Heart rate variability indices for very short-term (30 beat) analysis. Part 1: Survey and toolbox

Journal of Clinical Monitoring and Computing

Volumn 27, Issue 5, 2013, Pages 569-576

  Smith, Anne Louise ^a,b   Owen, Harry ^c   Reynolds, Karen J ^a  

^a Flinders University   (Australia)

^b FLINDERS MEDICAL CENTRE   (Australia)

^c FLINDERS UNIVERSITY   (Australia)

Author keywords

Autonomic nervous system (ANS) modulation; Biomedical signal processing; Heart rate variability (HRV); Software algorithms

Indexed keywords

AUTONOMIC NERVOUS SYSTEM; AUTONOMIC NERVOUS SYSTEM ACTIVITIES; BIOMEDICAL SIGNAL PROCESSING; HEART RATE VARIABILITY; RESPIRATORY SINUS ARRHYTHMIA; SOFTWARE ALGORITHMS; STEADY-STATE CONDITION; SYMPATHETIC ACTIVITIES;

HEART; SIGNAL PROCESSING; SURVEYS;

TIME DOMAIN ANALYSIS;

ARTICLE; AUTONOMIC NERVOUS SYSTEM FUNCTION; COMPUTER PROGRAM; FREQUENCY ANALYSIS; HEART BEAT; HEART RATE; HEART RATE VARIABILITY; MATHEMATICAL ANALYSIS; PRIORITY JOURNAL; SINUS ARRHYTHMIA; TIME;

ALGORITHMS; DATABASES, FACTUAL; DIAGNOSIS, COMPUTER-ASSISTED; ELECTROCARDIOGRAPHY; HEART RATE; HUMANS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SOFTWARE;

EID: 84885018059     PISSN: 13871307     EISSN: 15732614     Source Type: Journal    
DOI: 10.1007/s10877-013-9471-4     Document Type: Article

References (82)

