Abstract
Heart rate (HR) and respiratory rate (RR) vital signs provide useful cardiorespiratory information, and their monitoring is routinely carried out in clinical settings via electrocardiography, photoplethysmography, and capnography. However, these and other specialized biomedical devices are not easily translated to everyday use outside clinical and research settings. Hence, there is still a need for HR and RR monitoring devices that could be used on a daily basis by the general population. In this study, we employed a contact approach to estimate both HR and RR directly from image plethysmography (iPPG) signals extracted from smartphone-acquired videos. Video recordings of the fingertips from eight (N = 8) volunteers were acquired with an Android smartphone while the subjects performed metronome breathing maneuvers. The iPPG waveform was extracted via the Extended Blind End-member and Abundance Extraction (EBEAE) algorithm. Simultaneous ECG recordings were used to compute reference HR and RR time series. We found that iPPG-based estimates are highly correlated by those from ECG-derived ones (HR: \( \rho = 0.9953 \), RR: \( \rho = 0.9733 \) with low normalized root-mean-square errors (HR: \( NRMSE = \) 0.0855, RR: \( NRMSE = 0.3074 \) for both HR and RR estimation. The obtained results corroborate the feasibility of using contact iPPG methods to accurately estimate not only HR, but also RR without specialized biomedical devices.
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References
Kannel, W.B., Kannel, C., Paffenbarger, R.S., Cupples, L.A.: Heart rate and cardiovascular mortality: the Framingham Study. Am. Heart J. 113, 1489–1494 (1987). https://doi.org/10.1016/0002-8703(87)90666-1
Cretikos, M.A., Bellomo, R., Hillman, K., Chen, J., Finfer, S., Flabouris, A.: Respiratory rate: the neglected vital sign. Med. J. Aust. 188, 657 (2008). https://doi.org/10.5694/j.1326-5377.2008.tb01825.x
Sun, Y., Thakor, N.: Photoplethysmography revisited: from contact to noncontact, from point to imaging. IEEE Trans. Biomed. Eng. 63, 463–477 (2016). https://doi.org/10.1109/TBME.2015.2476337
Jonathan, E., Leahy, M.: Investigating a smartphone imaging unit for photoplethysmography. Physiol. Meas. 31, N79 (2010). https://doi.org/10.1088/0967-3334/31/11/N01
Grimaldi, D., Kurylyak, Y., Lamonaca, F., Nastro, A.: Photoplethysmography detection by smartphone’s videocamera. In: Intelligent Data Acquisition and Advanced Computing Systems (IDAACS), 2011 IEEE 6th International Conference, pp. 488–491. IEEE Press, New York (2011). https://doi.org/10.1109/idaacs.2011.6072801
Lázaro, J., Nam, Y., Gil, E., Laguna, P., Chon, K.H.: Respiratory rate derived from smartphone-camera-acquired pulse photoplethysmographic signals. Physiol. Meas. 36, 2317 (2015). https://doi.org/10.1088/0967-3334/36/11/2317
Lázaro, J., Gil, E., Bailón, R., Mincholé, A., Laguna, P.: Deriving respiration from photoplethysmographic pulse width. Med. Biol. Eng. Comput. 51, 233–242 (2012)
Nam, Y., Kong, Y., Reyes, B., Reljin, N., Chon, K.H.: Monitoring of heart and breathing rates using dual cameras on a smartphone. PLoS ONE 11, e0151013 (2016). https://doi.org/10.1371/journal.pone.0151013
Campos-Delgado, D.U., Gutierrez-Navarro, O., Jo, J.A.: Linear unmixing of optic signals by extended blind end-member and abundance extraction. In: Latin America Optics and Photonics Conference 2018, p. Tu4A.12. OSA Publishing, Washington, D.C. (2018). https://doi.org/10.1364/laop.2018.tu4a.12
Vidaurre, C., Sander, T.H., Schlögl, A.: BioSig: the free and open source software library for biomedical signal processing. Comput. Intell. Neurosci. 2011, 1–12 (2011). https://doi.org/10.1155/2011/935364
Lee, J., Reyes, B.A., McManus, D.D., Mathias, O., Chon, K.H.: Atrial fibrillation detection using an iPhone 4S. IEEE Trans. Biomed. Eng. 60, 203–206 (2013). https://doi.org/10.1109/TBME.2012.2208112
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The authors would like to thank CONACYT for the financial support through a Basic Science Grant (Ref. # 254637).
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García-López, R., Benítez-Benítez, J., Campos-Delgado, D.U., Reyes, B.A. (2020). Estimation of Heart Rate and Respiratory Rate via Blind Estimation from Smartphone-Based Contact Image Photoplethysmography. In: González Díaz, C., et al. VIII Latin American Conference on Biomedical Engineering and XLII National Conference on Biomedical Engineering. CLAIB 2019. IFMBE Proceedings, vol 75. Springer, Cham. https://doi.org/10.1007/978-3-030-30648-9_9
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DOI: https://doi.org/10.1007/978-3-030-30648-9_9
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