PDF(Pubmed)
Abstract：
Currently, there is a limited understanding of long-term outcomes of COVID-19, and a need for in-home measurements of patients through the whole course of their disease. We study a novel approach for monitoring the long-term trajectories of respiratory and behavioral symptoms of COVID-19 patients at home. We use a sensor that analyzes the radio signals in the room to infer patients\' respiration, sleep and activities in a passive and contactless manner. We report the results of continuous monitoring of three residents of an assisted living facility for 3 months, through the course of their disease and subsequent recovery. In total, we collected 4,358 measurements of gait speed, 294 nights of sleep, and 3,056 h of respiration. The data shows differences in the respiration signals between asymptomatic and symptomatic patients. Longitudinally, we note sleep and motor abnormalities that persisted for months after becoming COVID negative. Our study represents a novel phenotyping of the respiratory and behavioral trajectories of COVID recovery, and suggests that the two may be integral components of the COVID-19 syndrome. It further provides a proof-of-concept that contactless passive sensors may uniquely facilitate studying detailed longitudinal outcomes of COVID-19, particularly among older adults.
摘要：
目前,对COVID-19的长期结局了解有限,需要在患者的整个病程中进行家庭测量.我们研究了一种在家中监测COVID-19患者呼吸和行为症状长期轨迹的新方法。我们使用一个传感器来分析房间里的无线电信号来推断病人的呼吸，以被动和非接触的方式进行睡眠和活动。我们报告了对三名辅助生活设施的居民进行3个月的连续监测的结果，通过他们的疾病和随后的康复过程。总的来说,我们收集了4358个步态速度的测量值,294个夜晚的睡眠，和3,056小时的呼吸。数据显示无症状和有症状患者之间呼吸信号的差异。纵向,我们注意到睡眠和运动异常在COVID阴性后持续数月.我们的研究代表了COVID恢复的呼吸和行为轨迹的新表型，并提示两者可能是COVID-19综合征的组成部分。它进一步提供了一个概念验证，即非接触式无源传感器可以独特地促进研究COVID-19的详细纵向结果，特别是在老年人中。
