School of Public Health and Health Systems, University of Waterloo, Waterloo, ON, Canada.
Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, ON, Canada.
JMIR Mhealth Uhealth. 2020 Nov 20;8(11):e21016. doi: 10.2196/21016.
Advances in technology have made the development of remote patient monitoring possible in recent years. However, there is still room for innovation in the types of technologies that are developed, used, and implemented. The smart thermostat solutions provided in this study can expand beyond typically defined features and be used for improved holistic health monitoring purposes.
The aim of this study is to validate the hypothesis that remote motion sensors could be used to quantify and track an individual's movements around the house. On the basis of our results, the next step would be to determine if using remote motion sensors could be a novel data collection method compared with the national census-level surveys administered by governmental bodies. The results will be used to inform a more extensive implementation study of similar smart home technologies to gather data for machine learning algorithms and to build upon pattern recognition and comprehensive health monitoring.
We conducted a pilot study with a sample size of 8 to validate the use of remote motion sensors to quantify movement in the house. A large database containing data from smart home thermostats was analyzed to compare the following indicators; sleep, physical activity, and sedentary behavior. These indicators were developed by the Public Health Agency of Canada and are collected through traditional survey methods.
The results showed a significant Spearman rank correlation coefficient of 0.8 (P<.001), which indicates a positive linear association between the total number of sensors activated and the total number of indoor steps traveled by study participants. In addition, the indicators of sleep, physical activity, and sedentary behavior were all found to be highly comparable with those attained by the Public Health Agency of Canada.
The findings demonstrate that remote motion sensors data from a smart thermostat solution are a viable option when compared with traditional survey data collection methods for health data collection and are also a form of zero-effort technology that can be used to monitor the activity levels and nature of activity of occupants within the home.
近年来,技术的进步使得远程患者监测成为可能。然而,在开发、使用和实施的技术类型方面仍有创新的空间。本研究中提供的智能恒温器解决方案可以超越通常定义的功能,并用于改善整体健康监测目的。
本研究的目的是验证远程运动传感器可用于量化和跟踪个体在房屋周围的运动的假设。基于我们的结果,下一步将确定使用远程运动传感器是否可以成为与政府机构管理的全国人口普查级调查相比的一种新颖的数据收集方法。结果将用于告知更广泛的类似智能家居技术的实施研究,以收集数据用于机器学习算法,并建立在模式识别和全面健康监测的基础上。
我们进行了一项试点研究,样本量为 8 人,以验证远程运动传感器在量化房屋内运动方面的使用。分析了一个包含智能家居恒温器数据的大型数据库,以比较以下指标:睡眠、身体活动和久坐行为。这些指标由加拿大公共卫生局制定,并通过传统调查方法收集。
结果显示,总传感器激活数与研究参与者在室内行走的总步数之间存在显著的斯皮尔曼等级相关系数 0.8(P<.001),这表明存在正线性关联。此外,睡眠、身体活动和久坐行为的指标都与加拿大公共卫生局获得的指标高度一致。
研究结果表明,与传统的调查数据收集方法相比,智能恒温器解决方案的远程运动传感器数据是一种可行的健康数据收集选项,也是一种可以用于监测家庭居住者活动水平和活动性质的零努力技术形式。