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Cardiac and gait rhythms in healthy younger and older adults during treadmill walking tasks

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Abstract

Background

Aging and pathology result in changes in the dynamics of several physiological subsystems. Often, these changes are concurrent, altering the dynamics between subsystems. Cardiac and gait rhythms are one example in which patterns change during physical activity.

Aims

The purpose of this research is to simultaneously monitor changes in cardiac and gait rhythms when participants complete various treadmill walking tasks—normal speed, fast speed, and while synchronizing steps with a blinking metronome.

Methods

The cardiac and gait rhythms of younger and older healthy adults were examined in this study during treadmill walking tasks. Pre-test and post-test walking at a preferred walking speed were compared to fast walking and walking with a gait synchronization test. Cardiac and gait rhythms were observed to calculate the mean, standard deviation, coefficient of variation, detrended fluctuation analysis scaling exponent alpha (DFA α), and sample entropy from each 15-min trial. Separate MANOVAs were used to examine the two experimental conditions for cardiac and gait rhythm variability.

Results

During the gait synchronization experiment, main effects for phase were exhibited for all gait variables, but none were shown during the fast walking task. Meanwhile, the cardiac rhythms demonstrated decreased mean and increased DFA α only during the synchronization condition.

Discussion

Participants, regardless of age, exhibited similar patterns of change in their cardiac and locomotor rhythms during the treadmill walking tasks. Cardiac rhythms were only altered during the gait synchronization task, suggesting it may be possible to simultaneously influence the variability and structure of cardiac and gait rhythms.

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Fig. 1

Adapted from Rhea et al. [5]

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References

  1. Zhang J (2007) Effect of age and sex on heart rate variability in healthy subjects. J Manip Physiol Ther 30:374–379

    Article  CAS  Google Scholar 

  2. Jordan K, Challis JH, Cusumano JP et al (2009) Stability and the time-dependent structure of gait variability in walking and running. Hum Mov Sci 28:113–128

    Article  PubMed  Google Scholar 

  3. Routledge FS, Campbell TS, McFetridge-Durdle JA et al (2010) Improvements in heart rate variability with exercise therapy. Can J Cardiol 26:303–312

    Article  PubMed  PubMed Central  Google Scholar 

  4. Hausdorff JM, Rios DA, Edelberg HK (2001) Gait variability and fall risk in community-living older adults: a 1-year prospective study. Arch Phys Med Rehabil 82:1050–1056. https://doi.org/10.1053/apmr.2001.24893

    Article  CAS  PubMed  Google Scholar 

  5. Rhea CK, Kiefer AW, Wittstein MW et al (2014) Fractal gait patterns are retained after entrainment to a fractal stimulus. PLoS One 9:e106755. https://doi.org/10.1371/journal.pone.0106755

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Krishnan MMR, Sree SV, Ghista DN et al (2012) Automated diagnosis of cardiac health using recurrence quantification analysis. J Mech Med Biol 12

  7. Riva F, Toebes MJP, Pijnappels M et al (2013) Estimating fall risk with inertial sensors using gait stability measures that do not require step detection. Gait Posture 38:170–174

    Article  CAS  PubMed  Google Scholar 

  8. Wayne PM, Manor B, Novak V et al (2013) A systems biology approach to studying Tai Chi, physiological complexity and healthy aging: design and rationale of a pragmatic randomized controlled trial. Contemp Clin Trials 34:21–34. https://doi.org/10.1016/j.cct.2012.09.006

    Article  PubMed  Google Scholar 

  9. Schulz S, Adochiei F, Edu I et al (2013) Cardiovascular and cardiorespiratory coupling analyses: a review. Philos Trans A Math Phys Eng Sci 371:20120191. https://doi.org/10.1098/rsta.2012.0191

    Article  PubMed  Google Scholar 

  10. Godin PJ, Buchman TG (1996) Uncoupling of biological oscillators: a complementary hypothesis concerning the pathogenesis of multiple organ dysfunction syndrome. Crit Care Med 24:1107–1116

    Article  CAS  PubMed  Google Scholar 

  11. Seely AJE, Christou NV (2000) Multiple organ dysfunction syndrome: exploring the paradigm of complex nonlinear systems. Crit Care Med 28:2193–2200

    Article  CAS  PubMed  Google Scholar 

  12. Novak V, Hu K, Vyas M et al (2007) Cardiolocomotor coupling in young and elderly people. J Gerontol A Biol Sci Med Sci 62:86–92

