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Reproducibility and Validity of the Myotest for Measuring Step Frequency and Ground Contact Time in Recreational Runners

DOI:10.1515/hukin-2015-0003
Authors:
Vincent Gouttebarge at Amsterdam University Medical Centers / University of Pretoria
Vincent Gouttebarge
  • Amsterdam University Medical Centers / University of Pretoria
Robin Wolfard
Robin Wolfard
Robin Wolfard
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Nouschka Griek
Nouschka Griek
Nouschka Griek
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Cornelis J. de Ruiter at Vrije Universiteit Amsterdam
Cornelis J. de Ruiter
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Abstract and Figures

The purpose of this study was to assess the reproducibility (test-retest reliability and agreement) and concurrent validity of the Myotest for measuring step frequency (SF) and ground contact time (GCT) in recreational runners. Based on a within-subjects design (test and retest), SF and GCT of 14 participants (11 males, 3 females) were measured at three different running speeds with the Myotest during two test sessions. SF and GCT were also assessed with a foot-mounted accelerometer (Gold Standard, previously validated by comparing to force plate data) during the first test session. Levels of test-retest reliability and concurrent validity were expressed with intraclass correlation coefficients (ICC), agreement with standard errors of measurement (SEM). For SF, test-retest reliability (ICC's > 0.75) and agreement of the Myotest were considered as good at all running speeds. For GCT, test-retest reliability was found to be moderate at a running speed of 14 km/h and poor at speeds of 10 and 12 km/h (ICC < 0.50). Agreement of the Myotest for GCT at all three running speeds was considered not acceptable given the SEM's calculated. Concurrent validity of the Myotest with the foot-mounted accelerometer (Gold Standard) at all three running speeds was found to be good for SF (ICC's > 0.75) and moderate for GCT (0.50 < ICC's < 0.75). The conclusion of our study is that estimates obtained with the Myotest are reproducible and valid for SF but not for GCT.
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Journal of Human Kinetics volume 45/2015, 19-26 DOI: 10.1515/hukin-2015-0003 19
Section I – Kinesiology
1 - Department of Orthopaedic Surgery, Academic Medical Center, Amsterdam, The Netherlands.
2 - MOVE Research Institute Amsterdam, Faculty of Human Movement Sciences, VU University Amsterdam, Amsterdam, The
Netherlands.
3 - Vintta | Research and Consultancy for Sport Health, Almere, The Netherlands.
4 - King Abdulaziz University, Jeddah, Saudi Arabia.
.
Authors submitted their contribution to the article to the editorial board.
Accepted for printing in the Journal of Human Kinetics vol. 45/2015 in March 2015.
Reproducibility and Validity of the Myotest for Measuring
Step Frequency and Ground Contact Time
in Recreational Runners
by
Vincent Gouttebarge1, Robin Wolfard2, Nouschka Griek2, Cornelis J. de Ruiter2,
Julitta S. Boschman3, Jaap H. van Dieën2,4
The purpose of this study was to assess the reproducibility (test-retest reliability and agreement) and
concurrent validity of the Myotest for measuring step frequency (SF) and ground contact time (GCT) in recreational
runners. Based on a within-subjects design (test and retest), SF and GCT of 14 participants (11 males, 3 females) were
measured at three different running speeds with the Myotest during two test sessions. SF and GCT were also assessed
with a foot-mounted accelerometer (Gold Standard, previously validated by comparing to force plate data) during the
first test session. Levels of test-retest reliability and concurrent validity were expressed with intraclass correlation
coefficients (ICC), agreement with standard errors of measurement (SEM). For SF, test-retest reliability (ICC’s > 0.75)
and agreement of the Myotest were considered as good at all running speeds. For GCT, test-retest reliability was found
to be moderate at a running speed of 14 km/h and poor at speeds of 10 and 12 km/h (ICC < 0.50). Agreement of the
Myotest for GCT at all three running speeds was considered not acceptable given the SEM’s calculated. Concurrent
validity of the Myotest with the foot-mounted accelerometer (Gold Standard) at all three running speeds was found to
be good for SF (ICC’s > 0.75) and moderate for GCT (0.50 < ICC’s < 0.75). The conclusion of our study is that
estimates obtained with the Myotest are reproducible and valid for SF but not for GCT.
Key words: agreement, concurrent validity, step frequency, ground contact time.
Introduction
As a consequence of its practicality and
positive effects for physical health and mental
well-being, running has in the past years become
one of the most popular forms of physical activity
(Thompson Coon et al., 2011; Williams, 2012a;
Williams, 2012b). The total number of recreational
runners has increased by 18% from 2007 to 2008 in
the United States (Running-U.S.A, 2012), while
the running population doubled within the latest
decade in the Netherlands (van Bottenburg, 2009).
Next to its beneficial health effects,
running is also associated with negative effects,
runners being at high risk of musculoskeletal
injuries (Hespanhol Junior et al., 2011; Lopes et al.,
2012). A new acute musculoskeletal injury occurs
in one out of five runners during a marathon,
with injury lasting longer than 3 months in 25% of
them (van Middelkoop et al., 2008). Known risk
factors for running injuries are diverse, among
which gender, high body mass index, history of
previous running injuries, muscle functions and
weekly training distance and frequency are the
20 Reproducibility and validity of the Myotest for measuring step frequency and ground contact time
Journal of Human Kinetics - volume 45/2015 http://www.johk.pl
most important ones (van Middelkoop et al., 2008;
Buist et al., 2010; Lopes et al., 2012; Moen et al.,
2012). Lately, running technique elements have
gained attention as risk factors for
musculoskeletal injuries. Several authors have
suggested that many running injuries might
derive from poor running technique and that
alterations in running technique elements, such as
step frequency, stride length, vertical oscillation,
ground contact time or foot strike pattern,
decrease the biomechanical load on lower
extremities, which might prevent the occurrence
of musculoskeletal injuries (Collier, 2011;
Lieberman, 2012; Rixe et al., 2012; Bochman and
Gouttebarge, 2013). Consequently, measuring and
monitoring running technique elements such as
step frequency (SF) and ground contact time
(GCT) in a practical way might be valuable for
many runners and coaches.
