Abstract

Remote measurements of the cardiac pulse can provide comfortable physiological assessment without electrodes. However, attempts so far are non-automated, susceptible to motion artifacts and typically expensive. In this paper, we introduce a new methodology that overcomes these problems. This novel approach can be applied to color video recordings of the human face and is based on automatic face tracking along with blind source separation of the color channels into independent components. Using Bland-Altman and correlation analysis, we compared the cardiac pulse rate extracted from videos recorded by a basic webcam to an FDA-approved finger blood volume pulse (BVP) sensor and achieved high accuracy and correlation even in the presence of movement artifacts. Furthermore, we applied this technique to perform heart rate measurements from three participants simultaneously. This is the first demonstration of a low-cost accurate video-based method for contact-free heart rate measurements that is automated, motion-tolerant and capable of performing concomitant measurements on more than one person at a time.

© 2010 OSA

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2010 (1)

J. Fei and I. Pavlidis, “Thermistor at a Distance: Unobtrusive Measurement of Breathing,” IEEE Trans. Biomed. Eng. 57(4), 988–998 (2010).
[CrossRef]

2008 (3)

W. Verkruysse, L. O. Svaasand, and J. S. Nelson, “Remote plethysmographic imaging using ambient light,” Opt. Express 16(26), 21434–21445 (2008).
[CrossRef] [PubMed]

M. P. Chawla, H. K. Verma, and V. Kumar, “Artifacts and noise removal in electrocardiograms using independent component analysis,” Int. J. Cardiol. 129(2), 278–281 (2008).
[CrossRef]

H.-Y. Chen, C.-L. Huang, and C.-M. Fu, “Hybrid-boost learning for multi-pose face detection and facial expression recognition,” Pattern Recognit. 41(3), 1173–1185 (2008).
[CrossRef]

2007 (6)

I. Pavlidis, J. Dowdall, N. Sun, C. Puri, J. Fei, and M. Garbey, “Interacting with human physiology,” Comput. Vis. Image Underst. 108(1-2), 150–170 (2007).
[CrossRef]

M. Garbey, N. Sun, A. Merla, and I. Pavlidis, “Contact-free measurement of cardiac pulse based on the analysis of thermal imagery,” IEEE Trans. Biomed. Eng. 54(8), 1418–1426 (2007).
[CrossRef] [PubMed]

B. Heisele, T. Serre, and T. Poggio, “A component-based framework for face detection and identification,” Int. J. Comput. Vis. 74(2), 167–181 (2007).
[CrossRef]

J. Allen, “Photoplethysmography and its application in clinical physiological measurement,” Physiol. Meas. 28(3), R1–R39 (2007).
[CrossRef] [PubMed]

K. Humphreys, T. Ward, and C. Markham, “Noncontact simultaneous dual wavelength photoplethysmography: a further step toward noncontact pulse oximetry,” Rev. Sci. Instrum. 78(4), 044304 (2007).
[CrossRef] [PubMed]

C. Takano and Y. Ohta, “Heart rate measurement based on a time-lapse image,” Med. Eng. Phys. 29(8), 853–857 (2007).
[CrossRef]

2006 (3)

S. Cook, M. Togni, M. C. Schaub, P. Wenaweser, and O. M. Hess, “High heart rate: a cardiovascular risk factor?” Eur. Heart J. 27(20), 2387–2393 (2006).
[CrossRef] [PubMed]

B. S. Kim and S. K. Yoo, “Motion artifact reduction in photoplethysmography using independent component analysis,” IEEE Trans. Biomed. Eng. 53(3), 566–568 (2006).
[CrossRef] [PubMed]

S. Munder and D. M. Gavrila, “An experimental study on pedestrian classification,” IEEE Trans. Pattern Anal. Mach. Intell. 28(11), 1863–1868 (2006).
[CrossRef] [PubMed]

2005 (2)

C. J. James and C. W. Hesse, “Independent component analysis for biomedical signals,” Physiol. Meas. 26(1), R15–R39 (2005).
[CrossRef] [PubMed]

F. P. Wieringa, F. Mastik, and A. F. van der Steen, “Contactless multiple wavelength photoplethysmographic imaging: a first step toward “SpO2 camera” technology,” Ann. Biomed. Eng. 33(8), 1034–1041 (2005).
[CrossRef] [PubMed]

2001 (2)

R. C. Wuerz, D. Travers, N. Gilboy, D. R. Eitel, A. Rosenau, and R. Yazhari, “Implementation and refinement of the emergency severity index,” Acad. Emerg. Med. 8(2), 170–176 (2001).
[CrossRef] [PubMed]

S. Rhee, B. H. Yang, and H. H. Asada, “Artifact-resistant power-efficient design of finger-ring plethysmographic sensors,” IEEE Trans. Biomed. Eng. 48(7), 795–805 (2001).
[CrossRef] [PubMed]

2000 (1)

T. P. Jung, S. Makeig, C. Humphries, T. W. Lee, M. J. McKeown, V. Iragui, and T. J. Sejnowski, “Removing electroencephalographic artifacts by blind source separation,” Psychophysiology 37(2), 163–178 (2000).
[CrossRef] [PubMed]

1999 (1)

J.-F. Cardoso, “High-order contrasts for independent component analysis,” Neural Comput. 11(1), 157–192 (1999).
[CrossRef] [PubMed]

1998 (1)

M. J. McKeown, S. Makeig, G. G. Brown, T.-P. Jung, S. S. Kindermann, A. J. Bell, and T. J. Sejnowski, “Analysis of fMRI data by blind separation into independent spatial components,” Hum. Brain Mapp. 6(3), 160–188 (1998).
[CrossRef] [PubMed]

1994 (1)

P. Comon, “Independent component analysis, a new concept?” Signal Process. 36(3), 287–314 (1994).
[CrossRef]

1991 (1)

W. G. Zijlstra, A. Buursma, and W. P. Meeuwsen-van der Roest, “Absorption spectra of human fetal and adult oxyhemoglobin, de-oxyhemoglobin, carboxyhemoglobin, and methemoglobin,” Clin. Chem. 37(9), 1633–1638 (1991).
[PubMed]

1990 (1)

W. J. Cui, L. E. Ostrander, and B. Y. Lee, “In vivo reflectance of blood and tissue as a function of light wavelength,” IEEE Trans. Biomed. Eng. 37(6), 632–639 (1990).
[CrossRef] [PubMed]

1986 (1)

J. M. Bland and D. G. Altman, “Statistical methods for assessing agreement between two methods of clinical measurement,” Lancet 1(8476), 307–310 (1986).
[CrossRef] [PubMed]

1959 (1)

H. Trotter, “An elementary proof of the central limit theorem,” Arch. Math. 10(1), 226–234 (1959).
[CrossRef]

Allen, J.

J. Allen, “Photoplethysmography and its application in clinical physiological measurement,” Physiol. Meas. 28(3), R1–R39 (2007).
[CrossRef] [PubMed]

Altman, D. G.

J. M. Bland and D. G. Altman, “Statistical methods for assessing agreement between two methods of clinical measurement,” Lancet 1(8476), 307–310 (1986).
[CrossRef] [PubMed]

Asada, H. H.

S. Rhee, B. H. Yang, and H. H. Asada, “Artifact-resistant power-efficient design of finger-ring plethysmographic sensors,” IEEE Trans. Biomed. Eng. 48(7), 795–805 (2001).
[CrossRef] [PubMed]

Bell, A. J.

M. J. McKeown, S. Makeig, G. G. Brown, T.-P. Jung, S. S. Kindermann, A. J. Bell, and T. J. Sejnowski, “Analysis of fMRI data by blind separation into independent spatial components,” Hum. Brain Mapp. 6(3), 160–188 (1998).
[CrossRef] [PubMed]

Bland, J. M.

J. M. Bland and D. G. Altman, “Statistical methods for assessing agreement between two methods of clinical measurement,” Lancet 1(8476), 307–310 (1986).
[CrossRef] [PubMed]

Brown, G. G.

M. J. McKeown, S. Makeig, G. G. Brown, T.-P. Jung, S. S. Kindermann, A. J. Bell, and T. J. Sejnowski, “Analysis of fMRI data by blind separation into independent spatial components,” Hum. Brain Mapp. 6(3), 160–188 (1998).
[CrossRef] [PubMed]

Buursma, A.

W. G. Zijlstra, A. Buursma, and W. P. Meeuwsen-van der Roest, “Absorption spectra of human fetal and adult oxyhemoglobin, de-oxyhemoglobin, carboxyhemoglobin, and methemoglobin,” Clin. Chem. 37(9), 1633–1638 (1991).
[PubMed]

Cardoso, J.-F.

J.-F. Cardoso, “High-order contrasts for independent component analysis,” Neural Comput. 11(1), 157–192 (1999).
[CrossRef] [PubMed]

Chawla, M. P.

M. P. Chawla, H. K. Verma, and V. Kumar, “Artifacts and noise removal in electrocardiograms using independent component analysis,” Int. J. Cardiol. 129(2), 278–281 (2008).
[CrossRef]

Chen, H.-Y.

H.-Y. Chen, C.-L. Huang, and C.-M. Fu, “Hybrid-boost learning for multi-pose face detection and facial expression recognition,” Pattern Recognit. 41(3), 1173–1185 (2008).
[CrossRef]

Comon, P.

P. Comon, “Independent component analysis, a new concept?” Signal Process. 36(3), 287–314 (1994).
[CrossRef]

Cook, S.

S. Cook, M. Togni, M. C. Schaub, P. Wenaweser, and O. M. Hess, “High heart rate: a cardiovascular risk factor?” Eur. Heart J. 27(20), 2387–2393 (2006).
[CrossRef] [PubMed]

Cui, W. J.

W. J. Cui, L. E. Ostrander, and B. Y. Lee, “In vivo reflectance of blood and tissue as a function of light wavelength,” IEEE Trans. Biomed. Eng. 37(6), 632–639 (1990).
[CrossRef] [PubMed]

Dowdall, J.

I. Pavlidis, J. Dowdall, N. Sun, C. Puri, J. Fei, and M. Garbey, “Interacting with human physiology,” Comput. Vis. Image Underst. 108(1-2), 150–170 (2007).
[CrossRef]

Eitel, D. R.

R. C. Wuerz, D. Travers, N. Gilboy, D. R. Eitel, A. Rosenau, and R. Yazhari, “Implementation and refinement of the emergency severity index,” Acad. Emerg. Med. 8(2), 170–176 (2001).
[CrossRef] [PubMed]

Fei, J.

J. Fei and I. Pavlidis, “Thermistor at a Distance: Unobtrusive Measurement of Breathing,” IEEE Trans. Biomed. Eng. 57(4), 988–998 (2010).
[CrossRef]

I. Pavlidis, J. Dowdall, N. Sun, C. Puri, J. Fei, and M. Garbey, “Interacting with human physiology,” Comput. Vis. Image Underst. 108(1-2), 150–170 (2007).
[CrossRef]

Fu, C.-M.

H.-Y. Chen, C.-L. Huang, and C.-M. Fu, “Hybrid-boost learning for multi-pose face detection and facial expression recognition,” Pattern Recognit. 41(3), 1173–1185 (2008).
[CrossRef]

Garbey, M.

M. Garbey, N. Sun, A. Merla, and I. Pavlidis, “Contact-free measurement of cardiac pulse based on the analysis of thermal imagery,” IEEE Trans. Biomed. Eng. 54(8), 1418–1426 (2007).
[CrossRef] [PubMed]

I. Pavlidis, J. Dowdall, N. Sun, C. Puri, J. Fei, and M. Garbey, “Interacting with human physiology,” Comput. Vis. Image Underst. 108(1-2), 150–170 (2007).
[CrossRef]

Gavrila, D. M.

S. Munder and D. M. Gavrila, “An experimental study on pedestrian classification,” IEEE Trans. Pattern Anal. Mach. Intell. 28(11), 1863–1868 (2006).
[CrossRef] [PubMed]

Gilboy, N.

R. C. Wuerz, D. Travers, N. Gilboy, D. R. Eitel, A. Rosenau, and R. Yazhari, “Implementation and refinement of the emergency severity index,” Acad. Emerg. Med. 8(2), 170–176 (2001).
[CrossRef] [PubMed]

Heisele, B.

B. Heisele, T. Serre, and T. Poggio, “A component-based framework for face detection and identification,” Int. J. Comput. Vis. 74(2), 167–181 (2007).
[CrossRef]

Hess, O. M.

S. Cook, M. Togni, M. C. Schaub, P. Wenaweser, and O. M. Hess, “High heart rate: a cardiovascular risk factor?” Eur. Heart J. 27(20), 2387–2393 (2006).
[CrossRef] [PubMed]

Hesse, C. W.

C. J. James and C. W. Hesse, “Independent component analysis for biomedical signals,” Physiol. Meas. 26(1), R15–R39 (2005).
[CrossRef] [PubMed]

Huang, C.-L.

H.-Y. Chen, C.-L. Huang, and C.-M. Fu, “Hybrid-boost learning for multi-pose face detection and facial expression recognition,” Pattern Recognit. 41(3), 1173–1185 (2008).
[CrossRef]

Humphreys, K.

K. Humphreys, T. Ward, and C. Markham, “Noncontact simultaneous dual wavelength photoplethysmography: a further step toward noncontact pulse oximetry,” Rev. Sci. Instrum. 78(4), 044304 (2007).
[CrossRef] [PubMed]

Humphries, C.

T. P. Jung, S. Makeig, C. Humphries, T. W. Lee, M. J. McKeown, V. Iragui, and T. J. Sejnowski, “Removing electroencephalographic artifacts by blind source separation,” Psychophysiology 37(2), 163–178 (2000).
[CrossRef] [PubMed]

Iragui, V.

T. P. Jung, S. Makeig, C. Humphries, T. W. Lee, M. J. McKeown, V. Iragui, and T. J. Sejnowski, “Removing electroencephalographic artifacts by blind source separation,” Psychophysiology 37(2), 163–178 (2000).
[CrossRef] [PubMed]

James, C. J.

C. J. James and C. W. Hesse, “Independent component analysis for biomedical signals,” Physiol. Meas. 26(1), R15–R39 (2005).
[CrossRef] [PubMed]

Jung, T. P.

T. P. Jung, S. Makeig, C. Humphries, T. W. Lee, M. J. McKeown, V. Iragui, and T. J. Sejnowski, “Removing electroencephalographic artifacts by blind source separation,” Psychophysiology 37(2), 163–178 (2000).
[CrossRef] [PubMed]

Jung, T.-P.

M. J. McKeown, S. Makeig, G. G. Brown, T.-P. Jung, S. S. Kindermann, A. J. Bell, and T. J. Sejnowski, “Analysis of fMRI data by blind separation into independent spatial components,” Hum. Brain Mapp. 6(3), 160–188 (1998).
[CrossRef] [PubMed]

Kim, B. S.

B. S. Kim and S. K. Yoo, “Motion artifact reduction in photoplethysmography using independent component analysis,” IEEE Trans. Biomed. Eng. 53(3), 566–568 (2006).
[CrossRef] [PubMed]

Kindermann, S. S.

M. J. McKeown, S. Makeig, G. G. Brown, T.-P. Jung, S. S. Kindermann, A. J. Bell, and T. J. Sejnowski, “Analysis of fMRI data by blind separation into independent spatial components,” Hum. Brain Mapp. 6(3), 160–188 (1998).
[CrossRef] [PubMed]

Kumar, V.

M. P. Chawla, H. K. Verma, and V. Kumar, “Artifacts and noise removal in electrocardiograms using independent component analysis,” Int. J. Cardiol. 129(2), 278–281 (2008).
[CrossRef]

Lee, B. Y.

W. J. Cui, L. E. Ostrander, and B. Y. Lee, “In vivo reflectance of blood and tissue as a function of light wavelength,” IEEE Trans. Biomed. Eng. 37(6), 632–639 (1990).
[CrossRef] [PubMed]

Lee, T. W.

T. P. Jung, S. Makeig, C. Humphries, T. W. Lee, M. J. McKeown, V. Iragui, and T. J. Sejnowski, “Removing electroencephalographic artifacts by blind source separation,” Psychophysiology 37(2), 163–178 (2000).
[CrossRef] [PubMed]

Makeig, S.

T. P. Jung, S. Makeig, C. Humphries, T. W. Lee, M. J. McKeown, V. Iragui, and T. J. Sejnowski, “Removing electroencephalographic artifacts by blind source separation,” Psychophysiology 37(2), 163–178 (2000).
[CrossRef] [PubMed]

M. J. McKeown, S. Makeig, G. G. Brown, T.-P. Jung, S. S. Kindermann, A. J. Bell, and T. J. Sejnowski, “Analysis of fMRI data by blind separation into independent spatial components,” Hum. Brain Mapp. 6(3), 160–188 (1998).
[CrossRef] [PubMed]

Markham, C.

K. Humphreys, T. Ward, and C. Markham, “Noncontact simultaneous dual wavelength photoplethysmography: a further step toward noncontact pulse oximetry,” Rev. Sci. Instrum. 78(4), 044304 (2007).
[CrossRef] [PubMed]

Mastik, F.

F. P. Wieringa, F. Mastik, and A. F. van der Steen, “Contactless multiple wavelength photoplethysmographic imaging: a first step toward “SpO2 camera” technology,” Ann. Biomed. Eng. 33(8), 1034–1041 (2005).
[CrossRef] [PubMed]

McKeown, M. J.

T. P. Jung, S. Makeig, C. Humphries, T. W. Lee, M. J. McKeown, V. Iragui, and T. J. Sejnowski, “Removing electroencephalographic artifacts by blind source separation,” Psychophysiology 37(2), 163–178 (2000).
[CrossRef] [PubMed]

M. J. McKeown, S. Makeig, G. G. Brown, T.-P. Jung, S. S. Kindermann, A. J. Bell, and T. J. Sejnowski, “Analysis of fMRI data by blind separation into independent spatial components,” Hum. Brain Mapp. 6(3), 160–188 (1998).
[CrossRef] [PubMed]

Meeuwsen-van der Roest, W. P.

W. G. Zijlstra, A. Buursma, and W. P. Meeuwsen-van der Roest, “Absorption spectra of human fetal and adult oxyhemoglobin, de-oxyhemoglobin, carboxyhemoglobin, and methemoglobin,” Clin. Chem. 37(9), 1633–1638 (1991).
[PubMed]

Merla, A.

M. Garbey, N. Sun, A. Merla, and I. Pavlidis, “Contact-free measurement of cardiac pulse based on the analysis of thermal imagery,” IEEE Trans. Biomed. Eng. 54(8), 1418–1426 (2007).
[CrossRef] [PubMed]

Munder, S.

S. Munder and D. M. Gavrila, “An experimental study on pedestrian classification,” IEEE Trans. Pattern Anal. Mach. Intell. 28(11), 1863–1868 (2006).
[CrossRef] [PubMed]

Nelson, J. S.

Ohta, Y.

C. Takano and Y. Ohta, “Heart rate measurement based on a time-lapse image,” Med. Eng. Phys. 29(8), 853–857 (2007).
[CrossRef]

Ostrander, L. E.

W. J. Cui, L. E. Ostrander, and B. Y. Lee, “In vivo reflectance of blood and tissue as a function of light wavelength,” IEEE Trans. Biomed. Eng. 37(6), 632–639 (1990).
[CrossRef] [PubMed]

Pavlidis, I.

J. Fei and I. Pavlidis, “Thermistor at a Distance: Unobtrusive Measurement of Breathing,” IEEE Trans. Biomed. Eng. 57(4), 988–998 (2010).
[CrossRef]

I. Pavlidis, J. Dowdall, N. Sun, C. Puri, J. Fei, and M. Garbey, “Interacting with human physiology,” Comput. Vis. Image Underst. 108(1-2), 150–170 (2007).
[CrossRef]

M. Garbey, N. Sun, A. Merla, and I. Pavlidis, “Contact-free measurement of cardiac pulse based on the analysis of thermal imagery,” IEEE Trans. Biomed. Eng. 54(8), 1418–1426 (2007).
[CrossRef] [PubMed]

Poggio, T.

B. Heisele, T. Serre, and T. Poggio, “A component-based framework for face detection and identification,” Int. J. Comput. Vis. 74(2), 167–181 (2007).
[CrossRef]

Puri, C.

I. Pavlidis, J. Dowdall, N. Sun, C. Puri, J. Fei, and M. Garbey, “Interacting with human physiology,” Comput. Vis. Image Underst. 108(1-2), 150–170 (2007).
[CrossRef]

Rhee, S.

S. Rhee, B. H. Yang, and H. H. Asada, “Artifact-resistant power-efficient design of finger-ring plethysmographic sensors,” IEEE Trans. Biomed. Eng. 48(7), 795–805 (2001).
[CrossRef] [PubMed]

Rosenau, A.

R. C. Wuerz, D. Travers, N. Gilboy, D. R. Eitel, A. Rosenau, and R. Yazhari, “Implementation and refinement of the emergency severity index,” Acad. Emerg. Med. 8(2), 170–176 (2001).
[CrossRef] [PubMed]

Schaub, M. C.

S. Cook, M. Togni, M. C. Schaub, P. Wenaweser, and O. M. Hess, “High heart rate: a cardiovascular risk factor?” Eur. Heart J. 27(20), 2387–2393 (2006).
[CrossRef] [PubMed]

Sejnowski, T. J.

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Supplementary Material (3)

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» Media 3: MOV (2500 KB)     

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Figures (7)

Fig. 1
Fig. 1

Experimental setup.

Fig. 2
Fig. 2

Cardiac pulse recovery methodology. (a) The region of interest (ROI) is automatically detected using a face tracker. (b) The ROI is decomposed into the RGB channels and spatially averaged to obtain (c) the raw RGB traces. ICA is applied on the normalized RGB traces to recover (d) three independent source signals.

Fig. 3
Fig. 3

Recovery of the cardiac pulse from a webcam video recording of a participant at rest. (a) 30 s raw RGB traces and (b) their respective power spectra. (c) The independent components recovered using ICA along with the reference finger BVP signal and (d) their respective power spectra. (e) (Media 1) A single-frame excerpt from the webcam video recording with localized ROI (white box). (f) Evolution of the localized ROI over 1 min.

Fig. 4
Fig. 4

Bland-Altman plots demonstrating the agreement between 30 s epoch heart rate measurements obtained from participants sitting at rest using finger BVP and (a) the raw green channel trace (black circles), (b) the proposed ICA method (red circles) (a total of 372 measurement pairs from 12 participants). The lines represent the mean and 95% limits of agreement.

Fig. 5
Fig. 5

Recovery of the cardiac pulse from a webcam video recording of a moving participant. (a) 30 s raw RGB traces and (b) their respective power spectra. (c) The independent components recovered using ICA along with the reference finger BVP signal and (d) their respective power spectra. (e) (Media 2) A single-frame excerpt from the webcam video recording with localized ROI (white box). (f) Evolution of the localized ROI over 1 min.

Fig. 6
Fig. 6

Bland-Altman plots demonstrating the agreement between 30 s epoch heart rate measurements obtained from moving participants using finger BVP and (a) the raw green channel trace (black circles) and (b) the proposed ICA method (red circles) (a total of 372 measurement pairs from 12 participants). The lines represent the mean and 95% limits of agreement.

Fig. 7
Fig. 7

Simultaneous heart rate measurements of multiple persons in a single webcam video recording. (a) (Media 3) A single-frame excerpt from the webcam video recording with the ROI for each participant highlighted (white boxes). (b) Comparison between heart rate measurements obtained using the proposed methodology (colored lines) and a reference BVP sensor (black lines).

Tables (1)

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Table 1 Descriptive Statistics of Heart Rate Measurements by Proposed Methodology and Reference BVP

Equations (3)

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x(t)=As(t)
s^(t)=Wx(t)
xi(t)=xi(t)μiσi

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