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Spectral analysis of heart rate variability signal and respiration in diabetic subjects

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Abstract

The paper deals with methods of processing ECG and respiration signals which aim at detecting parameters whose values may be correlated to normal and diabetic subjects with or without cardiovascular autonomic neuropathy (CAN). Beatto-beat R-R duration values of the ECG and discrete series of respiration are obtained from original signals using a recognition algorithm. Power spectrum analysis (autospectra, cross-spectra and coherence via autoregressive modelling) is carried out on segments of about 200 consecutive cardiac cycles. Spectral parameters of the R-R variability signal are obtained as follows: total power, power of low-frequency (LF) and high-frequency (HF) components, power of the signal which is (or is not) coherent with respiration, in absolute or in percentage values. The experimental protocol considers 40 diabetic patients (21 of whom have diabetic neuropathy) and 14 normals in three different conditions: resting, standing and controlled respiration. The developed spectral parameters seem sensitive enough to differentiate between normal and pathological subjects. These parameters may constitute a quantitative means to be edded to the classical diabetic tests for the diagnosis of cardiovascular autonomic neuropathy.

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References

  • Akselrod, S., Gordon, D., Ubel, F. A., Shannon, D. C., Barger, A. C. andCohen, R. J. (1981) Power spectrum analysis of heart rate flucturation: a quantitative probe of beat-to-beat cardiovascular control.Science,213, 220–222.

    Google Scholar 

  • Bartoli, F., Baselli, G. andCerutti, S. (1982) Application of identification and linear filtering algorithms to the R-R interval measurement. Proc. IEEE Computers in Cardiology Conf., Seattle, Washington.

  • Baselli, G. andCerutti, S. (1985) Identification techniques applied to processing of signals from cardiovascular systems.Med. Inform.,10, 223–235.

    Article  Google Scholar 

  • Baselli, G., Cerutti, S., Civardi, S., Liberati, D., Lombardi, F., Malliani, A. andPagani, M. (1986) Spectral and crossspectral analysis of heart rate and arterial blood pressure variability signals.Comput. & Biomed. Res.,19, 520–534.

    Article  Google Scholar 

  • Baselli, G., Cerutti, S., Civardi, S., Lombardi, F., Malliani, A., Merri, M. Pagani, M. andRizzo, G. (1987) Heart rate variability signal processing: a quantitative approach as an aid to diagnosis in cardiovascular pathologies.Int. J. Bio-Med. Comput.,20, 51–70.

    Article  Google Scholar 

  • Baselli, G., Cerutti, S., Civardi, S., Malliani, A. andPagani, M. (1988a) Cardiovascular variability signals: towards the identification of a closed loop model of the neutral control mechanisms.IEEE Trans.,BMI-35, 1033–1046.

    Google Scholar 

  • Baselli, G., Cerutti, S., Livraghi, M., Meneghini, C., Pagani, M. andRimoldi, O. (1988b) Causal relationship between heart rate and arterial blood pressure variability signals.Med. & Biol. Eng. & Comput.,26, 374–378.

    Google Scholar 

  • Bennett, T., Fentem, P. H., Fitton, D., Hampton, J. R., Hoksing, D. J. andRiggott, P. A. (1977) Assemsment of vagal control of the heart in diabetes; measures of R-R interval variations under different conditions.Br. Heart J.,39, 25–28.

    Google Scholar 

  • Berger, R. D., Saul, J. P., Stain, S. P. andCohen, R. J. (1988) Respiratory effects on arterial pressure: a novel signal analysis approach. Proc. IEEE Eng. in Med. & Biol. Soc. 10th Ann. Int. Conf., New Orleans.

  • Box, G. E. P. andJenkins, G. M. (1976)Time series analysis: forecasting and control. Holden-Day, San Francisco.

    MATH  Google Scholar 

  • Cerutti, S., Alberti, M., Baselli, G., Rimoldi, O., Malliani, A., Merri, M. andPagani, M. (1988) Automatic assessment of the interaction between respiration and heart rate variability signal.Med. Progr. through Technol.,14, 7–19.

    Google Scholar 

  • Chess, G. F., Tam, R. M. K. andCalaresu, F. R. (1975) Influence or cardiac neural inputs on rhythmic variations of heart period in the cat.Am. J. Physiol.,128, 775–789.

    Google Scholar 

  • de Boer, R. W., Karemaker, J. M. andStrackee, J. (1983) Beat-to-beat variability of heart rate interval and blood pressure.Automedica,4, 217–222.

