Using complexity metrics with R-R intervals and BPM heart rate measures

Frontiers in Physiology

Volumn 4 AUG, Issue , 2013, Pages

  Wallot, Sebastian ^a   Fusaroli, Riccardo ^a,b   Tylén, Kristian ^a,b   Jegindø, Else Marie ^a,b  

^a AARHUS UNIVERSITY   (Denmark)

^b AARHUS UNIVERSITY HOSPITAL   (Denmark)

Author keywords

BPM; Detrended fluctuation analysis; Exercise; Heart beat complexity; R R interval; Recurrence quantification analysis

Indexed keywords

ADULT; ANALYTIC METHOD; ARTICLE; EXERCISE TEST; FEMALE; HEART FUNCTION; HEART RATE VARIABILITY; HUMAN; HUMAN EXPERIMENT; LINEAR SYSTEM; MALE; MATHEMATICAL COMPUTING; NONLINEAR SYSTEM; NORMAL HUMAN; RR INTERVAL; STATISTICAL MODEL; STIMULUS RESPONSE; TASK PERFORMANCE; TIME SERIES ANALYSIS;

EID: 84884544705     PISSN: None     EISSN: 1664042X     Source Type: Journal    
DOI: 10.3389/fphys.2013.00211     Document Type: Article

References (41)

