Key result
RGB camera-based monitoring outperforms standard heart rate methods by compensating for environmental effects.
Why the study?
A novel method to estimate heart rate and respiratory rate using an RGB camera was developed to improve robustness in naturalistic environments compared to existing methods.
Does a novel RGB camera-based method improve heart rate and respiratory rate estimation compared to state-of-the-art methods in naturalistic environments?
Does a novel RGB camera-based method improve heart rate and respiratory rate estimation compared to state-of-the-art methods in naturalistic environments?
A novel RGB camera-based method using multivariate de-noising and a periodicity-based voting scheme robustly estimates heart rate and respiratory rate, outperforming existing methods in naturalistic environments.
May enable contactless vital sign monitoring in real-world settings; leaves open prospective clinical validation before adoption.
In this paper we present a novel health monitoring method by estimating the heart rate and respiratory rate using an RGB camera. The heart rate and the respiratory rate are estimated from the photoplethysmography (PPG) and the respiratory motion. The method mainly operates by using the green spectrum of the RGB camera to generate a multivariate PPG signal to perform multivariate de-noising on the video signal to extract the resultant PPG signal. A periodicity based voting scheme (PVS) was used to measure the heart rate and respiratory rate from the estimated PPG signal. We evaluated our proposed method with a state of the art heart rate measuring method for two scenarios using the MAHNOB-HCI database and a self collected naturalistic environment database. The methods were furthermore evaluated for various scenarios at naturalistic environments such as a motion variance session and a skin tone variance session. Our proposed method operated robustly during the experiments and outperformed the state of the art heart rate measuring methods by compensating the effects of the naturalistic environment.
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Hassan et al. (2017) studied this question. RGB camera-based health monitoring method vs. State of the art heart rate measuring method was evaluated on Heart rate and respiratory rate estimation. The proposed RGB camera-based health monitoring method operated robustly and outperformed state-of-the-art heart rate measuring methods by compensating for naturalistic environment effects.
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