Department of Psychology, West Virginia University, Morgantown, West Virginia.
Department of Biobehavioral Health, Pennsylvania State University, State College, Pennsylvania.
J Clin Sleep Med. 2019 Jul 15;15(7):1051-1061. doi: 10.5664/jcsm.7892.
To assess the sleep detection and staging validity of a non-contact, commercially available bedside bio-motion sensing device (S+, ResMed) and evaluate the impact of algorithm updates.
Polysomnography data from 27 healthy adult participants was compared epoch-by-epoch to synchronized data that were recorded and staged by actigraphy and S+. An update to the S+ algorithm (common in the rapidly evolving commercial sleep tracker industry) permitted comparison of the original (S+V1) and updated (S+V2) versions.
Sleep detection accuracy by S+V1 (93.3%), S+V2 (93.8%), and actigraphy (96.0%) was high; wake detection accuracy by each (69.6%, 73.1%, and 47.9%, respectively) was low. Higher overall S+ specificity, compared to actigraphy, was driven by higher accuracy in detecting wake before sleep onset (WBSO), which differed between S+V2 (90.4%) and actigraphy (46.5%). Stage detection accuracy by the S+ did not exceed 67.6% (for stage N2 sleep, by S+V2) for any stage. Performance is compared to previously established variance in polysomnography scored by humans: a performance standard which commercial devices should ideally strive to reach.
Similar limitations in detecting wake after sleep onset (WASO) were found for the S+ as have been previously reported for actigraphy and other commercial sleep tracking devices. S+ WBSO detection was higher than actigraphy, and S+V2 algorithm further improved WASO accuracy. Researchers and clinicians should remain aware of the potential for algorithm updates to impact validity.
A commentary on this article appears in this issue on page 935.
评估一种非接触式、商业可用的床边生物运动感应设备（S+，ResMed）的睡眠检测和分期有效性，并评估算法更新的影响。
将 27 名健康成年参与者的多导睡眠图数据逐时与同步记录和由活动计和 S+分期的同步数据进行比较。S+算法的更新（在快速发展的商业睡眠追踪器行业中很常见）允许比较原始版本（S+V1）和更新版本（S+V2）。
S+V1（93.3%）、S+V2（93.8%）和活动计（96.0%）的睡眠检测准确性很高；而每个的觉醒检测准确性（分别为 69.6%、73.1%和 47.9%）较低。与活动计相比，S+的总体特异性较高，这是由于在检测睡眠开始前的觉醒（WBSO）方面的准确性较高，而 S+V2（90.4%）和活动计（46.5%）之间存在差异。S+对任何阶段的分期检测准确性都未超过 67.6%（S+V2 对 N2 期睡眠）。性能与以前多导睡眠图由人类评分的差异进行了比较：商业设备理想上应努力达到的性能标准。
与活动计和其他商业睡眠追踪设备以前报道的一样，S+在检测睡眠开始后的觉醒（WASO）方面也存在类似的局限性。S+对 WBSO 的检测高于活动计，并且 S+V2 算法进一步提高了 WASO 的准确性。研究人员和临床医生应始终意识到算法更新可能会影响有效性。
本文的一篇评论文章发表在本期第 935 页。
