Measuring pulse rate variability using long-range, non-contact imaging photoplethysmography

Camera-based measurement of the blood volume pulse via non-contact, imaging photoplethysmography is a very popular approach for measuring pulse rate using a remote imaging sensor. Comparatively less attention has been paid to the usefulness of the method for measuring features of pulse rate variability, and even less focus has been put on the accuracy of any cardiac activity feature that can be achieved at long imager-to-subject distances. In this study, video was recorded from 19 participants, while at rest, at a distance of 25 meters from the imaging sensor. A digital camera was used to record video while cardiovascular measures of both electrical and optical physiological ground truth were recorded. Pulse rate data obtained from the imager using a common blind source separation and periodogram approach were compared to physiological ground truth signals. The quality of the recovered blood volume pulse morphology was sufficient to calculate time-domain measures of pulse rate using inter-pulse interval (IPI) time series. Following this, several features of pulse rate variability were calculated from the IPI time series and compared to those calculated from the corresponding physiological ground truth signals. Use of the time-domain data as compared to the periodogram approach to measure pulse rate reduced the error in the estimate from 1.6 to 0.2 beats per minute. Correlation analysis (r2) between the camera-based measures of pulse rate variability and ECG-derived heart rate variability ranged from 0.779 to 0.973; these results are of comparable outcome to those obtained at imager-to-subject distances of no more than 3 meters. This study demonstrates that pulse rates of less than one beat-per-minute error can be obtained when the recovered blood volume pulse morphology is of adequate quality to resolve systolic onsets for individual cardiac cycles. Further, this approach can yield data of very promising quality for estimating measures of pulse rate variability.

[1]  Daniel McDuff,et al.  Remote measurement of cognitive stress via heart rate variability , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[2]  K. Charlot,et al.  Interchangeability between heart rate and photoplethysmography variabilities during sympathetic stimulations , 2009, Physiological measurement.

[3]  Daniel McDuff,et al.  Advancements in Noncontact, Multiparameter Physiological Measurements Using a Webcam , 2011, IEEE Transactions on Biomedical Engineering.

[4]  Chiung-Cheng Chuang,et al.  Photoplethysmography variability as an alternative approach to obtain heart rate variability information in chronic pain patient , 2015, Journal of Clinical Monitoring and Computing.

[5]  L. Tarassenko,et al.  Continuous non-contact vital sign monitoring in neonatal intensive care unit , 2014, Healthcare technology letters.

[6]  J. Vagedes,et al.  How accurate is pulse rate variability as an estimate of heart rate variability? A review on studies comparing photoplethysmographic technology with an electrocardiogram. , 2013, International journal of cardiology.

[7]  Rachit Mohan,et al.  The importance of illumination in a non-contact photoplethysmography imaging system for burn wound assessment , 2015, Photonics West - Biomedical Optics.

[8]  S. Porges,et al.  The analysis of periodic processes in psychophysiological research , 1989 .

[9]  A. Malliani,et al.  Heart rate variability. Standards of measurement, physiological interpretation, and clinical use , 1996 .

[10]  Westgate Road,et al.  Photoplethysmography and its application in clinical physiological measurement , 2007 .

[11]  Albert van der Veen,et al.  Development of a baby friendly non-contact method for measuring vital signs: First results of clinical measurements in an open incubator at a neonatal intensive care unit , 2014, Photonics West - Biomedical Optics.

[12]  王磊 刘赫.  A review of non-contact, low-cost physiological information measurement based on photoplethysmographic imaging , 2012 .

[13]  Janko Drnovsek,et al.  Non-contact heart rate and heart rate variability measurements: A review , 2014, Biomed. Signal Process. Control..

[14]  Hugo F. Posada-Quintero,et al.  Evaluation of pulse rate variability obtained by the pulse onsets of the photoplethysmographic signal , 2013, Physiological measurement.

[15]  Sijung Hu,et al.  Non-contact Reflection Photoplethysmography towards Effective Human Physiological Monitoring , 2010 .

[16]  Janis Spigulis,et al.  Real-Time Photoplethysmography Imaging System , 2011 .

