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J Appl Physiol (1985). 2018 Dec 13. doi: 10.1152/japplphysiol.00374.2018. [Epub ahead of print]

Step Frequency Patterns of Elite Ultramarathon Runners during a 100-km Road Race.

Author information

1
Kinesiology, University of Michigan, United States.
2
School of Kinesiology, University of Michigan, United States.
3
Director, Bone & Joint Injury Prevention & Rehabilitation Center, University of Michigan, United States.

Abstract

Step frequency (SF) in running has received substantial interest from researchers, coaches, therapists, and runners. It has been widely studied in controlled settings, but no study has measured it continuously in elite-level competition. The current study used wrist-based accelerometers in consumer-grade watches to monitor SF and SF variability of competitors in the 2016 100-km World Championship road race. Using linear mixed-model regression, SF and SF variability were assessed across the race. The average SF (steps-per-minute) of competitors (n=20) was 182.0 spm (range: 155.4-203.1 spm). Race fluctuations in SF were only influenced by the speed the competitors were running, with faster speeds being associated with greater SF (5.6 spm/m*s^-1, p<0.001). SF did not otherwise change over the course of the race. SF was further linked to the runner's stature (-123.1 spm/m, p=0.01), but not significantly related to sex, weight, age, or years of experience. The SF Coefficient-of-Variation was inversely associated with running speed and distance covered, with runners demonstrating decreasing variability at both faster speeds and as the race progressed. Together, these results add ecological evidence to observations of a speed-dependency of SF in a highly trained, elite population of runners and suggest that in road race conditions, SF changes only with speed and not fatigue. Furthermore, it presents evidence that the variability of an elite runner's SF is linked to both speed and fatigue, but not any other characteristics of the runner. The current findings are important for runners, clinicians, and coaches as they seek to monitor or manipulate SF.

KEYWORDS:

Cadence; Running; Stride Rate; Variability; Wearable Technology

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