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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
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| COVID-19 | Individuals experiencing COVID-19 like symptoms. |
| |
| Healthy Controls | Individuals without any known significant health problems |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| ADAM Sensor | Device | 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. |
| 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 |
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Inclusion Criteria:
Exclusion Criteria:
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Individuals who may have experienced COVID-19 like symptoms.
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| Name | Affiliation | Role |
|---|---|---|
| Arun Jayaraman, PhD | Shirley Ryan AbilityLab | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Shirley Ryan AbilityLab | Chicago | Illinois | 60611 | United States |
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| ID | Term |
|---|---|
| D000086382 | COVID-19 |
| ID | Term |
|---|---|
| D011024 | Pneumonia, Viral |
| D011014 | Pneumonia |
| D012141 | Respiratory Tract Infections |
| D007239 | Infections |
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| D014777 |
| Virus Diseases |
| D018352 | Coronavirus Infections |
| D003333 | Coronaviridae Infections |
| D030341 | Nidovirales Infections |
| D012327 | RNA Virus Infections |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |