Remote patient monitoring (RPM) using wearable sensors has the potential to improve Chronic Obstructive Pulmonary Disease (COPD) patients' treatment and outcome by providing patients and physicians with early actionable insights, therefore reducing, or preventing exacerbations and increasing the quality of life. Previous published studies on sensor-based remote patient monitoring in patients with COPD suggest that such an approach is scientifically feasible and clinically promising, especially for decreasing the number of hospitalizations associated with exacerbations and improving overall outcome.
The purpose of this study is to generate biometric sensor-derived data, correlate them to clinical parameters and patient reported outcomes and develop predictive models for COPD exacerbations and patients’ disease status as a basis for a future RPM solution for patients with COPD.