The Myotest Run is a practical 3D
accelerometer that has been developed as a field-
based running device meant to be used outside
such as on an athletic track by individual runners
and coaches (Myotest, 2012). The Myotest allows
to record, process, display and store data related
to running economy and performance.
Specifically, the Myotest provides data on
variables related to running technique such as SF,
stride length, vertical oscillation, GCT and
reactivity. Previous studies conducted in
laboratory setting on a treadmill have shown
some favorable findings towards the
measurement quality of this field-based running
device (high reproducibility) (Bampouras et al.,
2010; Nuzzo et al., 2011). Whether the
measurement quality of the Myotest for the
assessment of important running-related
technique aspects such as SF and GCT is also
favorable in a more practical setting such as an
athletic track remains unknown.
The measurement quality of any
instrument, test or device, specifically referring to
reproducibility and validity, needs to be explored
before its use in practice (de Vet et al., 2011). An
instrument is considered reproducible if its
measurements are consistent and stable over time
from one test moment to another (free from
significant random error), under the assumption
that the characteristic being measured does not
change over time (de Vet et al., 2011).
Reproducibility relates to two concepts, namely
reliability and agreement (de Vet et al., 2011).
Reliability refers to an instrument’s ability to
distinguish one subject from another despite
measurement errors, while agreement concerns
the absolute measurement error, evaluating how
close the scores are in repeated measurements (de
Vet et al., 2011). An instrument is considered valid
when it measures what it intends to measure (free
from significant systematic error) (de Vet et al.,
2011). Concurrent validity, an important aspect of
validity, examines at the same time how the
evaluated instrument relates to an existing, highly
valued instrument called a gold standard (shown
to be reproducible and valid) that measures the
same parameter or concept (de Vet et al., 2011).
According to the aforementioned
considerations, we aimed to explore the
measurement quality of the Myotest in terms of
reproducibility and validity, using a foot-
mounted accelerometer as gold standard as it has
been shown valid to measure SF and GCT. Our
research questions were twofold: what is the
reproducibility (test-retest reliability and
agreement) of the Myotest for measuring SF and
GCT in recreational runners and what is the
concurrent validity of the Myotest with foot-
mounted accelerometers for measuring SF and
GCT in recreational runners?
Material and Methods
Participants
Participants were healthy recreational
runners, recruited at a running association in
Amsterdam. To be eligible to be enrolled in our
study, participants were required to meet the
following inclusion criteria: (1) free from any
running-related musculoskeletal injury in the past
month, (2) being weekly active in running during
the past month, and (3) being 18 years old or
older. Sample size calculation (nQuery Advisor:
confidence interval [CI] method with a confidence
level of 0.95, correlation coefficient set at 0.90 and
limit at 0.70) indicated that at least 14 subjects
were required for this study. Consequently, 14
recreational runners (11 men, 3 women)
participated in our study. Their mean age was 45
±14 years (range, 20-68 yrs), mean height was 181
±7cm (range, 165-188 cm), and mean body weight
was 77 ±11kg (range 53-90 kg). Prior to
enrollment, and after receiving verbal and written
information on the study aim and procedures,
by Vincent Gouttebarge et al. 21
© Editorial Committee of Journal of Human Kinetics
participants signed statements of informed
consent. Subjects were free to quit the study at
any time.
Myotest
The Myotest is a small device (W x L x H:
54.2 x 102.5 x 10.7 mm, weight 59 g, sample
frequency 200-500 Hz) attached with a Velcro
waistband to the runner (Moytest, 2012). The
Myotest Runcheck software provides several
running-related parameters among which SF (in
steps per minute) and GCT (in milliseconds).
Once set up in accordance to a runner’s
characteristics (sex, height, weight and level of
expertise), the device was attached to the Velcro
waistband around the runner’s iliac crest, on the
ventral side of the body. This standardized
position allows the runner to keep their full range
of motion. Then, the runner only had to press the
enter button in the middle of the device to start
the data collection. The same enter button needed
to be pressed to stop the device. For our study, the
level of expertise was set to “Expert” for all
subjects.
Gold standard
Foot-mounted accelerometer was used in
our study as gold standard, as it has been
developed and validated to measure SF and GCT
(de Ruiter et al., 2013). Containing a tri-axial
accelerometer (+6 g; 1000 Hz, MMA7361L,
Freescale Semiconductor, Austin, Texas, USA), the
foot-mounted accelerometer uses a software
algorithm (MATLAB R2010a, Mathworks, Natick,
USA) based on the open-source platform
Arduino. A foot-mounted accelerometer was
attached at each shoe of the participant by using
the shoe lace, sports tape being also used to secure
its sustainable position (Figure 1). Transmitting
data wirelessly, SF (in steps per minute) and GCT
(in milliseconds) were calculated automatically
and exported directly to a Microsoft Excel file.
Procedures
An experimental study using a within-
subjects design (test-retest) was conducted to
assess reproducibility and concurrent validity of
the Myotest. Each participant was assessed during
two test sessions, using a time interval of 7 ±4
days between both test days. We assumed that
such a time interval was optimal to assure a
steady state in participants. In addition,
participants were asked to wear the same running
shoes during both test sessions. Participants were
asked before each test session to avoid any
training session and exhaustive event in the
previous 24 and 36 hours, respectively. Prior to
each test session, measurement devices (Myotest
and foot-mounted accelerometer) were attached
to the participants by the same researcher (NG)
and set up in order to be ready for measurement.
