Absolute Reliability and Concurrent Validity of the Stryd System for the Assessment of Running Stride Kinematics at Different Velocities

Abstract

García-Pinillos, F, Roche-Seruendo, LE, Marcen-Cinca, N, Marco-Contreras, LA, and Latorre-Román, PA. Absolute reliability and concurrent validity of the Stryd system for the assessment of running stride kinematics at different velocities. J Strength Cond Res XX(X): 000-000, 2018-This study aimed to determine the absolute reliability and to evaluate the concurrent validity of the Stryd system for measuring spatiotemporal variables during running at different velocities (8-20 km·h) by comparing data with another widely used device (the OptoGait system). Eighteen trained male endurance runners performed an incremental running test (8-20 km·h with 3-minute stages) on a treadmill. Spatiotemporal parameters (contact time [CT], flight time [FT], step length [SL], and step frequency [SF]) were measured using 2 different devices (Stryd and OptoGait systems). The Stryd system showed a coefficient of variation (CV) <3%, except for FT (3.7-11.6%). The OptoGait achieved CV <4%, except for FT (6.0-30.6%). Pearson correlation analysis showed large correlations for CT and FT, and almost perfect for SL and SF over the entire protocol. The intraclass correlation coefficients partially support those results. Paired t-tests showed that CT was underestimated (p < 0.05, effect size [ES] > 0.7; ∼4-8%), FT overestimated (p < 0.05, ES > 0.7; ∼7-65%), whereas SL and SF were very similar between systems (ES < 0.1, with differences <1%). The Stryd is a practical portable device that is reliable for measuring CT, FT, SL, and SF during running. It provides accurate SL and SF measures but underestimates CT (0.5-8%) and overestimates FT (3-67%) compared with a photocell-based system.

Full text

ABSOLUTE RELIABILITY AND CONCURRENT VALIDITY OF
THE STRYD SYSTEM FOR THE ASSESSMENT OF RUNNING
STRIDE KINEMATICS AT DIFFERENT VELOCITIES
FELIPE GARCI
´A-PINILLOS,
1
LUIS E. ROCHE-SERUENDO,
2
NEOL MARCEN-CINCA,
2
LUIS A. MARCO-
CONTRERAS,
2
AND PEDRO A. LATORRE-ROMA
´N
3
1
Department of Physical Education, Sport and Recreation, Universidad de La Frontera, Temuco, Chile;
2
Universidad San
Jorge, Campus Universitario, Zaragoza, Spain; an
AU1 d
3
Universidad de Jae´n, Campus de Las Lagunillas, Jaen, SpainAU2
ABSTRACT
Garcı
´a-Pinillos, F, Roche-Seruendo, LE, Marcen-Cinca, N,
Marco-Contreras, LA, and Latorre-Roma
´n, PA. Absolute reliabil-
ity and concurrent validity of the Stryd system for the assess-
ment of running stride kinematics at different velocities. J
Strength Cond Res XX(X): 000–000, 2018—This study aimed
to determine the absolute reliability and to evaluate the concur-
rent validity of the Stryd system for measuring spatiotemporal
variables during running at different velocities (8–20 km$h
21
)by
comparing data with another widely used device (the OptoGait
system). Eighteen trained male endurance runners performed an
incremental running test (8–20 km$h
21
with 3-minute stages) on
a treadmill. Spatiotemporal parameters (contact time [CT], flight
time [FT], step length [SL], and step frequency [SF]) were mea-
sured using 2 different devices (Stryd and OptoGait systems).
