bioRxivPhysiologyPreprint
Steeper or Faster? Impacts of Similar-intensity Running Conditions on Heart Rate Variability
V. M. ElDash, I. M. C. A. ElDash, F. S. Marques, J. E. S. Natali, J. G. Chaui-Berlinck
Abstract
Increases in speed or slope promote different adjustments in the locomotor system and lead to a higher heart rate (HR). Because heart rate variability (HRV) is known to respond to exercise intensity and to biomechanical stimuli, we aimed to answer whether HRV would be sensitive to changes in speed and/or slope under similar HR. We hypothesize that HRV would depend solely on HR. To test this hypothesis, 6 healthy male runners (age 30 {+/-} 7.5 yrs.) were recruited and a velocity V, with similar HR/HRmax was selected per volunteer. Changes in HR were referred to these particular velocities V, resulting in comparable exercise intensities. HRV was estimated through standard deviation (sdt) and root mean square of successive RR intervals (rmst), normalized per volunteer. Four running conditions were compared. We found that rmst decreased with speed and slope, with significant interaction between the independent variables. The run {0.7 V, 0% slope} was different from the remaining 3 conditions, which, in turn, were no different from one another. Thus, this estimator did not show a distinct sensitivity to variations in speed or slope. On the other hand, sdt decreased with both speed and slope, with no significant interactions. The runs performed at {0.7 V, 0% slope} and {0.7 V, 6% slope} were different from those at {1 V, 0% slope} and {1 V, 6% slope}. Therefore, sdt presented different values under similar HR. This finding leads us to conclude that cardiac control operates sensitively due to the mode of the changes imposed on the metabolic demand. Summary StatementDoes heart rate variability respond similarly to running in different combinations of speed and slope? While one estimator depended on the exercise intensity, another was sensitive to the running conditions.
- organism: human
- assay: electrophysiology
- research focus: cell signaling & trafficking
- approach: statistical model
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