Abstract
In healthcare applications, the photoplethysmography concept is widely employed to estimate the heart rate, breathing rate, and other vital signs of humans, by using facial videos. However, the latter physiological indicators are fundamentally used to determine the physiological and pathological state of a person. In consequence, the present study will notably concentrate on the respiratory rate value extraction through a non-contact technique. The current approach is mainly based on image processing for PPG data gathering, and plethysmography (PPG) signal normalization, signal decomposition, and Fourier transform in order to extract the adequate candidate for breathing rate estimation. Moreover, our study contains a result comparison of the decomposition eminent methods such as the Empirical Mode Decomposition (EMD) and Empirical Wavelet Transform (EWT), the metrological interpretation of the results achieved from the experiment’s research is discussed and conclusions are presented.
Supported by organization Laboratory of Systems Engineering and Information Technology LiSTi.
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References
Rolfe, S.: The importance of respiratory rate monitoring. Br. J. Nurs. 28(8), 504–508 (2020)
Lei, R., Ling, B.W.K., Feng, P., Chen, J.: Estimation of heart rate and respiratory rate from PPG signal using complementary ensemble empirical mode decomposition with both independent component analysis and non-negative matrix factorization. Sensors 20(11), 3238 (2020)
Sharma, H.: Extraction of respiratory rate from PPG using ensemble empirical mode decomposition with Kalman filter. Electron. Lett. 56(13), 650–653 (2020)
Iqbal, T., Elahi, A., Ganly, S., et al.: Photoplethysmography-based respiratory rate estimation algorithm for health monitoring applications. J. Med. Biol. Eng. 42(2), 242–252 (2022)
Viola, P., Jones, M.: Robust real-time face detection. In: Eighth IEEE International Conference on Computer Vision, ICCV 2001. Proceedings, pp. 747–747 (2001)
Huang, N.E., et al.: The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc. Roy. Soc. London Ser. A Math. Phys. Eng. Sci. 454(1971), 903–995 (1998)
Gilles, J.: Empirical wavelet transform. IEEE Trans. Signal Process. 61(16), 3999–4010 (2013)
Morlet, J., Arens, G., Fourgeau, E., Gıard, D.: Wave propagation and sampling theory-Part I: complex signal and scattering in multilayered media. Geophysics 47(2), 203–221 (1982)
Heckbert, P.: Fourier Transforms and the Fast Fourier Transform (FFT) algorithm. Notes Comput. Graph. 3, 15–463 (1995)
Wörner, S.: Fast Fourier transform numerical analysis seminar (2008)
Poh, M.Z., McDuff, D.J., Picard, R.W.: Non-contact, automated cardiac pulse measurements using video imaging and blind source separation. Opt. Express 18(10), 10762–10774 (2010)
Verkruysse, W., Svaasand, L.O., Nelson, J.S.: Remote plethysmographic imaging using ambient light. Opt. Express 16(26), 21434–21445 (2008)
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El Khadiri, Z., Latif, R., Saddik, A. (2023). Breathing Pattern Assessment Through the Empirical Mode Decomposition and the Empirical Wavelet Transform Algorithms. In: Hassanien, A.E., et al. The 3rd International Conference on Artificial Intelligence and Computer Vision (AICV2023), March 5–7, 2023. AICV 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 164. Springer, Cham. https://doi.org/10.1007/978-3-031-27762-7_25
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DOI: https://doi.org/10.1007/978-3-031-27762-7_25
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