Covid-19：可穿戴物可以检测到症状

战士观察研究发现，参与者的心率变异性（HRV）的微妙变化苹果手表能够用信号发出发出新冠肺炎在个人通过诊断患有感染前七天鼻拭子，也识别那些有症状的人。

“This study highlights the future of digital health,” says the study’s corresponding author Robert P. Hirten, MD, Assistant Professor of Medicine (Gastroenterology) at the Icahn School of Medicine at Mount Sinai, and member of the Hasso Plattner Institute for Digital Health at Mount Sinai and the Mount Sinai Clinical Intelligence Center (MSCIC). “It shows that we can use these technologies to better address evolving health needs, which will hopefully help us improve the management of disease. Our goal is to operationalize these platforms to improve the health of our patients and this study is a significant step in that direction. Developing a way to identify people who might be sick even before they know they are infected would be a breakthrough in the management of COVID-19.”

研究人员在4月和9月20日期间在持续的数字研究中招募了山上卫生系统的数百名医疗工作者。参与者通过定制的应用程序佩戴Apple Watches并回答日常问题。

他们的HRV变化 - 一种检测到的神经系统函数的量度可穿戴设备- 用来识别和预测工人是否被Covid-19感染或有症状。收集的其他日常症状包括发烧或寒冷，疲倦或弱点，身体疼痛，干咳，打喷嚏，流鼻涕，腹泻，喉咙痛，头痛，呼吸急促，嗅觉或味道，眼睛瘙痒。

此外，研究人员发现，使用Covid-19诊断后7至14天，HRV模式开始正常化，并且不再与未被感染的人的模式有统计学不同。

“This technology allows us not only to track and predict health outcomes, but also to intervene in a timely and remote manner, which is essential during a pandemic that requires people to stay apart,” says the study’s co-author Zahi Fayad, PhD, Director of the BioMedical Engineering and Imaging Institute, and the Lucy G. Moses Professor of Medical Imaging and Bioengineering at the Icahn School of Medicine at Mount Sinai.

战士观察研究涉及哈索普拉特纳数字健康研究所和MSCIC的协作努力，这代表了一群多样化的数据科学家，工程师，临床医师和跨春季山上卫生系统的研究人员2020年打击Covid-19。该研究将接下来仔细看看生物识别学，包括HRV，睡眠中断和身体活动，以更好地了解哪些医疗工作者面临大流行的心理影响的风险。

调查结果发表在了医科互联网研究杂志。