Coherence Analysis between Respiration and PPG Signal by Bivariate AR Model
PPG is a potential tool in clinical applications. Among such, the relationship between respiration and PPG signal has attracted attention in past decades. In this research, a bivariate AR spectral estimation method was utilized for the coherence analysis between these two signals. Ten healthy subjects participated in this research with signals measured at different respiratory rates. The results demonstrate that high coherence exists between respiration and PPG signal, whereas the coherence disappears in breath-holding experiments. These results imply that PPG signal reveals the respiratory information. The utilized method may provide an attractive alternative approach for the related researches.
[1] A. B. Hertzman and C. R. Spielman, "Observations on the finger volume
pulse recorded photoelectrically", Am. J. Physiol., 1937, vol.119,
pp.334-335.
[2] J. Allen, "Photoplethysmography and its application in clinical
physiological measurement", Physiol. Meas., 2007, vol.28, no.3,
pp.R1-R39.
[3] R. D. Allison, E. L. Holmes and J. Nyboer, "Volumetric dynamic of
respiration as measured by electrical impedance plethysmography", J.
Appl. Physiol., 1964, vol.19, pp.166-173.
[4] A. M. Cyna, V. Kulkarni, M. E. Tunstall, J. M. S. Hutchinson and J. R.
Mallard, "Aura: a new respiratory monitoring and apnea alarm for
spontaneously breathing patients", Br. J. Anaesth., 1991, vol.67,
pp.341-345.
[5] A. Johansson, P. Å. ├ûberg and G. Sedin, "Monitoring of heart and
respiratory rates in newborn infants using a new photoplethysmographic
technique", J. Clin. Monit., 1999, vol.15, pp.461-467.
[6] L. Nilsson, A. Johansson and S. Kalman, "Monitoring of respiratory rate
in postoperative care using a new photoplethysmographic technique", J.
Clin. Monit., 2000, vol.16, pp.309-315.
[7] A. Johansson and P. Å. ├ûberg, "Estimation of respiratory volumes from
the photoplethysmographic signal. Part I: experimental results", Med.
Biol. Eng. Comput., 1999, vol.37, pp.42-47.
[8] A. Johansson and P. Å. ├ûberg, "Estimation of respiratory volumes from
the photoplethysmographic signal. Part II: a model study", Med. Biol.
Eng. Comput., 1999, vol.37, pp.48-53.
[9] L. Nilsson, A. Johansson and S. Kalman, "Macrocirculation is not the sole
determinant of respiratory induced variations in the reflection mode
photoplethysmographic signal", Physiol. Meas., 2003, vol.24, pp.925-
937.
[10] M. Morf, A. Vieira, D. T. Lee and T. Kailath, "Recursive multichannel
maximum entropy spectral estimation", IEEE Trans. Geosci. Electron.,
1978, vol.16, pp.85-94.
[11] S. L. Marple Jr., Digital Spectral Analysis with Applications. New Jersey:
Prentice-Hall, 1987, ch.15.
[12] N. Levinson, "The Wiener RMS (root mean square) error criterion in filter
design and prediction", J. Math. Phys., 1947, vol.25, pp.261-278.
[1] A. B. Hertzman and C. R. Spielman, "Observations on the finger volume
pulse recorded photoelectrically", Am. J. Physiol., 1937, vol.119,
pp.334-335.
[2] J. Allen, "Photoplethysmography and its application in clinical
physiological measurement", Physiol. Meas., 2007, vol.28, no.3,
pp.R1-R39.
[3] R. D. Allison, E. L. Holmes and J. Nyboer, "Volumetric dynamic of
respiration as measured by electrical impedance plethysmography", J.
Appl. Physiol., 1964, vol.19, pp.166-173.
[4] A. M. Cyna, V. Kulkarni, M. E. Tunstall, J. M. S. Hutchinson and J. R.
Mallard, "Aura: a new respiratory monitoring and apnea alarm for
spontaneously breathing patients", Br. J. Anaesth., 1991, vol.67,
pp.341-345.
[5] A. Johansson, P. Å. ├ûberg and G. Sedin, "Monitoring of heart and
respiratory rates in newborn infants using a new photoplethysmographic
technique", J. Clin. Monit., 1999, vol.15, pp.461-467.
[6] L. Nilsson, A. Johansson and S. Kalman, "Monitoring of respiratory rate
in postoperative care using a new photoplethysmographic technique", J.
Clin. Monit., 2000, vol.16, pp.309-315.
[7] A. Johansson and P. Å. ├ûberg, "Estimation of respiratory volumes from
the photoplethysmographic signal. Part I: experimental results", Med.
Biol. Eng. Comput., 1999, vol.37, pp.42-47.
[8] A. Johansson and P. Å. ├ûberg, "Estimation of respiratory volumes from
the photoplethysmographic signal. Part II: a model study", Med. Biol.
Eng. Comput., 1999, vol.37, pp.48-53.
[9] L. Nilsson, A. Johansson and S. Kalman, "Macrocirculation is not the sole
determinant of respiratory induced variations in the reflection mode
photoplethysmographic signal", Physiol. Meas., 2003, vol.24, pp.925-
937.
[10] M. Morf, A. Vieira, D. T. Lee and T. Kailath, "Recursive multichannel
maximum entropy spectral estimation", IEEE Trans. Geosci. Electron.,
1978, vol.16, pp.85-94.
[11] S. L. Marple Jr., Digital Spectral Analysis with Applications. New Jersey:
Prentice-Hall, 1987, ch.15.
[12] N. Levinson, "The Wiener RMS (root mean square) error criterion in filter
design and prediction", J. Math. Phys., 1947, vol.25, pp.261-278.
@article{"International Journal of Electrical, Electronic and Communication Sciences:50370", author = "Yue-Der Lin and Wei-Ting Liu and Ching-Che Tsai and Wen-Hsiu Chen", title = "Coherence Analysis between Respiration and PPG Signal by Bivariate AR Model", abstract = "PPG is a potential tool in clinical applications. Among such, the relationship between respiration and PPG signal has attracted attention in past decades. In this research, a bivariate AR spectral estimation method was utilized for the coherence analysis between these two signals. Ten healthy subjects participated in this research with signals measured at different respiratory rates. The results demonstrate that high coherence exists between respiration and PPG signal, whereas the coherence disappears in breath-holding experiments. These results imply that PPG signal reveals the respiratory information. The utilized method may provide an attractive alternative approach for the related researches.
", keywords = "Coherence analysis, photoplethysmography (PPG),
bivariate AR spectral estimation.", volume = "3", number = "5", pages = "1084-6", }