Before each test session, participants were
informed one more time about the experimental
procedures in order to prevent misunderstanding,
and were asked to perform a standardized warm-
up (jogging at a comfortable pace without fatigue
development). A test session consisted of three
runs of 400 meters on an outdoor athletic track:
the first run at an approximated speed of 10 km/h,
the second run at an approximated speed of 12
km/h, and the third run at an approximated speed
of 14 km/h (approximated speed fed back verbally
every 100 m). Between the three runs, participants
were allowed to rest as required but up to 2
minutes. During the first test session, SF and GCT
were assessed concurrently by the Myotest and
the foot-mounted accelerometer (gold standard).
During the second test session, SF and GCT were
measured only by the Myotest. Ethical approval
was not needed from the ethical committee of the
Faculty of Human Movement Sciences of the VU
University as the study did not fall into the
Medical Research Involving Human Subjects Act.
The study was carried out in accordance with the
Declaration of Helsinki (2000).
Statistical Analysis
Means, standard deviations (SD’s), and
ranges were calculated for each outcome measure
at each test session. Reliability and agreement
were determined using the SF and GCT outcomes
assessed by the Myotest during the two test
sessions (test and retest). The level of test-retest
reliability was expressed with the intraclass
correlation coefficient (ICC; two-way random
model, agreement, single measures) and its 95%
confidence interval (95% CI) (Portney and
Watkins, 2008; de Vet et al., 2011). Agreement was
expressed with the standard error of
measurement (SEM = √ [var(raters) + var(error)] or
SEM = SD x √[1 – ICC]). Concurrent validity was
investigated by comparing the SF and GCT
outcomes assessed by the Myotest to the SF and
GCT outcomes assessed by the foot-mounted
accelerometer (gold standard) (Portney and
22 Reproducibility and validity of the Myotest for measuring step frequency and ground contact time
Journal of Human Kinetics - volume 45/2015 http://www.johk.pl
Watkins, 2008; de Vet et al., 2011). The level of
concurrent validity was expressed with the
intraclass correlation coefficient (ICC; two-way
random model, consistency, single measures) and
its 95% confidence interval (95% CI) (Portney and
Watkins, 2008; de Vet et al., 2011). ICC’s obtained
for reliability and concurrent validity were
interpreted as good for ICC > 0.75, as moderate
for 0.50 ≤ ICC ≤ 0.75, and as poor for ICC < 0.50
(Portney and Watkins, 2008; de Vet et al., 2011).
All data analyses were performed using the
statistical software IBM SPSS Statistics 22.0 for
Windows.
Results
Reliability and agreement
Table 1 presents the averages, SD’s, and
ranges of the SF and GCT measured with the
Myotest at different speeds during both test
sessions (test and retest), and their related ICC’s
(95% confidence interval) and SEM’s. The level of
test-retest reliability of the Myotest for SF was
good at all three running speeds, with ICC’s
ranging from 0.78 to 0.92. The SEM of the Myotest
for SF, expressed in steps per minute, were rather
small given the mean values found during both
test sessions. For instance, mean SF measured by
the Myotest at 14 km/h was 175-176 steps per
minute and its SEM 3 steps per minute, indicating
that an increase or decrease of 6 steps per minute
cannot be interpreted as a random measurement
error. The level of test-retest reliability of the
Myotest for GCT was poor to moderate at
different running speeds as ICC’s ranged from -
0.24 to 0.67. The SEM of the Myotest for GCT,
expressed in ms, were not acceptable, being large
relative to the mean values found during both test
sessions. For instance, mean GCT measured by
the Myotest at 12 km/h was 156-159 ms and its
SEM 15 ms, indicating that an increase or decrease
of more than 30 ms needs to be reached before
one can interpret it as more than a random
measurement error.
Concurrent validity
Table 2 presents the averages, SD’s, and ranges
of the SF and GCT measured with the Myotest
and foot-mounted accelerometer (gold standard)
at different speeds during the first test session,
and their related ICC’s (95% confidence interval).
The level of concurrent validity of the Myotest
with the foot-mounted accelerometer (gold
standard) for SF was good at all three running
speeds as ICC’s ranged from 0.78 to 0.90. The
level of concurrent validity of the Myotest with
the foot-mounted accelerometer (gold standard)
for GCT was only moderate at all three running
speeds as ICC’s ranged from 0.48 to 0.50.
Table 1
Mean scores, standard deviation and range obtained from the Myotest for step frequency
(SF; step per minute) and ground contact time (GCT; ms)
at different running speed, and the level of test-retest reliability and agreement of the Myotest
Test session 1 Test session 2 ICC (95% CI) SEM
Mean SD Range Mean SD Range
SF at 10 km/h 164.3 7 155-181 164.4 9 153-183 0.82 0.52-0.94 3.5
SF at 12 km/h 168.9 8 161-185 169.4 10 161-193 0.78 0.44-0.92 4.1
SF at 14 km/h 175.9 10 163-199 176.9 10 164-203 0.92 0.77-0.97 3.0
GCT at 10 km/h 172.0 15 154-204 165.4 17 113-188 -0.24 -0.69-0.32 n/a
GCT at 12 km/h 159.1 17 123-194 156.4 20 106-189 0.35 -0.23-0.74 14.8
GCT at 14 km/h 144.2 16 103-177 142.9 18 102-176 0.67 0.22-0.88 10.1
SD, standard deviation; ICC, Intra-Class correlation coefficient;
CI, confidence interval; SEM, standard error of measurement; n/a, not applicable
by Vincent Gouttebarge et al. 23
© Editorial Committee of Journal of Human Kinetics
Table 2
Mean scores, standard deviation and range obtained from the Myotest
and foot-mounted accelerometer (Gold Standard) for step frequency
(SF; step per minute) and ground contact time (GCT; ms)
at different running speed, and the level of concurrent validity
Myotest foot-mounted accelerometer ICC (95% CI)
Mean SD Range Mean SD Range
SF at 10 km/h 164.3 7 155-181 165.6 8 156-183 0.89 0.69-0.96
SF at 12 km/h 168.9 8 161-185 169.4 8 161-184 0.78 0.45-0.96
SF at 14 km/h 175.9 10 163-199 175.7 13 157-198 0.90 0.72-0.97
GCT at 10 km/h 172.0 15 154-204 297.1 20 256-331 0.49 -0.03-0.80
GCT at 12 km/h 159.1 17 123-194 278.4 25 241-314 0.50 -0.02-0.81
GCT at 14 km/h 144.2 16 103-177 251.3 24 205-274 0.48 -0.07-0.81
SD, standard deviation; ICC, Intra-Class correlation coefficient; CI,
confidence interval; n/a, not applicable
Figure 1
Foot-mounted accelerometer (Gold Standard) attached to the runner’s shoe
24 Reproducibility and validity of the Myotest for measuring step frequency and ground contact time
Journal of Human Kinetics - volume 45/2015 http://www.johk.pl
Discussion
Using a within-subjects design on runners
free from musculoskeletal injuries, the purpose of
our study was to evaluate the reliability,
agreement and concurrent validity of the Myotest
for measuring SF and GCT at three different
running speeds. For SF, test-retest reliability and
agreement of the Myotest were evaluated as good
at all running speeds. For GCT, test-retest
reliability was found to be moderate at a running
speed of 14 km/h and poor at speeds of 10 and 12
km/h. Agreement of the Myotest for GCT at all
three running speeds was not acceptable given the
large SEM. Concurrent validity of the Myotest
with the foot-mounted accelerometer (gold
standard) at all three running speeds was found
to be good for SF and moderate for GCT.
