Camera-based heart rate estimation for hospitalized newborns in the presence of motion artifacts

BioMedical Engineering OnLine

Yalin Wang¹  Qiong Chen¹  Wei Chen¹  Bin Yin²  Xi Long³  Chen Chen⁴  Xiangyu Liu⁵ 

[1] Center for Intelligent Medical Electronics, School of Information Science and Technology, Fudan University, Shanghai, China;Connected Care and Personal Health Department, Philips Research, Shanghai, China;Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands;Human Phenome Institute, Fudan University, Shanghai, China;School of Art Design and Media, East China University of Science and Technology, Shanghai, China;

关键词: Biomedical signal processing;    Heart rate;    Motion artifacts;    Eulerian video magnification;    Remote photoplethysmography (rPPG);   

DOI  :  10.1186/s12938-021-00958-5

来源: Springer

【 摘 要 】

BackgroundHeart rate (HR) is an important vital sign for evaluating the physiological condition of a newborn infant. Recently, for measuring HR, novel RGB camera-based non-contact techniques have demonstrated their specific superiority compared with other techniques, such as dopplers and thermal cameras. However, they still suffered poor robustness in infants’ HR measurements due to frequent body movement.MethodsThis paper introduces a framework to improve the robustness of infants’ HR measurements by solving motion artifact problems. Our solution is based on the following steps: morphology-based filtering, region-of-interest (ROI) dividing, Eulerian video magnification and majority voting. In particular, ROI dividing improves ROI information utilization. The majority voting scheme improves the statistical robustness by choosing the HR with the highest probability. Additionally, we determined the dividing parameter that leads to the most accurate HR measurements. In order to examine the performance of the proposed method, we collected 4 hours of videos and recorded the corresponding electrocardiogram (ECG) of 9 hospitalized neonates under two different conditions—rest still and visible movements.ResultsExperimental results indicate a promising performance: the mean absolute error during rest still and visible movements are 3.39 beats per minute (BPM) and 4.34 BPM, respectively, which improves at least 2.00 and 1.88 BPM compared with previous works. The Bland-Altman plots also show the remarkable consistency of our results and the HR derived from the ground-truth ECG.ConclusionsTo the best of our knowledge, this is the first study aimed at improving the robustness of neonatal HR measurement under motion artifacts using an RGB camera. The preliminary results have shown the promising prospects of the proposed method, which hopefully reduce neonatal mortality in hospitals.

【 授权许可】

CC BY