The Stryd system showed a coefficient of variation (CV) ,3%,
except for FT (3.7–11.6%). The OptoGait achieved CV ,4%,
except for FT (6.0–30.6%). Pearson correlation analysis showed
large correlations for CT and FT, and almost perfect for SL and
SF over the entire protocol. The intraclass correlation coeffi-
cients partially support those results. Paired t-tests showed that
CT was underestimated (p,0.05, effect size [ES] .0.7; ;4–
8%), FT overestimated (p,0.05, ES .0.7; ;7–65%),
whereas SL and SF were very similar between systems (ES ,
0.1, with differences ,1%). The Stryd is a practical portable
device that is reliable for measuring CT, FT, SL, and SF during
running. It provides accurate SL and SF measures but under-
estimates CT (0.5–8%) and overestimates FT (3–67%) com-
pared with a photocell-based system.
KEY WORDS biomechanics, technology
AU3
INTRODUCTION
Interest in running gait analysis is appropriate in both
an injury prevention (11,17) and an athletic perfor-
mance context (1,3,13,18). Although previous meth-
ods of analysis have generally required well-equipped
research laboratories, recently, there has been a move to
produce low-cost, portable gait analysis equipment. This
has allowed researchers to remove participants from an arti-
ficial laboratory environment and measure participants in
a more natural environment (14).
In the current study, the authors compared Stryd data
with a widely used device for assessing spatiotemporal
variables during locomotion. The OptoGait system is
composed of photoelectric cells positioned along
transmitting-receiving bars of 1 m in length with a maxi-
mum distance of 6 m between bars. The transmitting-
receiving bars contain infrared light-emitting diodes
(LEDs), enabling communication between the 2 bars.
When a subject passes between the transmitting bar and
the receiving bar, the system automatically calculates
spatiotemporal parameters by sensing interruptions in
communication. The assessment results of this gait analysis
system have been previously validated in healthy adults
walking at a comfortable speed (9), and the system has
been used to examine spatiotemporal parameters of ath-
letes when running at different velocities and under differ-
ent conditions (12,16).
Stryd system (www.stryd.com) is a pioneer in
manufacturing wearable power meters for running. Power
meters have helped performance-focused cyclists revolu-
tionize their training and racing (15), and the same may
soon be accomplished for runners. This power meter for
runners is a foot pod that attaches to a running shoe to
measure 12 metrics to quantify performance: pace, dis-
tance, elevation, running power, form power, cadence,
ground contact time (CT), vertical oscillation, and leg stiff-
ness. This is a relativel AU4
y new tool, and yet, there are no data
to demonstrate validity and reliability of this device, mak-
ing this type of study beneficial.
Address correspondence to Felipe Garcı
´a-Pinillos, fegarpi@gmail.com.
00(00)/1–7
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The variety of available technologies for gait analysis
(e.g., accelerometers, gyroscopes, force plates, pressure
plates, and photoelectric cells) implies that a variety of
devices should exist for analyzing stride characteristics.
However, some of these devices have not yet been
validated. The validity and reliability of a gait analysis
system are essential to determine whether results are due
to changes in gait pattern or are simply systematic
measurement errors. Therefore, the aim of the current
study is to determine the absolute reliability (within-subject
variation) and to evaluate the concurrent validity of the
Stryd system for measuring spatiotemporal variables during
running at different velocities (usual for endurance runners
at training and competing, 8–20 km$h
21
) by comparing
data with a widely used device for this purpose (i.e., the
OptoGait system).
TABLE 1. Coefficient of variation (%) of the spatiotemporal parameters (CT, FT, SL, and SF) at different running
velocities (8–20 km$h
21
) from OptoGait system and from Stryd system.
