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Comparison of heart rate variability analysis methods in patients with Parkinson's disease

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Abstract

The aim of the present study was to evaluate different analysis methods for revealing heart rate variability (HRV) differences between untreated patients with Parkinson's disease and healthy controls. HRV in standard cardiovascular reflex tests and during a 10 min rest period were measured by time-and frequency-domain and geometrical and non-linear analysis methods. Both frequency-and time-domain measures revealed abnormal HRV in the patients, whereas non-linear and geometrical measures did not. The absolute high-frequency spectral power of HRV was the strongest independent predictor to separate the patients from the controls (p=0.001), when the main time-domain and absolute frequency-domain measures were compared with each other. When the corresponding normalised spectral units, instead of the absolute units, were used in the comparison, the two best single measures for separating the groups were the 30/15 ratio of the tilting test (p=0.003) and the max/min ratio during deep breathing (p=0.024). When the correlations between the different measures were estimated, the time-domain measures, fractal dimension and absolute spectral powers correlated with each other. The frequencyand time-domain analysis techniques of stationary short-term HRV recordings revealed significant differences in cardiovascular regulation between untreated patients with Parkinson's disease and the controls. This confirms cardiovascular regulation failure before treatment in the early stages of Parkinson's disease. The HRV spectral powers, in absolute units, were the most effective single parameters in segregating the two groups, emphasising the role of spectral analysis in the evaluation of HRV in Parkinson's disease.

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References

  • Akselrod, S., Barak, Y., Ben-Dov, Y., Keselbrener, L. andBaharav, A. (2001). ‘Estimation of autonomic response based on individually determined time axis’,Auton. Neurosci.,90, pp. 13–23

    Google Scholar 

  • Awerbuch, G. I., andSandyk, R. (1992). ‘Autonomic functions in the early stages of Parkinson's disease’,Int. J. Neurosci.,64, pp. 7–14.

    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. Biomed. Comput. 20, pp. 51–70

    Article  Google Scholar 

  • Bernardi, L., Bianchini, B., Spadacini, G., Leuzzi, S., Valle, F., Marchesi, E., Passino, C., Calciati, A., Viganó, M., Rinaldini, M., Martinelli, L., Finardi, G., andSleight, P. (1995). ‘Demonstrable cardiac reinnervation after human heart transplantation by carotid baroreflex modulation of RR interval’,Circulation,92, pp. 2895–2903

    Google Scholar 

  • Bianchi, A. M., Bontempi, B., Cerutti, S., Gianoglio, P., Comi, G. andNatali Sora, M. G. (1990): ‘Spectral analysis of heart rate variability signal and respiration in diabetic subjects’,Med. Biol. Eng. Comput.,28, pp. 205–211

    Google Scholar 

  • Bigger, J. T., Steinman, R. C., Rolnitzky, L. M., Fleiss, J. L., Albrecht, P., Cohen, R. J. (1996). ‘Power law behaviour of R-R-interval variability in healthy middle-aged persons, patients with recent acute myocardial infarction, and patients with heart transplants’,Circulation,93, pp. 2142–2151

    Google Scholar 

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

    Google Scholar 

  • Camerlingo, M., Aillon, C., Bottachi, E., Gambaro, P., D'Alessandro, G., Franceschi, M., Devoti, G., andMamoli, A. (1987). ‘Parasympathetic assessment in Parkinson's disease’,Adv. Neurl.,45, pp. 267–269

    Google Scholar 

  • Cloarec-Blanchard, L., Girard, A., Houhou, S., Grunfeld, J. P., andElghozi, J. L. (1992). ‘Spectral analysis of short-term blood pressure and heart rate variability in uremic patients’,Kidney Int. 37, pp. S14-S18

    Google Scholar 

  • Daniel, S. E., andLees, A. J. (1993): ‘Parkinson's disease society brain bank, London: overview and research’,J. Neural Transmiss,39, pp. S165-S172

    Google Scholar 

  • Den Hartok Jager, W. A., andBethlem, J. (1960): ‘The distribution of Lewy bodies in the central and autonomic nervous system in idiopathic paralysis agitans’,J. Neurol. Neurosurg. Psychiatry,23, pp. 283–290

    Google Scholar 

  • Donchin, Y., Feld, J. M., andPorges, S. W. (1985): ‘Respiratory sinus arrhythmia during recovery from isoflurane-nitrous oxide anesthesia’.Anesthesia & Analgesia,64, pp. 811–815

