Sleep Analysis Using Motion and Head Detection

Abstract

Videosomnography (VSG) is a range of video-based methods used to record and assess sleep vs. wake states in adults and children. Traditional behavioral-VSG (B-VSG) coding requires almost real-time visual inspection by a trained technicians/coders to determine sleep vs wake states. In this paper we describe an automated VSG sleep detection system (auto-VSG) which employs motion analysis to determine sleep vs. wake states in young children. We used child head size to normalize the motion index and to provide an individual motion maximum for each child. We compared the proposed auto-VSG method to (1) traditional B-VSG codes and (2) actigraphy sleep vs. wake estimates across four sleep parameters: sleep onset time, sleep offset time, awake duration, and sleep duration. In sum, analyses revealed that estimates generated from the proposed auto-VSG method and B-VSG are comparable.