[17]  Yadong Wang,et al.  A review of non-contact, low-cost physiological information measurement based on photoplethysmographic imaging , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[18]  Yu Sun,et al.  Photoplethysmography Revisited: From Contact to Noncontact, From Point to Imaging , 2016, IEEE Transactions on Biomedical Engineering.

[19]  W. Verkruysse,et al.  Non-contact heart rate monitoring utilizing camera photoplethysmography in the neonatal intensive care unit - a pilot study. , 2013, Early human development.

[20]  Ethan B. Blackford,et al.  Long-range non-contact imaging photoplethysmography: cardiac pulse wave sensing at a distance , 2016, SPIE BiOS.

[21]  Xiang Chen,et al.  Effect of changes in sympathovagal balance on the accuracy of heart rate variability obtained from photoplethysmography. , 2015, Experimental and therapeutic medicine.

[23]  R. Edelberg,et al.  Comparison of finger plethysmograph to ECG in the measurement of heart rate variability. , 2002, Psychophysiology.

[24]  Ethan B. Blackford,et al.  Recovering pulse rate during motion artifact with a multi-imager array for non-contact imaging photoplethysmography , 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[25]  Sijung Hu,et al.  A high performance biometric signal and image processing method to reveal blood perfusion towards 3D oxygen saturation mapping , 2014, Photonics West - Biomedical Optics.

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

[27]  Sijung Hu,et al.  Analysis of pulse rate variability derived from photoplethysmography with the combination of lagged Poincaré plots and spectral characteristics. , 2009, Medical engineering & physics.

[28]  Willis J. Tompkins,et al.  Quantitative Investigation of QRS Detection Rules Using the MIT/BIH Arrhythmia Database , 1986, IEEE Transactions on Biomedical Engineering.

[29]  Daniel Teichmann,et al.  Non-contact monitoring techniques - Principles and applications , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[30]  Sijung Hu,et al.  Development of a remote photoplethysmographic technique for human biometrics , 2009, BiOS.

[31]  Steffen Leonhardt,et al.  Hybrid optical imaging technology for long-term remote monitoring of skin perfusion and temperature behavior , 2014, Journal of biomedical optics.

[32]  D. Haan,et al.  Improved motion robustness of remote-PPG by using the blood volume pulse signature , 2014 .

[33]  Sijung Hu,et al.  Development of effective photoplethysmographic measurement techniques: From contact to non-contact and from point to imaging , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[34]  Yisheng Zhu,et al.  A Preliminary Attempt to Understand Compatibility of Photoplethysmographic Pulse Rate Variability with Electrocardiogramic Heart Rate Variability , 2008 .

[35]  Yuting Yang,et al.  Noncontact Monitoring Breathing Pattern, Exhalation Flow Rate and Pulse Transit Time , 2014, IEEE Transactions on Biomedical Engineering.

[36]  Daniel McDuff,et al.  Improvements in Remote Cardiopulmonary Measurement Using a Five Band Digital Camera , 2014, IEEE Transactions on Biomedical Engineering.

[37]  B. Li,et al.  Non-contact detection of oxygen saturation based on visible light imaging device using ambient light. , 2013, Optics express.

[38]  Paul Poirier,et al.  Measurement fidelity of heart rate variability signal processing: the devil is in the details. , 2012, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[39]  H. Emrah Tasli,et al.  Remote PPG based vital sign measurement using adaptive facial regions , 2014, 2014 IEEE International Conference on Image Processing (ICIP).

[40]  Ethan B. Blackford,et al.  Effects of frame rate and image resolution on pulse rate measured using multiple camera imaging photoplethysmography , 2015, Medical Imaging.

[41]  Daniel McDuff,et al.  A survey of remote optical photoplethysmographic imaging methods , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[42]  John Allen,et al.  Microvascular imaging: techniques and opportunities for clinical physiological measurements , 2014, Physiological measurement.

[43]  P. Laguna,et al.  Photoplethysmography pulse rate variability as a surrogate measurement of heart rate variability during non-stationary conditions , 2010, Physiological measurement.

[44]  J M Bland,et al.  Statistical methods for assessing agreement between two methods of clinical measurement , 1986 .

[45]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.