Estimation of HRV and SpO2 from wrist-worn commercial sensors for clinical settings
Open accessAbstract
We describe an evaluation of photoplethysmography (PPG) signals with two wavelengths channels (infrared and red) using a wrist-worn sensor for the estimation of heart rate variability (HRV) and oxygen saturation (SpO2). Five healthy subjects were equipped with a commercial wrist-worn pulse oximeter (Wavelet Health, USA) on the right hand, and both a commercial smart watch for fitness use (Huawei Watch, Series 2) and a clinically-validated transmission-mode pulse oximeter (Creative Medical PC-68B) on their left hand as a reference. Synchronised PPG signals from the Wavelet Health, the Huawei watch, and the PC-68B were recorded for approximately 10 minutes. Subjects were asked to leave the left hand in a resting state, while moving the right hand with two types of movement (periodic and random). A method is proposed to incorporate coupling information between the two wavelengths of PPGs based on the bivariate empirical mode decomposition algorithm. Our method is shown to improve the quality of red PPG allowing improved estimation of SpO2. A comparison of average heart rate (HR), HRV, and SpO2 from all devices is provided.
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It is difficult to estimate SpO2 during motion artifact.
“it is difficult to estimate SpO2 during motion artifact”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [140]
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Huang, N. E., Shen, Z., Long, S. R., Wu, M. C., Shih, H. H., Zheng, Q., Yen, N.-C., Tung, C. C., & Liu, H. H. (1998) · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rspa.1998.0193 · Cited by 23,707 · see citing works
Bivariate Empirical Mode Decomposition
Rilling, G., Flandrin, P., Gonçalvès, P., & Lilly, J. M. (2007) · IEEE Signal Processing Letters · doi:10.1109/lsp.2007.904710 · Cited by 600 · see citing works
Non-contact video-based vital sign monitoring using ambient light and auto-regressive models
Tarassenko, L., Villarroel, M., Guazzi, A., Jorge, J., Clifton, D. A., & Pugh, C. W. (2014) · Physiological Measurement · doi:10.1088/0967-3334/35/5/807 · Cited by 421 · see citing works
Self-citationLee, J., Matsumura, K., Yamakoshi, K.-I., Rolfe, P., Tanaka, S., & Yamakoshi, T. (2013) · 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2013.6609852 · Cited by 202 · see citing works
A Real Time Analysis of PPG Signal for Measurement of SpO2 and Pulse Rate
Bagha, S., & Shaw, L. (2011) · International Journal of Computer Applications · Cited by 143 · see citing works
Centile-based early warning scores derived from statistical distributions of vital signs
Tarassenko, L., Clifton, D. A., Pinsky, M. R., Hravnak, M., Woods, J. R., & Watkinson, P. (2011) · Resuscitation · doi:10.1016/j.resuscitation.2011.03.006 · Cited by 131 · see citing works
Self-citationJarchi, D., Wong, C., Kwasnicki, R. M., Heller, B. W., Tew, G. A., & Yang, G. (2014) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2014.2299772 · Cited by 73 · see citing works
Self-citationTowards Photoplethysmography-Based Estimation of Instantaneous Heart Rate During Physical Activity
Jarchi, D., & Casson, A. J. (2017) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2017.2668763 · Cited by 58 · see citing works
Self-citationTautan, A.-M., Young, A., Wentink, E., & Wieringa, F. (2015) · 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2015.7319795 · Cited by 47 · see citing works
Budidha, K., & Kyriacou, P. A. (2013) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2013.6609855 · Cited by 11 · see citing works
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Charlton, P. H., Kyriacou, P. A., Mant, J., Marozas, V., Chowienczyk, P., & Alastruey, J. (2022) · Proceedings of the IEEE · doi:10.1109/jproc.2022.3149785 · Cited by 250 · see citing works
Cao, R., Azimi, I., Sarhaddi, F., Niela-Vilen, H., Axelin, A., Liljeberg, P., & Rahmani, A. M. (2022) · Journal of Medical Internet Research · doi:10.2196/27487 · Cited by 159 · see citing works
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Islam, M. M., Mahmud, S., Muhammad, L. J., Islam, M. R., Nooruddin, S., & Ayon, S. I. (2020) · SN Computer Science · doi:10.1007/s42979-020-00335-4 · Cited by 125 · see citing works
Wearable Photoplethysmography for Cardiovascular Monitoring.
