The DOI matches its Crossref record; 40 of the 42 references it cites were found in a registry or an index.
Algorithms for Monitoring Heart Rate and Respiratory Rate From the Video of a User’s Face
Open accessAbstract
. In this pilot study, we have introduced a novel iPPG method where by measuring variations in color of reflected light, i.e., Hue, and can therefore measure both HR and respiratory rate (RR) from the video of a subject's face. This paper was performed on 25 healthy individuals (Ages 20-30, 15 males and 10 females, and skin color was Fitzpatrick scale 1-6). For each subject we took two 20 second video of the subject's face with minimal movement, one with flash ON and one with flash OFF. While recording the videos we simultaneously measuring HR using a Biosync B-50DL Finger Heart Rate Monitor, and RR using self-reporting. This paper shows that our proposed approach of measuring iPPG using Hue (range 0-0.1) gives more accurate readings than the Green channel. HR/Hue (range 0-0.1) ([Formula: see text], [Formula: see text]-value = 4.1617, and RMSE = 0.8887) is more accurate compared with HR/Green ([Formula: see text], [Formula: see text]-value = 11.60172, and RMSE = 0.9068). RR/Hue (range 0-0.1) ([Formula: see text], [Formula: see text]-value = 0.2885, and RMSE = 3.8884) is more accurate compared with RR/Green ([Formula: see text], [Formula: see text]-value = 0.5608, and RMSE = 5.6885). We hope that this hardware agnostic approach for detection of vital signals will have a huge potential impact in telemedicine, and can be used to tackle challenges, such as continuous non-contact monitoring of neo-natal and elderly patients. An implementation of the algorithm can be found at https://pulser.thinkbiosolution.com.
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“1/12 (8.33%) assessed that further studies with other clinical and patient-reported data are required to understand the effects of skin pigmentation on the accuracy [77]”
From Skin pigmentation influence on pulse oximetry accuracy: a systematic review and bibliometric analysis (2022) · cites this paper as [77]
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“We find that objective scales such as the Fitzpatrick Skin Pigmentation (FSP) scale or the Munsell scale were used by 6/37 studies (16.21%) [61,69,70,71,76,77] and 4/37 studies (10.81%) [47,48,74,89], respectively.”
From Skin pigmentation influence on pulse oximetry accuracy: a systematic review and bibliometric analysis (2022) · cites this paper as [77]
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Cites
Rapid object detection using a boosted cascade of simple features
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Heart Rate Variability: Standards of Measurement, Physiological Interpretation, and Clinical Use
Electrophysiology, T. F. O. T. E. S. O. C. T. N. A. (1996) · Circulation · doi:10.1161/01.cir.93.5.1043 · Cited by 17,159
Heart rate variability: Standards of measurement, physiological interpretation, and clinical use
Malik, M., Bigger, J. T., Camm, A. J., Kleiger, R. E., Malliani, A., Moss, A. J., & Schwartz, P. J. (1996) · European Heart Journal · doi:10.1093/oxfordjournals.eurheartj.a014868 · Cited by 15,289
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Remote plethysmographic imaging using ambient light
Verkruysse, W., Svaasand, L. O., & Nelson, J. S. (2008) · Optics Express · doi:10.1364/oe.16.021434 · Cited by 1,728
Non-contact, automated cardiac pulse measurements using video imaging and blind source separation
Poh, M., McDuff, D., & Picard, R. W. (2010) · Optics Express · doi:10.1364/oe.18.010762 · Cited by 1,652
Eulerian video magnification for revealing subtle changes in the world
Wu, H., Rubinstein, M., Shih, E. I., Guttag, J. V., Durand, F., & Freeman, W. T. (2012) · ACM Transactions on Graphics · doi:10.1145/2185520.2185561 · Cited by 1,365
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Research works printed but not linked: 7
- 2016, RGB to HSL Color Conversion
- 2016, OpenCV Library
- 2016, Instant Heart Rate by Azumio Inc
- 2016, Fitbit
- 2016, Kinsa Smart Thermometer
- 2018, Vital Signs (Body Temperature Pulse Rate Respiration Rate Blood Pressure) Johns Hopkins Medicine Health Library
- 2016, CMS50DL Pulse Oximeter User Manual
Cited by
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Smartphone Sensors for Health Monitoring and Diagnosis
Majumder, S., & Deen, M. J. (2019) · Sensors · doi:10.3390/s19092164 · Cited by 455
Recent development of respiratory rate measurement technologies
Liu, H., Allen, J., Zheng, D., & Chen, F. (2019) · Physiological Measurement · doi:10.1088/1361-6579/ab299e · Cited by 276
Contactless Methods For Measuring Respiratory Rate: A Review
Massaroni, C., Nicolò, A., Sacchetti, M., & Schena, E. (2020) · IEEE Sensors Journal · doi:10.1109/jsen.2020.3023486 · Cited by 190
Cabanas, A. M., Fuentes-Guajardo, M., Latorre, K., León, D., & Martín-Escudero, P. (2022) · Sensors · doi:10.3390/s22093402 · Cited by 124
Continuous Monitoring of Vital Signs Using Cameras: A Systematic Review
Vinothini, S., Spicher, N., Wang, J., Ganapathy, N., Warnecke, J. M., Leonhardt, S. K., Swaminathan, R., & Deserno, T. M. (2022) · Sensors · doi:10.3390/s22114097 · Cited by 122
Metadata
- Authors
- Sanyal, S., & Nundy, K. K.
- Venue
- IEEE Journal of Translational Engineering in Health and Medicine
- Published
- 2018
- Volume
- 6
- Pages
- 1-11
- ISSN
- 2168-2372 (ISSN-L)
- PMC
- PMC5957265
- OpenAlex
- W2797516094
- Cited by
- 125
- References
- 42
- Citations by year
- 2026: 8 · 2025: 12 · 2024: 13 · 2023: 16 · 2022: 19 · 2021: 26 · 2020: 16 · 2019: 14 · 2018: 1
- FWCI
- 5.70
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Journal of Translational Engineering in Health and Medicine (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Keywords
- photoplethysmography, heart rate monitoring, respiratory rate estimation, facial video, hue, green channel, non-contact vital sign monitoring, telemedicine, neonatal monitoring, elderly patients
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