Empirical studies assessing the
measurement quality of the Myotest are scarce,
especially related to the assessment of running
parameters. In a previous study, reliability,
agreement and validity of the Myotest for
measuring running economy and vertical
oscillation were explored among healthy runners
(Potter et al., submitted). For both running
economy and vertical oscillation, levels of (test-
retest) reliability were moderate to good (ICC >
0.50) while SEM (agreement) were acceptable
relative to the mean values (Potter et al.,
submitted). In contrast, the validity of the Myotest
for measuring running economy and vertical
oscillation was only poor to moderate (Potter et
al., submitted). For measuring other performance
parameters such as force (countermovement
vertical jump), the Myotest was found to be
highly reliable (test-retest reliability) and valid,
endorsing its application in the field for the
assessment of force related parameters
(Bampouras et al., 2010; Nuzzo et al., 2011). Other
accelerometers similar to the Myotest have also
shown some moderate to high evidence of test-
retest reliability and validity (Thompson and
Bemben, 1999; Brage et al., 2003; Esliger et al.,
2006). However, most of these studies were
conducted in laboratory setting and not
specifically related to running parameters.
Our study was conducted in a practical
context, which can be seen as a strength of our
experiment. The Myotest is a small and practical
3D accelerometer that has been developed as a
field-based running device meant to be used
outside such as on an athletic track by individual
runners and coaches (Myotest, 2012).
Consequently, even though the use of a treadmill
might offer safer and more controlled conditions,
the measurement quality of the Myotest should in
principle be determined for measurements in the
field such as on an athletic track. A gait on a
treadmill has been shown to differ from a gait on
an outside track, endorsing the choice for our
experimental conditions (Kirtley, 2006). When it
comes to criterion-related validity (concurrent and
predictive), the availability of a gold standard, an
instrument already known as reliable and valid
measuring the same construct, is crucial (de Vet et
al., 2011). In our study, we chose a foot-mounted
accelerometer, as it has been validated for SF and
GCT by comparing it to a force platform (de
Ruiter and al., 2013).
With regard to our findings, the Myotest
was found to be reproducible and valid for
measuring SF at 10, 12 and 14 km/h. It has been
shown that SF between 180 and 185 steps per
minute significantly decreases biomechanical
loads on the lower extremities (peak vertical
ground reaction force, energy generated by the
hip, knee and ankle joints, ground reaction force
and compartment pressures), compared to lower
SF usually preferred by novice runners
(Boschman and Gouttebarge, 2013). Also running
economy can be improved in novice runners by
adopting a higher SF (de Ruiter et al., 2013).
Consequently, runners (or their coaches) could
use the Myotest to get feedback about their
current SF, striving to learn to run at higher SF
and using the Myotest to monitor this process
over time. By contrast to SF, since no instrument
can be valid if not reliable (de Vet et al., 2011), the
Myotest was not reliable nor valid for measuring
GCT and thus cannot be used for measuring GCT.
In addition, the GCTs found with the myotest
(Table 2) are too low when compared with values
(250-350 ms) reported in the literature at these
speeds (de Ruiter et al., 2013).
In conclusion, our study results suggest
that the Myotest is a practical, useful, reliable and
valid device that can be used by runners and
coaches to assess and monitor SF outside on an
athletic track. For measuring GCT, the Myotest
should not be used yet as it was not sufficiently
reliable nor valid. Future research focusing on the
Myotests’s reproducibility and validity for
by Vincent Gouttebarge et al. 25
© Editorial Committee of Journal of Human Kinetics
measuring other running technique elements,
such as vertical oscillation, stride length or foot
strike pattern, when running on an athletic track
is needed. In addition, attention should also be
given to responsiveness when change in running
technique elements over time is aimed for.
Acknowledgements
This study received no specific grant from any funding agency in the public, commercial or not-for-
profit sectors. The authors would like to thank the recreational runners for their participation in the study.
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Corresponding author:
Dr. Vincent Gouttebarge
Department of Orthopaedic Surgery, Academic Medical Center, Amsterdam, The Netherlands
Phone: +31621547499
E-Mail: v.gouttebarge@amc.nl
... For example, one 15-s run [56,74], and 30 trials lasting 30 s (five trials, six conditions, last 30 s of 3-min trials) [71]. • Analysing running gait in trials lasting over 1 min and less than 5 min (n = 17) [32,36,49,72,75,80,83,92,97,98,101,120,123,128,134]. For example, three sessions each consisting of three 5-min runs at varying speeds [75], seven 100-m runs (outdoor) and seven 60-s runs (treadmill) [91], or 3 min [36]. ...