1. Goldberger JJ, Le FK, Lahiri M, Kannankeril PJ, Ng J, Kadish AH. Assessment of parasympathetic reactivation after exercise. Am J Physiol Heart Circ Physiol. 2006;290(6):H2446-52.
2. Vettorello M, Colombo R, De Grandis CE, Costantini E, Raimondi F. Effect of fentanyl on heart rate variability during spontaneous and paced breathing in healthy volunteers. Acta Anaesthesiol Scand. 2008;52(8):1064-70. doi: 10.1111/j.1399-6576.2008.01713.x.
3. Schachinger H, Muller BU, Strobel W, Drewe J, Ritz R. Effect of midazolam on transfer function between beat-to-beat arterial pressure and inter-beat interval length. Br J Anaesth. 2000;84(3):316-22.
4. Alcalay M, Izraeli S, Wallach-Kapon R, Tochner Z, Benjamini Y, Akselrod S. Paradoxical pharmacodynamic effect of atropine on parasympathetic control: a study by spectral analysis of heart rate fluctuations. Clin Pharmacol Ther. 1992;52(5):518-27.
5. Task Force of European Society of Cardiology. Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Eur Heart J. 1996;17(3):354-81.
6. Raetz SL, Richard CA, Garfinkel A, Harper RM. Dynamic characteristics of cardiac R-R intervals during sleep and waking states. Sleep. 1991;14(6):526-33.
7. Kamen PW, Tonkin AM. Application of the Poincaré plot to heart rate variability: a new measure of functional status in heart failure. Aust N Z J Med. 1995;25(1):18-26.
8. Toichi M, Sugiura T, Murai T, Sengoku A. A new method of assessing cardiac autonomic function and its comparison with spectral analysis and coefficient of variation of R-R interval. J Auton Nerv Syst. 1997;62(1-2):79-84.
9. Otzenberger H, Gronfier C, Simon C, Charloux A, Ehrhart J, Piquard F, Brandenberger G. Dynamic heart rate variability: a tool for exploring sympathovagal balance continuously during sleep in men. Am J Physiol. 1998;275(3 Pt 2):H946-50.
10. Bergfeldt L, Haga Y. Power spectral and Poincaré plot characteristics in sinus node dysfunction. J Appl Physiol. 2003;94(6):2217-24.
11. Boardman A, Schlindwein FS, Thakor NV, Kimura T, Geocadin RG. Detection of asphyxia using heart rate variability. Med Biol Eng Comput. 2002;40(6):618-24.
12. Goldberger AL, Amaral LA, Glass L, Hausdorff JM, Ivanov PC, Mark RG, Mietus JE, Moody GB, Peng CK, Stanley HE. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation. 2000;101(23):E215-20.
13. Tulppo MP, Makikallio TH, Takala TE, Seppanen T, Huikuri HV. Quantitative beat-to-beat analysis of heart rate dynamics during exercise. Am J Physiol. 1996;271(1 Pt 2):H244-52.
14. Smith AL, Reynolds KJ, Owen H. Correlated Poincaré indices for measuring heart rate variability. Australas Phys Eng Sci Med. 2007;30(4):336-41.
15. Voss A, Schulz S, Schroeder R, Baumert M, Caminal P. Methods derived from nonlinear dynamics for analysing heart rate variability. Philos Transact A Math Phys Eng Sci. 2009;367(1887):277-96. doi: 10.1098/rsta.2008.0232.
16. Katona PG, Jih F. Respiratory sinus arrhythmia: noninvasive measure of parasympathetic cardiac control. J Appl Physiol. 1975;39(5):801-5.
17. Seals DR, Chase PB. Influence of physical training on heart rate variability and baroreflex circulatory control. J Appl Physiol. 1989;66(4):1886-95.
18. Porges SW. Method and apparatus for evaluating rhythmic oscillations in aperiodic physiological response systems. United States Patent 4510944. 1985.
19. Cohen ME, Hudson DL, Deedwania PC. Applying continuous chaotic modeling to cardiac signal analysis. IEEE Eng Med Biol Mag. 1996;15(5):97-102.
20. Schmidt G, Malik M, Barthel P, Schneider R, Ulm K, Rolnitzky L, Camm AJ, Bigger JT Jr, Schomig A. Heart-rate turbulence after ventricular premature beats as a predictor of mortality after acute myocardial infarction. Lancet. 1999;353(9162):1390-6.
21. Watanabe MA, Alford M, Schneider R, Bauer A, Barthel P, Stein PK, Schmidt G. Demonstration of circadian rhythm in heart rate turbulence using novel application of correlator functions. Heart Rhythm. 2007;4(3):292-300. doi: 10.1016/j.hrthm.2006.11.016.
