Show simple item record

dc.contributor.authorZhang, Guo
dc.contributor.authorVahia, Ipsit V
dc.contributor.authorLiu, Yingcheng
dc.contributor.authorYang, Yuzhe
dc.contributor.authorMay, Rose
dc.contributor.authorCray, Hailey V
dc.contributor.authorMcGrory, William
dc.contributor.authorKatabi, Dina
dc.date.accessioned2022-07-13T16:05:26Z
dc.date.available2022-07-13T16:05:26Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/1721.1/143710
dc.description.abstract<jats:p>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.</jats:p>en_US
dc.language.isoen
dc.publisherFrontiers Media SAen_US
dc.relation.isversionof10.3389/FPSYT.2021.754169en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceFrontiersen_US
dc.titleContactless In-Home Monitoring of the Long-Term Respiratory and Behavioral Phenotypes in Older Adults With COVID-19: A Case Seriesen_US
dc.typeArticleen_US
dc.identifier.citationZhang, Guo, Vahia, Ipsit V, Liu, Yingcheng, Yang, Yuzhe, May, Rose et al. 2021. "Contactless In-Home Monitoring of the Long-Term Respiratory and Behavioral Phenotypes in Older Adults With COVID-19: A Case Series." Frontiers in Psychiatry, 12.
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.relation.journalFrontiers in Psychiatryen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2022-07-13T16:02:25Z
dspace.orderedauthorsZhang, G; Vahia, IV; Liu, Y; Yang, Y; May, R; Cray, HV; McGrory, W; Katabi, Den_US
dspace.date.submission2022-07-13T16:02:27Z
mit.journal.volume12en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record