... Fifty-six studies focussed on the validation of wearables for running gait assessments, with 18 also examining the reliability of devices [47,98,99,103,104,110,117,120,130,134,136,140,144,149]. Eleven studies investigated between-day reliability [34,47,98,106,117,120,122,140,142,144,149], and three studies solely examined the reliability of wearable technology [87,134,138] (Table 2 of the ESM). ...
... Fifty-six studies focussed on the validation of wearables for running gait assessments, with 18 also examining the reliability of devices [47,98,99,103,104,110,117,120,130,134,136,140,144,149]. Eleven studies investigated between-day reliability [34,47,98,106,117,120,122,140,142,144,149], and three studies solely examined the reliability of wearable technology [87,134,138] (Table 2 of the ESM). [26,27] and one study did not report age [24]. ...
Wearables for Running Gait Analysis: A Systematic Review
Article
Full-text available
Background Running gait assessment has traditionally been performed using subjective observation or expensive laboratory-based objective technologies, such as 3D motion capture or force plates. However, recent developments in wearable devices allow for continuous monitoring and analysis of running mechanics in any environment. Objective measurement of running gait is an important (clinical) tool for injury assessment and provides measures that can be used to enhance performance. Objectives To systematically review available literature investigating how wearable technology is being used for running gait analysis in adults. Methods A systematic search of literature was conducted in the following scientific databases: PubMed, Scopus, WebofScience, and SportDiscus. Information was extracted from each included article regarding the type of study, participants, protocol, wearable device(s), main outcomes/measures, analysis, and key findings. Results A total of 131 articles were reviewed: 56 investigated the validity of wearable technology, 22 examined the reliability and 77 focused on applied use. Most studies used inertial measurement units (IMU) (n=62) (i.e., a combination of accelerometers, gyroscopes, and magnetometers in a single unit) or solely accelerometers (n=40), with one using gyroscopes alone and 31 using pressure sensors. On average, studies used one wearable device to examine running gait. Wearable locations were distributed among the shank, shoe and waist. The mean number of participants was 26 (± 27), with an average age of 28.3 (± 7.0) years. Most studies took place indoors (n =93), using a treadmill (n =62), with the main aims seeking to identify running gait outcomes or investigate the effects of injury, fatigue, intrinsic factors (e.g., age, sex, morphology) or footwear on running gait outcomes. Generally, wearables were found to be valid and reliable tools for assessing running gait compared to reference standards. Conclusions This comprehensive review highlighted that most studies that have examined running gait using wearable sensors have done so with young adult recreational runners, using one IMU sensor, with participants running on a treadmill and reporting outcomes of ground contact time, stride length, stride frequency and tibial acceleration. Future studies are required to obtain consensus regarding terminology, protocols for testing validity and reliability of devices and suitability of gait outcomes.
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... A total of 657 participants were included across 39 studies (mean ± SD 16.8 ± 10.2), where the populations sampled included healthy active adults (n = 15 studies), recreational/amateur (n = 12) and high-level runners (n = 5), team-sport athletes (n = 6), elite track and field athletes (n = 1) and triathletes (n = 1). Sensor placement varied between foot [16,30,34,35,52,56,59,60,65,69,71,85], distal and mid tibia [29,31,40,58,60,62,69,70,84], hip [66], sacrum [32,57], lumbar spine [30,33,38,64,68,69,72,83], torso [53] and thoracic spine [36-39, 43, 54, 61, 86]. Two studies used multiple sensors and a combination Content courtesy of Springer Nature, terms of use apply. ...
... of placements to derive stride variables [55,87]. Validity was assessed using force plate systems (n = 17) [31, 33, 36, 38-40, 43, 54, 55, 57-59, 61, 62, 66, 69, 70], optical motion capture (n = 7) [29,32,52,55,64,65,85], instrumented treadmill (n = 7) [30,34,37,53,56,60,87], high-speed camera (n = 4) [16,33,35,68], photocell systems (n = 3) [68,71,72], foot-mounted accelerometer (n = 1) [83], in-shoe piezo-electric force sensitive resistors (FSRs) (n = 1) [63] and different stride time calculation methods (n = 1) [84] as criterions. Reliability was assessed in nine studies [16,38,40,43,59,68,71,83,86]. ...
... Validity was assessed using force plate systems (n = 17) [31, 33, 36, 38-40, 43, 54, 55, 57-59, 61, 62, 66, 69, 70], optical motion capture (n = 7) [29,32,52,55,64,65,85], instrumented treadmill (n = 7) [30,34,37,53,56,60,87], high-speed camera (n = 4) [16,33,35,68], photocell systems (n = 3) [68,71,72], foot-mounted accelerometer (n = 1) [83], in-shoe piezo-electric force sensitive resistors (FSRs) (n = 1) [63] and different stride time calculation methods (n = 1) [84] as criterions. Reliability was assessed in nine studies [16,38,40,43,59,68,71,83,86]. Contact time was the most commonly reported variable (n = 16) [16, 29, 30, 32-35, 37, 52, 53, 62, 68-71, 83], while six studies derived spatial data (step length and stride length) from accelerometers and gyroscopes [35,52,65,71,72,85]. ...
