Use of Wearable Sensors for Early Detection and Tracking of Viral Respiratory Tract Infections

NCT ID: NCT05290792

Last Updated: 2025-03-25

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 56 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2021-12-10
• Study Completion Date: 2022-10-31

Brief Summary

Viral respiratory tract infections (VRTI) are among the most common human illnesses, impacting billions globally. There is an unmet need to identify novel ways to detect, treat and prevent their spread. New wearable devices could address this need, using special biosensors worn by patients.

This is a single centre, controlled, before and after, longitudinal, clinical trial. Participants will receive FluMist, a live attenuated influenza vaccine, which will act as a proxy to a viral respiratory tract infection and create a very minor response to the immune system. Vital signs and activity levels will be monitored continuously using wearable biosensors for 7 days prior to and 7 days following, along with symptom tracking and blood tests to measure immune responses. Artificial intelligence (AI) and machine learning (ML) algorithms will be used to analyse the data.

AI and ML will identify subtle changes in vital signs and activity levels from the immune response to respiratory viruses. These data will help develop future methods to address important public health questions related to respiratory virus detection, containment and management.

The purpose of this study is to explore whether wearable sensors can detect, track the progress and recovery from viral respiratory tract infection.

Detailed Description

Presently, there are no tools to continuously assess the objective body's response to respiratory viral infection in real time. An individual's inflammatory response to infection is primarily measured by the presence of symptoms. For example, reliance on the presence of fever as a sensitive sign of viral infection, while objective and measurable, can miss at least 50% of symptomatic cases of influenza illness. Fever is also not a sufficient sign of infection in studies of SARS-CoV-2. An additional technology to pair with the present contact tracing, test and contain strategy could become a critical public health mitigation strategy for VRTIs. Evidence suggests that use of wearable biosensor technology may enable researchers and healthcare professionals to detect inflammatory responses. Therefore, they could assist in medical diagnosis at the early phase of disease development - even before the onset of clinical symptoms.

In this study, the investigators aim to leverage FLUMIST, an intranasal Live Attenuated Influenza Vaccine (LAIV), to create a very minor response of the immune system. FLUMIST is one of the vaccines recommended by the National Advisory Committee on Immunization (NACI), among other vaccines for this flu season. It will be used as a test case, representing body's response to a minor viral infection (like those of 'common cold'). In addition, the associated changes in vital signs (for example, changes in heart rate), activity levels, symptoms and inflammatory/immune markers will be monitored. Subtle patterns of change might only be detectable using artificial intelligence (AI). Applying AI and machine learning (ML) to the wearables' data can allow for the future early detection of VRTI, along with continuous tracking of its progress, recovery or deterioration.

Study schedule:

Patient participation in this research project will last 2 weeks and will include 14 visits. Each visit will last up to 60 minutes. During this 14-day follow-up period, participants will be required to wear 3 vital signs monitoring systems (shirt, watch and a ring) and to report twice daily about their wellbeing/symptoms and about their alcohol/caffeine/drugs consumption.

Assessments:

-VRTI detection: To rule out asymptomatic VRTI during the baseline (pre-LAIV) period, a nasopharyngeal 21-multiplex polymerase chain reaction (PCR) test, which includes influenza, SARS-CoV-2 and other respiratory viruses, will be performed at screening. For those eligible participants that enter the study, baseline assessments will start the morning of Day -7 and be performed 7 days before inoculation (Days -7 to 0), which will occur the morning of Day 0.

-Symptom assessment: The following symptoms will be assessed through an app-based survey sent to participants twice daily during the 14-day observation period: nasal discharge; nasal obstruction; sneezing; headache; sore throat; malaise; muscle ache; cough; chilliness; decreased appetite; stomach ache; vomiting; diarrhea; shortness of breath; and wheeze. Symptom severity will be graded as 0 (absent) to 7 (severe).

-Wearable vital sign monitoring systems: Three wearable smart platforms will be used for continuous monitoring of physiologic and activity parameters using biosensors: Oura ring (Oura Oy, Finland); Biobeat watch (Biobeat technologies LTD, Israel); and Astroskin shirt (by Hexoskin, Canada).

