Abstract
Study objectivesUnobtrusive monitoring of sleep and sleep disorders in children presents challenges. We investigated the possibility of using Ultra-Wide band (UWB) radar to measure sleep in children. MethodsThirty-two children scheduled to undergo a clinical polysomnography participated; their ages ranged from 2 months to 14 years. During the polysomnography, the children's body movements and breathing rate were measured by an UWB-radar. A total of 38 features were calculated from the motion signals and breathing rate obtained from the raw radar signals. Adaptive boosting was used as machine learning classifier to estimate sleep stages, with polysomnography as gold standard method for comparison. ResultsData of all participants combined, this study achieved a Cohen's Kappa coefficient of 0.67 and an overall accuracy of 89.8% for wake and sleep classification, a Kappa of 0.47 and an accuracy of 72.9% for wake, rapid-eye-movement (REM) sleep, and non-REM sleep classification, and a Kappa of 0.43 and an accuracy of 58.0% for wake, REM sleep, light sleep and deep sleep classification. ConclusionAlthough the current performance is not sufficient for clinical use yet, UWB radar is a promising method for non-contact sleep analysis in children.
Highlights
Sleep is thought to play a crucial role in infants' and children's brain development [1,2]
The aim of our study was to make a pediatric sleep stage classification algorithm based on Ultra-Wide band (UWB) radar data with PSG as gold standard method; a secondary aim was to assess the UWB radar accuracy in automatically determining sleep stages
This study shows that sleep stage classification in children can be accurately assessed using UWB-radar technology and shows that it can be a reliable technique to contactlessly assess children's sleep
Summary
Sleep is thought to play a crucial role in infants' and children's brain development [1,2]. The human sleep cycle has two main stages: rapid-eye-movement (REM) sleep and Non-REM (NREM) sleep [3]. The latter can be subdivided in three stages: N1 and N2 (light sleep) and N3 (deep sleep, slow wave sleep). REM sleep and NREM sleep each seem to contribute to different aspects of brain maturation [4]. During early brain development REM sleep is thought to provide important endogenous neural stimulation, laying the groundwork for early neural circuitry [4]. NREM sleep seems to be involved in regulating synaptic homeostasis [4]
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