Does Site Matter? Impact of Inertial Measurement Unit Placement on the Validity and Reliability of Stride Variables During Running: A Systematic Review and Meta-analysis
Article
Full-text available
Background Inertial measurement units (IMUs) are used for running gait analysis in a variety of sports. These sensors have been attached at various locations to capture stride data. However, it is unclear if different placement sites affect the derived outcome measures.Objective The aim of this systematic review and meta-analysis was to investigate the impact of placement on the validity and reliability of IMU-derived measures of running gait.Methods Online databases SPORTDiscus with Full Text, CINAHL Complete, MEDLINE (EBSCOhost), EMBASE (Ovid) and Scopus were searched from the earliest record to 6 August 2020. Articles were included if they (1) used an IMU during running (2) reported spatiotemporal variables, peak ground reaction force (GRF) or vertical stiffness and (3) assessed validity or reliability. Meta-analyses were performed for a pooled validity estimate when (1) studies reported means and standard deviation for variables derived from the IMU and criterion (2) used the same IMU placement and (3) determined validity at a comparable running velocity (≤ 1 m·s−1 difference).ResultsThirty-nine articles were included, where placement varied between the foot, tibia, hip, sacrum, lumbar spine (LS), torso and thoracic spine (TS). Initial contact, toe-off, contact time (CT), flight time (FT), step time, stride time, swing time, step frequency (SF), step length (SL), stride length, peak vertical and resultant GRF and vertical stiffness were analysed. Four variables (CT, FT, SF and SL) were meta-analysed, where CT was compared between the foot, tibia and LS placements and SF was compared between foot and LS. Foot placement data were meta-analysed for FT and SL. All data are the mean difference (MD [95%CI]). No significant difference was observed for any site compared to the criterion for CT (foot: − 11.47 ms [− 45.68, 22.74], p = 0.43; tibia: 22.34 ms [− 18.59, 63.27], p = 0.18; LS: − 48.74 ms [− 120.33, 22.85], p = 0.12), FT (foot: 11.93 ms [− 8.88, 32.74], p = 0.13), SF (foot: 0.45 step·min−1 [− 1.75, 2.66], p = 0.47; LS: − 3.45 step·min−1 [− 16.28, 9.39], p = 0.37) and SL (foot: 0.21 cm [− 1.76, 2.18], p = 0.69). Reliable derivations of CT (coefficient of variation [CV] < 9.9%), FT (CV < 11.6%) and SF (CV < 4.4%) were shown using foot- and LS-worn IMUs, while the CV was < 7.8% for foot-determined stride time, SL and stride length. Vertical GRF was reliable from the LS (CV = 4.2%) and TS (CV = 3.3%) using a spring-mass model, while vertical stiffness was moderately (r = 0.66) and nearly perfectly (r = 0.98) correlated with criterion measures from the TS.Conclusion Placement of IMUs on the foot, tibia and LS is suitable to derive valid and reliable stride data, suggesting measurement site may not be a critical factor. However, evidence regarding the ability to accurately detect stride events from the TS is unclear and this warrants further investigation.
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... Due to these advantages and less complexity compared to laboratory systems, such as marker and camera-based 3D motion capture systems, IMUs have become a more frequently used sports technology (12,18,28). This provides running gait analysis under real-life conditions in the athletes natural training court and habitual environment (16,19,25,29). An IMU system for in-field use is the Humotion SmarTracks Integrated System (HSTI). ...
... While the HSTI system demonstrates great potential for coaches, athletes and researchers, knowledge of the accuracy of HSTI is currently uncertain. In terms of previous in-field running studies, varying IMU-types and -technologies, as well as different data collection methods and sensor placements have been used, and showed varying validity for biomechancial running parameters (3,16,25,29,30). To our knowledge, no study has examined the validity of HSTI to date. ...
... In reference to cadence estimations, the studies of Gouttebarge et al. (2015) and Wunsch et al. (2017) used IMUs during 400 m track running at comparable running speeds to those in our jogging condition. Both studies found comparable ICCs to our study but higher systematic differences were observed (16,30). In addition, we found a critical magnitude of random errors. ...
Validation of an inertial measurement unit based magnetictiming gate system during running and sprinting
Article
Full-text available
  • Mar 2020
Problem: The technology of inertial measurement units (IMU) enables the collection of running biomechanical data under in-field conditions. This paper presents a validation study of an increasingly used IMU system using a corresponding below-ground magnetic timing gate system. Methods: Thirty active healthy participants ran with an IMU located at the lumbar spine on a 60 m-section of a 400 m tartan track. The IMUs were connected with magnetic timing gates installed below the tartan track. A photoelectric cell reference system was used for comparative analysis. Outcome measures were running speed, step length and cadence during running at slow and fast velocity. Intra-Class-Correlation (ICC), Bland-Altman analysis and regression-based Bland-Altman analysis were used to determine measurement agreement. Results: The analysis showed high measurement agreement for running speed, step length and cadence for both velocities (ICCs 0.745-0.996). Bland-Altman analysis showed high random errors and increased systematic and random errors for step length and cadence at fast running velocities. Regression-based Bland-Altman analysis indicated a systematic increase of bias (systematic error) with higher step length values. Discussion: Despite a high measurement agreement expressed by ICCs, study results also showed high error values for absolute measurements expressed by systematic and random errors for all parameters. Therefore, attention should be given to the comparability of both measurement systems. Further research should focus on details of step length calculations as well as reliability and validity under longer running conditions.
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... In that context, some previous papers [25][26][27][28] have determined the validity of other wearables (i.e. Stryd and Myotest) for measuring stride characteristics during running. ...
... The authors reported CT 34% shorter and FT 64% longer than the photocell-based system. However, Gouttebarge et al. 28 determined the validity of the Myotest system against another footmounted accelerometer (at 1000 Hz), reporting an accurate estimation of SF (\ 1% difference), but great between-system differences in CT (-175%) in endurance runners. ...
... Whereas this work used a high-speed video analysis system (1000 Hz) as a gold-standard, previous works used photoelectric cellbased systems (i.e. OptoGait system 25 and OptoJump system 26 ), force platforms 27 or accelerometry, 28 which might influence the differences reported. In addition, the placement of the wearables is not consistent between studies and it seems to be system-dependent. ...