1. Abarbanel, H. D. I. (1996). Analysis of Observed Chaotic Data. New York, NY: Springer. doi: 10.1007/978-1-4612-0763-4
2. Acharya, U. R., Faust, O., Sree, S. V., Ghista, D. N., Dua, S., Joseph, P., et al. (2011). An integrated diabetic index using heart rate variability signal features for diagnosis of diabetes. Comput. Methods Biomech. Biomed. Engin. 16, 1-13.
3. Akselrod, S., Gordon, D., Ubel, F. A., Shannon, D. C., Berger, A. C., and Cohen, R. J. (1981). Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control. Science 213, 220-222. doi: 10.1126/science.6166045
4. Aoyagi, N., Struzik, Z. R., Kiyono, K., and Yamamoto, Y. (2007). Autonomic imbalance induced breakdown of long-range dependence in healthy heart rate. Methods Inf. Med. 46, 174.
5. Bak, P. (1996). How Nature Works. The Science of Self-Organized Criticality. New York, NY: Copernicus.
6. Baumert, M., Brechtel, L., Lock, J., and Voss, A. (2006). Changes in heart rate variability of athletes during a training camp. Bimomed. Tech. 51, 201-204. doi: 10.1515/BMT.2006.037
7. Bravi, A., Longtin, A., and Seely, A. J. E. (2011). Review and classification of variability analysis techniques with clinical applications. Biomed. Eng. Online. 10:90. doi: 10.1186/1475-925X-10-90
8. Burton, D. A., Stokes, K., and Hall, G. M. (2004). Physiological effects of exercise. Contin. Educ. Anaesth. Crit. Care Pain 4, 185-188. doi: 10.1093/bjaceaccp/mkh050
9. Busha, B. F. (2010). Exercise modulation of cardiorespiratory variability in humans. Respir. Physiol. Neurobiol. 172, 72-80. doi: 10.1016/j.resp.2010.05.002
10. Castiglioni, P., Parati, G., Lombardi, C., Quintin, L., and Di Rienzo, M. (2011). Assessing the fractal structure of heart rate by the temporal spectrum of scale exponents: a new approach for detrended fluctuation analysis of heart rate variability. Biomed. Tech. 56, 175-183. doi: 10.1515/bmt.2011.010
11. Delignières, D., and Marmelat, V. (2013). Theoretical and methodological issues in serial correlation analysis. Adv. Exp. Med. Biol. 782, 127-148. doi: 10.1007/978-1-4614-5465-6_7
12. Faul, F., Erdfelder, E., Lang, A.-G., and Buchner, A. (2007). G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav. Res. Methods 39, 175-191. doi: 10.3758/BF03193146
13. Giuliani, A., Piccirillo, G., Marigliano, V., and Colosimo, A. (1998). A nonlinear explanation of aging-induced changes in heartbeat dynamics. Am. J. Physiol. Heart Circ. Physiol. 275, 1455-1461.
14. Goldberger, A. L., Amaral, L. A. N., Hausdorff, J. M., Ivanov, P. Ch., Peng, C.-K., et al. (2002). Fractal dynamics in physiology: alterations with disease and aging. Proc. Natl. Acad. Sci. U.S.A. 99, 2466-2472. doi: 10.1073/pnas.012579499
15. Hirsch, J. A., and Bishop, B. (1981). Respiratory sinus arrhythmia in humans: how breathing pattern modulates heart rate. Am. J. Physiol. Heart Circ. Physiol. 241, 620-629.
16. Holden, J. G. (2005). "Gauging the fractal dimension of response times from cognitive tasks," in Tutorials in Contemporary Nonlinear Methods for The Behavioral Sciences: A Webbook Tutorial, eds M. A. Riley and G. Van Orden. 267-318. Available online at: http://www.nsf.gov/sbe/bcs/pac/nmbs/nmbs.jep
17. Karavirta, L., Tulppo, M., Laaksonen, D. E., Nyman, K., Laukkanen, R. T., Kinnunen, H., et al. (2009). Heart rate dynamics after combined endurance and strength training in older man. Med. Sci. Sports. Exerc. 41, 1436-1443. doi: 10.1249/MSS.0b013e3181994a91
18. Konvalinka, I., Xygalatas, D., Bulbulia, J., Schjødt, U., Jegindø, E. M., Wallot, S., et al. (2011). Synchronized arousal between performers and related spectators in a fire-walking ritual. Proc. Natl. Acad. Sci. U.S.A. 108, 8514-8519. doi: 10.1073/pnas.1016955108
19. Laukkanen, R. M. R., and Virtanen, P. K. (1998). Heart rate monitors: state of the art. J. Sports Sci. 16, 3-7.
20. Liu, Y., Kankaanpaa, M., Zbilut, J., and Webber, C. L. Jr. (2004). EMG recurrence quantifications in dynamic exercise. Biol. Cybern 90, 337-348. doi: 10.1007/s00422-004-0474-6
21. Mandelbrot, B. B. (1997). Fractals and Scaling in Finance. New York, NY: Springer. doi: 10.1007/978-1-4757-2763-0
22. Marwan, N. (2013a). A Comprehensive Bibliography About RPs, RQA An Their Applications. Available online at: from: http://www.recurrence-plot.tk/bibliography.php
23. Marwan, N. (2013b). Commandline Recurrence Plots. Available online at: http://tocsy.pik-potsdam.de/commandline-rp.php
24. Marwan, N., Wessel, N., Meyerfeldt, U., Schirdewan, A., and Kurths, J. (2002). Recurrence-plot-based measures of complexity and their application to heart-rate-variability data. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 66, 026702. doi: 10.1103/PhysRevE.66.026702
25. Mohr, E., Langbein, J., and Nuernberg, G. (2002). Heart rate variability: a noninvasive approach to measure stress in calves and cows. Physiol. Behav. 75, 251-259. doi: 10.1016/S0031-9384(01)00651-5
26. Moody, G. B. (2013). RR Intervals, Heart Rate, and HRV Howto. Available online at: http://www.physionet.org/tutorials/hrv/
27. Peng, C.-K., Havlin, S., Stanley, H. E., and Goldberger, A. L. (1995). Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. Chaos 5, 82-87. doi: 10.1063/1.166141
28. Polar. (2013). Polar Team2 Pro. Available online at: http://www.polar.com/us-en/b2b_products/team_sports/polar_team2_prp
29. Richardson, M. J., Schmidt, R. C., and Kay, B. A. (2007). Distinguishing the noise and attractor strength of coordinated limb movements using recurrence analysis. Biol. Cybern 96, 59-78. doi: 10.1007/s00422-006-0104-6
30. SPSS 13. (2013). IBM SPSS Software. Available online at: www.ibm.com/software/analytics/spss/
31. Takens, F. (1981). Detecting strange attractors in turbulence. Lect. Notes Math. 898, 366-381. doi: 10.1007/BFb0091924
32. Terkelsen, A. J., Molgaard, H., Hansen, J., Finnerup, N. B., Kroner, K., and Jensen, T. S. (2012). Heart rate variability in complex regional pain syndrome during rest and mental and orthostatic stress. Anesthesiology 116, 133-146. doi: 10.1097/ALN.0b013e31823bbfb0
33. Van Orden, G., Kloos, H., and Wallot, S. (2011). "Living in the pink: intentionality, wellbeing, and complexity," in Philosophy of Complex Systems. Handbook of The Philosophy of Science, ed C. A. Hooker (Amsterdam: Elsevier), 629-672.
34. Vanderlei, L. C., Silva, R. A., Pastre, C. M., Azevedo, F. M., and Godoy, M. F. (2008). Comparison of the Polar S810i monitor and the ECG for the analysis of heart rate variability in the time and frequency domains. Braz. J. Med. Biol. Res. 41, 854-859. doi: 10.1590/S0100-879X2008005000039
35. Webber, C. L. Jr. (2005). The meaning and measurement of physiological variability. Crit. Care Med. 33, 677-678. doi: 10.1097/01.CCM.0000155772.47288.EC
36. Webber., C. L. Jr., and Zbilut, J. P. (2005). "Recurrence quantification analysis of nonlinear dynamical systems," in Tutorials in Contemporary Nonlinear Methods for The Behavioral Sciences: A Webbook Tutorial, eds M. A. Riley and G. Van Orden. 26-96. Available online at: http://www.nsf.gov/sbe/bcs/pac/nmbs/nmbs.jep
37. Webber, C. L. Jr., Marwan, N., Facchini, A., and Giuliani, A. (2009). Simpler methods do it better: success of recurrence quantification analysis as a general purpose data analysis tool. Phys. Lett. A 373, 3753-3756. doi: 10.1016/j.physleta.2009.08.052
38. Weippert, M., Kumar, M., Kreuzfeld, S., Arndt, D., Rieger, A., and Stoll, R. (2010). Comparison of three mobile devices for measuring R-R intervals and heart rate variability: Polar S810i, Suunto t6 and an ambulatory ECG system. Eur. J. Appl. Physiol. 109, 779-786. doi: 10.1007/s00421-010-1415-9
39. Wessel, N., Marwan, N., Schirdewan, A., and Kurths, J. (2003). Beat-to-beat complexity analysis before the onset of ventricular Tachycardia. Comput. Cardiol. 30, 477-480.
40. West, B. J. (2006). Where Medicine Went Wrong. Rediscovering the Path to Complexity. London: World Scientific.
41. Zbilut, J. P., Thomasson, N., and Webber, C. L. (2002). Recurrence quantification analysis as a tool for nonlinear exploration of nonstationary cardiac signals. Med. Eng. Phys. 24, 53-60. doi: 10.1016/S1350-4533(01)00112-6