-Inflammatory cytokines and biomarkers: A venous blood sample for measurement of inflammatory cytokines and biomarkers will be obtained by a healthcare professional once in the morning of Day -7 (baseline sample 1) and then twice daily starting Day 0, with baseline sample #2 collected prior to inoculation on Day 0.

-Physiological response assessment: Participants will complete five, 3-minute constant-rate stair stepping tests (3-min CRSST). The 3-min CRSST requires participants to step up and down a 20cm step to the pace of a constant external audio beep. Participants will complete all trials at a 30 steps/min stepping rate. Cardiac and respiratory parameters will be collected at rest and during each 3-min CRSST using the wearable devices.

Conditions

Viral Respiratory Tract Infection; Influenza

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: SCREENING
• Blinding Strategy: NONE

Study Groups

Intra-individual changes of physiological and activity parameters

Participants will be administered FluMist (live attenuated influenza vaccine) to induce a low grade VRTI (Day 0). Participants will be monitored in the 7 days prior and 7 days after vaccination via symptom questionnaires, blood draws, stair tests and vital sign monitoring from wearable sensors.

Each participant will serve as their own control, relying on the baseline measurements obtained over the 7-day period prior to inoculation.

Group Type: OTHER

Administration of FluMist (Live Attenuated Influenza Vaccine)

Intervention Type: BIOLOGICAL

Participants will received the intranasal FluMist vaccine that will serve as a proxy for a viral respiratory tract infection and trigger a mild immune response.

Interventions

Administration of FluMist (Live Attenuated Influenza Vaccine)

Participants will received the intranasal FluMist vaccine that will serve as a proxy for a viral respiratory tract infection and trigger a mild immune response.

Intervention Type: BIOLOGICAL

Eligibility Criteria

Inclusion Criteria

• Men or women aged 18-59 years
• Did not receive the 2021-2022 seasonal influenza vaccine
• Not planning to get another vaccine during the 14-day observation period.

Exclusion Criteria

• PCR-confirmed VRTI at screening
• Any infectious symptoms (fever, cough, rhinorrhea, sore throat, diarrhea, loss of smell or taste) within the previous 7 days
• Any chronic medical condition;
• Obesity (BMI>35 kg/m2);
• Any prescription drug other than oral contraceptives or routine and stable dose medications;
• Contraindication to LAIV
• Current smoker or ex-smoker with >20 pack years of smoking
• Recreational drug use
• Self-reported history of substance abuse
• Pregnant or attempting to become pregnant
• Guillain-Barré syndrome (GBS) or BGS-like episode has occurred within 6 weeks of any prior influenza vaccination
• Immunocompromised
• People with severe asthma or medically attended wheezing in the 7 days prior to the proposed date of vaccination.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 59 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Canadian Institutes of Health Research (CIHR)

OTHER_GOV

Sponsor Role: collaborator

Université de Montréal

OTHER

Sponsor Role: collaborator

Emily McDonald

OTHER

Sponsor Role: lead

Responsible Party

Emily McDonald

Associate Professor of Medicine, MD MSc FRCPC

Responsibility Role: SPONSOR_INVESTIGATOR

Principal Investigators

Emily G McDonald, MD

Role: PRINCIPAL_INVESTIGATOR

McGill University Health Centre/Research Institute of the McGill University Health Centre

Dennis Jensen, PhD

Role: PRINCIPAL_INVESTIGATOR

McGill University

Locations

Centre for Innovative Medicine - McGill University Health Centre

Montreal, Quebec, Canada

Countries

Canada

References

Molinari NA, Ortega-Sanchez IR, Messonnier ML, Thompson WW, Wortley PM, Weintraub E, Bridges CB. The annual impact of seasonal influenza in the US: measuring disease burden and costs. Vaccine. 2007 Jun 28;25(27):5086-96. doi: 10.1016/j.vaccine.2007.03.046. Epub 2007 Apr 20.

Reference Type: BACKGROUND

PMID: 17544181 (View on PubMed)

Schanzer DL, McGeer A, Morris K. Statistical estimates of respiratory admissions attributable to seasonal and pandemic influenza for Canada. Influenza Other Respir Viruses. 2013 Sep;7(5):799-808. doi: 10.1111/irv.12011. Epub 2012 Nov 5.