Influence of RunScribe™ placement on the accuracy of spatiotemporal gait characteristics during running
Article
  • Sep 2019
This study aimed to examine the influence of RunScribe location (i.e. lace shoe vs heel shoe) on the accuracy of spatiotemporal gait characteristics during running by comparing data with a high-speed video analysis system at 1000 Hz. A total of 49 endurance runners performed a running protocol on a treadmill at comfortable velocity. Two systems were used to determine spatiotemporal parameters (i.e. contact time, flight time, step frequency, and step length) during running: high-speed video analysis at 1000 Hz and two different RunScribe placements (i.e. lace shoe vs heel shoe). The pairwise comparisons showed some between-system differences in both lace shoe (contact time: p = 0.009; step frequency: p = 0.001) and heel shoe (flight time: p = 0.006; step frequency: p = 0.010), although the effect sizes were small (effect size < 0.3 in all cases). The intraclass correlation coefficients revealed an almost perfect association between systems for contact time and flight time (intraclass correlation coefficient: 0.85–0.90), and step length and step frequency (intraclass correlation coefficient: 0.96–0.97), regardless of the RunScribe placement. Bland–Altman plots revealed that the lace shoe location yielded smaller systematic bias, random errors, and narrower limits of agreement for spatiotemporal parameters during running, except for SF, which had a higher accuracy in a heel shoe location. The results suggest that RunScribe is a valid system to measure spatiotemporal parameters during running on a treadmill according to a high-speed video analysis at 1000 Hz. In addition, the data indicate that the location of the RunScribe system (lace shoe vs heel shoe) plays an important role on the accuracy of spatiotemporal parameters. The lace shoe placement showed smaller systematic bias, random errors, and narrower limits of agreement for contact time, flight time, and step length, whereas the heel shoe placement was slightly more accurate for the step frequency.
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... Previous studies [9][10][11][12] have focused on determining the validity of some wearable devices (i.e. Stryd™ and Myotest™) for measuring stride characteristics during running. ...
... Stryd™ and Myotest™) for measuring stride characteristics during running. García-Pinillos et al. [9] examined the validity of the Stryd™ system compared to OptoGait™, whereas others [10,12] assessed the validity of the Myotest™ system against a photocell-based system [10] and a foot-mounted accelerometer at 1,000 Hz [12]. However, no previous studies have considered the validation of the RunScribe™ system for measuring spatiotemporal parameters, or the comparison of this foot pod with a very similar one (i.e., Stryd™ system), which represents a very popular alternative among practitioners. ...
... Stryd™ and Myotest™) for measuring stride characteristics during running. García-Pinillos et al. [9] examined the validity of the Stryd™ system compared to OptoGait™, whereas others [10,12] assessed the validity of the Myotest™ system against a photocell-based system [10] and a foot-mounted accelerometer at 1,000 Hz [12]. However, no previous studies have considered the validation of the RunScribe™ system for measuring spatiotemporal parameters, or the comparison of this foot pod with a very similar one (i.e., Stryd™ system), which represents a very popular alternative among practitioners. ...
Agreement between the spatiotemporal gait parameters from two different wearable devices and high-speed video analysis
Article
Full-text available
This study aimed to evaluate the concurrent validity of two different inertial measurement units for measuring spatiotemporal parameters during running on a treadmill, by comparing data with a high-speed video analysis (VA) at 1,000 Hz. Forty-nine endurance runners performed a running protocol on a treadmill at comfortable velocity (i.e., 3.25 ± 0.36 m.s-1). Those wearable devices (i.e., Stryd™ and RunScribe™ systems) were compared to a high-speed VA, as a reference system for measuring spatiotemporal parameters (i.e. contact time [CT], flight time [FT], step frequency [SF] and step length [SL]) during running at comfortable velocity. The pairwise comparison revealed that the Stryd™ system underestimated CT (5.2%, p < 0.001) and overestimated FT (15.1%, p < 0.001) compared to the VA; whereas the RunScribe™ system underestimated CT (2.3%, p = 0.009). No significant differences were observed in SF and SL between the wearable devices and VA. The intra class correlation coefficient (ICC) revealed an almost perfect association between both systems and high-speed VA (ICC > 0.81). The Bland-Altman plots revealed heteroscedasticity of error (r2 = 0.166) for the CT from the Stryd™ system, whereas no heteroscedasticity of error (r2 < 0.1) was revealed in the rest of parameters. In conclusion, the results obtained suggest that both foot pods are valid tools for measuring spatiotemporal parameters during running on a treadmill at comfortable velocity. If the limits of agreement of both systems are considered in respect to high-speed VA, the RunScribe™ seems to be a more accurate system for measuring temporal parameters and SL than the Stryd™ system.
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... Revolution rate was characterised for a bowling ball [180] and during cycling [302,313]. Phase segmentation was performed in swimming (to identify front crawl stroke phases [80,164,246,247]), in cross-country skiing [120,207,237] and uphill mountaineering [121] (to determine cycle rate from plant and lift-off of each ski and pole ground contact), in ice hockey skating (to determine cycle rate from initial contact to blade-off for each skate [293]), and during running on a track (trunk placement [61,149,153,194] and shank or foot placement [140,209,295]), on a treadmill (trunk placement [77,203,315,320] and shank or foot ...
... For swimming, sensor placement at the trunk/limbs/head was used to provide either arm strokes (for front crawl [63,80,107,110,263]), kick strokes (for front crawl [124,126] and freestyle [125]), or generic strokes (for front crawl [24,68,85,108,156,164,168,263,323,332], butterfly [24,68,85,156], breaststroke [24,68,85,164,291]). Stride and step frequency/duration have been assessed during running [153,157,160,162,174,191,202,204,229,230,242,243,262,294,295,302,321,327], skating [293], and in the run up of cricket ball delivery [264]. Revolution rate was characterised for a bowling ball [180] and during cycling [302,313]. ...
... Revolution rate was characterised for a bowling ball [180] and during cycling [302,313]. Phase segmentation was performed in swimming (to identify front crawl stroke phases [80,164,246,247]), in cross-country skiing [120,207,237] and uphill mountaineering [121] (to determine cycle rate from plant and lift-off of each ski and pole ground contact), in ice hockey skating (to determine cycle rate from initial contact to blade-off for each skate [293]), and during running on a track (trunk placement [61,149,153,194] and shank or foot placement [140,209,295]), on a treadmill (trunk placement [77,203,315,320] and shank or foot placement [87,140,148,222,229,230,294,318]), and during the acceleration/maintenance phase of sprint running (trunk placement [70] and foot placement [57]). ...
