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. 2023 May:128:107103.
doi: 10.1016/j.cct.2023.107103. Epub 2023 Mar 29.

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

Amir Hadid  1 , Emily G McDonald  2 , Matthew P Cheng  3 , Jesse Papenburg  4 , Michael Libman  3 , Phillipe C Dixon  5 , Dennis Jensen  6
Affiliations

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

Amir Hadid et al. Contemp Clin Trials. 2023 May.

Abstract

Background: Viral respiratory tract infections (VRTI) are extremely common. Considering the profound social and economic impact of COVID-19, it is imperative to identify novel mechanisms for early detection and prevention of VRTIs, to prevent future pandemics. Wearable biosensor technology may facilitate this. Early asymptomatic detection of VRTIs could reduce stress on the healthcare system by reducing transmission and decreasing the overall number of cases. The aim of the current study is to define a sensitive set of physiological and immunological signature patterns of VRTI through machine learning (ML) to analyze physiological data collected continuously using wearable vital signs sensors.

Methods: A controlled, prospective longitudinal study with an induced low grade viral challenge, coupled with 12 days of continuous wearable biosensors monitoring surrounding viral induction. We aim to recruit and simulate a low grade VRTI in 60 healthy adults aged 18-59 years via administration of live attenuated influenza vaccine (LAIV). Continuous monitoring with wearable biosensors will include 7 days pre (baseline) and 5 days post LAIV administration, during which vital signs and activity-monitoring biosensors (embedded in a shirt, wristwatch and ring) will continuously monitor physiological and activity parameters. Novel infection detection techniques will be developed based on inflammatory biomarker mapping, PCR testing, and app-based VRTI symptom tracking. Subtle patterns of change will be assessed via ML algorithms developed to analyze large datasets and generate a predictive algorithm.

Conclusion: This study presents an infrastructure to test wearables for the detection of asymptomatic VRTI using multimodal biosensors, based on immune host response signature. CliniclTrials.govregistration:NCT05290792.

Keywords: Early detection; Inflammatory biomarkers; Machine learning; Physiomarkers; Respiratory tract infections.

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Conflict of interest statement

Declaration of Competing Interest None.

Figures

Fig. 1
Fig. 1
Physiological and activity parameters that will be assessed by wearable vital signs monitoring systems in the WE SENSE study. ⁎ denotes Astroskin only. ECG- electrocardiogram, NREM- non rapid eye movement, REM- rapid eye movement.
See this image and copyright information in PMC

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