Abstract
Analysis of heart rate variability (HRV) is a valuable, non-invasive method for quantifying autonomic cardiac control in humans. Frequency-domain analysis of HRV involving myocardial ischaemic episodes should take into account its non-stationary behaviour. The wavelet transform is an alternative tool for the analysis of non-stationary signals. Fourteen patients have been analysed, ranging from 40 to 64 years old and selected from the European Electrocardiographic ST-T Database (ESDB). These records contain 33 ST episodes, according to the notation of the ESDB, with durations of between 40s and 12min. A method for analysing HRV signals using the wavelet transform was applied to obtain a time-scale representation for very low-frequency (VLF), low-frequency (LF) and high-frequency (HF) bands using the orthogonal multiresolution pyramidal algorithm. The design and implementation using fast algorithms included a specially adapted decomposition quadrature mirror filter bank for the frequency bands of interest. Comparing a normality zone against the ischaemic episode in the same record, increases in LF (0.0112±0.0101 against 0.0175±0.0208s2Hz−1; p<0.1) and HF (0.0011±0.0008 against 0.0017±0.0020s2Hz−1; p<0.05) were obtained. The possibility of using these indexes to develop an ischaemic-episode classifier was also tested. Results suggest that wavelet analysis provides useful information for the assessment of dynamic changes and patterns of HRV during myocardial ischaemia.
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References
Barber, M. J., Mueller, T. M., Henry, D. P., Felten, S. Y., andZipes, D. P. (1983): ‘Transmural myocardial infarction in the dog produces sympathectomy in noninfarcted myocardium’,Circulation,67, pp. 787–796
Barber, M. J., Mueller, T. M., Davies, B. G., Gill, R. M., andZipes, D. (1985): ‘Interruption of sympathetic and vagal-mediated afferent responses by transmural myocardial infarction’,Circulation,72, pp. 623–631
Berger, R. D., Akselrod, S., Gordon, D., andCohen, J. (1986): ‘An efficient algorithm for spectral analysis of heart rate variability’,IEEE Trans. Biomed. Eng.,33, pp. 900–904
Berger, R. D., Saul, J. P., andCohen, R. J. (1986): ‘An efficient algorithm for spectral analysis of heart rate variability’,IEEE Trans. Biomed. Eng.,33, pp. 900–904
Bianchi, A. M., Mainardi, L., Petrucci, E., Signorini, M. G., Mainardi, M., andCerutti, S. (1993): ‘Time-variant power spectrum analysis for the detection of transient episodes in HRV signal’,IEEE Trans. Biomed. Eng.,40, pp. 136–144
Cerutti, S., Mainardi, L., Bianchi, A., Signorini, M. G., andBertinelli, M. (1992): ‘Time-variant autoregressive spectral estimation in acute ischemic episodes’,Comput. Cardiol., pp. 315–318
Chui, C. (1992): ‘An introduction to wavelets’ (Academic Press, 1992)
Gamero, L., Risk, M., Sobh, J., Ramirez, A., andSaul, J. P. (1996): ‘Heart rate variability analysis using wavelet transform’,Comput. Cardiol.,23, pp. 177–180
Herre, J. M., Westein, L., Lin, Y. L., Mills, A. S., Dae, M., andThames, M. D. (1988): ‘Effect of transmural versus nontransmural myocardial infarction on inducibility of ventricular arrhythmias during sympathetic stimulation in dogs’,J. Am. Coll. Cardiol.,11, pp. 414–421
Inoue, H., andZipes, D. P. (1987): ‘Increased afferent vagal responses produced by epicardial application of nicotine on the canine posterior left ventricle’,Am. Heart J.,114, pp. 757–764
Jager, F., Moody, G. B., Pavlic, B., Blazina, I., Zupic, I., andMark, R. G. (1996): ‘Characterization of temporal patterns of transient ischemic ST change episodes during ambulatory ECG monitoring’,Comput. Cardiol., pp. 681–684
Johnson, R. A., andBattacharyva, G. K. (1992): ‘Statistical principles and methods’ (John Wiley & Sons, 1992)
Malik, M., Farrell, T., Cripps, T., andCamm, A. J. (1989): ‘Prognosis value of heart rate variability after myocardial infarction. A comparison of different data-processing methods’,Med. Biol. Eng. Comput.,27, pp. 603–611
