Predicting Acute Exacerbations of COPD Using Wearable Devices and Remote Monitoring Technology With AI/ML Models
Early Prediction of Acute Exacerbations of COPD Using Wearable and Portable Remote Monitoring Technology With AI/ML Empowered Platforms: A Prospective Clinical Study
About This Trial
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.
Who May Be Eligible (Plain English)
Original Eligibility Criteria
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Treatments Being Tested
Biometric wearable and handheld devices
In this study, participants will be equipped with biometric wearable devices, i.e. ring and wristband, as well as with a handheld oscillometer, to measure their physiological parameters and lung mechanical changes (lung function).