Speed (km$h
21
)
Contact time (CT) Flight time (FT) Step length (SL) Step frequency (SF)
Stryd OptoGait Stryd OptoGait Stryd OptoGait Stryd OptoGait
8 1.46 3.01 11.60 30.58 1.32 3.78 1.31 3.13
9 1.38 2.91 9.38 24.17 1.38 3.61 1.33 3.30
10 1.53 2.90 7.35 18.62 1.22 3.39 1.19 3.14
11 1.43 2.79 5.78 14.01 1.13 3.28 1.11 3.06
12 1.37 2.59 5.21 11.44 1.24 3.04 1.19 2.77
13 1.22 2.56 4.27 9.05 1.09 2.74 1.05 2.79
14 1.27 2.48 4.18 8.26 1.14 2.63 1.13 2.52
15 1.34 2.41 4.29 7.05 1.33 2.24 1.26 2.35
16 1.91 2.53 4.59 6.46 1.20 1.98 1.17 2.33
17 1.56 2.38 3.73 6.38 1.32 2.02 1.29 2.30
18 1.98 2.33 5.11 6.37 1.86 2.08 1.69 2.15
19 2.23 2.45 5.39 6.41 2.02 2.24 1.87 2.27
20 2.32 2.48 7.56 6.01 2.08 2.66 2.01 3.54
TABLE 2. SEM of the spatiotemporal parameters (CT, FT, SL, and SF) at different running velocities (8–20 km$h
21
)
from OptoGait system and from Stryd system.
Speed (km$h
21
)
Contact time (CT) Flight time (FT) Step length (SL) Step frequency (SF)
Stryd OptoGait Stryd OptoGait Stryd OptoGait Stryd OptoGait
8 0.005 0.005 0.008 0.009 1.345 1.259 2.483 2.269
9 0.004 0.005 0.007 0.009 1.228 1.179 2.138 2.068
10 0.003 0.004 0.005 0.007 1.071 1.032 1.746 1.777
11 0.003 0.003 0.005 0.007 1.479 1.539 2.213 2.234
12 0.003 0.003 0.005 0.007 1.572 1.539 2.227 2.229
13 0.003 0.002 0.004 0.005 1.583 1.497 2.108 2.103
14 0.003 0.002 0.004 0.005 1.704 1.757 2.198 2.179
15 0.002 0.002 0.003 0.004 1.794 1.730 2.207 2.164
16 0.002 0.002 0.003 0.004 1.930 1.881 2.318 2.355
17 0.002 0.002 0.003 0.004 2.146 2.151 2.507 2.529
18 0.001 0.002 0.004 0.004 2.412 2.484 2.771 2.787
19 0.001 0.002 0.003 0.003 2.252 2.278 2.535 2.591
20 0.001 0.003 0.003 0.003 2.013 2.079 2.211 2.406
Stryd System and Running Stride Kinematics
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METHODS
Experimental Approach to the Problem
With the introduction of new wireless devices, establishment
of their reliability and validity are essential before practical
use. In this study, the Stryd system was compared with the
OptoGait system for measuring spatiotemporal variables
during running at different velocities (8–20 km$h
21
).
Subject
AU5 s
A grou
AU6 p of 18 recreationally trained male endurance runners
(age range: 19–46 years; age: 34 67 years; height: 1.76 6
0.05 m; body mass: 70.5 66.2 k
AU7 g) voluntarily participated
in this study. All participants met the inclusion criteria: (a)
older than 18 years, (b) able to run 10 km in less than 40 mi-
nutes, (c) training on a treadmill at least once per week, and
(d) not suffering from any injury (points 3 and 4 related to
the last 6 months before the data collection). After receiving
detailed information on the objectives and procedures of the
study, each subject signed an informed consent form to par-
ticipate, which complied with the ethical standards of the
World Medical Association’s Declaration of Helsinki (2013).
It was made clear that the participants were free to leave the
study if they saw fit. The study was approved by the Ethics
Committee of the San Jorge University (Zaragoza, Spain)
AU8 .
Procedures
The study was conducted in June 2017. At the time of these
observations, the subjects had completed between 6 and 7
months of training. Subjects were individually tested on one
day (between 16:00 and 21:00 hours). Before all testing,
subjects refrained from severe physical activity for at least 48
hours and all testing was at least 3 hours after eating. Tests
were performed with the subjects’ usual training shoes to
measure their typical performance.
