Ignite Creation Date:
2025-12-25 @ 12:12 AM
Ignite Modification Date:
2025-12-25 @ 10:13 PM
Study NCT ID:
NCT04393558
Status:
COMPLETED
Last Update Posted:
2025-04-17
First Post:
2020-05-16
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Wearable Sensor to Monitor COVID-19 Like Signs and Symptoms
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D000086382', 'term': 'COVID-19'}], 'ancestors': [{'id': 'D011024', 'term': 'Pneumonia, Viral'}, {'id': 'D011014', 'term': 'Pneumonia'}, {'id': 'D012141', 'term': 'Respiratory Tract Infections'}, {'id': 'D007239', 'term': 'Infections'}, {'id': 'D014777', 'term': 'Virus Diseases'}, {'id': 'D018352', 'term': 'Coronavirus Infections'}, {'id': 'D003333', 'term': 'Coronaviridae Infections'}, {'id': 'D030341', 'term': 'Nidovirales Infections'}, {'id': 'D012327', 'term': 'RNA Virus Infections'}, {'id': 'D008171', 'term': 'Lung Diseases'}, {'id': 'D012140', 'term': 'Respiratory Tract Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 75}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2020-04-20', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-04', 'completionDateStruct': {'date': '2020-10-26', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2025-04-16', 'studyFirstSubmitDate': '2020-05-16', 'studyFirstSubmitQcDate': '2020-05-16', 'lastUpdatePostDateStruct': {'date': '2025-04-17', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2020-05-19', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2020-10-26', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Body temperature', 'timeFrame': 'Minimum 7 days from day 1 of study enrollment up to 60 days', 'description': 'Body temperature : Periodic temperature readings over the day (every 15 minutes)'}, {'measure': 'Cough Frequency', 'timeFrame': 'Minimum 7 days from day 1 of study enrollment up to 60 days', 'description': 'Number of coughing episodes in an hour'}, {'measure': 'Respiratory frequency', 'timeFrame': 'Minimum 7 days from day 1 of study enrollment up to 60 days', 'description': 'Number of breaths per minute'}, {'measure': 'Heart Rate Instantaneous heart rate every 15 minutes.', 'timeFrame': 'Minimum 7 days from day 1 of study enrollment up to 60 days', 'description': 'Instantaneous heart rate every 15 minutes'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Wearable sensor', 'COVID-19', 'Machine learning'], 'conditions': ['COVID-19', 'Healthy Control']}, 'descriptionModule': {'briefSummary': '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.\n2. 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.', 'detailedDescription': "Aim 1:\n\nEach 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.\n\nAim 2:\n\nData 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\n\nWearable 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.\n\nThis 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"}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '95 Years', 'minimumAge': '18 Years', 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'Individuals who may have experienced COVID-19 like symptoms.', 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Ages between 18-95 years old\n* 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.\n* Individuals who are not experience any COVID like signs and symptoms (will be asked to be healthy control)\n* Able and willing to give written consent and comply with study procedures.\n\nExclusion Criteria:\n\n* Inability to understand instructions and follow a three step command.\n* The subject is pregnant, nursing or planning a pregnancy.\n* Inability to provide written consent.'}, 'identificationModule': {'nctId': 'NCT04393558', 'briefTitle': 'Wearable Sensor to Monitor COVID-19 Like Signs and Symptoms', 'organization': {'class': 'OTHER', 'fullName': 'Shirley Ryan AbilityLab'}, 'officialTitle': 'Wearable Sensor to Monitor COVID-19 Like Signs and Symptoms', 'orgStudyIdInfo': {'id': 'STU00212522'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'COVID-19', 'description': 'Individuals experiencing COVID-19 like symptoms.', 'interventionNames': ['Device: ADAM Sensor']}, {'label': 'Healthy Controls', 'description': 'Individuals without any known significant health problems', 'interventionNames': ['Device: ADAM Sensor']}], 'interventions': [{'name': 'ADAM Sensor', 'type': 'DEVICE', 'description': '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.', 'armGroupLabels': ['COVID-19', 'Healthy Controls']}]}, 'contactsLocationsModule': {'locations': [{'zip': '60611', 'city': 'Chicago', 'state': 'Illinois', 'country': 'United States', 'facility': 'Shirley Ryan AbilityLab', 'geoPoint': {'lat': 41.85003, 'lon': -87.65005}}], 'overallOfficials': [{'name': 'Arun Jayaraman, PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Shirley Ryan AbilityLab'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Shirley Ryan AbilityLab', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Director Max Nader Laboratory', 'investigatorFullName': 'Arun Jayaraman, PT, PhD', 'investigatorAffiliation': 'Shirley Ryan AbilityLab'}}}}