Pediatric Videosomnography: Can Signal/Video Processing Distinguish Sleep and Wake States?

Abstract

The term videosomnography captures a range of video-based methods used to record and subsequently score sleep behaviors (most commonly sleep vs. wake states). Until recently, the time consuming nature of behavioral videosomnography coding has limited its clinical and research applications. However, with recent technological advancements, the use of auto-videosomnography techniques may be a practical and valuable extension of behavioral videosomnography coding. To test an auto-videosomnography system within a pediatric sample, we processed 30 videos of infant/toddler sleep using a series of signal/video-processing techniques. The resulting auto-videosomnography system provided minute-by-minute sleep vs. wake estimates, which were then compared to behaviorally coded videosomnography and actigraphy. Minute-by-minute estimates demonstrated moderate agreement across compared methods (auto-videosomnography with behavioral videosomnography, Cohen's kappa = 0.46; with actigraphy = 0.41). Additionally, auto-videosomnography agreements exhibited high sensitivity for sleep but only about half of the wake minutes were correctly identified. For sleep timing (sleep onset and morning rise time), behavioral videosomnography and auto-videosomnography demonstrated strong agreement. However, nighttime waking agreements were poor across both behavioral videosomnography and actigraphy comparisons. Overall, this study provides preliminary support for the use of an auto-videosomnography system to index sleep onset and morning rise time only, which may have potential telemedicine implications. With replication, auto-videosomnography may be useful for researchers and clinicians as a minimally invasive sleep timing assessment method.