350 rub
Journal Biomedical Radioelectronics №10 for 2014 г.
Article in number:
Contactless photoplethysmography and arterial pulse rate measurements by means of a webcam
Authors:
A.A. Taranov - Post-graduate Student, Biomedical Department, Bauman Moscow State Technical University
I.N. Spiridonov - Dr.Sc. (Eng.), Professor, Head of Biomedical Department, Bauman Moscow State Technical University
Abstract:
It is known that arterial pulse rate is one of the most frequently measured characteristics in medical practice/researches. And today you can find a lot of different approaches to arterial pulse rate measurements (manual, ultrasound, ECG, reoplethysmography, sphygmography and etc.) But all those standard methods demand a direct contact with patient body that is not always suitable. For the instance it is not comfortable in case of long term real time measurements (which is often required in medical researches), or in case of pulse measurement on immobilized patients. But in a recent time it was shown that this problem can be solved by means of non-contact photoplethysmography and that such technique can be performed by means of an ordinary personal computer with a webcam. Nevertheless until now you, probably, could find this technology only as set of commercial applications for various mobile platforms and without properly metrological support. This work is the first representation of open-source project, devoted to development of free photoplethysmographic measurement system. Its prototype already provides accurate contactless measurements of arterial pulse rate in a real time mode (with absolute error of measurements not more than 6 bpm) and, in the near future, will be capable to measure respiration rate and cardiovascular pulse wave variability. The hardware base of a system is a personal computer (on x86 CPU architecture, operated by MS Windows XP/7/8) and an ordinary webcam. Software part was developed on the base of OpenCV, Qt, FFTW and ALGLIB libraries. The sources are hosted on internet resource https://github.com/pi-null-mezon/QPULSECAPTURE.git. The article describes a video processing algorithm and provides the results of measurement accuracy examination.
Pages: 71-80
References

  1. Ming-Zher Poh, McDuff D.J., Picard R.W. Non-contact, automated cardiac pulse measurements using video imaging and blind source separation // OPTICS EXPRESS. 2010. V. 18. № 10. R. 10763(10774.
  2. Takano C., Ohta Y. Heart rate measurement based on a time-lapse image // Med. Eng. Phys. 2007. № 29(8). R. 853-857.
  3. Hao-Yu Wu, Rubinstein M., Shih E., Guttag J., Durand F., Freeman W. Eulerian video magnification for revealing subtle changes in the world // ACM Transactions on Graphics (TOG) ? SIGGRAPH 2012 Conference Proceedings 31. 2012.
  4. Balakrishnan G., Durand F., Guttag J. Detecting Pulse from Head Motions in Video // MIT CSAIL [URL in internet]: http://people.csail.mit.edu/balakg//cvpr2013_pulsepaper.pdf  (revision date: 17.12.2013);
  5. Verkruysse W., Svaasand L.O., Nelson J.S. Remote plethysmographic imaging using ambient light // Opt. Express. 2008. № 16(26). R. 21434-21445.
  6. Sahindrakar P., de Haan G., Kirenko I. Improving motion robustness of contact-less Monitoring of Heart Rate using video analysis // Department of Mathematics and Computer Science of Technische Universiteit Eindhoven [URL in internet]: http://alexand­ria.tue.nl/extra1//afstversl/wsk-i/ sa­hindrakar2011.pdf (revision date: 23.08.2013).
  7. Viola P., Jones M. Rapid object detection using a boosted cascade of simple features // Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. 2001. R. 511.
  8. Jun Jiang, Dengyu Liu, Jinwei Gu, Sabine Süsstrunk Samera Spectral Sensitivity Database [URL in internet]: http://www.cis.rit.edu/jwgu/re­search/camspec/db.php, 2014 (revision date: 01.05.2014).
  9. Glants S. Mediko-biologicheskaya statistika: per. s angl. M.: Praktika. 1998. 459 s.