Schütz Narayan, Saner Hugo, Botros Angela, Buluschek Philipp, Urwyler Prabitha, Müri René M, Nef Tobias
ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.
Sechenov First Moscow State Medical University, Moscow, Russia.
Front Digit Health. 2021 Jan 20;2:566595. doi: 10.3389/fdgth.2020.566595. eCollection 2020.
Passive infrared motion sensors are commonly used in telemonitoring applications to monitor older community-dwelling adults at risk. One possible use case is quantification of in-home physical activity, a key factor and potential digital biomarker for healthy and independent aging. A major disadvantage of passive infrared sensors is their lack of performance and comparability in physical activity quantification. In this work, we calibrate passive infrared motion sensors for in-home physical activity quantification with simultaneously acquired data from wearable accelerometers and use the data to find a suitable correlation between in-home and out-of-home physical activity. We use data from 20 community-dwelling older adults that were simultaneously provided with wireless passive infrared motion sensors in their homes, and a wearable accelerometer for at least 60 days. We applied multiple calibration algorithms and evaluated results based on several statistical and clinical metrics. We found that using even relatively small amounts of wearable based ground-truth data over 7-14 days, passive infrared based wireless sensor systems can be calibrated to give largely better estimates of older adults' daily physical activity. This increase in performance translates directly to stronger correlations of measured physical activity levels with a variety of age relevant health indicators and outcomes known to be associated with physical activity.
被动红外运动传感器常用于远程监测应用中,以监测有风险的社区老年居民。一个可能的用例是对家庭内身体活动进行量化,这是健康和独立衰老的关键因素及潜在的数字生物标志物。被动红外传感器的一个主要缺点是它们在身体活动量化方面缺乏性能和可比性。在这项工作中,我们利用可穿戴加速度计同时采集的数据,对用于家庭内身体活动量化的被动红外运动传感器进行校准,并使用这些数据来找到家庭内和家庭外身体活动之间的合适相关性。我们使用了来自20名社区老年居民的数据,他们在家中同时配备了无线被动红外运动传感器和一个可穿戴加速度计,持续至少60天。我们应用了多种校准算法,并基于多个统计和临床指标评估结果。我们发现,即使使用相对少量的基于可穿戴设备的7至14天的地面真值数据,基于被动红外的无线传感器系统也可以进行校准,从而对老年人的日常身体活动给出更好的估计。性能的提升直接转化为测量的身体活动水平与各种与年龄相关的健康指标以及已知与身体活动相关的结果之间更强的相关性。