22. Brennan M, Palaniswami M, Kamen P. Do existing measures of poincare plot geometry reflect nonlinear features of heart rate variability? IEEE Trans Biomed Eng. 2001;48(11):1342-7.
23. Arif M, Aziz W. Application of threshold-based acceleration change index (TACI) in heart rate variability analysis. Physiol Meas. 2005;26(5):653-65.
24. Laguna P, Moody GB, Mark RG. Power spectral density of unevenly sampled data by least-square analysis: performance and application to heart rate signals. IEEE Trans Biomed Eng. 1998;45(6):698-715.
25. Moody GB. Spectral analysis of heart rate without resampling. Paper presented at the Computers in Cardiology. Proc., London, UK, 1993. p. 5-8.
26. Chang KL, Monahan KJ, Griffin MP, Lake D, Moorman JR. Comparison and clinical application of frequency domain methods in analysis of neonatal heart rate time series. Ann Biomed Eng. 2001;29(9):764-74.
27. Clifford GD. Signal processing methods for heart rate variability. PhD Thesis, Oxford: Oxford University; 2002.
28. Savransky D. Lomb (Lomb-Scargle) periodogram. The MathWorks. http://www.mathworks.com.au/matlabcentral/fileexchange/20004-lomb-lomb-scargle- periodogram (2008). Accessed 26 Aug. 2010.
29. Press WH, Rybicki GB. Fast algorithm for spectral analysis of unevenly sampled data. Astrophys J. 1989;338:277-80.
30. Hamilton RM, McKechnie PS, Macfarlane PW. Can cardiac vagal tone be estimated from the 10-second ECG? Int J Cardiol. 2004;95(1):109-15.
31. Thong T, Li K, McNames J, Aboy M, Goldstein B. Accuracy of ultra-short heart rate variability measures. Paper presented at the 25th Annu. Int. Conf. IEEE Engineering in Medicine and Biology Society. Cancun, Mexico: 2003. p 17-21.
32. Fouad FM, Tarazi RC, Ferrario CM, Fighaly S, Alicandri C. Assessment of parasympathetic control of heart rate by a noninvasive method. Am J Physiol. 1984;246(6 Pt 2):H838-42.
33. Sosnowski M, Petelenz T, Leski J. Return maps: a non-linear method for evaluation of respiratory sinus arrhythmia. Paper presented at the Computers in Cardiology 1994. Bethesda, MD: 1994 p. 25-28.
34. Gaitan-Gonzalez MJ, Carrasco-Sosa S, Gonzalez-Camarena R, Yanez-Suarez O (2005) Non-linear relationship between heart period and root mean square of successive differences during ramp exercise and early recovery. Paper presented at the Computers in Cardiology 2005, Lyon, Sep. 25-28.
35. Desok K, Yunhwan S, Sook-hyun K, Suntae J.Short term analysis of long term patterns of heart rate variability in subjects under mental stress. Paper presented at the Int. Conf. BioMedical Engineering and Informatics (BMEI 2008). Saanya, China; 2008. p. 27-30.
36. Julu PO-O, Little CJ. Apparatus and method for measuring cardiac vagal tone. United States Patent 6442420. 2002.
37. Little CJ, Julu PO, Hansen S, Reid SW. Real-time measurement of cardiac vagal tone in conscious dogs. Am J Physiol. 1999;276(2 Pt 2):H758-65.
38. van Bemmel T, Vinkers DJ, Macfarlane PW, Gussekloo J, Westendorp RG. Markers of autonomic tone on a standard ECG are predictive of mortality in old age. Int J Cardiol. 2006;107(1):36-41.
39. Halliwill JR, Billman GE. Effect of general anesthesia on cardiac vagal tone. Am J Physiol. 1992;262(6 Pt 2):H1719-24.
40. Porges SW. Vagal mediation of respiratory sinus arrhythmia. Implications for drug delivery. Ann N Y Acad Sci. 1991;618(1):57-66.
41. Kristiansen NK, Fleischer J, Jensen MS, Andersen KS, Nygaard H. Design and evaluation of a handheld impedance plethysmograph for measuring heart rate variability. Med Biol Eng Comput. 2005;43(4):516-21.
42. Ejskjaer N, Fleischer J, Jacobsen PE, Poulsen PL, Nygaard H. A pocket-size device to detect autonomic neuropathy. J Diabetes Sci Technol. 2008;2(4):692-6.
43. Sandercock GR, Brodie DA. The use of heart rate variability measures to assess autonomic control during exercise. Scand J Med Sci Sports. 2006;16(5):302-13. doi: 10.1111/j.1600-0838.2006.00556.x.
