Wavelet Based Measurement on Photoplethysmography by Smartphone Imaging

[Purpose] Smartphones video cameras can be used to detect the photoplethysmograph (PPG) signal.The pulse wave signal detected by smartphone always mixed mass noise because of finger moving, unevenness of pressure and outer light interference. Previous studies limit to the filtering algorithm that denoising signals, without considering characteristics information of pulse wave itself. [Method] In this paper, we propose an algorithm based on wavelet to detect qualified PPG, which captures three critical characteristic quantities through wavelet high frequency coefficient. [Results] Experiment illustrates that the detected PPG signal contain dicrotic wave, and whats more, further experiment on artery elasticity indexes indicates good robust of the algorithm. [Conclusions] Wavelet Based Measurement on Photoplethysmography by Smartphone Imaging can be used for the calculation of cardiovascular parameter such as angiosclerosis, arrhythmia, and vascular resistance.

[1]  Y. Mendelson Pulse oximetry: theory and applications for noninvasive monitoring. , 1992, Clinical chemistry.

[2]  Liu Gang,et al.  Selection of the best wavelet base for speech signal , 2004, Proceedings of 2004 International Symposium on Intelligent Multimedia, Video and Speech Processing, 2004..

[3]  John Allen Photoplethysmography and its application in clinical physiological measurement , 2007, Physiological measurement.

[4]  Ki H. Chon,et al.  Physiological Parameter Monitoring from Optical Recordings With a Mobile Phone , 2012, IEEE Transactions on Biomedical Engineering.

[5]  Mathew Gregoski,et al.  Photoplethysmograph (PPG) derived heart rate (HR) acquisition using an Android smart phone , 2011, Wireless Health.

[6]  Martin J Leahy,et al.  Cellular phone‐based photoplethysmographic imaging , 2011, Journal of biophotonics.

[7]  Sijung Hu,et al.  The preliminary investigation of imaging photoplethysmographic system , 2007 .

[8]  Tomas E. Ward,et al.  A CMOS camera-based system for clinical photoplethysmographic applications , 2005, SPIE OPTO-Ireland.

[9]  Chen Wei,et al.  Study on conditioning and feature extraction algorithm of photoplethysmography signal for physiological parameters detection , 2011, 2011 4th International Congress on Image and Signal Processing.

[10]  R. Erts,et al.  The blood perfusion mapping in the human skin by photoplethysmography imaging , 2010 .

[11]  Sijung Hu,et al.  Feasibility of Imaging Photoplethysmography , 2008, 2008 International Conference on BioMedical Engineering and Informatics.

[12]  Roy Kalawsky,et al.  Noncontact imaging photoplethysmography to effectively access pulse rate variability , 2012, Journal of biomedical optics.

[13]  Domenico Grimaldi,et al.  Photoplethysmography detection by smartphone's videocamera , 2011, Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems.