DistancePPG: Robust non-contact vital signs monitoring using a camera
Open accessAbstract
Vital signs such as pulse rate and breathing rate are currently measured using contact probes. But, non-contact methods for measuring vital signs are desirable both in hospital settings (e.g. in NICU) and for ubiquitous in-situ health tracking (e.g. on mobile phone and computers with webcams). Recently, camera-based non-contact vital sign monitoring have been shown to be feasible. However, camera-based vital sign monitoring is challenging for people with darker skin tone, under low lighting conditions, and/or during movement of an individual in front of the camera. In this paper, we propose distancePPG, a new camera-based vital sign estimation algorithm which addresses these challenges. DistancePPG proposes a new method of combining skin-color change signals from different tracked regions of the face using a weighted average, where the weights depend on the blood perfusion and incident light intensity in the region, to improve the signal-to-noise ratio (SNR) of camera-based estimate. One of our key contributions is a new automatic method for determining the weights based only on the video recording of the subject. The gains in SNR of camera-based PPG estimated using distancePPG translate into reduction of the error in vital sign estimation, and thus expand the scope of camera-based vital sign monitoring to potentially challenging scenarios. Further, a dataset will be released, comprising of synchronized video recordings of face and pulse oximeter based ground truth recordings from the earlobe for people with different skin tones, under different lighting conditions and for various motion scenarios.
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Other subjective scales were employed in 13 studies (35.14%).
“and other subjective scales were employed in 13 studies (35.14%) [30,42,43,44,45,50,52,56,72,78,80,87,88].”
From Skin pigmentation influence on pulse oximetry accuracy: a systematic review and bibliometric analysis (2022) · cites this paper as [78]
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BackgroundMotion robust remote photoplethysmography in CIELab color space
Yang, Y., Liu, C., Yu, H., Shao, D.-D., Tsow, F., & Tao, N. (2016) · Journal of Biomedical Optics · doi:10.1117/1.jbo.21.11.117001 · Cited by 52 · see citing works
“divide the face area into many small regions, and then reduce the body movement-induced artifacts on the rPPG from the entire face area by adjusting the weighting factors for different regions.(15) Since rPPG signals have different amplitudes in the three color channels of RGB color space,(16,17) algorithms based on a…”
BackgroundFouad, R. M., Omer, O. A., & Aly, M. H. (2019) · IEEE Access · doi:10.1109/access.2019.2922304 · Cited by 51 · see citing works
\Accurate measurement of the pulse wave delay with imaging photoplethysmography
Kamshilin, A. A., Sidorov, I. S., Babayan, L., Volynsky, M. A., Giniatullin, R. A., & Mamontov, O. V. (2016) · Biomedical Optics Express · doi:10.1364/boe.7.005138 · Cited by 50 · see citing works
Wei, B., He, X., Zhang, C., & Wu, X. (2017) · BioMedical Engineering OnLine · doi:10.1186/s12938-016-0300-0 · Cited by 50 · see citing works
“Mayank Kumar also mentioned the similar issue, and introduced a new method for generating high SNR PPG signals from the tracked golden ROIs structured by a weighted average approach [28].”
Huynh, S., Balan, R. K., Ko, J., & Lee, Y. (2019) · ACM Conference on Embedded Networked Sensor Systems (SenSys) · doi:10.1145/3356250.3360036 · Cited by 51 · see citing works
“Prior work has shown that the green channel captured by RGB camera is better than red and blue channels in detecting these colour changes [31, 62].”
BackgroundNon-intrusive Human Vital Sign Detection Using mmWave Sensing Technologies: A Review
Wu, Y., Ni, H., Mao, C., Han, J., & Xu, W. (2023) · ACM Transactions on Sensor Networks · doi:10.1145/3627161 · Cited by 51 · see citing works
“RGB cameras monitor subtle skin color variations due to inconsistent blood volume in arteries and capillaries [34][35].”
BackgroundBlood pressure estimation using video plethysmography
Šećerbegović, A., Bergsland, J., Halvorsen, P. S., Suljanović, N., Mujčić, A., & Balasingham, I. (2016) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2016.7493307 · Cited by 47 · see citing works
Liu, S., Lan, X., & Yuen, P. C. (2021) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2021.3050060 · Cited by 47 · see citing works
“It is observed that the rPPG signal varies around ± 2 for an RGB24 video when using an entire face as the observation region [42].”
MethodMarcinkevičs, Z., Rubīns, U., Zaharans, J., Miščuks, A., Urtane, E., & Ozoliņa-Moll, L. (2016) · Journal of Biomedical Optics · doi:10.1117/1.jbo.21.3.035005 · Cited by 46 · see citing works
Illumination variation-resistant video-based heart rate monitoring using LAB color space
Zhang, Y., Dong, Z., Zhang, K., Shu, S., Lu, F., & Chen, J. (2020) · Optics and Lasers in Engineering · doi:10.1016/j.optlaseng.2020.106328 · Cited by 45 · see citing works
HRVCam: robust camera-based measurement of heart rate variability
Pai, A., Veeraraghavan, A., & Sabharwal, A. (2021) · Journal of Biomedical Optics · doi:10.1117/1.jbo.26.2.022707 · Cited by 45 · see citing works
“A peak detection-based algorithm performs poorly in low SNR iPPG signals because it gives rise to false positives that adversely affect HRV estimation.(16) Previous works(7,19) used custom approaches to filter false positives and reduce errors in HRV measurements.”