44. Malliani A, Pagani M, Montano N, Mela GS. Sympathovagal balance: a reappraisal [Letter]. Circulation. 1998;98(23):2640-3.
45. Salahuddin L, Cho J, Jeong MG, Kim D. Ultra short term analysis of heart rate variability for monitoring mental stress in mobile settings. Paper presented at the 29th Annu. Int. Conf. IEEE Engineering in Medicine and Biology Society. Lyon; 2007. p. 23-26.
46. Salahuddin L, Jeong MG, Kim D Ultra short term analysis of heart rate variability using normal sinus rhythm and atrial fibrillation EGG data. Paper presented at the 9th Int. Conf. e-Health Networking, Application and Services. Taipei; 2007. 19-22.
47. Balocchi R, Cantini F, Varanini M, Raimondi G, Legramante JM, Macerata A. Revisiting the potential of time-domain indexes in short-term HRV analysis. Biomed Tech (Berl). 2006;51(4):190-3.
48. Goldberger JJ. Sympathovagal balance: how should we measure it? Am J Physiol. 1999;276(4 Pt 2):H1273-80.
49. Griffin MP, Moorman JR. Toward the early diagnosis of neonatal sepsis and sepsis-like illness using novel heart rate analysis. Pediatrics. 2001;107(1):97-104.
50. Schirdewan A, Meyerfeldt U, Wessel N, Bondke HJ, Schreiber P, Sadowski R, Kamke W, Wiedemann M. Heart rate dynamics before the onset of ventricular tachyarrhythmias: Results of the cardioverter defibrillator registry MARITA. J Am College of Cardiol. 2004;43 (5, Supplement 1): A125-A126.
51. Wessel N, Malberg H, Bauernschmitt R, Kurths J. Nonlinear methods of cardiovascular physics and their clinical applicability. Int J Bifurc Chaos. 2007;17(10):3325-71. doi: 10.1142/S0218127407019093.
52. Voss A, Kurths J, Kleiner HJ, Witt A, Wessel N, Saparin P, Osterziel KJ, Schurath R, Dietz R. The application of methods of non-linear dynamics for the improved and predictive recognition of patients threatened by sudden cardiac death. Cardiovasc Res. 1996;31(3):419-33.
53. Persson A, Solders G. R-R variations, a test of autonomic dysfunction. Acta Neurol Scand. 1983;67(5):285-93.
54. Persson A, Solders G. R-R variations in Guillain-Barré syndrome: a test of autonomic dysfunction. Acta Neurol Scand. 1983;67(5):294-300.
55. Bergfeldt BL, Edhag KO, Solders G, Vallin HO. Analysis of sinus cycle variation: a new method for evaluation of suspected sinus node dysfunction. Am Heart J. 1987;114(2):321-7.
56. Ribeiro AL, Cassini P, Peixoto SV, Lima-Costa MF. Vagal impairment in elderly Chagas disease patients: a population-based study (The Bambuí Study). Int J Cardiol. 2011;147(3):359-65. doi: 10.1016/j.ijcard.2009.10.002.
57. Macfarlane PW, Norrie J. The value of the electrocardiogram in risk assessment in primary prevention: experience from the West of Scotland Coronary Prevention Study. J Electrocardiol. 2007;40(1):101-9. doi: 10.1016/j. jelectrocard.2006.05.003.
58. de Bruyne MC, Kors JA, Hoes AW, Klootwijk P, Dekker JM, Hofman A, van Bemmel JH, Grobbee DE. Both decreased and increased heart rate variability on the standard 10-second electrocardiogram predict cardiac mortality in the elderly: the Rotterdam Study. Am J Epidemiol. 1999;150(12):1282-8.
59. Thakre TP, Smith ML. Loss of lag-response curvilinearity of indices of heart rate variability in congestive heart failure. BMC Cardiovasc Disord. 2006;6(1):27. doi: 10.1186/1471-2261-6-27.
60. Tateno K, Glass L. Automatic detection of atrial fibrillation using the coefficient of variation and density histograms of RR and deltaRR intervals. Med Biol Eng Comput. 2001;39(6):664-71.
61. Copie X, Le Heuzey JY, Iliou MC, Khouri R, Lavergne T, Pousset F, Guize L. Correlation between time-domain measures of heart rate variability and scatterplots in postinfarction patients. Pacing Clin Electrophysiol. 1996;19(3):342-7.
62. Voss A, Hnatkova K, Wessel N, Kurths J, Sander A, Schirdewan A, Camm AJ, Malik M. Multiparametric analysis of heart rate variability used for risk stratification among survivors of acute myocardial infarction. Pacing Clin Electrophysiol. 1998;21(1 Pt 2):186-92.