    Google Scholar 

  • Ewing, D. J., Neilson, J. M. M., andTravis, P. (1984): ‘New method for assessing cardiac parasympathetic activity using 24 hour electrocardiograms’,Brit. Heart. J.,52, pp. 396–402

    Google Scholar 

  • Ewing, D. J. (1988): ‘Recent advances in the non-invasive investigation of diabetic autonomic neuropathy’, inBannister R (Ed.): ‘Autonomic failure. A textbook of clinical disorder of the autonomic nervous system’ (Oxford University Press, NY, 1988), pp. 667–689

    Google Scholar 

  • Freeman, R., Saul, J. P., Roberts, M. S., andBerger, R. D. (1991): ‘Spectral analysis of heart rate in diabetic autonomic neuropathy. A comparison with standard tests of autonomic function’,Arch. Neurol.,48, pp. 185–190

    Google Scholar 

  • Goldberger, A. L. (1996): ‘Non-linear dynamics for clinicians: chaos theory, fractals, and the complexity at the bedside’,The Lancet,347, pp. 1312–1314

    Article  Google Scholar 

  • Hayano, J., Sakakibara, Y., Yamada, A., Yamada, M., Mukai, S., Fuhinami, T., Yokoyama, K., Watanabe, Y., andTakata, K. (1991): ‘Accuracy of assessment of cardiac heart rate variability in normal subjects’,Am. J. Cardiol.,67, pp. 199–204

    Article  Google Scholar 

  • Ho, K. K. L., Moody, G. B., Peng, C.-K., Mietus, J. E., Larson, M. G., Levy, D., Goldberger, A. L. (1997): ‘Predicting survival in heart failure case and control subjects by use of fully automated methods for deriving nonlinear and conventional indices of heart rate dynamics’,Circulation,96, pp. 842–848

    Google Scholar 

  • Holmberg, B., Kallio, M., Johnels, B., andElam, M. (2001): ‘Cardiovascular reflex testing contributes to clinical evaluation and differential diagnosis of Parkinsonian syndromes’,Movement Disord.,16, pp. 217–225

    Article  Google Scholar 

  • Hoyer, D., Kaplan, D., Palus, M., Pompe, B., andSeidel, H. (1998): ‘New systems-analytical approaches to nonlinear coordination’,IEEE Eng. Med. Biol.,17, pp. 58–61

    Google Scholar 

  • Huikuri, H. V., Seppäncen, T., Koistinen, M. J., Airaksinen, K. E. J., Ikäheimo, M. J., Castellanos, A., andMyerburg, R. J. (1996): ‘Abnormalities in beat-to-beat dynamics of heart rate before the spontaneous onset of life-threatening ventricular tachyarrhytmias in patients with prior myocardial infarction’.Circulation,93, pp. 1836–1844

    Google Scholar 

  • Huikuri, II, V., Mäkikallio, T. H., Airaksinen, K. E. J., Seppänen, T. Puukka, P., Räihä, I. J., andSourander, L. B. (1998): ‘Powerlaw relationship of heart rate variability as a predictor of mortality in the elderly’,Circulation,97, pp. 2031–2036

    Google Scholar 

  • Jellinger, K. (1987): ‘The pathology of Parkinsonism’, inMarsden C. D., andFahn, S. (Eds) ‘Movement disoder 2’ (Butterworths, London, 1987), pp. 124–165

    Google Scholar 

  • Jellinger, K. A. (1991): ‘Pathology of Parkinson's disease. Changes other than the nigrostriatal pathway’,Mol Chem Neuropathol,14, pp. 153–197

    Google Scholar 

  • Kallio, M., Haapaniemi, T., Turkka, J., Suominen, K., Tolonen, U., Sotaniemi, K. A., Heikkilä, V.-P., andMyllylä, V. V. (2000): ‘Heart rate variability in patients with untreated Parkinson's disease’,Eur. J. Neurol.,7, pp. 667–672

    Article  Google Scholar 

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

    Google Scholar 

  • Kimber, J., Mathias, C. J., Lees, A. J., Bleasdale-Barr, K., Chang, H. S., Churchyard, A., andWatson, L. (2000): ‘Physiological, pharmacological and neurohormonal assessment of autonomic function in progressive supranuclear palsy’,Brain,123, pp. 1422–1430

    Article  Google Scholar 

  • Linden, D., andDiehl, R. R. (1996): ‘Comparison of standard autonomic tests and power spectral analysis in normal adults’,Muscle Nerve,19, pp. 556–562

