Abstract
BackgroundRemote physiological measurement might be very useful for biomedical diagnostics and monitoring. This study presents an efficient method for remotely measuring heart rate and respiratory rate from video captured by a hovering unmanned aerial vehicle (UVA). The proposed method estimates heart rate and respiratory rate based on the acquired signals obtained from video-photoplethysmography that are synchronous with cardiorespiratory activity.MethodsSince the PPG signal is highly affected by the noise variations (illumination variations, subject’s motions and camera movement), we have used advanced signal processing techniques, including complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and canonical correlation analysis (CCA) to remove noise under these assumptions.ResultsTo evaluate the performance and effectiveness of the proposed method, a set of experiments were performed on 15 healthy volunteers in a front-facing position involving motion resulting from both the subject and the UAV under different scenarios and different lighting conditions.ConclusionThe experimental results demonstrated that the proposed system with and without the magnification process achieves robust and accurate readings and have significant correlations compared to a standard pulse oximeter and Piezo respiratory belt. Also, the squared correlation coefficient, root mean square error, and mean error rate yielded by the proposed method with and without the magnification process were significantly better than the state-of-the-art methodologies, including independent component analysis (ICA) and principal component analysis (PCA).
Highlights
Remote physiological measurement might be very useful for bio‐ medical diagnostics and monitoring
To remove the effects of illumination variations, subject’s movement and camera movement, we proposed a combination of a complete ensemble EMD with adaptive noise (CEEMDAN) and a canonical correlation analysis (CCA) to remove noise acquired from these effects in the PPG signal and present a robust non-contact method to remotely extract cardiorespiratory signals using video sequences captured by a hovering Unmanned aerial vehicles (UAVs)
We have used a combination of both CEEMDAN and CCA techniques to remove noise acquired from the illumination variations, subject’s movement and camera movement
Summary
Remote physiological measurement might be very useful for bio‐ medical diagnostics and monitoring. This study presents an efficient method for remotely measuring heart rate and respiratory rate from video captured by a hovering unmanned aerial vehicle (UVA). The proposed method estimates heart rate and respira‐ tory rate based on the acquired signals obtained from video-photoplethysmography that are synchronous with cardiorespiratory activity. Remote-sensing imaging systems provide a convenient way to monitor human vital signs without any physical restrictions. Imaging Photoplethysmography (iPPG) is one of the most promising methods that uses a video camera as a photodetector to detect optical properties passing through or reflecting from the skin due to cardiac synchronous variations. The desire to solve the problems associated with contact monitoring systems has led to research using video cameras as a non-contact sensor for monitoring of vital signs
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