age. APPROACH: A convolutional neural network is developed to perform 2- and 4-class sleep classification in neonates. The network takes as input an 8-channel 30 s EEG segment and outputs the sleep state probabilities. Apart from simple downsampling of the input and smoothing of the output, the suggested network is an end-to-end algorithm that avoids the need for hand-crafted feature selection or complex pre/post processing steps. To train and test this method, 113 EEG recordings from 42 infants are used. MAIN RESULTS: For quiet sleep detection (the 2-class problem), mean kappa between the network estimate and the ground truth annotated by EEG human experts is 0.76. The sensitivity and specificity are 90% and 88%, respectively. For 4-class classification, mean kappa is 0.64. The averaged sensitivity and specificity (1 versus all) respectively equal 72% and 91%. The results outperform current state-of-the-art methods for which kappa ranges from 0.66 to 0.70 in preterm and from 0.51 to 0.61 in term infants, based on training and testing using the same database. SIGNIFICANCE: The proposed method has the highest reported accuracy for EEG sleep state classification for both preterm and term age neonates.