About: Early Detection Of COVID-19 Using A Smartwatch

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Early Detection Of COVID-19 Using A Smartwatch
Creator	Wang, Tao Li, Xiao Snyder, Michael Wang, Meng Brooks, Andrew Alavi, Arash Bahmani, Amir Bogu, Gireesh Celli, Alessandra Dagan-Rosenfeld, Orit Fay, Bethany Ganz, Ariel Gibson, Michelle Higgs, Emily Kellogg, Ryan Kirkpatrick, Susan Metwally, Ahmed Mishra, Tejaswini Rolnik, Benjamin
Source	MedRxiv
abstract	Wearable devices digitally measuring vital signs have been used for monitoring health and illness onset and have high potential for real-time monitoring and disease detection. As such they are potentially useful during public health crises, such as the current COVID-19 global pandemic. Using smartwatch data from 31 infected individuals identified from a cohort of over 5000 participants, we investigated the use of wearables for early, presymptomatic detection of COVID-19. From physiological and activity data, we first demonstrate that COVID-19 infections are associated with alterations in heart rate, steps and sleep in 80% of COVID-19 infection cases. Failure to detect these changes in the remaining patients often occurred in those with chronic respiratory/lung disease. Importantly the physiological alterations were detected prior to, or at, symptom onset in over 85% of the positive cases (21/24), in some cases nine or more days before symptoms. Through daily surveys we can track physiological changes with symptom onset and severity. Finally, we develop a method to detect onset of COVID-19 infection in real-time which detects 67% of infection cases at or before symptom onset. Our study provides a roadmap to a rapid and universal diagnostic method for the large-scale detection of respiratory viral infections in advance of symptoms, highlighting a useful approach for managing epidemics using digital tracking and health monitoring.
has issue date	2020-07-07(xsd:dateTime)
bibo:doi	10.1101/2020.07.06.20147512
has license	medrxiv
sha1sum (hex)	2b8cf30eb93245f8b3deb5222fefe689593cd7a8
schema:url	https://doi.org/10.1101/2020.07.06.20147512
resource representing a document's title	Early Detection Of COVID-19 Using A Smartwatch
resource representing a document's body	covid:2b8cf30eb93245f8b3deb5222fefe689593cd7a8#body_text
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