The University of Queensland, School of Health and Rehabilitation Sciences, Brisbane QLD, Australia.
Department of Physiotherapy, Medicine and Biomedical Sciences, University of A Coruña, Spain.
Physiol Meas. 2022 Jan 31;43(1). doi: 10.1088/1361-6579/ac482f.
. Understanding sleeping behaviours could improve prevention and treatment of sleep problems and associated health conditions. This study aimed to evaluate a method to assess body posture and movement during sleep using trunk-worn accelerometers for 28 nights.. Participants (50 adults with low back pain (66% female); aged 32(±9) years) wore two activPAL-micro sensors (thigh, trunk) during their normal daily life for 28 consecutive days. Parameters related to body posture (e.g. time spent lying supine or prone) and movement (e.g. number of turns) during sleep were calculated for each night. Average values for each parameter were identified for different periods, the Spearman-Brown Prophecy Formula was used to estimate the minimum number of nights required to obtain a reliable estimate of each parameter, and repeatability of measures between different weeks was calculated.. Participants spent 8.1(±0.8) h asleep and most time (44%) was spent in a supine posture. The minimum number of nights required for reliable estimates varied between sleep parameters, range 4-21 nights. The most stable parameters (i.e. requiring less than seven nights) were 'average activity', 'no. of turns', 'time spent prone', and 'posture changes in the first hour'. Some measures differed substantially between weeks.. Most sleep parameters related to body posture and movement require a week or more of monitoring to provide reliable estimates of behaviour over one month. Notably, one week may not reflect behaviour in another week, and the time varying nature of sleep needs to be considered.
. 了解睡眠行为可以改善睡眠问题和相关健康状况的预防和治疗。本研究旨在评估一种使用躯干佩戴加速度计评估睡眠期间身体姿势和运动的方法,共进行了 28 晚的研究。.. 参与者(50 名患有下腰痛的成年人(66%为女性);年龄 32(±9)岁)在 28 天的连续时间内,每天正常生活时佩戴两个 activPAL-micro 传感器(大腿、躯干)。计算了睡眠期间与身体姿势(例如仰卧或俯卧时间)和运动(例如翻身次数)相关的参数。为不同时间段确定了每个参数的平均值,使用 Spearman-Brown 预测公式估计获得每个参数可靠估计所需的最少夜间数,并计算了不同周之间测量的可重复性。.. 参与者平均每晚睡眠时间为 8.1(±0.8)小时,大部分时间(44%)处于仰卧位。获得可靠估计所需的最少夜间数因睡眠参数而异,范围为 4-21 晚。最稳定的参数(即需要少于七晚)是“平均活动”、“翻身次数”、“俯卧时间”和“第一小时内的姿势变化”。一些措施在不同周之间存在显著差异。.. 与身体姿势和运动相关的大多数睡眠参数需要一周或更长时间的监测,才能提供一个月内行为的可靠估计。值得注意的是,一周的行为可能与另一周不同,并且需要考虑睡眠的时间变化性质。