Chow Chin Moi, Wong Shi Ngar, Shin Mirim, Maddox Rebecca G, Feilds Kristy-Lee, Paxton Karen, Hawke Catherine, Hazell Philip, Steinbeck Katharine
Discipline of Exercise and Sport Science, Faculty of Health Sciences.
Sydney Medical School.
Nat Sci Sleep. 2016 Nov 21;8:321-328. doi: 10.2147/NSS.S114969. eCollection 2016.
Actigraphy is increasingly used for sleep monitoring. However, there is a lack of standardized methodology for data processing and analysis, which often makes between study comparisons difficult, if not impossible, and thus open to flawed interpretation. This study evaluated a manual method for detection of the rest interval in actigraph data collected with Actiwatch 2. The rest interval (time in bed), defined as the bedtime and rise time and set by proprietary software, is an essential requirement for the estimation of sleep indices. This study manually and systematically detected the rest interval of 187 nights of recording from seven healthy males and three females, aged 13.5±0.7 (mean ± standard deviation) years. Data were analyzed for agreement between software default algorithm and manual scoring. Inter-rater reliability in manual scoring was also tested between two scorers. Data showed consistency between default settings and manual scorers for bedtime and rise time, but only moderate agreement for the rest interval duration and poor agreement for activity level at bedtime and rise time. Manual detection of rest intervals between scorers showed a high degree of agreement for all parameters (intraclass correlations range 0.864 to 0.995). The findings demonstrate that the default algorithm on occasions was unable to detect rest intervals or set the exact interval. Participant issues and inter-scorer issues also made difficult the detection of rest intervals. These findings have led to a manual detection protocol to define bedtime and rise time, supplemented with an event diary.
活动记录仪越来越多地用于睡眠监测。然而,目前缺乏用于数据处理和分析的标准化方法,这常常使得不同研究之间的比较变得困难,甚至无法进行,从而容易导致有缺陷的解读。本研究评估了一种手动方法,用于检测使用Actiwatch 2收集的活动记录仪数据中的休息间隔。休息间隔(卧床时间)由专有软件定义为就寝时间和起床时间,是估算睡眠指标的一项基本要求。本研究手动并系统地检测了7名健康男性和3名健康女性187个夜晚的记录中的休息间隔,这些参与者年龄为13.5±0.7(均值±标准差)岁。分析数据以比较软件默认算法和手动评分之间的一致性。还测试了两名评分者之间手动评分的评分者间信度。数据显示,就寝时间和起床时间在默认设置和手动评分之间具有一致性,但休息间隔时长的一致性一般,就寝时间和起床时间的活动水平一致性较差。评分者之间对休息间隔的手动检测在所有参数上都显示出高度一致性(组内相关系数范围为0.864至0.995)。研究结果表明,默认算法有时无法检测到休息间隔或设定准确的间隔。参与者的问题和评分者之间的问题也使得休息间隔的检测变得困难。这些研究结果促成了一种用于定义就寝时间和起床时间的手动检测方案,并辅以事件日记。