63. Wessel N, Malberg H, Bauernschmitt R, Schirdewan A, Kurths J. Nonlinear additive autoregressive model-based analysis of short-term heart rate variability. Med Biol Eng Comput. 2006;44(4):321-30. doi: 10.1007/s11517-006- 0038-0.
64. Hyndman BW, Zeelenberg C (1993) Spectral analysis of heart rate variability revisited: comparison of the methods. Paper presented at the Computers in Cardiology. Proc., London; 1993. p. 5-8.
65. Carrasco S, Gaitán MJ, González R, Yánez O. Correlation among Poincaré plot indexes and time and frequency domain measures of heart rate variability. J Med Eng Technol. 2001;25(6):240-8.
66. Smith AL, Reynolds KJ, Owen H. Heart Rate Variability Indices for Very Short-term (30 beat) Analysis. Part 2: Validation. J Clin Monit Comput Submitted for publication. 2013.
67. Antelmi I, de Paula RS, Shinzato AR, Peres CA, Mansur AJ, Grupi CJ. Influence of age, gender, body mass index, and functional capacity on heart rate variability in a cohort of subjects without heart disease. Am J Cardiol. 2004;93(3):381-5.
68. Mietus JE, Peng CK, Henry I, Goldsmith RL, Goldberger AL. The pNNx files: re-examining a widely used heart rate variability measure. Heart. 2002;88(4):378-80.
69. Ewing DJ, Neilson JM, Travis P. New method for assessing cardiac parasympathetic activity using 24 hour electrocardiograms. Br Heart J. 1984;52(4):396-402.
70. Eckoldt K. Procedure and results of the quantitative automatic analysis of the heart frequency and their spontaneous variability. Dtsch Gesundheitswes. 1984;39:856-63.
71. Moser M, Lehofer M, Sedminek A, Lux M, Zapotoczky HG, Kenner T, Noordergraaf A. Heart rate variability as a prognostic tool in cardiology. A contribution to the problem from a theoretical point of view. Circulation. 1994;90(2):1078-82.
72. Eckoldt K. Problems and results of the analysis of sinus rhythm. Psychiatrie, Neurologie und medizinische Psychologie. 1990;43:53-63.
73. Guzik P, Piskorski J, Krauze T, Wykretowicz A, Wysocki H. Heart rate asymmetry by Poincaré plots of RR intervals. Biomed Tech (Berl). 2006;51(4):272-5.
74. Piskorski J, Guzik P. Geometry of the Poincaré plot of RR intervals and its asymmetry in healthy adults. Physiol Meas. 2007;28(3):287-300.
75. Nikolopoulos S, Alexandridi A, Nikolakeas S, Manis G. Experimental analysis of heart rate variability of long-recording electrocardiograms in normal subjects and patients with coronary artery disease and normal left ventricular function. J Biomed Inform. 2003;36(3):202-17.
76. Kovatchev BP, Farhy LS, Cao H, Griffin MP, Lake DE, Moorman JR. Sample asymmetry analysis of heart rate characteristics with application to neonatal sepsis and systemic inflammatory response syndrome. Pediatr Res. 2003;54(6):892-8.
77. Contreras P, Canetti R, Migliaro ER. Correlations between frequency-domain HRV indices and lagged Poincaré plot width in healthy and diabetic subjects. Physiol Meas. 2007;28(1):85-94.
78. Hirose M, Imai H, Ohmori M, Matsumoto Y, Amaya F, Hosokawa T, Tanaka Y. Heart rate variability during chemical thoracic sympathectomy. Anesthesiology. 1998;89(3):666-70.
79. Van Hoogenhuyze D, Weinstein N, Martin GJ, Weiss JS, Schaad JW, Sahyouni XN, Fintel D, Remme WJ, Singer DH. Reproducibility and relation to mean heart rate of heart rate variability in normal subjects and in patients with congestive heart failure secondary to coronary artery disease. Am J Cardiol. 1991;68(17):1668-76.
80. Marciano F, Migaux ML, Acanfora D, Furgi G, Rengo F. Quantification of Poincaré maps for the evaluation of heart rate variability. Paper presented at the Computers in Cardiology. Bethesda; 1994. p. 25-28.
81. Olesen RM, Thomsen PE, Saermark K, Glikson M, Feldman S, Lewkowicz M, Levitan J. Statistical analysis of the DIAMOND MI study by the multipole method. Physiol Meas. 2005;26(5):591-8.
82. Ashkenazy Y, Ivanov PC, Havlin S, Peng CK, Goldberger AL, Stanley HE. Magnitude and sign correlations in heartbeat fluctuations. Phys Rev Lett. 2001;86(9):1900-3.