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智能手表的研究扩展到识别COVID-19症状

亚洲必赢在杜克大学的研究人员正在帮助建立早期症兆检测更全面的方法。数据收集,分析和报警并行工业级人机界面(HMI)的移动应用软件。

杜克大学 2020年6月23日
智能手表研究通过提供设计,检测COVID-19设备的扩展。礼貌:杜克大学

亚洲必赢杜克大学的研究人员正在扩大近期旨在帮助研究确定COVID-19,造成新型冠状病毒疾病的症状。这种扩展的努力将帮助球队建立早期症兆检测更全面的方法,并提供有关如何将病毒可以通过社区传播更多的信息。

原本4月推出,CovIdentify旨在探讨如何通过智能手机收集到的数据,苹果手表和其他智能手表可以帮助确定设备用户是否拥有COVID-19。该项目由(杜克大学医学+工程)生物医学工程Jessilyn邓恩,赖恩·肖,卫生创新实验室的护理和导演的副教授助理教授,并在杜克大学健康与MEDX其他合作者的带领下,探讨如何生物特征信息,像睡眠时间表,氧气水平,活动水平和心脏率,可用于指示COVID-19的早期症状。

在他们的研究的展开阶段,团队将推出iOS应用程序和发送设备的目标人群和服务不足的社区是处于感染冠状病毒的风险最高。他们还建立了与Garmin和Fitbit正式的伙伴关系,以扩大可用于研究的各种设备。

“Our team recognized that COVID-19 was going to be a long-term health care problem, and we knew that wearable devices and smartphones would be a good way to develop digital biomarkers that could determine a COVID-19 infection,” said Shaw. “One of our goals is to expand our data collection capabilities, which will increase our ability to differentiate the COVID-19 infection from other illnesses. This differentiation is going to be key, as we expect to see waves of resurgence pop up as the country opens back up, and some of these flare-ups may coincide with flu season.”

邓恩和她的团队已经注意到冠状病毒已对不足的社区,少数民族和患有慢性疾病,如糖尿病和高血压的人不成比例的影响。与合作者合作,该小组计划目标,并从这些社区收集更全面的生物识别数据。

“我们看到,少数族裔是在两个订约COVID-19和开发更严重的疾病的风险要大得多,所以我们探索什么生物识别因素可能会导致这种风险是很重要的,”肖说。

In the first phase of CovIdentfy, the team launched the covidentify.org website, which allows participants to input their relevant demographics and medical information. Delivered via text or email, the daily survey asks participants about people they’ve been in contact with and about specific symptoms if they feel sick. Participants are also asked to share biometric data from their smartphones and smartwatches. The team then matches the biometric data with answers from the survey questions to use the relationship between reported symptoms and any changes in the biometric data to develop biomarkers.

“的iOS应用会非常简化注册和调查过程,它扩展了我们可以工作的工具,”邓恩说。“该CovIdentify应用程序将能够从任何设备中提取数据的同步处理与苹果Healthkit应用,这是对所有iPhone标准的应用程序。”

To ensure that they’re also pulling data from a variety of sources and communities, the team developed a plan to target recruitment of people that have a higher risk of contracting the disease, including delivery drivers, grocery store workers, hospital cleaning and cafeteria staff and nurse aids. They are also exploring how they can deploy watches in high-density housing like nursing homes, college dorms, military barracks and homeless shelters.

Study sponsors are supplying devices to people in these key populations who would not otherwise be able to afford a wearable device. The team also is ramping up their targeting efforts in locations outside of the United States where viral hotspots have been identified.

“我们已经把有针对性的社交媒体广告为研究对象,其部署在周围,可报告在阳性病例增加了全球范围内的城市,”邓恩说。“这是一个全球性的流行病,所以这一点很重要,我们可以我们可以从世界各地收集的数据开始开发全面的诊断解决方案和管理爆发工作。”

最初,CovIdentify是预计到2020年底,这将让球队从可穿戴式设备六个月数据的前进收集12份个月的历史数据来运行。从杜克大学的扩展支持,该项目将通过现在运行2021。

“If CovIdentify is successful, it will be a non-invasive and accessible tool that can help us control the spread of the coronavirus,” Dunn said. “This expanded support brings this goal closer to becoming a reality, and we’re grateful for the support from Duke and from our partners in industry.”

- 编辑克里斯Vavra,副主编,必赢亚洲平台,CFE媒体和技术,cvavra@cfemedia.com


杜克大学