MethodInfluentialPark, J.-Y., Lee, Y., Choi, Y.-W., Heo, R., Park, H., Cho, S. H., Cho, S. H., & Lim, Y. (2019) · Scientific Reports · doi:10.1038/s41598-019-48386-9 · Cited by 44 · see citing works
Jindal, V. (2016) · IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft) · doi:10.1145/2897073.2897132 · Cited by 43 · see citing works
“In our approach, the new PPG signal is obtained using a wearable sensor device like Fitbit or using the mobile phone camera by placing the index finger on the camera lens [2].”
MethodNovel health monitoring method using an RGB camera
Hassan, M., Malik, A. S., David Fofi, B., Saad, M. N. M., & Mériaudeau, F. (2017) · Biomedical Optics Express · doi:10.1364/boe.8.004838 · Cited by 41 · see citing works
Is Continuous Heart Rate Monitoring of Livestock a Dream or Is It Realistic? A Review
Nie, L., Berckmans, D., Wang, C., & Li, B. (2020) · Sensors · doi:10.3390/s20082291 · Cited by 43 · see citing works
Synthetic Generation of Face Videos with Plethysmograph Physiology
Wang, Z., Ba, Y., Chari, P., Bozkurt, O. D., Brown, G., Patwa, P., Vaddi, N., Jalilian, L., & Kadambi, A. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.01993 · Cited by 41 · see citing works
“Traditional rPPG methods either use Blind Source Separation (BSS) [17, 36, 37] or models based on skin re-flectance [9, 16, 43] to separate out the pulse signal from the color changes on the face.”
MethodA study of color illumination effect on the SNR of rPPG signals
Lin, Y.-C., & Lin, Y. (2017) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2017.8037807 · Cited by 40 · see citing works
Remote Photoplethysmography: Rarely Considered Factors
Mironenko, Y., Kalinin, K. B., Kopeliovich, M. V., & Petrushan, M. V. (2020) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw50498.2020.00156 · Cited by 39 · see citing works
“…Four iOS applications for contact and non-contact PPG cICA [37] cICA [37], ICA [28], PCA [29], G [4], CHROM [8], POS [9] SparsePPG [38] DistancePPG [39], CHROM [8], ICA [28] HR-CNN [40] 2SR [35], Li2014 [32], SAMC [30] SynRhythm [41] ICA [28], BCG [31], Li2014 [32], CHROM [8], Niu2017 [42], SAMC…”
MethodKamshilin, A. A., Zaytsev, V. V., Lodygin, A. V., & Кащенко, В. А. (2022) · Scientific Reports · doi:10.1038/s41598-022-05080-7 · Cited by 39 · see citing works
Gupta, A. R., Ravelo-García, A. G., & Morgado‐Dias, F. (2022) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2022.106771 · Cited by 38 · see citing works
Blood Pressure Measurement: From Cuff-Based to Contactless Monitoring
Man, P.-K., Cheung, K.-L., Sangsiri, N., Shek, W., Wong, K. L., Chin, J. W., Chan, T. T., & So, R. H. Y. (2022) · Healthcare · doi:10.3390/healthcare10102113 · Cited by 40 · see citing works
Zhang, X., Hu, M., Zhang, Y., Zhai, G., & Zhang, X.-P. S. (2023) · Advanced Intelligent Systems · doi:10.1002/aisy.202200345 · Cited by 37 · see citing works
Liu, Y., Qin, B., Li, R., Li, X., Huang, A., Liu, H., Lv, Y., & Liu, M. (2021) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2021.3060572 · Cited by 38 · see citing works
“…occurred between sequential frames, KLT tracking accuracy on unsolved challenges inherent in the optical flow technique [18], such as large face movement and partial occlusion cases as well as handling textureless facial areas, is not ideal for estimating motion-robust HR for rPPG [16], [17].”
BackgroundPrivacy-Phys: Facial Video-Based Physiological Modification for Privacy Protection
Sun, Z., & Li, X. (2022) · IEEE Signal Processing Letters · doi:10.1109/lsp.2022.3185964 · Cited by 37 · see citing works
“Our method has large perturbation in the cheek and forehead area, which follows the rPPG spatial distribution [38].”
MethodBeat-to-beat heart rate estimation fusing multimodal video and sensor data.
Antink, C. H., Gao, H., Brüser, C., & Leonhardt, S. (2015) · Biomedical Optics Express · doi:10.1364/boe.6.002895 · Cited by 36 · see citing works
“Noise and artifacts might influence channels by varying degrees: While the BCG and the pulse-related head oscillations are very susceptible to motion artifacts, advanced video processing methods allow the extraction of PPG signals even if the subject is moving [10].”