    Article  PubMed  PubMed Central  Google Scholar 

  13. Lipsitz LA (2002) Dynamics of stability: the physiologic basis of functional health and frailty. J Gerontol A Biol Sci Med Sci 57:B115-25

    Article  PubMed  Google Scholar 

  14. Manor BD, Lipsitz LA (2013) Physiologic complexity and aging: implications for physical function and rehabilitation. Prog Neuropsychopharmacol Biol Psychiatry 45:287–293. https://doi.org/10.1016/j.pnpbp.2012.08.020

    Article  PubMed  Google Scholar 

  15. Rhea CK, Kiefer AW, D’Andrea SE et al (2014) Entrainment to a real time fractal visual stimulus modulates fractal gait dynamics. Hum Mov Sci 36:20–34

    Article  PubMed  Google Scholar 

  16. Hove MJ, Suzuki K, Uchitomi H et al (2012) Interactive rhythmic auditory stimulation reinstates natural 1/f timing in gait of parkinson’s patients. PLoS One 7:e32600. https://doi.org/10.1371/journal.pone.0032600

    Article  PubMed  PubMed Central  Google Scholar 

  17. Marmelat V, Torre K, Beek PJ et al (2014) Persistent fluctuations in stride intervals under fractal auditory stimulation. PLoS One 9:e91949

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Uchitomi H, Ota L, Ogawa K et al (2013) Interactive rhythmic cue facilitates gait relearning in patients with Parkinson’s disease. PLoS One 8:e72176. https://doi.org/10.1371/journal.pone.0072176

    Article  PubMed  PubMed Central  Google Scholar 

  19. Kaipust JP, McGrath D, Mukherjee M et al (2013) Gait variability is altered in older adults when listening to auditory stimuli with differing temporal structures. Ann Biomed Eng 41:1595–1603. https://doi.org/10.1007/s10439-012-0654-9

    Article  PubMed  Google Scholar 

  20. Hausdorff JM, Purdon PL, Peng C-K et al (1996) Fractal dynamics of human gait: stability of long-range correlations in stride interval fluctuations. J Appl Physiol 80:1448–1457

    Article  CAS  PubMed  Google Scholar 

  21. Hausdorff JM (2007) Gait dynamics, fractals and falls: finding meaning in the stride-to-stride fluctuations of human walking. Hum Mov Sci 26:555–589. https://doi.org/10.1016/j.humov.2007.05.003

    Article  PubMed  PubMed Central  Google Scholar 

  22. Stergiou N, Decker LM (2011) Human movement variability, nonlinear dynamics, and pathology: is there a connection? Hum Mov Sci 30:869–888. https://doi.org/10.1016/j.humov.2011.06.002

    Article  PubMed  PubMed Central  Google Scholar 

  23. Rhea CK, Kiefer AW (2014) Patterned variability in gait behavior: how can it be measured and what does it mean. In: Li L, Georgia SU, Holmes M (eds) Gait biometrics basic patterns, role neurol. Disord. Eff. Phys. Act. Nova Science, Hauppauge, pp 17–44

    Google Scholar 

  24. Vaillancourt D, Newell KM (2002) Changing complexity in human behavior and physiology through aging and disease. Neurobiol Aging 23:1–11

    Article  PubMed  Google Scholar 

  25. Jordan K, Challis JH, Newell KM (2007) Walking speed influences on gait cycle variability. Gait Posture 26:128–134

    Article  PubMed  Google Scholar 

  26. Iyengar N, Peng C-KK, Morin R et al (1996) Age-related alterations in the fractal scaling of cardiac interbeat interval dynamics. Am J Physiol 271:R1078–R1084

    CAS  PubMed  Google Scholar 

  27. Berntson GG, Bigger JT Jr, Eckberg DL et al (1997) Heart rate variability: origins, methods, and interpretive caveats. Psychophysiology 34:623–648

    Google Scholar 

  28. Pikkujämsä SM, Mäkikallio TH, Sourander LB et al (1999) Cardiac interbeat interval dynamics from childhood to senescence comparison of conventional and new measures based on fractals and chaos theory. Circulation 100:393–399

    Article  PubMed  Google Scholar 

  29. American College of Sports Medicine, Thompson WR, Gordon NF, Pescatello LS (2010) ACSM’s guidelines for exercise testing and prescription, 8th edn. Philadelphia: Wolters Kluwer/Lippincott Williams & Wilkins