Subjects performed an incremental running test on
a motorized treadmill (HP cosmos Pulsar 4P; HP cosmos
Sports & Medical, Gmbh, Nußdorf, Germany). The initial
speed was set at 8 km$h
21
and speed increased by 1 km$h
21
every 3 minutes until running speed reached 20 km$h
21
.
The slope was maintained at 1% (0.98). The treadmill pro-
tocol was preceded by a standardized 10-minute accommo-
dation programme (5 minutes walking at 5 km$h
21
, and
5 minutes running at 10 km$h
21
). Athletes were experienced
in running on a treadmill.
Materials and Testing. (a) Anthropometry: For descriptive
purposes, height (cm) and body mass (kg) were measured.
(b) Biomechanics: Spatiotemporal parameters were mea-
sured using 2 different devices:
TABLE 3. Pearson correlation between kinematics variables from Stryd vs. Optogait over an incremental running test
(8–20 km$h
21
).
Speed
(km$h
21
) 8 9 1011121314151617181920
Contact time 0.657* 0.636* 0.574†0.525†0.433 0.435 0.507†0.504†0.503†0.453 0.415 0.429 0.078
Flight time 0.602* 0.656* 0.685* 0.703* 0.722* 0.739z0.722z0.782z0.811z0.800z0.775z0.680†0.834†
Step length 0.934z0.999z0.999z0.999z0.999z0.998z0.997z0.998z0.999z0.999z0.999z0.997z0.991z
Step frequency 0.959z0.996z0.999z0.999z0.999z0.999z0.999z0.999z0.999z0.999z0.999z0.999z0.999z
*p,0.01.
†p,0.05.
zp,0.001
AU12 .
TABLE 4. Intraclass correlation coefficients between kinematics variables from Stryd vs. Optogait over an incremental
running test (8–20 km$h
21
).
Speed (km$h
21
)8 9 1011121314151617181920
Contact time 0.457 0.463 0.416 0.386 0.303 0.330 0.407 0.400 0.380 0.329 0.294 0.381 0.063
Flight time 0.555 0.599 0.655 0.679 0.702 0.726 0.758 0.768 0.799 0.778 0.744 0.635 0.806
Step length 0.934 0.998 0.999 0.999 0.999 0.998 0.997 0.998 0.999 0.999 0.999 0.997 0.991
Step frequency 0.956 0.995 0.999 0.999 0.999 0.999 0.999 0.999 0.999 0.999 0.999 0.997 0.983
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The OptoGait system (Optogait; Microgate, Bolzano,
Italy) was previously validated for the assessment of
spatiotemporal parameters of the gait of young adults
(9). As indicated by Lee et al. (9), the OptoGait
achieved a high level of correlation with all spatiotem-
poral parameters by intraclass correlation coefficients
(ICCs) (0.785–0.952), coefficients of variation (1.66–
4.06%), SEM (2.17–5.96%), and minimum detectable
change (6.01–16.52%). The system detects any inter-
ruptions and therefore measures both CT and flight
time (FT) with a precision of 1/1,000 seconds. The 2
parallel bars of the device system were placed on the
side edges of the treadmill at the same level as the
contact surface. Contact time, FT, step length (SL),
and step frequency (SF or cadence) were measured
for every step during the treadmill test and were
defined as follows:
(a) CT (second): time from when the foot contacts the
ground to when the toes lift off the ground.
(b) FT (second): time from toe-off to initial ground
contact of consecutive footfalls (e.g., right-left).
(c) SL (meter): length the treadmill belt moves from
toe-off to initial ground contact in successive steps.
(d) SF or cadence (steps per minutes): number of
ground contact events per minute.
