![](/images/graphics-bg.png)
Learning from Large-Scale Wearable Device Data for Predicting Epidemics Trend of COVID-19
المؤلفون المشاركون
Zhu, Guokang
Li, Jia
Meng, Zi
Yu, Yi
Li, Yanan
Tang, Xiao
Dong, Yuling
Sun, Guangxin
Zhou, Rui
Wang, Hui
Wang, Kongqiao
Huang, Wang
المصدر
Discrete Dynamics in Nature and Society
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-05-05
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
The coronavirus disease 2019 (COVID-19) pandemic has triggered a new response involving public health surveillance.
The popularity of personal wearable devices creates a new opportunity for tracking and precaution of spread of such infectious diseases.
In this study, we propose a framework, which is based on the heart rate and sleep data collected from wearable devices, to predict the epidemic trend of COVID-19 in different countries and cities.
In addition to a physiological anomaly detection algorithm defined based on data from wearable devices, an online neural network prediction modelling methodology combining both detected physiological anomaly rate and historical COVID-19 infection rate is explored.
Four models are trained separately according to geographical segmentation, i.e., North China, Central China, South China, and South-Central Europe.
The anonymised sensor data from approximately 1.3 million wearable device users are used for model verification.
Our experiment's results indicate that the prediction models can be utilized to alert to an outbreak of COVID-19 in advance, which suggests there is potential for a health surveillance system utilising wearable device data.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhu, Guokang& Li, Jia& Meng, Zi& Yu, Yi& Li, Yanan& Tang, Xiao…[et al.]. 2020. Learning from Large-Scale Wearable Device Data for Predicting Epidemics Trend of COVID-19. Discrete Dynamics in Nature and Society،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1153246
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhu, Guokang…[et al.]. Learning from Large-Scale Wearable Device Data for Predicting Epidemics Trend of COVID-19. Discrete Dynamics in Nature and Society No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1153246
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhu, Guokang& Li, Jia& Meng, Zi& Yu, Yi& Li, Yanan& Tang, Xiao…[et al.]. Learning from Large-Scale Wearable Device Data for Predicting Epidemics Trend of COVID-19. Discrete Dynamics in Nature and Society. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1153246
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1153246
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
![](/images/ebook-kashef.png)
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
![](/images/kashef-image.png)