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Monitoring of cardiopulmonary activity is a challenge when attempted under adverse conditions, including different sleeping postures, environmental settings, and an unclear region of interest (ROI). This study proposes an efficient remote imaging system based on a Microsoft Kinect v2 sensor for the observation of cardiopulmonary-signal-and-detection-related abnormal cardiopulmonary events (e.g., tachycardia, bradycardia, tachypnea, bradypnea, and central apnoea) in many possible sleepingdoi:10.3390/s18030920 pmid:29558414 pmcid:PMC5876730 fatcat:l6zo7vp3rje7jcoug644vdczwa