Non-contact Heart Rate Monitoring Using Multiple RGB Cameras

Abstract

Recent advances in computer vision and signal processing are enabling researchers to realize mechanisms for the remote monitoring of vital signs. The remote measurement of vital signs, including heart rate (HR), Heart Rate Variability (HRV), and respiratory rate, presents important advantages for patients. For instance, continuous remote monitoring alleviates the discomfort due to skin irritation and/or mobility limitation associated with contact-based measurement techniques. Recently, several studies presented methods to measure HR and HRV by detecting the Blood Volume Pulse (BVP) from the human skin. They use a single camera to capture a visible segment of the skin such as face, hand, or foot to monitor the BVP. We propose a remote HR measurement algorithm that uses multiple cameras to capture the facial video recordings of still and moving subjects. Using Independent Component Analysis (ICA) as a Blind Source Separation (BSS) method, we isolate the physiological signals from noise in the RGB facial video recordings. With respect to the ECG measurement ground truth, the proposed method decreases the RMSE by 18% compared to the state-of-the-art in the subject movement condition. The proposed method achieves an RMSE of 1.43 bpm and 0.96 bpm in the stationary and movement conditions respectively.