使用运动和头部检测进行睡眠分析

J. Choe, D. M. Montserrat, A. Schwichtenberg, E. Delp
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引用次数: 3

摘要

视频睡眠记录仪(VSG)是一系列基于视频的方法,用于记录和评估成人和儿童的睡眠和清醒状态。传统的行为- vsg (B-VSG)编码需要训练有素的技术人员/编码器进行几乎实时的视觉检查,以确定睡眠和清醒状态。在本文中,我们描述了一个自动VSG睡眠检测系统(auto-VSG),该系统采用运动分析来确定幼儿的睡眠和清醒状态。我们使用儿童头部大小来标准化运动指数,并为每个儿童提供单独的运动最大值。我们将提出的自动vsg方法与(1)传统的B-VSG编码和(2)在四个睡眠参数(睡眠开始时间、睡眠偏移时间、清醒持续时间和睡眠持续时间)上的睡眠与清醒估计进行了比较。总而言之,分析表明,所提出的auto-VSG方法和B-VSG方法产生的估计具有可比性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sleep Analysis Using Motion and Head Detection
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.
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