    Google Scholar 

  • Ewing, D. J., Martyn, C. N., Young, R. J. andClarke, B. F. (1985) The value of cardiovascular autonomic function tests: 10 years experience in diabetes.Diabetes Care,8, 491–498.

    Google Scholar 

  • Guzzetti, S., Piccaluga, E., Casati, R., Cerutti, S., Lombardi, F., Pagani, M. andMalliani, A. (1988) Sympathetic predominance in essential hypertension: a study employing spectral analysis of heart rate variability.J. Hypertens.,6, 711–717.

    Google Scholar 

  • Hirsch, J. A. andBishop, B. (1981) Respiratory sinus arrhythmia in humans: how breathing pattern modulates heart rate.Am. J. Physiol.,241, H620-H629.

    Google Scholar 

  • Katona, P. G. andJih, F. (1975) Respiratory sinus arrhythmia: noninvasive measure of parasympathetic cardiac control.J. Appl. Physiol.,39, 801–805.

    Google Scholar 

  • Kay, S. M. andMarple, S. L. (1981) Spectrum analysis: a modern perspective.Proc. IEEE,69, 1380–1418.

    Google Scholar 

  • Kittney, R. I. (1979) A nonlinear model for studying oscillations in the blood pressure control system.J. Biomed. Eng.,1, 89–99.

    Google Scholar 

  • Kitney, R. I., Byrne, S., Edmonds, M. E., Watkins, P. J. andRoberts, V. C. (1982) Heart rate variability in the assessment of autonomic diabetic neuropathy.Automedica,4, 155–167.

    Google Scholar 

  • Lishner, M., Akselrod, S., Mor Avi, V., Oz, O., Divon, M. andRavid, M. (1987) Spectral analysis of heart rate fluctuations. A non-invasive sensitive method for the early diagnosis of autonomic neuropathy in diabetes mellitus.J. Auton. Nerv. Syst,19, 119–125.

    Article  Google Scholar 

  • Lombardi, F., Sandrone, G., Pernpruner, S., Sala, R., Garimoldi, M., Cerutti, S., Baselli, G., Pagani, M. andMalliani, A. (1987) Heart rate variability as an index of sympathovagal interaction after acute myocardial infarction.Am. J. Cardiol.,60, 1239–1245.

    Article  Google Scholar 

  • Niakan, E., Harati, Y. andComstock, J. P. (1986) Diabetic autonomic neuropathy.Metabolism,35, 224–234.

    Article  Google Scholar 

  • Pagani, M., Lombardi, F., Guzzetti, S., Rimoldi, O., Furlan, R., Pizzinelli, P., Sandrone, G., Malfatti, G., Dell'Orto, S., Piccaluga, E., Turiel, M., Baselli, G., Cerutti, S. andMalliani, A. (1986) Power spectral analysis of heart rate and arterial blood pressure variabilities as a marker of sympathovagal interaction in man and conscious dog.Circ. Res.,59, 178–193.

    Google Scholar 

  • Pagani, M., Malfatto, G., Pierini, S., Casati, R., Masu, A. M., Poli, M., Guzzeth, S., Lombardi, F., Cerutti, S. andMalliani, A. (1988) Spectral analysis of the heat rate variability in the assessment of autonomic diabetic neuropathy.J. Auton. Nerv. Syst.,23, 143–153.

    Article  Google Scholar 

  • Rompelman, O., Coenen, A. J. R. M. andKitney, R. I. (1977) Mearuement of heart rate variability: part 1—Comparative study of heart rate variability analysis methods.IEEE Trans.,BME-29, 503–510.

    Google Scholar 

  • Sayers, B. McA. (1973) Analysis of heart rate variability.Ergonomics,16, 17–32.

    Google Scholar 

  • van den Akker, T. J., Koeleman, A. S. M., Hogenhuis, L. A. H. andRompelman, O. (1982) Heart rate variability and blood pressure oscillations in diabetics with autonomic neuropathy: some preliminary results. Int. Workshop on the Analysis of Heart rate Variability and Blood Pressure Fluctuations, Delf.

  • Wiggins, R. A. andRobinson, E. A. (1965) Recursive solution to the multi channel filtering probem.J. Geophys. Res.,70, 1885–1891.

    Article  MathSciNet  Google Scholar 

  • Zetterberg, L. H. (1979) Estimation of parameters for linear difference equation with application to EEG analysis.Math. Biosci.,5, 227.

    Article  MathSciNet  Google Scholar 

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Bianchi, A., Bontempi, B., Cerutti, S. et al. Spectral analysis of heart rate variability signal and respiration in diabetic subjects. Med. Biol. Eng. Comput. 28, 205–211 (1990). https://doi.org/10.1007/BF02442668

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