Vital Sensor Monitors for CV19 Detection

ICU-Grade Wearable Sensors With Novel Respiratory Biomarkers to Diagnose and Detect Pre- and Very Early Symptomatic COVID-19 Infection Using Predictive Machine Learning Algorithms

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT04635787

Enrollment

324

Registered

2020-11-19

Start date

2020-11-05

Completion date

2021-08-31

Last updated

2023-05-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Covid19

Brief summary

This study will monitor physical bio-markers such as heart rate, respiratory rate, and temperature to detect potential COVID-19 infections.

Detailed description

The purpose of this research is to assess the accuracy of wearable sensors at detecting and monitoring COVID-19 infections. Our small, wearable sensor can get data on your respiration, body temperature, heart rate, and blood oxygen level, which may help physicians better identify if a respiratory condition is worsening overtime. If successful, our sensor could help healthcare professionals detect early symptoms of COVID-19 respiratory infection and monitor recovery and treat people before their condition worsens significantly.

Interventions

DEVICEANNE One

Wireless vital sign monitoring device

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

Inclusion criteria

* Adults aged 18 years old or over * Recent (within 1 week) occupational or home exposure to a newly diagnosed COVID-19 infected individual * Able and willing to give written consent and comply with study procedures

Exclusion criteria

* Inability to understand instructions and follow a three step command * The subject is pregnant, nursing or planning a pregnancy * Inability to provide written consent * Past confirmed COVID-19 infection with resolution of symptoms * Past confirmed COVID-19 active infection moderate or severe symptoms

Design outcomes

Primary

Measure	Time frame	Description
1.Efficacy of wearable device to detect respiratory infection parameters: cough count	1 year	Device data measuring cough count. Captured by analysis of peak acclerometer graphing and duration in meters per second squared (m/s2).

Secondary

Measure	Time frame	Description
2.Monitoring of respiratory infection symptoms, WURSS-11 Survey	Time Frame: 1 year	WURSS-11 survey. https://www.fammed.wisc.edu/files/webfm-uploads/documents/research/wurss-11.pdf The WURSS-11 survey will be conducted on a weekly basis by study subjects for the duration of the study (up to 52 weeks).

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026