Comput Methods Programs Biomed - Optimal channel selection for analysis of EEG-sleep patterns of neonates.

Tópicos

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Resumo

This paper extends our previous work on automated detection and classification of neonate EEG sleep stages. In [19] we adapted and integrated a range of computational, mathematical and statistical tools for the analysis of neonatal electroencephalogram (EEG) sleep recordings with the aim of facilitating the assessment of neonatal brain maturation and dismaturity by studying the structure and temporal patterns of their sleep. That work relied on algorithms using a single channel of EEG. The present paper builds on our previous work by incorporating a larger selection of EEG channels that capture both the spatial distribution and temporal patterns of EEG during sleep. Using a multivariate analysis approach, we obtain the "optimal" selection of the EEG channels and characteristics that are most suitable for EEG sleep state separation.

Resumo Limpo

paper extend previous work autom detect classif neonat eeg sleep stage adapt integr rang comput mathemat statist tool analysi neonat electroencephalogram eeg sleep record aim facilit assess neonat brain matur dismatur studi structur tempor pattern sleep work reli algorithm use singl channel eeg present paper build previous work incorpor larger select eeg channel captur spatial distribut tempor pattern eeg sleep use multivari analysi approach obtain optim select eeg channel characterist suitabl eeg sleep state separ

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