    Google Scholar 

  • Malliani, A., Pagani, M., Lombardi, F., Furlan, R., Guzzetti, S. andCerutti, S. (1991): ‘Spectral analysis to assess increased sympathetic tone in arterial hypertension’,Hypertension,17, pp. SIII36-SIII42

    Google Scholar 

  • Mandelbrot, B. B. (1982): ‘The fractal geometry of nature’ (WH Freeman and Company, New York, 1982)

    Google Scholar 

  • Myers, G. A., Martin, G. J., Magid, M. N., Barnett, P. S., Schaad, J. W., Weiss, J. S., Lesch, M., andSinger, D. H. (1986): ‘Power spectral analysis of heart rate variability in sudden death: comparison to other methods’,IEEE Trans. Biomed. Eng.,33, pp. 1149–1156

    Google Scholar 

  • Myllylä, V. V., Korpelainen, J. T., Tolonen, U., Havanka, H., andSaari, A. (2000): ‘Neuropathology and cardiovascular regulation’, inTer Horst, G. J. (Ed.): ‘The nervous system and the heart’ (Human Press Inc. Totowa, New Jersey, 2000), pp. 181–237

    Google Scholar 

  • Peleg, S., Naor, J., Hartley, R., andAvnir, D. (1984): ‘Multiple resolution texture and classification’,IEEE Trans. Pattern Anal,4, pp. 518–523

    Google Scholar 

  • Peng, C. K., Havlin, S., Stanley, H. E., Goldberger, A. L. (1995): ‘Quantification of scaling exponents and crossover phenomenon in nonstationary heart beat series’,Chaos,5, pp. 82–87

    Article  Google Scholar 

  • Pincus, S. M., andGoldberger, A. L. (1994): ‘Physiologic time-series analysis: what does regularity quantify?’,Am. J. Physiol.,226, pp. H1643-H1656

    Google Scholar 

  • Pincus, S. M. (1991): ‘Approximate entropy as a measure of system complexity’Proc. Natl. Acad. Sci. USA,88, pp. 2297–2301

    MATH  MathSciNet  Google Scholar 

  • Porges, S. W. (1985): ‘Method and apparatus for evaluating rhytmic oscillations in a periodic physiological response systems’. United States Patent 4,510,9444, April 16

  • Saul, J. P., Albrecht, P., Berger, R. D., andCohen, R. J. (1987): ‘Analysis of long-term heart rate variability: methods, 1/f scaling and implications’, in ‘Computers in cardiology’ (IEEE Computer Society Press, Silver Spring, MD, 1987), pp. 419–422

    Google Scholar 

  • Šega, S., Jager, F., andKiauta, T. (1993): ‘A comparison of cardiovascular reflex tests and spectral analysis of heart rate variability in healthy subjects’,Clin. Auton. Res.,3, pp. 175–182

    Google Scholar 

  • Suominen, K. (1997): ‘Design and implementation of a PC-based data acquisition system for measuring ECG and respiratory signals’,Int. J. Clin. Monit. Com.,14, pp. 225–230

    Google Scholar 

  • Task Force European Society of Cardiology andNorth American Society of Pacing & Electrophysiology (1996): ‘Heart rate variability. Standards of measurement, physiological interpretation, and clinical use’,Circulation,93, pp. 1043–1065

    Google Scholar 

  • Turkka, J., Suominen, K., Tolonen, U., Sotaniemi, K., andMyllylä, V. (1997): ‘Selegiline diminishes cardiovascular autonomic responses in Parkinson's disease’,Neurology,48, pp. 662–667

    Google Scholar 

  • Zetterberg, L. H. (1969): ‘Estimation parameters for a linear difference equation with application to EEG analysis’,Math. Biosci.,5, pp. 227–275

    Article  MATH  MathSciNet  Google Scholar 

  • Zwiener, U., Hoyer, D., Lüthke, B., Schmidt, K., andBauer, R. (1996): ‘Relations between parameters of spectral power densities and deterministic chaos of heart-rate variability’,J. Auton. Nerv. Syst.,57, pp. 132–135.

    Article  Google Scholar 

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Kallio, M., Suominen, K., Bianchi, A.M. et al. Comparison of heart rate variability analysis methods in patients with Parkinson's disease. Med. Biol. Eng. Comput. 40, 408–414 (2002). https://doi.org/10.1007/BF02345073

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