An Evaluation of Biometric Monitoring Technologies for Vital Signs in the Era of COVID-19

Overview

Journal Clin Transl Sci

Specialties Biomedical Engineering
General Medicine

Date 2020 Sep 1

PMID 32866314

Citations 23

Authors

Christine Manta

Sneha S Jain

Andrea Coravos

Dena Mendelsohn

Elena S Izmailova

Affiliations

Soon will be listed here.

Abstract

The novel coronavirus disease 2019 (COVID-19) global pandemic has shifted how many patients receive outpatient care. Telehealth and remote monitoring have become more prevalent, and measurements taken in a patient's home using biometric monitoring technologies (BioMeTs) offer convenient opportunities to collect vital sign data. Healthcare providers may lack prior experience using BioMeTs in remote patient care, and, therefore, may be unfamiliar with the many versions of BioMeTs, novel data collection protocols, and context of the values collected. To make informed patient care decisions based on the biometric data collected remotely, it is important to understand the engineering solutions embedded in the products, data collection protocols, form factors (physical size and shape), data quality considerations, and availability of validation information. This article provides an overview of BioMeTs available for collecting vital signs (temperature, heart rate, blood pressure, oxygen saturation, and respiratory rate) and discusses the strengths and limitations of continuous monitoring. We provide considerations for remote data collection and sources of validation information to guide BioMeT use in the era of COVID-19 and beyond.

Citing Articles

Evaluation of a Telemonitoring System Using Electronic National Early Warning Scores for Patients Receiving Medical Home Care: Pilot Implementation Study.

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Implementing sensor-based digital health technologies in clinical trials: Key considerations from the eCOA Consortium.

Izmailova E, Middleton D, Yunis R, Lakeland J, Sowalsky K, Kling J Clin Transl Sci. 2024; 17(11):e70054.

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Contactless Blood Oxygen Saturation Estimation from Facial Videos Using Deep Learning.

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A proposed multi-domain, digital model for capturing functional status and health-related quality of life in oncology.

Izmailova E, Wagner J, Bakker J, Kilian R, Ellis R, Ohri N Clin Transl Sci. 2024; 17(1):e13712.

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A systematic review and knowledge mapping on ICT-based remote and automatic COVID-19 patient monitoring and care.

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