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

Influenza Clinical Trial

Official title: Use of Wearable Sensors for Early Detection and Tracking of Viral Respiratory Tract Infections: The WE SENSE Study

Status Completed

Clinical Trial 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.

Clinical Trial 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. ;

Related Conditions & MeSH terms

• Communicable Diseases
• Infections
• Influenza
• Respiratory Tract Infections
• Viral Respiratory Tract Infection

• NCT number: NCT05290792
• Study type: Interventional
• Source: McGill University Health Centre/Research Institute of the McGill University Health Centre
• Status: Completed
• Phase: N/A
• Start date: December 10, 2021
• Completion date: October 31, 2022