Running Technique is an Important Component of Running Economy and Performance

Abstract

Despite an intuitive relationship between technique and both running economy (RE) and performance, and the diverse techniques used by runners to achieve forward locomotion, the objective importance of overall technique and the key components therein remain to be elucidated.PurposeThis study aimed to determine the relationship between individual and combined kinematic measures of technique with both RE and performance.MethodsNinety-seven endurance runners (47 females) of diverse competitive standards performed a discontinuous protocol of incremental treadmill running (4-min stages, 1-km·h−1 increments). Measurements included three-dimensional full-body kinematics, respiratory gases to determine energy cost, and velocity of lactate turn point. Five categories of kinematic measures (vertical oscillation, braking, posture, stride parameters, and lower limb angles) and locomotory energy cost (LEc) were averaged across 10–12 km·h−1 (the highest common velocity < velocity of lactate turn point). Performance was measured as season's best (SB) time converted to a sex-specific z-score.ResultsNumerous kinematic variables were correlated with RE and performance (LEc, 19 variables; SB time, 11 variables). Regression analysis found three variables (pelvis vertical oscillation during ground contact normalized to height, minimum knee joint angle during ground contact, and minimum horizontal pelvis velocity) explained 39% of LEc variability. In addition, four variables (minimum horizontal pelvis velocity, shank touchdown angle, duty factor, and trunk forward lean) combined to explain 31% of the variability in performance (SB time).ConclusionsThis study provides novel and robust evidence that technique explains a substantial proportion of the variance in RE and performance. We recommend that runners and coaches are attentive to specific aspects of stride parameters and lower limb angles in part to optimize pelvis movement, and ultimately enhance performance.

The implications of time on the ground on running economy: less is not always better

“…1). The DF values in our population are in line with those previously reported in the literature at similar running speeds and agree with the proposition that running locomotion DF values should be under 0.500 (Folland et al, 2017;Minetti, 1998). Running speed also affected DF (main effect, P<0.001), with the change in DF with speed being group specific (interaction effect, P=0.003).…”

“…These authors claimed that a long t c allows force to be generated over a longer period, reducing EC. Moreover, for a given step frequency, a decrease in t c would lengthen the duration of the aerial phase (t a ) and promote vertical displacement of the COM (Δz), which is known to increase EC (Folland et al, 2017). The relationship between EC and movement pattern is complex.…”

“…The duty factor (DF) is the ratio of one to the other, with a greater DF reflecting a greater relative contribution of t c and a lesser relative contribution of t s (and therefore t a ) to the running step (Minetti, 1998). DF has been reported to be highly variable amongst runners, with values ranging from 0.257 to 0.403 at similar running speeds (Folland et al, 2017). However, DF has not been studied intensively and no relationship between DF and economy has yet been described.…”

Textile‐Based Inductive Soft Strain Sensors for Fast Frequency Movement and Their Application in Wearable Devices Measuring Multiaxial Hip Joint Angles during Running

“…CCET sensors show little drift and the ability to capture motion at a high frequency (>15 Hz) and strain rates (>450% s −1 ), without any discernable hysteresis up to a frequency of 4 Hz and strain rate of 186% s −1 . This shows great potential for inductive‐based sensor smart textile systems to provide feedback useful for injury prevention, performance tracking and enhancement, or robotics . Future work will involve the incorporation of additional sensors and chips to improve the accuracy of the more difficult‐to‐track transverse and frontal planes, especially to enable tracking at faster running speeds.…”

“…Optoelectric motion capture (OMC) systems are capable of providing accurate kinematic human motion data, which may be used to prevent injury and enhance performance. For example, runners—spanning professional athletes to those that run for casual exercise—utilize wearable devices to track a variety of metrics; various kinematic variables have been correlated with running economy and performance and systems that are able to provide these data are valuable . The spatial limitation of OMC systems reduces the ability to use these systems to track everyday activities where they could be highly useful for sports (such as our running example), rehabilitation, and occupational settings.…”