Stryd (Stryd Powermeter; Stryd, Inc., Boulder, CO,
USA): a relatively new device, which estimates power
in watts. Stryd is carbon fiber–reinforced foot pod
(attached to your shoe) that weights 9.1 g. Based on a 6-
axis inertial motion sensor (3-axis gyroscope and 3-axis
accelerometer), this device provides spatiotemporal
data including CT and SF. From CTand SF, in addition
to running velocity, the authors calculated FT and SL as
follows:
FT ðsÞ¼step time ðsÞ2CT ðsÞ;(1)
where step time is the time from the beginning of the step
cycle (take-off ) to the end (previous frame to take-off ).
step time ðsÞ¼60=SF ðsteps=minÞ:
SL ðmÞ¼running velocitym$min21.SFðsteps=minÞ:
(2)
Statistical Analyses
Descriptive statistics are represented as mean (SD). Tests of
normal distribution and homogeneity (Shapiro-Wilk and Lev-
ene’s test, respectively) were conducted on all data before anal-
ysis. Coefficient of variation (CV, %) and SEM were calculated
as a measure of absolute reliability (within-subject variation and
SD of a sampling distribution, respectively) (2,6). Intraclass cor-
relation coefficients were calculated between OptoGait and
Stryd data for each spatiotemporal variable analyzed (CT,
FT, SL, and SF). Values less than 0.5 are indicative of poor
reliability, values between 0.5 and 0.75 indicate moderate reli-
ability, values between 0.75 and 0.9 indicate good reliability,
and values greater than 0.90 indicate excellent reliability (8).
To determine concurrent validity, a Pearson correlation analysis
was also performed between OptoGait and Stryd data. The
following criteria were adopted to interpret the magnitude of
correlations between measure-
ment variables: ,0.1 (trivial),
0.1–0.3 (small), 0.3–0.5 (moder-
ate), 0.5–0.7 (large), 0.7–0.9 (very
large), and 0.9–1.0 (almost per-
fect) (7). Pairwise comparisons
of mean (t-test) were also con-
ducted between data (CT, FT,
SL, and SF) from the 2 devices
(OptoGait and Stryd) at different
running speeds (8–20 km$h
21
).
In addition, the magnitude of the
differences between values was
also interpreted using the
Cohen’s deffect size (ES) (19).
Effect sizes of less than 0.4 rep-
resented a small magnitude of
change, whereas 0.41–0.7 and
greater than 0.7 represented
moderate and large magnitudes
of change, respectively (19). The
level of significance used was
p,0.05. Data analysis was
Figure 1. Contact time (s) during running measured by Stryd and OptoGait systems. *p,0.05, **p,0.01, ***p
,0.01.
Stryd System and Running Stride Kinematics
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performed using SPSS (version 21; SPSS, Inc., Chicago, IL,
USA).
RESULTS
Reliability
T1 Table 1 shows the CV (as a measure of absolute reliability)
of spatiotemporal parameters at different running velocities
from both Stryd and OptoGait. For the Stryd system, CV
ranged between 1.2–2.3% (CT), 3.7–11.6% (FT), 1.1–2.1%
(SL), and 1.1–2.0% (SF), whereas for the OptoGait system,
CV was 2.3–3.0% (CT), 6.0–
30.6% (FT), 2.0–3.8% (SL),
and2.2–3.6%(SF).Inaddition,
the SEM is provided in
T2Tab l e 2.
Validity
The Pearson correlation analy-
sis is shown in T3Table 3 (CT,
FT, SL, and SF or cadence at
8–20 km$h
21
running veloci-
ties). Contact time from both
devices showed large correla-
tions (0.5–0.7, p,0.05) at
low speeds (8–11 km$h
21
)
and race speeds (14–16
km$h
21
). Flight time from Op-
toGait and Stryd showed large
and very large correlations,
respectively (0.602 ,r.
0.834, p,0.05), over the veloc-
ities tested (8–20 km$h
21
). Step
length and SF from both devices were nearly perfectly corre-
lated (r.0.9, p,0.001) at every running velocity tested.
The ICCs between kinematic variables from both Stryd
vs. OptoGait systems over the entire protocol (8–20
km$h
21
)areincludedin T4Table4.Contacttimeshowed
a low coefficient (,0.5), FT a moderate coefficient
(0.5–0.75), whereas SL and SF showed excellent coeffi-
cients (.0.9).