Charlton, P. H., Kyriacou, P. A., Mant, J., Marozas, V., Chowienczyk, P., & Alastruey, J. (2022) · KTUePubl (Repository of Kaunas University of Technology) · doi:10.17863/cam.81148 · Cited by 113 · see citing works
Dcosta, J. V., Ochoa, D., & Sanaur, S. (2023) · Advanced Science · doi:10.1002/advs.202302752 · Cited by 86 · see citing works
Abeltino, A., Riente, A., Bianchetti, G., Serantoni, C., Spirito, M. D., Capezzone, S., Esposito, R., & Maulucci, G. (2024) · Nutrition Reviews · doi:10.1093/nutrit/nuae035 · Cited by 93 · see citing works
Saber, D., & El-Aziz, K. A. (2021) · Journal of Industrial Textiles · doi:10.1177/15280837211041771 · Cited by 50 · see citing works
Gradl, S., Wirth, M., Richer, R., Rohleder, N., & Eskofier, B. M. (2019) · International Conference on Pervasive Computing Technologies for Healthcare · doi:10.1145/3329189.3329233 · Cited by 49 · see citing works
Rentz, L. E., Ulman, H. K., & Galster, S. M. (2021) · Sensors · doi:10.3390/s21155071 · Cited by 46 · see citing works
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Jarchi, D., Salvi, D., Tarassenko, L., & Clifton, D. A. (2018) · Sensors · doi:10.3390/s18113705 · Cited by 39 · see citing works
Self-citationDudarev, V., Barral, O., Zhang, C., Davis, G., & Enns, J. T. (2023) · Sensors · doi:10.3390/s23135863 · Cited by 35 · see citing works
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Mologne, M. S., Hu, J. C., Carrillo, E., Gómez, D., Yamamoto, T., Lu, S., Browne, J. D., & Dolezal, B. A. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20010210 · Cited by 28 · see citing works
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Ilyas, T., Mahmood, D., Ahmed, G., & Akhunzada, A. (2021) · Energies · doi:10.3390/en14217023 · Cited by 9 · see citing works
Anderson, T., van Mourik, R. A., Martin, K. J., Eijsvogels, T. M. H., & Longoria, K. (2023) · International Journal of Sports Physiology and Performance · doi:10.1123/ijspp.2022-0327 · Cited by 6 · see citing works
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Zhang, Q., Li, L., Zhang, Z., & Chen, Z. (2023) · IEEE Sensors Journal · doi:10.1109/jsen.2023.3344572 · Cited by 5 · see citing works
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Rodríguez-Pellejero, J. M., Mulero-Henríquez, I., & Amador, Z. S. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03410-w · Cited by 4 · see citing works
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Naveena, C. P., Mary, X. A., Sharmeli, M., & Rajappa, D. (2018) · International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET) · doi:10.1109/iccsdet.2018.8821089 · Cited by 5 · see citing works
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Mathieu, A. J. W., Charlton, P. H., & Alastruey, J. (2018) · International Electronic Conference on Sensors and Applications (ECSA) · doi:10.3390/ecsa-5-05744 · Cited by 3 · see citing works
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Sakthimohan, M., Rani, G. E., Deny, J., Susmitha, S. N., & Sobiya, S. (2021) · 3C Tecnología_Glosas de innovación aplicadas a la pyme · doi:10.17993/3ctecno.2021.specialissue8.41-51 · Cited by 1 · see citing works
Sriraam, N., & Chakravarty, P. (2023) · Critical Reviews in Biomedical Engineering · doi:10.1615/critrevbiomedeng.2023045334 · Cited by 2 · see citing works
Koteska, B., Ackovska, N., Bogdanova, A. M., Kostoska, M., Sidorenko, M., Lehocki, F., & Trajkovik, V. (2024) · Biomedical Engineering Applications Basis and Communications · doi:10.4015/s1016237224300049 · Cited by 1 · see citing works
Anderson, T., Martin, K., & Bausek, N. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.27.661934 · Cited by 1 · see citing works
Schipper, R. M., Djibrillah, F. O., Roosink, M., Winkens, L. H. H., John, A., Hazebroek, E. J., Witteveen, A., & Berendsen, A. A. M. (2025) · doi:10.2196/preprints.87324 · Cited by 1 · see citing works
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Sanei, S., Jarchi, D., & Constantinides, A. G. (2020) · Wiley eBooks · doi:10.1002/9781119390060.ch4
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Mahdi, M. M., Gharghan, S. K., Mohammed, S. L., & Ibrahim, I. A. (2023) · IEEE International Conference on System Engineering and Technology (ICSET) · doi:10.1109/icset59111.2023.10295074
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Chen, Y., Zheng, Y., Worrall, A., Johnson, S. R., Wiffen, R., & Yang, B. (2025) · Biomedical Engineering Advances · doi:10.1016/j.bea.2025.100150
RetractedJun, 樊. F., Zexi, 郑. Z., Huazhong, 项. X., & Jiaqing, 陶. T. (2025) · Chinese Journal of Lasers · doi:10.3788/cjl250479
Schipper, R. M., Djibrillah, F. O., Roosink, M., Winkens, L. H. H., John, A., Hazebroek, E. J., Witteveen, A., & Berendsen, A. A. M. (2026) · JMIR mhealth and uhealth · doi:10.2196/87324 · Cited by 1 · see citing works
- Authors
- Jarchi, D., Salvi, D., Velardo, C., Mahdi, A., Tarassenko, L., & Clifton, D. A.
- Affiliations
- University of Oxford (GB)
- Venue
- 2018 IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks (BSN)
- Publisher
- IEEE
- Published
- 2018-03
- Pages
- 144-147
- ISSN
- 2376-8886 (ISSN-L)
- OpenAlex
- W2796183804
- Cited by
- 38
- References
- 10
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 4 · 2023: 8 · 2022: 6 · 2021: 7 · 2020: 2 · 2019: 1 · 2018: 3
- FWCI
- 7.12
- Type
- conference paper
- Language
- en
- Open access
- Locations
- Wearable and Implantable Body Sensor Networks (publishedVersion)
- Open Access at Essex (University of Essex) (submittedVersion)
- 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 › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Keywords
- heart rate variability, oxygen saturation, photoplethysmography, wrist-worn sensors, pulse oximetry, smartwatches, bivariate empirical mode decomposition
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