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Exploring kinematic asymmetry by means of wearable sensors during marathon race

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Footwear Science
ISSN: 1942-4280 (Print) 1942-4299 (Online) Journal homepage: https://www.tandfonline.com/loi/tfws20
Exploring kinematic asymmetry by means of
wearable sensors during marathon race
Aliaksandr Leuchanka, Zachary Switaj & Tim Clark
To cite this article: Aliaksandr Leuchanka, Zachary Switaj & Tim Clark (2019) Exploring kinematic
asymmetry by means of wearable sensors during marathon race, Footwear Science, 11:sup1,
S193-S194, DOI: 10.1080/19424280.2019.1606328
To link to this article: https://doi.org/10.1080/19424280.2019.1606328
Published online: 26 Jul 2019.
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Exploring kinematic asymmetry by means of wearable sensors during marathon race
Aliaksandr Leuchanka
a
, Zachary Switaj
a
and Tim Clark
b
a
VF Global Innovation Center Research and Testing, Dover, DE, USA;
b
Scribe Labs Inc., Moss Beach, CA, USA
(Received 15 February 2019; accepted 31 March 2019)
Keywords: asymmetry; marathon; inertial measurement unit; RunScribe; wearable
Introduction
Overuse injuries are common among the sport of running
and the general nature of such injuries is often unilateral.
Natural movements such as running have natural vari-
ability, hence may contain some asymmetry (Moran
et al., 2015). There is no current consensus on what
magnitude of asymmetry is deemed as abnormal or as a
risk factor to the injury. Currently, measurements of
asymmetry are often utilized in a clinical setting during
rehabilitation from a prior injury or during the manage-
ment process of a chronic medical condition. In a recent
study, the use of inertial measurement units (IMUs) was
demonstrated to accurately assess running asymmetry;
however, the study utilized a loosely controlled testing
session with an imposed asymmetry test (Moran et al.,
2015). Therefore, a fatiguing real-world testing method
utilizing IMUs may serve as an unobtrusive way to
measure asymmetry in running.
Purpose of the study
The purpose of this study was to unobtrusively measure
the kinematic asymmetry during a marathon race.
Methods
Fifty subjects participated in this study and were
recruited through an open forum after providing proof of
acceptance to the 2019 TCS New York City Marathon.
Each subject was provided an electronic consent form
and was provided with two RunScribe
TM
IMUs (Scribe
Labs Inc., Moss Beach, CA, USA) to place on the
dorsum of each foot via a lace mounted cradle. The
RunScribe
TM
IMU contains a tri-axial accelerometer, a
magnetometer, and a gyroscope, along with a barometric
altimeter. The sample rate is 500 Hz. Each subject was
provided a guide for the use of the mobile application
Corresponding author. Email: Alex_Leuchanka@vfc.com
https://doi.org/10.1080/19424280.2019.1606328
Figure 1. Mean value kinematic variables over three kilometer
points during a marathon race. and # denote significant
(p<0.05) differences over each point as measured by left and
right foot, respectively. Solid lines represent left foot data while
dashed lines present right foot data.
Abstracts S193
and appropriate mounting and calibration procedures for
the RunScribes
TM
. Due to poor mounting and calibra-
tion, data from 36 subjects were excluded from the ana-
lysis. Footstrike index is a novel method developed by
Scribe Labs Inc. to determine footstrike pattern. The
index is a range of values from 1 to 16 at which 1 is a
rearfoot most strike and 16 is a forefoot most strike. For
clarity purposes, metrics from the 5th, 23rd and 37th km
will be presented, representing the attest sections
spread along the course. Statistical comparisons were
made using repeated measures ANOVA (alpha ¼0.05).
Results
No signicant differences in any variable were found
when comparing right and left feet during each marathon
measurement point (Table 1). Right and left kinematic
variables were found signicant across the various meas-
urement points as illustrated in Figure 1.
