The Role of Unobtrusive Home-Based Continuous Sensing in the Management of Postacute Sequelae of SARS CoV-2.
J Med Internet Res
; 24(1): e32713, 2022 01 26.
Article
in English
| MEDLINE | ID: covidwho-1592501
ABSTRACT
Amid the COVID-19 pandemic, it has been reported that greater than 35% of patients with confirmed or suspected COVID-19 develop postacute sequelae of SARS CoV-2 (PASC). PASC is still a disease for which preliminary medical data are being collected-mostly measurements collected during hospital or clinical visits-and pathophysiological understanding is yet in its infancy. The disease is notable for its prevalence and its variable symptom presentation, and as such, management plans could be more holistically made if health care providers had access to unobtrusive home-based wearable and contactless continuous physiologic and physical sensor data. Such between-hospital or between-clinic data can quantitatively elucidate a majority of the temporal evolution of PASC symptoms. Although not universally of comparable accuracy to gold standard medical devices, home-deployed sensors offer great insights into the development and progression of PASC. Suitable sensors include those providing vital signs and activity measurements that correlate directly or by proxy to documented PASC symptoms. Such continuous, home-based data can give care providers contextualized information from which symptom exacerbation or relieving factors may be classified. Such data can also improve the collective academic understanding of PASC by providing temporally and activity-associated symptom cataloging. In this viewpoint, we make a case for the utilization of home-based continuous sensing that can serve as a foundation from which medical professionals and engineers may develop and pursue long-term mitigation strategies for PASC.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
SARS-CoV-2
/
COVID-19
Type of study:
Observational study
/
Prognostic study
Topics:
Long Covid
Limits:
Humans
Language:
English
Journal:
J Med Internet Res
Journal subject:
Medical Informatics
Year:
2022
Document Type:
Article
Affiliation country:
32713
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