Terrill Philip I, Mason David G, Wilson Stephen J
The School of Information Technology and Electrical Engineering at the University of Queensland, St. Lucia, 4067 Australia.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:6150-3. doi: 10.1109/IEMBS.2010.5627780.
Actigraphy has proven to be a useful tool in the assessment of circadian rhythms, and more recently in the automatic staging of sleep and wake states. Whilst accuracy of commercial systems appears good over 24 hour periods, the sensitivity of detecting wake during time in bed is poor. One possible explanation for these poor results is the technical limitations of currently available commercial actigraphs. In particular, raw data is generally not available to the user. Instead, activity counts for each epoch (typically between 10-60 secs) are calculated using various algorithms, from which sleep state is identified. Consequently morphologically different movements observed during sleep and wake states may not be detected as such. In this paper, the development of a continuous multisite, accelerometry system (CMAS) is described. Initial results, comparing data collected using a commercial actigraph (Actiwatch- Mini Motionlogger), and the continuous multisite accelerometry system are presented. The CMAS is able to differentiate brief movement "twitches" from postural changes.
活动记录仪已被证明是评估昼夜节律的有用工具，最近还用于睡眠和清醒状态的自动分期。虽然商业系统在24小时期间的准确性似乎不错，但检测卧床期间清醒状态的灵敏度较差。这些不佳结果的一个可能解释是当前可用商业活动记录仪的技术限制。特别是，原始数据通常不对用户开放。相反，使用各种算法计算每个时段（通常为10 - 60秒）的活动计数，从中识别睡眠状态。因此，在睡眠和清醒状态期间观察到的形态不同的运动可能无法被如此检测到。本文描述了一种连续多部位加速度测量系统（CMAS）的开发。展示了使用商业活动记录仪（Actiwatch - Mini Motionlogger）收集的数据与连续多部位加速度测量系统进行比较的初步结果。CMAS能够区分短暂的运动“抽搐”和姿势变化。
