Wearable Sensor to Monitor COVID-19 Like Signs and Symptoms

1. Develop a wearable sensor package to gather data on COVID-19-like signs and symptoms such as elevated body temperature, respiratory parameters, heart rate ,cough and gait.
2. Create algorithms to monitor and track changes to COVID19-like signs and symptoms for developing a better care and isolation strategies for COVID-19 pandemic.

Study Overview

• Status: Active, not recruiting
• Conditions: COVID-19; Healthy Control
• Intervention / Treatment: Device: ADAM Sensor

Detailed Description

Aim 1:

Each enrolled participant will be asked to wear the sensor on a daily basis. Duration of the participation varies based on the symptom severity. With the currently available information, recovery times are ranging from 7 days to 56 days. The duration of the study participation can begin at the early detection to all the way until complete recovery or discharge. Participants may be asked to use the sensors anywhere from 7 days to 60 days. Duration of study will be based on the participant's self-reported symptoms or as appropriate determined by the PI. This will allow the research team to collect a comprehensive data set that can characterize both COVID-like and non-COVID-like signs and symptoms.

Aim 2:

Data collected from Aim#1 will aid in generating machine learning algorithms to characterize the signs and symptoms. Further algorithm development will be carried out to develop signs and symptoms progression and regression models for early warning or warning to prevent return to work of health-care staff or civilians

Wearable sensors are compact battery powered miniature electronic devices that are attached to a user's body to record physiological, biochemical and physical activity information. Different types of sensors can be used to monitor these digital biomarkers. Inertial measurement units (IMUs), including accelerometers, gyroscopes, magnetometers are typically used to measure physical activity, movement signatures. Miniature temperature, galvanic skin response (GSR), photoplethysmogram (PPG), oxygen saturation (SPO2) sensors are increasingly embedded in wearable devices for vital sign monitoring. Non-invasive monitoring is very ideal in the current pandemic situation. These sensors can be potentially deployed in large scale to monitor cases of suspected infection and patients recovering from COVID-19.

This project is planning to develop a sensor system that is capable of gathering data on COVID-19 like symptoms such as cough, body temperature, respiratory parameters. Machine algorithms will be developed to handle data analysis and derive useful clinical and monitor signs and symptoms in cases of suspected infection and individuals actively recovering from COVID-19 like symptoms

• Study Type: Observational
• Enrollment (Estimated): 100

Contacts and Locations

Study Locations

• United States
  • Illinois
    • Chicago, Illinois, United States, 60611
      • Shirley Ryan AbilityLab

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 95 years (Adult, Older Adult)
• Accepts Healthy Volunteers: N/A

• Sampling Method: Probability Sample

Study Population

Individuals who may have experienced COVID-19 like symptoms.

Description

Inclusion Criteria:

• Ages between 18-95 years old
• Currently experiencing any COVID-like signs and symptoms such as fever, cough, shortness of breath, trouble breathing, persistent pain or pressure in the chest, confusion or inability to arouse, bluish lips or face.
• Individuals who are not experience any COVID like signs and symptoms (will be asked to be healthy control)
• 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.

Study Plan

How is the study designed?

Design Details

• Observational Models: Cohort
• Time Perspectives: Prospective

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
COVID-19; Individuals experiencing COVID-19 like symptoms.	Device: ADAM Sensor; ADAM sensor The data collected from this sensor contains a wide range of core and novel respiratory digital biomarkers as a home-based early identification system. The core measurements include: heart rate, heart rate variability, temperature, physical activity (including sleep quality) and respiratory rate. The novel respiratory digital biomarkers include: respiratory cadence (expiration / inspiration time), coughing, swallowing, throat clearing, and talk time.
Healthy Controls; Individuals without any known significant health problems	Device: ADAM Sensor; ADAM sensor The data collected from this sensor contains a wide range of core and novel respiratory digital biomarkers as a home-based early identification system. The core measurements include: heart rate, heart rate variability, temperature, physical activity (including sleep quality) and respiratory rate. The novel respiratory digital biomarkers include: respiratory cadence (expiration / inspiration time), coughing, swallowing, throat clearing, and talk time.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Body temperature	Body temperature : Periodic temperature readings over the day (every 15 minutes)	Minimum 7 days from day 1 of study enrollment up to 60 days
Cough Frequency	Number of coughing episodes in an hour	Minimum 7 days from day 1 of study enrollment up to 60 days
Respiratory frequency	Number of breaths per minute	Minimum 7 days from day 1 of study enrollment up to 60 days
Heart Rate Instantaneous heart rate every 15 minutes.	Instantaneous heart rate every 15 minutes	Minimum 7 days from day 1 of study enrollment up to 60 days

Collaborators and Investigators

• Sponsor: Shirley Ryan AbilityLab
• Investigators: Principal Investigator: Arun Jayaraman, PhD, Shirley Ryan AbilityLab

Study record dates

Study Major Dates

• Study Start (Actual): April 20, 2020
• Primary Completion (Estimated): December 31, 2024
• Study Completion (Estimated): December 31, 2024

Study Registration Dates

• First Submitted: May 16, 2020
• First Submitted That Met QC Criteria: May 16, 2020
• First Posted (Actual): May 19, 2020

Study Record Updates

• Last Update Posted (Actual): January 31, 2024
• Last Update Submitted That Met QC Criteria: January 29, 2024
• Last Verified: January 1, 2024

More Information

Terms related to this study

• Keywords: COVID-19; Wearable sensor; Machine learning
• Additional Relevant MeSH Terms: Coronavirus Infections; Coronaviridae Infections; Nidovirales Infections; RNA Virus Infections; Virus Diseases; Infections; Respiratory Tract Infections; Respiratory Tract Diseases; Pneumonia, Viral; Pneumonia; Lung Diseases; COVID-19
• Other Study ID Numbers: STU00212522

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No