A paired t-test demonstrated some significant differences
(p,0.05) and large ES (.0.7) in the variables analyzed (CT,
FT, SL, and cadence) (Figures 1–4, respectively). Contact
time ( F1Figure 1) was underesti-
mated for Stryd compared
with OptoGait data (8–18
km$h
21
,p,0.001, and ES .
0.7; ;6–8%). Differences were
smaller at 19 km$h
21
(p,0.05
and ES .0.7; ;4%), and no
differences were observed at 20
km$h
21
(p$0.05 and ES ,
0.1; ;0.5%).
Flight time ( F2Figure 2) was
overestimated for Stryd based
on OptoGait data at running
velocities between 8 and 19
km$h
21
(p,0.05, ES .0.7;
from ;65% at 8 km$h
21
to
;7% at 19 km$h
21
). No signif-
icant differences were found at
20 km$h
21
(p$0.05 and ES =
0.57; ;3%).
Step length from both devi-
ces is shown in F3Figure 3.
Figure 3. Step length (cm) during Running measured by Stryd and OptoGait systems. *p,0.05, **p,0.01,
***p,0.01.
Figure 2. Flight time (s) during running masured by Stryd and OptoGait systems. *p,0.05, **p,0.01, ***p,
0.01.
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pvalues show significant differences (p,0.05) between data
from Stryd and OptoGait at most analyzed velocities,
although Cohen’s dshowed a very small magnitude of
changes (ES ,0.1), with Stryd data overestimated com-
pared with OptoGait data (,1%). Likewise, significant dif-
ferences (p,0.05) were found in cadence between the 2
devices (
F4 Figure 4), but Cohen’s dreported a very small
change (ES ,0.1) with differences smaller than 1%.
DISCUSSION
This study aimed to determine the absolute reliability and to
evaluate the concurrent validity of the Stryd system for
measuring spatiotemporal variables during running at differ-
ent velocities (8–20 km$h
21
) by comparing data with
a device widely used for this purpose (OptoGait system).
The major findings of this study were (a) CV, as a measure
of reliability, was lower in all analyzed variables for the Stryd
system than for the OptoGait system (,5% in all cases,
except for FT), whereas SEM was almost identical for every
variable over the entire protocol (8–20 km$h
21
), and (b)
concurrent validity of the Stryd and OptoGait systems
regarding spatiotemporal variables is not yet settled: moder-
ate for CT, low for FT, and very high for SL and SF. Results
from Pearson correlation analysis indicated a strong concur-
rent validity over the entire range of running velocities (8–20
km$h
21
), with large correlations in CT, very large correla-
tions in FT, and almost perfect correlations in SL and SF.
The ICCs partially provide support to those results with
excellent coefficients for SL and SF and moderate for FT,
but poor coefficients for CT (over the entire protocol). In
addition, the paired t-test let us improve our comparison and
some interesting findings are worth noting: (a) The Stryd
system underestimated CT (up to ;8% at low velocities)
and overestimated FT (up to
;65% at low velocities) com-
pared with the OptoGait sys-
tem, with reduced differences
at high running velocities, and
(b) despite differences in pval-
ues, the very small magnitude
of changes reported suggests
that SL and SF (from the Stryd
system) are valid variables over
running velocities of 8–20
km$h
21
, compared with the
OptoGait system.
As mentioned earlier, scien-
tists have discovered the
potential of accelerometers
(and inertial measurement
units [IMUs]) in assessing gait
analysis without the restric-
tions of laboratory technology.
Having the chance to measure
athletes or clients in a natural
environment and using less expensive and more time-
efficient equipment is a huge step forward for coaches and
clinicians. Nevertheless, this advantage would be worthless if
the data were not valid. The Stryd system (based on a 6-axis
inertial motion sensor: 3-axis gyroscope and 3-axis acceler-
ometer) is mainly a running power meter, but it also provides
spatiotemporal variables that are used by coaches and
clinicians (information easily accessible to users) as a feed-
back, necessitating confirmation of the validity of these data.
