Condition: COPD · AE COPD · Sponsor: McGill University Health Centre/Research Institute of the McGill University Health Centre
This study is aimed to collect real-time physiological data using two wearable devices (a biometric ring and a biometric wristband), daily lung mechanical measurements by a handheld oscillometer, and participant-reported symptoms in patients with COPD remotely from their home environment. The data will be used to train and validate artificial intelligence and machine learning (AI/ML) models to predict COPD exacerbations in advance of their actual occurrence. The data will also be used to test the new severity classification system for exacerbations of COPD, as well as to determine important relationships between physiological measurements from the wearable devices, the handheld oscillometer, the self-reported symptoms, and the tests performed at the baseline visit.
This description comes directly from the study's public registry record.
Bryan A. Ross, MD, MSc (Physiol), MSc (Epi) · (514) 843-1465 · bryan.ross@mcgill.ca
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| McGill University Health Centre | Montreal, Quebec, Canada | Recruiting |
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Source record: clinicaltrials.gov/study/NCT06802003