%X In this paper, vital signs are estimated using smartphone device based video camera imaging technique. The standard color conversion technique and Plane-Orthogonal-to-Skin (POS) algorithm have been applied to estimate the Remote photoplethysmography (rPPG) signal efficiently. Furthermore, the color distortion filtering method is used for pre-processing in order to extract the less noisy YCbCr signal. This rPPG signal could perform better as compared to the standard vital signs estimation methods. The Inter beat interval (IBI) based on maximum peak detection approach has been used for heart rate variability estimation. The results are compared with the ground truth data to compute the accuracy and compared with the existing vital sign monitoring methods. The results show less mean absolute percentage error (MAPE) using our proposed method based on smart phone digital camera than the existing approaches. © 2017 IEEE.
%P 202-205
%L scholars8543
%I Institute of Electrical and Electronics Engineers Inc.
%A A. Qayyum
%A A.S. Malik
%A A.N. Shuaibu
%A N. Nasir
%J 2017 IEEE Life Sciences Conference, LSC 2017
%K Color; Patient monitoring; Video cameras; Video signal processing, Color conversions; Color distortions; Estimation methods; Filtering method; Less noisy; Non-contact; Pre-processing; Smart phones; Vital sign; Vital signs monitoring, Smartphones
%D 2017
%O cited By 6; Conference of 1st International IEEE Life-Science Conference, LSC 2017 ; Conference Date: 13 December 2017 Through 15 December 2017; Conference Code:134414
%V 2018-J
%T Estimation of non-contact smartphone video-based vital sign monitoring using filtering and standard color conversion techniques
%R 10.1109/LSC.2017.8268178