BackgroundYour face your heart: Secure mobile face authentication with photoplethysmograms
Chen, Y.-M., Sun, J., Jin, X., Li, T., Zhang, R., & Zhang, Y.-C. (2017) · IEEE Conference on Computer Communications · doi:10.1109/infocom.2017.8057220 · Cited by 35 · see citing works
“In the literature [16], [18], [19], [25], [26], it is widely accepted that the three channels carry different amount of photoplethysmogram information.”
BackgroundMethodInfluentialPulseCam: a camera-based, motion-robust and highly sensitive blood perfusion imaging modality
Kumar, M., Suliburk, J. W., Veeraraghavan, A., & Sabharwal, A. (2020) · Scientific Reports · doi:10.1038/s41598-020-61576-0 · Cited by 36 · see citing works
Park, J.-Y., Cho, H. K., Balan, R. K., & Ko, J. (2020) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3411843 · Cited by 36 · see citing works
“In order to solve such problems, non-contact (remote) PPG schemes have recently been proposed to monitor heart rate variability (HRV) using webcams [53, 56, 73, 115], or the smartphone’s front camera [39, 54].”
Addison, P. S., Jacquel, D., Foo, D. M. H., Antunes, A., & Borg, U. (2017) · Anesthesia & Analgesia · doi:10.1213/ane.0000000000001989 · Cited by 36 · see citing works
Chen, W., Yi, Z., Lim, L. J. R., Lim, R. Q. R., Zhang, A., Qian, Z., Huang, J., He, J., & Лю, Б. (2024) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2024.1420100 · Cited by 39 · see citing works
“Still, the algorithm implemented by this method is complex and time-consuming, and the pulse wave extracted by this method can not see apparent dicrotic waves (Kumar et al., 2015).”
MethodRemote Photoplethysmography for Heart Rate and Blood Oxygenation Measurement: A Review
Pirzada, P., Wilde, A., & Harris‐Birtill, D. (2024) · IEEE Sensors Journal · doi:10.1109/jsen.2024.3405414 · Cited by 38 · see citing works
“A pulse oximeter must be physically placed on a finger, which is hard for some patients with incapacities or cognitive challenges [45], [46], [47], during surgery [46], sensitive skin [18], burned skin [46], and in those with severe illness [18] as well as infants [48], [49] and young children [22].”
Camera-based photoplethysmography in an intraoperative setting
Trumpp, A., Lohr, J., Wedekind, D., Schmidt, M. U., Burghardt, M., Heller, A. R., Malberg, H., & Zaunseder, S. (2018) · BioMedical Engineering OnLine · doi:10.1186/s12938-018-0467-7 · Cited by 34 · see citing works
Remote Heart Rate Measurement from RGB-NIR Video Based on Spatial and Spectral Face Patch Selection
Kado, S., Monno, Y., Moriwaki, K., 吉崎和徳, Tanaka, M., & Okutomi, M. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8513464 · Cited by 34 · see citing works
Detail-preserving pulse wave extraction from facial videos using consumer-level camera
Wang, D., Yang, X., Liu, X., Jin, J., & Fang, S. (2020) · Biomedical Optics Express · doi:10.1364/boe.380646 · Cited by 34 · see citing works
Color-Distortion Filtering for Remote Photoplethysmography
Wang, W., Brinker, A. C. D., Stuijk, S., & de Haan, G. (2017) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2017.18 · Cited by 34 · see citing works
“, G [1], [13], [14], GR [15], HUE [11], PCA [4], ICA [5], CHROM [7], [16], [17], PBV [8], and POS [9].”
Video pulse rate variability analysis in stationary and motion conditions
Rodríguez, A., & Ramos-Castro, J. J. (2018) · BioMedical Engineering OnLine · doi:10.1186/s12938-018-0437-0 · Cited by 34 · see citing works
“[24] performed the acquisition of signals in three natural motion scenarios.”
BackgroundMethodInfluential
- Authors
- Kumar, M., Veeraraghavan, A., & Sabharwal, A.
- Affiliations
- Rice University (US)
- Venue
- Biomedical Optics Express
- Publisher
- Optica Publishing Group
- Published
- 2015-04-06
- Volume
- 6
- Issue
- 5
- Pages
- 1565
- ISSN
- 2156-7085 (ISSN-L)
- PMC
- PMC4467696
- OpenAlex
- W2029745771
- Cited by
- 417
- References
- 17
- Citations by year
- 2026: 9 · 2025: 21 · 2024: 36 · 2023: 46 · 2022: 49 · 2021: 57 · 2020: 35 · 2019: 47 · 2018: 46 · 2017: 33 · 2016: 31 · 2015: 7
- FWCI
- 19.38
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Biomedical Optics Express (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Rice Research Repository (Rice University) (submittedVersion)
- Funders
- National Science Foundation (NSF) (1126478, 1429047)
- Texas Higher Education Coordinating Board (THECB) (THECB-NHARP 13308)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Optical Imaging and Spectroscopy Techniques
- Keywords
- respiratory rate estimation, photoplethysmography, skin color change, blood perfusion, incident light intensity, signal-to-noise ratio, darker skin tones, motion robustness
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