Reference Type: BACKGROUND

PMID: 23122189 (View on PubMed)

Casadevall A, Pirofski LA. The damage-response framework of microbial pathogenesis. Nat Rev Microbiol. 2003 Oct;1(1):17-24. doi: 10.1038/nrmicro732.

Reference Type: BACKGROUND

PMID: 15040176 (View on PubMed)

Menni C, Valdes AM, Freidin MB, Sudre CH, Nguyen LH, Drew DA, Ganesh S, Varsavsky T, Cardoso MJ, El-Sayed Moustafa JS, Visconti A, Hysi P, Bowyer RCE, Mangino M, Falchi M, Wolf J, Ourselin S, Chan AT, Steves CJ, Spector TD. Real-time tracking of self-reported symptoms to predict potential COVID-19. Nat Med. 2020 Jul;26(7):1037-1040. doi: 10.1038/s41591-020-0916-2. Epub 2020 May 11.

Reference Type: BACKGROUND

PMID: 32393804 (View on PubMed)

Yanes-Lane M, Winters N, Fregonese F, Bastos M, Perlman-Arrow S, Campbell JR, Menzies D. Proportion of asymptomatic infection among COVID-19 positive persons and their transmission potential: A systematic review and meta-analysis. PLoS One. 2020 Nov 3;15(11):e0241536. doi: 10.1371/journal.pone.0241536. eCollection 2020.

Reference Type: BACKGROUND

PMID: 33141862 (View on PubMed)

Watson J, Whiting PF, Brush JE. Interpreting a covid-19 test result. BMJ. 2020 May 12;369:m1808. doi: 10.1136/bmj.m1808. No abstract available.

Reference Type: BACKGROUND

PMID: 32398230 (View on PubMed)

Li X, Dunn J, Salins D, Zhou G, Zhou W, Schussler-Fiorenza Rose SM, Perelman D, Colbert E, Runge R, Rego S, Sonecha R, Datta S, McLaughlin T, Snyder MP. Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information. PLoS Biol. 2017 Jan 12;15(1):e2001402. doi: 10.1371/journal.pbio.2001402. eCollection 2017 Jan.

Reference Type: BACKGROUND

PMID: 28081144 (View on PubMed)

Radin JM, Wineinger NE, Topol EJ, Steinhubl SR. Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study. Lancet Digit Health. 2020 Feb;2(2):e85-e93. doi: 10.1016/S2589-7500(19)30222-5. Epub 2020 Jan 16.

Reference Type: BACKGROUND

PMID: 33334565 (View on PubMed)

Emery JC, Russell TW, Liu Y, Hellewell J, Pearson CA; CMMID COVID-19 Working Group; Knight GM, Eggo RM, Kucharski AJ, Funk S, Flasche S, Houben RM. The contribution of asymptomatic SARS-CoV-2 infections to transmission on the Diamond Princess cruise ship. Elife. 2020 Aug 24;9:e58699. doi: 10.7554/eLife.58699.

Reference Type: BACKGROUND

PMID: 32831176 (View on PubMed)

Quer G, Radin JM, Gadaleta M, Baca-Motes K, Ariniello L, Ramos E, Kheterpal V, Topol EJ, Steinhubl SR. Wearable sensor data and self-reported symptoms for COVID-19 detection. Nat Med. 2021 Jan;27(1):73-77. doi: 10.1038/s41591-020-1123-x. Epub 2020 Oct 29.

Reference Type: BACKGROUND

PMID: 33122860 (View on PubMed)

Hadid A, McDonald EG, Cheng MP, Papenburg J, Libman M, Dixon PC, Jensen D. The WE SENSE study protocol: A controlled, longitudinal clinical trial on the use of wearable sensors for early detection and tracking of viral respiratory tract infections. Contemp Clin Trials. 2023 May;128:107103. doi: 10.1016/j.cct.2023.107103. Epub 2023 Mar 29.

Reference Type: DERIVED

PMID: 37147083 (View on PubMed)

Other Identifiers

2022-7591

Identifier Type: -

Identifier Source: org_study_id