The wrist is not the brain: Estimation of sleep by clinical and consumer wearable actigraphy devices is impacted by multiple patient- and device-specific factors
The wrist is not the brain: Estimation of sleep by clinical and consumer wearable actigraphy devices is impacted by multiple patient- and device-specific factors
复制标题
DOI：
10.1111/jsr.12926
复制
发表时间：
2019-10-17
影响因子：
4.4
通讯作者：
Trotti, Lynn Marie
中科院分区：
文献类型：
--
作者：
Danzig, Rachel;Wang, Mengxi;Trotti, Lynn Marie
临床活动记录仪提供了大量人群睡眠测量的适当估计。在实践中，供应商被要求将临床或消费者可穿戴数据应用于个体患者评估。器械性能的个体差异将影响这种针对患者的解释。我们评估了两种设备，临床和消费者，以确定这种个体水平变异性的大小和预测因素。102例接受多导睡眠检查的患者（55例[53.9%]女性；56.4例[+/- 16.3]岁）佩戴了Jawbone UP3和/或Actiwatch2。用多导睡眠仪比较设备总睡眠时间、睡眠效率、睡眠后觉醒和睡眠潜伏期。将人口统计学、睡眠结构和临床测量与设备性能进行比较。Actiwatch高估了总睡眠时间27.2分钟（95%置信限[CL]，高于138.3分钟至低于84.0分钟），高估了睡眠效率6.8%(95%置信限，高于34.1%至低于20.5%)，高估了睡眠开始潜伏期2.6分钟（95%置信限，高于63.3分钟至低于58.2分钟），低估了睡眠开始后醒来时间50.7分钟（95%置信限，低于162.5分钟至高于61.2分钟）。Jawbone高估了总睡眠时间59.1分钟（95% CL，高于208.6分钟至低于90.5分钟），高估了睡眠效率14.9% （95% CL，高于52.6%至低于22.7%）。在多变量模型中，年龄、睡眠开始潜伏期、睡眠开始后醒来、% N1和呼吸暂停低通气指数只能解释设备性能的部分差异。性别也会影响成绩。Actiwatch和Jawbone对睡眠测量的错误估计有很宽的置信限，准确度因多个患者水平的特征而异。考虑到这些巨大的个体不准确性，这些设备的数据在临床实践中必须非常谨慎地应用。
Clinical actigraphy devices provide adequate estimates of some sleep measures across large groups. In practice, providers are asked to apply clinical or consumer wearable data to individual patient assessments. Inter-individual variability in device performance will impact such patient-specific interpretation. We assessed two devices, clinical and consumer, to determine the magnitude and predictors of this individual-level variability. One hundred and two patients (55 [53.9%] female; 56.4 [+/- 16.3] years old) undergoing polysomnography wore Jawbone UP3 and/or Actiwatch2. Device total sleep time, sleep efficiency, wake after sleep onset and sleep latency were compared with polysomnography. Demographics, sleep architecture and clinical measures were compared to device performance. Actiwatch overestimated total sleep time by 27.2 min (95% confidence limits [CL], 138.3 min over to 84.0 under), overestimated sleep efficiency by 6.8% (95% CL, 34.1% over to 20.5% under), overestimated sleep onset latency by 2.6 min (95% CL, 63.3 over to 58.2 under) and underestimated wake after sleep onset by 50.7 min (95% CL, 162.5 under to 61.2 over). Jawbone overestimated total sleep time by 59.1 min (95% CL, 208.6 min over to 90.5 under) and overestimated sleep efficiency by 14.9% (95% CL, 52.6% over to 22.7% under). In multivariate models, age, sleep onset latency, wake after sleep onset, % N1 and apnea-hypopnea index explained only some of the variance in device performance. Gender also affected performance. Actiwatch and Jawbone mis-estimate sleep measures with very wide confidence limits and accuracy varies with multiple patient-level characteristics. Given these large individual inaccuracies, data from these devices must be applied only with extreme caution in clinical practice.