Comparing between devices and technologies (i.e.,
photoelectric cells vs. IMUs), the authors hypothesize that
differences in temporal variables might be at least partially
explained by the height of the OptoGait system’s LEDs. As
described by Lienhard et al. (10), the LEDs of the OptoGait
system are positioned 3 mm above ground, and thereby,
sensing of heel contact occurs earlier, whereas sensing of
toe lift-off occurs later in the gait cycle (timing differences).
In a similar previously published study (4), the authors
assessed the reliability and validity of an accelerometer-
based system (Myotest) against a photocell-based system
(OptoJump) for measuring running stride kinematics. In
line with our data, the authors reported CT 34% shorter
and FT 64% longer than the photocell-based system. That
work (4) also found a good validity in SF. Therefore, the
data obtained in the current study agree with those re-
ported by previous studies that compared accelerometer-
based systems to photocell-based systems, and our results
support the explanation for this discrepancy given by
Lienhard et al. (10).
Some final limitations need to be taken into consideration.
First, the use of photocell-based systems as the gold standard
reference for establishing concurrent validity should be
evaluated, instead of instruments that measure ground
Figure 4. Step frequency (cadence, step per minute) during running measured by Stryd and OptoGait systems.
*p,0.05, **p,0.01, ***p,0.01.
Stryd System and Running Stride Kinematics
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reaction force, such as a force platform. Because we do not
possess such equipment in our laboratory, the use of the
OptoGait system was considered to be an adequate proxy
system, given its demonstrated good validity compared with
GAITRite system—pressure platform (9) or compared with
force platform during jumping tests (5). Furthermore, the
OptoGait system is more practical and portable for record-
ing several consecutive steps than force or pressure platforms
imbedded into the ground in series where participants often
have to adjust SL and target platforms to obtain clearly
defined foot contact data. A second consideration is that
validation data were obtained from an analysis based on
within-subject variation (CV) rather than on different days.
Although the number of steps analyzed in 3-minutes of run-
ning at these velocities is high (400–500 steps in 3 minutes),
our current reliability statistics might not generalize to runs
performed several days apart.
To s u m u
AU9 p, based on traditional thresholds, the absolute
(i.e., CV) reliability of CT, FT, SL, and SF derived using the
Stryd device were classified as adequate for running assess-
ments, and this suggests that the Stryd is useful for monitoring
individuals and quantifying changes in functional performance
over time. However, the concurrent validity of Stryd as com-
pared to OptoGait was low-moderate for CT and FT, and
excellent for SL and SF. The paired comparisons added to
those correlations showed that the Stryd system underesti-
mated CT (0.5–8%) and overestimated FT (3–67%) compared
with OptoGait system, with reduced differences at elevated
running velocities (8–20 km$h
21
). However, SL and SF were
valid variables (,1%) over the entire range of running veloc-
ities, as compared with the OptoGait system.
PRACTICAL APPLICATIONS
From a practical point of view and considering that both
systems are widely used, scientists and clinicians should
know that both devices showed an adequate reliability for
running assessments, and thereby, spatiotemporal parame-
ters reported from these devices can be compared over time
(if using the same device). However, the clients also should
be aware about the limitations of comparing data reported
from these 2 devices.
REFERENCES
1. Anderson, T. Biomechanics and running economy. Sport Med 22:
76–89, 1996.
2. Atkinson, G and Nevill, AM. Statistical methods for assessing
measurement error (reliability) in variables relevant to sports
medicine. Sport Med 26: 217–238, 1998.
3. Barnes, KR and Kilding, AE. Running economy: Measurement,
norms, and determining factors. Sport Med Open 1: 8, 2015.
4. Gindre, C, Lussiana, T, Hebert-Losier, K, and Morin, JB. Reliability
and validity of the Myotest for measuring running stride kinematics.