  30. Brach JS, Studenski SA, Perera S et al (2008) Stance time and step width variability have unique contributing impairments in older persons. Gait Posture 27:431–439. https://doi.org/10.1016/j.gaitpost.2007.05.016

    Article  PubMed  Google Scholar 

  31. Brach JS, Berlin JE, VanSwearingen JM et al (2005) Too much or too little step width variability is associated with a fall history in older persons who walk at or near normal gait speed. J Neuroeng Rehabil 2:21. https://doi.org/10.1186/1743-0003-2-21

    Article  PubMed  PubMed Central  Google Scholar 

  32. Gabell A, Nayak US (1984) The effect of age on variability in gait. J Gerontol 39:662–666

    Article  CAS  PubMed  Google Scholar 

  33. Hargittai S (2005) Savitzky-Golay least-squares polynomial filters in ECG signal processing. Comput Cardiol 2005:763–766

    Google Scholar 

  34. Zeni JA Jr, Richards JG, Higginson JS (2008) Two simple methods for determining gait events during treadmill and overground walking using kinematic data. Gait Posture 27:710–714

    Article  PubMed  Google Scholar 

  35. Peng C-K, Buldyrev SV, Havlin S et al (1994) Mosaic organization of DNA nucleotides. Phys Rev E 49:1685

    Article  CAS  Google Scholar 

  36. Richman JS, Moorman JR (2000) Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Hear Circ Physiol 278:H2039-49

    Google Scholar 

  37. Jordan K, Challis JH, Newell KM (2007) Speed influences on the scaling behavior of gait cycle fluctuations during treadmill running. Hum Mov Sci 26:87–102. https://doi.org/10.1016/j.humov.2006.10.001

    Article  PubMed  Google Scholar 

  38. Lake DE, Richman JS, Griffin MP et al (2002) Sample entropy analysis of neonatal heart rate variability. Am J Physiol Integr Comp Physiol 283:R789–R797

    Article  CAS  Google Scholar 

  39. Porta A, Castiglioni P, Bari V et al (2013) K-nearest-neighbor conditional entropy approach for the assessment of the short-term complexity of cardiovascular control. Physiol Meas 34:17–33. https://doi.org/10.1088/0967-3334/34/1/17

    Article  CAS  PubMed  Google Scholar 

  40. Yentes JM, Hunt N, Schmid KK et al (2013) The appropriate use of approximate entropy and sample entropy with short data sets. Ann Biomed Eng 41:349–365

    Article  PubMed  Google Scholar 

  41. Eduardo Virgilio Silva L, Otavio Murta L (2012) Evaluation of physiologic complexity in time series using generalized sample entropy and surrogate data analysis. Chaos 22:43105. https://doi.org/10.1063/1.4758815

    Article  Google Scholar 

  42. Goldberger AL, Peng C-K, Lipsitz LA (2002) What is physiologic complexity and how does it change with aging and disease? Neurobiol Aging 23:23–26

    Article  PubMed  Google Scholar 

  43. Lipsitz LA, Goldberger AL (1992) Loss of complexity and aging. J Am Med Assoc 267:1806–1809

    Article  CAS  Google Scholar 

  44. Kirby RL, Nugent ST, Marlow RW et al (1989) Coupling of cardiac and locomotor rhythms. J Appl Physiol 66:323–329

    Article  CAS  PubMed  Google Scholar 

  45. Niizeki K, Kawahara K, Miyamoto Y (1993) Interaction among cardiac, respiratory, and locomotor rhythms during cardiolocomotor synchronization. J Appl Physiol 75:1815–1821

    Article  CAS  PubMed  Google Scholar 

  46. Censi F, Calcagnini G, Cerutti S (2002) Coupling patterns between spontaneous rhythms and respiration in cardiovascular variability signals. Comput Methods Programs Biomed 68:37–47

    Article  CAS  PubMed  Google Scholar 

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Correspondence to Matthew W. Wittstein.

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All procedures were approved by the University of North Carolina Greensboro Institutional Review Board.

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Wittstein, M.W., Starobin, J.M., Schmitz, R.J. et al. Cardiac and gait rhythms in healthy younger and older adults during treadmill walking tasks. Aging Clin Exp Res 31, 367–375 (2019). https://doi.org/10.1007/s40520-018-0962-5

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  • DOI: https://doi.org/10.1007/s40520-018-0962-5

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