Abstract
It is well-known that the electrocardiogram (ECG) is a non-invasive method that can be used to measure heart rate variability (HRV). Photoplethysmogram (PPG) signals also reflect the cardiac rhythm since the mechanical activity of the heart is coupled to its electrical activity. Photoplethysmography is a non-invasive, safe, and easy-to-use technique that has been developed for experimental use in vascular disease. A useful algorithm for a-wave detection in the acceleration plethysmogram (APG, the second derivative of the PPG) is introduced to determine the interval between successive heartbeats and heart rate variability. In this study, finger-tip PPG signals were recorded for twenty seconds from 27 healthy subjects measured at rest. The use of the aa interval in APG signals showed very promising results in calculating the HRV statistical indices, SDNN and rMSSD.
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References
Berntson, G., et al.: Heart rate variability: origins, methods, and interpretive caveats. Psychophysiology 34(6), 623–648 (1997)
Giardino, N., Lehrer, P., Edelberg, R.: Comparison of finger plethysmograph to ECG in the measurement of heart rate variability. Psychophysiology 39(2), 246–253 (2002)
Lu, S., et al.: Can photoplethysmography variability serve as an alternative approach to obtain heart rate variability information? J. Clin. Monit. Comput. 22(1), 23–29 (2008)
Jianfeng, W., Zhiqian, Y., Jianling, W.: An Improved Pre-processing Approach for Photoplethysmographic Signal. IEEE-EMBS in Engineering in Medicine and Biology Society (2005)
Takazawa, K., et al.: Clinical usefulness of the second derivative of a plethysmogram (acceralation plethysmogram). Cardiology 23, 207–217 (1993)
Taniguchi, K., et al.: Evaluating the surgeon’s stress when using surgical assistant robots. In: The 16th IEEE International Symposium on Robot and Human Interactive Communication, ROMAN 2007, pp. 888–893 (2007)
Matsuyama, A.: ECG and APG Signal Analysis during Exercise in a Hot Environment, in School of Engineering and Information Technology. Charles Darwin University, Darwin (2009)
Oppenheim, A., Shafer, R.: Discrete-time Signal Processing. Prentice-Hall, NJ
Rangayyan, R.M.: Biomedical Signal Analysis A Case-Study Approach. In: Akay, M. (ed.). IEEE Press Series on Biomedical Engineering, p. 516. John Wiley & Sons, New York (2002)
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Elgendi, M., Jonkman, M., DeBoer, F. (2011). Heart Rate Variability and the Acceleration Plethysmogram Signals Measured at Rest. In: Fred, A., Filipe, J., Gamboa, H. (eds) Biomedical Engineering Systems and Technologies. BIOSTEC 2010. Communications in Computer and Information Science, vol 127. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18472-7_21
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DOI: https://doi.org/10.1007/978-3-642-18472-7_21
Publisher Name: Springer, Berlin, Heidelberg
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