Malik, M., andCamm, A. J. (1996): ‘Heart rate variability’ (Futura Publishing Company, Armonk, New York, 1996)
Mallat, S. G. (1989): ‘A theory of multiresolution of signal decomposition: the wavelet representation’IEEE Trans. Patt. Anal. Mach. Intell.,7, pp. 674–693
Marciano, F., Bonaduce, D., Petretta, M., Valva, G., andMigaux, M. L. (1995): ‘Spectral behavior of heart rate variability in acute ischemic episodes’,Comput. Cardiol., pp. 111–114
Miyazaki, T., andZipes, D. P. (1990): ‘Presynaptic modulation of efferent sympathetic and vagal neurotransmission in the canine heart by hypoxia, high K+, low pH and adenosine: Possible relevance to ischemia-induced denervation’,Circ. Res.,66, pp. 289–301
Pichot, V., Gaspoz, J. M., Molliex, S., Antoniadis, A., Busso, T., Roche, F., Costes, F., Quintin, L., Lacour, J. R., andBarthelemy, J. C. (1999): ‘Wavelet transform to quantify heart rate variability and to assess its instantaneous changes’,J. Appl. Physiol.,86, pp. 1081–1091
Pola, A., Macerata, A., Emdin, M., andMarchesi, C. (1996): ‘Estimation of the power spectral density in nonstationary cardiovascular time series: assessing the role of the time-frequency representations (TFR)’,IEEE Trans. Biomed. Eng.,43, pp. 46–59
Rioul, O., andVetterli, M. (1991): ‘Wavelets and signal processing’,IEEE Signal Process. Mag., pp. 14–38
Taddei, A., Biagini, A., Distante, G., Emdin, M., Mazzei, M. G., Pisani, P., Roggero, N., Varanini, M., Mark, R. G., Moody, G. B., Braakson, L., Zeelemberg, C., andMarchesi, C. (1990): ‘The European ST-T database: development, distribution and use’,Comput. Cardiol., pp. 177–180
Taddei, A., Constantino, G., Silipo, R., Emdin, M., andMarchesi, C. (1995): ‘A system for the detection of ischemic episodes in ambulatory ECG’,Comput. Cardiol., pp. 705–708
Task Force of European Society of Cardiology and North American Society of Pacing and Electrophysiology (1996): ‘Heart rate variability: standards of measurement, physiological interpretation and clinical use’,Circulation,93, pp. 1043–1065
Thames, M. D., Klopfenstein, H. S., Abboud, F. M., Mark, A. L., andWalker, J. L. (1978): ‘Preferential distribution of inhibitory cardiac receptors with vagal afferents to the inferoposterior wall of the left ventricle activated during coronary occlusion in the 1dog’,Circ. Res.,43, pp. 512–519
Thames, M. D., Dibner-Dunlap, M. E., andMinisi, A. (1993): ‘Cardiovascular reflex during myocardial ischemia’, in ‘Cardiovascular reflex control in health and disease’ (Saunders, 1993)
Vila, J., Barro, S., Presedo, J., Ruiz, R., andPalacios, F. (1992): ‘Analysis of heart rate variability with evenly spaced time values’. 14th Annual International Conference of IEEE-EMBS,2, pp. 575–576
Vila, J., Palacios, F., Presedo, J., Fernández-Delgado, M., Feliz, P., andBarro, S. (1997): ‘Time frequency analysis of heart rate variability: an improved method for monitoring and diagnosing myocardial ischemia’,IEEE Eng. Med. Biol. Mag.,16, pp. 119–126
Vila, J. (1997): ‘Variability analysis of physiological signals. Integration on an intelligent monitoring system’, PhD thesis. Universidad de Santiago de Compostela, Spain
Webb, S. W., Adgey, A. A. J., andPantridge, J. F. (1972): ‘Autonomic disturbance at onset of acute myocardial ischemia’,Br. Med. J.,2, pp. 89–92
Wiklund, U., Akay, M., andNiklasson, U. (1997): ‘Short-term analysis of heart-rate variability by adapted wavelet transforms’,IEEE Eng. Med. Biol. Mag.,16, pp. 113–118, 138
Yang, F., andLiao, W. (1997): ‘Modeling and decomposition of HRV signals with wavelet transforms’,IEEE Eng. Med. Biol. Mag.,16, pp. 17–22
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Gamero, L.G., Vila, J. & Palacios, F. Wavelet transform analysis of heart rate variability during myocardial ischaemia. Med. Biol. Eng. Comput. 40, 72–78 (2002). https://doi.org/10.1007/BF02347698
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DOI: https://doi.org/10.1007/BF02347698