Discussion and conclusion
The measure of kinematic variables by RunScribe
TM
has
previously been validated over various velocities and ter-
rain, but the footstrike index has yet to be externally vali-
dated (Hollis, Koldenhoven, Resch, Hertel, 2017). Novel
methods of assessing footstrike pattern have previously
been developed (Giandolini et al., 2014). Our objective
was to measure the change in footfall patterns over time,
which has been internally validated by gold standard
high-speed video capture. Although our ndings on asym-
metry were not found to be statistically signicant, we
were successfully able to measure the change between
kinematic variables over the marathon race distance. The
measured changes by the left and right foot over the race
distance may serve to be a useful biomechanics insight
for a clinically oriented practice or into the running econ-
omy of elite runners while also serving as a variable in
discovering the inuence of fatigue.
References
Giandolini, M., Poupard, T., Gimenez, P., Horvais, N., Millet,
G. Y., Morin, J. B., & Samozino, P. (2014). A simple field
method to identify foot strike pattern during running.
Journal of Biomechanics,47, 15881593. doi:10.1016/
j.jbiomech.2014.03.002
Hollis, C., Koldenhoven, R. M., Resch, J. E., & Hertel, J.
(2017). Gait mechanics as measured by a wearable sensor
while running at two speed on different surfaces. Journal
of Athletic Training,52,S1S76.
Moran, K., Richter, C., Farrell, E., Mitchell, E., Ahmadi, A., &
OConnor, N. E. (2015). Detection of running asymmetry
using a wearable sensor system. Procedia Engineering,
112, 180183. doi:10.1016/j.proeng.2015.07.196
Table 1. Mean and standard deviation values for kinematic variables over three kilometer points during a marathon race.
Kinematic asymmetry variables 5 km 23 km 37 km
Right foot Stride pace (m/s) 3.53 ± 0.7 3.49 ± 0.7 3.32 ± 0.6
Foot strike index 8.61 ± 4.3 9.08 ± 3.9 9.49 ± 3.8
Pronation excursion ()14.6. ± 7.3 13.3 ± 6.7 12.8 ± 6.1
Max pronation velocity (/s) 714.7 ± 239.6 742.7 ± 295.8 707.9 ± 305.1
Left foot Stride pace (m/s) 3.53 ± 0.7 3.49 ± 0.7 3.32 ± 0.6
Foot strike index 8.22 ± 3.7 8.69 ± 3.5 9.49 ± 3.5
Pronation excursion ()13.7 ± 8.2 11.8 ± 7.0 11.8 ± 6.0
Max pronation velocity (/s) 725.7 ± 281.9 747.0 ± 340.0 714.5 ± 336.5
S194 Abstracts
... Additionally, two further works [30,31] analyse the application of mathematical models, based on power laws, to predict running performance, whereas a recent study [32] assesses the agreement level between two mathematical models and five power meter devices through different running conditions. Other studies examined some parameters provided by the RunScribe power meter to describe the effects of the fatigue induced over a marathon [33,34] and the influence of different types of ankle treatments on running biomechanics [35]. The two-point method based on distant velocities was able to provide P with the same accuracy than the multiple-point method. ...
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We demonstrate a wearable ambulatory analysis framework that could be used to evaluate running asymmetry, day-today during unconstrained training. The system can automatically differentiate running from other training movement tasks, and extract all of the runner's associated step-cycles (heel-strike to heel-strike). We evaluate the system's ability in 21 participants who have artificially induced asymmetry. Impact accelerations differentiate asymmetry more effectively than angular velocities (gyroscope), and tibial inertial sensors differentiate more effectively than sensors attached to the thigh.
Gait mechanics as measured by a wearable sensor while running at two speed on different surfaces
  • C Hollis
  • R M Koldenhoven
  • J E Resch
  • J Hertel
Hollis, C., Koldenhoven, R. M., Resch, J. E., & Hertel, J. (2017). Gait mechanics as measured by a wearable sensor while running at two speed on different surfaces. Journal of Athletic Training, 52, S1-S76.