An electroencephalography-based sleep index and supervised machine learning as a suitable tool for automated sleep classification in children.
Journal:
Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
Published Date:
Mar 1, 2024
Abstract
STUDY OBJECTIVES: Although sleep is frequently disrupted in the pediatric intensive care unit, it is currently not possible to perform real-time sleep monitoring at the bedside. In this study, spectral band powers of electroencephalography data are used to derive a simple index for sleep classification.