Abstract
Heart rate is a major internal psychological parameter that defines the function of human body along with its response. In conventional heart rate measurement, electrodes and chest straps are attached to the patient’s body, but this system is a bit uncomfortable. So, in this paper a non-invasive heart rate measurement technique is proposed from Photoplethysmography (PPG signal). PPG signal will be extracted from the facial video in realistic frame that involves three approaches, firstly when the face is in at standstill, secondly when human face is motion and finally at real time scenario. Region of interest is selected according to their skin color variation in response with the heart rate. This color variation is implemented on the RGB color space and PPG signal is obtained. Independent component analysis (ICA) and Fast Fourier Transform are applied on this signal and heart rate is estimated from FFT. This method is also compared with the conventional heart rate measurement technique with ECG signal. Among the three conditions, the results are more accurate for motionless face video. For real time heart rate measurement, a Graphical User Interface (GUI) is designed in this work which will play a significant role at instant critical condition in remote areas.
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References
Allen J (2007) Photoplethysmography and its application in clinical physiological measurement. Physiol Meas 28(3). https://doi.org/10.1088/0967-3334/28/3/r01
Verkruysse W, Svaasand LO, Nelson JS (2008) Remote plethysmographic imaging using ambient light. Opt Express 16(26):21434. https://doi.org/10.1364/oe.16.021434
Poh M, Mcduff DJ, Picard RW (2010) Non-contact, automated cardiac pulse measurements using video imaging and blind source separation. Opt Express 18(10):10762. https://doi.org/10.1364/oe.18.010762
Lewandowska M, Rumiński J, Kocejko T, Nowak J (2011) Measuring pulse rate with a webcam—a non-contact method for evaluating cardiac activity. In: IEEE proceedings of computer science and information systems (FedCSIS). Szczecin, Poland
Gault TR, Farag AA (2013) A fully automatic method to extract the heart rate from thermal video. In: 2013 IEEE conference on computer vision and pattern recognition workshops. https://doi.org/10.1109/cvprw.2013.57
Datcu D, Cidota M, Lukosch S, Rothkrantz L (2013) Noncontact automatic heart rate analysis in visible spectrum by specific face regions. In: Proceedings of the 14th international conference on computer systems and technologies—CompSysTech 13. https://doi.org/10.1145/2516775.2516805
Balakrishnan G, Durand F, Guttag J (2013) Detecting pulse from head motions in video. In: 2013 IEEE conference on computer vision and pattern recognition. https://doi.org/10.1109/cvpr.2013.440
Tanaka H, Monahan KD, Seals DR (2001) Age-predicted maximal heart rate revisited. J Am Coll Cardiol 37(1):153–156. https://doi.org/10.1016/s0735-1097(00)01054-8
Viola P, Jones M (n.d.) Rapid object detection using a boosted cascade of simple features. In: Proceedings of the 2001 IEEE computer society conference on computer vision and pattern recognition. CVPR 2001. https://doi.org/10.1109/cvpr.2001.990517
Tomasi C, Kanade T (1991) Detection and tracking of point features. Int J Comput Vis
Lempe G, Zaunseder S, Wirthgen T, Zipser S, Malberg H (2013) ROI selection for remote photoplethysmography. Bildverarbeitung Für Die Medizin 2013 Informatik Aktuell: 99–103. https://doi.org/10.1007/978-3-642-36480-8_19
Cardoso J (1999) High-order contrasts for independent component analysis. Neural Comput 11(1):157–192. https://doi.org/10.1162/089976699300016863
Kim B, Yoo S (2006) Motion artifact reduction in photoplethysmography using independent component analysis. IEEE Trans Biomed Eng 53(3):566–568. https://doi.org/10.1109/tbme.2005.869784
Cochran D (n.d.) A consequence of signal normalization in spectrum analysis. In: International conference on acoustics, speech, and signal processing. ICASSP-88. https://doi.org/10.1109/icassp.1988.197121
Akti G, Goularas D (2012) Frequency component extraction from color images for specific sound transformation and analysis. In: 2012 3rd international conference on image processing theory, tools and applications (IPTA). https://doi.org/10.1109/ipta.2012.6469573
Acknowledgements
This work is supported by the Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology (KUET), Bangladesh. Special thanks are due to the subject who has given her kind consent for taking her video as experimental data and also appreciation to the other subjects for their support.
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Islam, M., Biswas, T., Saad, A.M., Haque, C.A., Salah Uddin Yusuf, M. (2020). A Non-invasive Heart Rate Estimation Approach from Photoplethysmography. In: Uddin, M., Bansal, J. (eds) Proceedings of International Joint Conference on Computational Intelligence. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-13-7564-4_33
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DOI: https://doi.org/10.1007/978-981-13-7564-4_33
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