J Sport Sci: 1–7, 2015. Available at: https://www.researchgate.net/
profile/Thibault_Lussiana2/publication/280089781_Reliability_
and_validity_of_the_MyotestR_for_measuring_running_stride_
kinematics/links/55a8083e08ae815a04212eb1/Reliability-and-
validity-of-the-MyotestR-for-measuring-running-st AU10.
5. Glatthorn, JF, Gouge, S, Nussbaumer, S, Stauffacher, S, Impellizzeri,
FM, and Maffiuletti, NA. Validity and reliability of Optojump
photoelectric cells for estimating vertical jump height. J Strength
Cond Res 25: 556–560, 2011.
6. Hopkins, WG. Measures of reliability in sports medicine and
science. Sport Med 30: 1–15, 2000.
7. Hopkins, WG, Marshall, SW, Batterham, AM, and Hanin, J.
Progressive statistics for studies in sports medicine and exercise
science. Med Sci Sports Exerc 41: 3–13, 2009.
8. Koo, TK and Li, MY. A guideline of selecting and reporting
intraclass correlation coefficients for reliability research. J Chiropr
Med 15: 155–163, 2016.
9. Lee, MM, Song, CH, Lee, KJ, Jung, SW, Shin, DC, and Shin, SH.
Concurrent validity and test-retest reliability of the OPTOGait
photoelectric cell system for the assessment of spatio-temporal
parameters of the gait of young adults. J Phys Ther Sci 26: 81–85,
2014.
10. Lienhard, K, Schneider, D, and Maffiuletti, NA. Validity of the
Optogait photoelectric system for the assessment of spatiotemporal
gait parameters. Med Eng Phys 35: 500–504, 2013.
11. Luedke, LE, Heiderscheit, BC, Williams, DSB, and Rauh, MJ.
Influence of step rate on shin injury and anterior knee pain in high
school runners. Med Sci Sports Exerc 48: 1244–1250, 2016.
12. Lussiana, T, He
´bert-Losier, K, Millet, GP, and Mourot, L.
Biomechanical changes during a 50-minute run in different footwear
and on various slopes. J Appl Biomech 32: 40–49, 2016.
13. Mooses, M, Mooses, K, Haile, DW, Durussel, J, Kaasik, P, and
Pitsiladis, YP. Dissociation between running economy and running
performance in elite Kenyan distance runners. J Sports Sci 33:
136–144, 2015.
14. Norris, M, Anderson, R, and Kenny, IC. Method analysis of
accelerometers and gyroscopes in running gait: A systematic review.
Proc Inst Mech Eng P J Sports Eng Technol 228: 3–15, 2014.
15. Passfield, L, Hopker, J, Jobson, S, Friel, D, and Zabala, M.
Knowledge is power: Issues of measuring training and performance
in cycling. J Sports Sci 35: 1426–1434, 2017.
16. Roche-Seruendo, LE, Garcı
´a-Pinillos, F, Haicaguerre, J, Bataller-
Cervero, AV, Soto-Hermoso, VM, and Latorre-Roma
´n, PA
´. Lack
of influence of muscular performance parameters on spatio-
temporal adaptations with increased running velocity. JStrength
Cond Res,2017 AU11.
17. Schubert, AG, Kempf, J, and Heiderscheit, BC. Influence of stride
frequency and length on running mechanics: A systematic review.
Sports Health 6: 210–217, 2014.
18. Tartaruga, MP, Brisswalter, J, Peyre
´-Tar t a ruga, LA , A
´vila, AOV,
Alberton,CL,Coertjens,M,Tiggemann,CL,Silva,EM,andKruel,
LF. The relationship between running economy and
biomechanical variables in distance runners. Res Q Exerc Sport 83:
367–375, 2012.
19. Thomas, JR, Silverman, SS, Nelson, JK. Research Methods in Physical
Activity. (7th ed.). Champaign, IL: Human Kinetics, 2015.
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