Trends Supporting the In-Field Use of Wearable Inertial Sensors for Sport Performance Evaluation: A Systematic Review
Article
Full-text available
Recent technological developments have led to the production of inexpensive, non-invasive, miniature magneto-inertial sensors, ideal for obtaining sport performance measures during training or competition. This systematic review evaluates current evidence and the future potential of their use in sport performance evaluation. Articles published in English (April 2017) were searched in Web-of-Science, Scopus, Pubmed, and Sport-Discus databases. A keyword search of titles, abstracts and keywords which included studies using accelerometers, gyroscopes and/or magnetometers to analyse sport motor-tasks performed by athletes (excluding risk of injury, physical activity, and energy expenditure) resulted in 2040 papers. Papers and reference list screening led to the selection of 286 studies and 23 reviews. Information on sport, motor-tasks, participants, device characteristics, sensor position and fixing, experimental setting and performance indicators was extracted. The selected papers dealt with motor capacity assessment (51 papers), technique analysis (163), activity classification (19), and physical demands assessment (61). Focus was placed mainly on elite and sub-elite athletes (59%) performing their sport in-field during training (62%) and competition (7%). Measuring movement outdoors created opportunities in winter sports (8%), water sports (16%), team sports (25%), and other outdoor activities (27%). Indications on the reliability of sensor-based performance indicators are provided, together with critical considerations and future trends.
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... Gindre et al [10] proposent une équation permettant de retrouver les valeurs de TA et TV à partir du MyotestRun qui seraient comparables à celles de l'Optojump et de la caméra haute vitesse. Une autre étude, réalisée par Goutebarge et al [17], confirme la bonne validité des mesures de fréquence ainsi que les différences observées pour le temps d'appui. Elle pemet par contre en évidence une faible reproductibilité inter-séance de TA ce qui est en contradiction avec l'étude de Gindre et al [10] qui, dans une approche méthodologique différente, montre que les trois paramètres du MyotestRun étudiés possèdent une bonne reproductibilité inter-essais avec des coefficients de corrélation intraclasse (CCI) ≥ 0,82 et des coefficients de variation inférieurs à 10%. ...
... Ces observations sont valables aussi bien à 10km/h qu'à 90% de la VMA. Dans notre étude ainsi que dans celle de Gindre et al[10], l'analyse de la foulée a été réalisée dans une ligne droite conformément aux recommandations des constructeurs alors que l'enregistrement dans l'étude de Goutebarge et al[17] s'est réalisé sur un tour complet d'une piste d'athlétisme incluant de la course en virage. Par ailleurs, il apparait que le MyotestRun était positionné à la hanche et non sous l'ombilic. ...
Influence de la fatigue sur les paramètres biomécaniques de la foulée mesurés par accéléromètrie
Article
Full-text available
Aims of the study: The aim of the study was to investigate the influence of fatigue on stride biomechanics measured by a portable accelerometer, the MyotestRun. Opportunities of the protocol allowed additional analysis on the device reliability and sensitivity. Methods: Thirty-two male subjects, divided in two groups (runners and control), were involved in the study and achieved a treadmill progressive VO2max test; repeated run at constant velocity on a track and a field test at 90% of the VvO2max until exhaustion. The biomechanical measurements obtained from the MyotestRun allow exploring the reliability, the influence of speed, the differences between treadmill and track stride and the influence of fatigue. Results: Results show an excellent reproducibility of the MyotestRun values, except for the asymmetry of the stride. No significant stride difference appears between treadmill and track conditions. The progressive test shows that all the parameters evolve with speed increment, confirming the sensitivity of the MyotestRun. The study shows changes in the stride with the fatigue, such as an increase of the contact time, a decrease of the force. However any change in the stride frequency is observed. If the study shows that the fatigue pattern is more constant in the runners group it also highlights adaptations to fatigue that can be very different from one subject to another. Conclusion: This study confirmed that MyotestRun is a useful device in the stride analysis. The influence of fatigue on the stride is in accordance with most of the studies while confirming very important interindividual differences.
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... We used the value reported in previous studies [2,21] to calculated the effect size of training effect on contact time (Cohen's d = 2.56), and the effect size of region effect on FSA (Cohen's d = 2.21). We used these two values to determine how many participants should be recruited in each group using G*Power [22]. ...
How do training experience and geographical origin of a runner affect running biomechanics?
Article
Background Several studies compared African runners with runners from other places with difference ethnicities to identify biomechanical factors that may contribute to their extraordinary running performance. However, most studies only assessed runners at the elite level. Whether the performance difference was a result of nature or nurture remains unclear. Research questions: This case study aimed to assess the effect of geographical origin and the effect of training on running biomechanics. Methods: We recruited twenty male runners from two regions (Asian and Africa) at two performance levels (elite and recreational), and asked them to run on an instrumented treadmill at 12 km∙h⁻¹. We measured running kinetics and kinematics parameters, and focused on the parameters that have been shown associated with running performance. We used Friedman test to compare the effect of geographical origin and training on running biomechanics. Results: Compared to recreational runners, elite runners applied higher amount of ground reaction force in both vertical and anterior-posterior directions (P < 0.05, Cohen’s d = 1.63 – 2.03), together with a longer aerial time (P = 0.039, Cohen’s d = 1.11). On the other hand, African runners expressed higher vertical stiffness than Asian runners (P = 0.027, Cohen’s d = 0.98). However, the increased vertical stiffness in African runners did not lead to a higher vertical loading rate (P > 0.555, Cohen’s d < 0.3), which could be a result of a lower footstrike angle during landing (P = 0.012, Cohen’s d = 1.36). Significance: For elite runners, the higher amount of ground reaction force might facilitate a longer aerial time, but could also lead to higher amount of mechanical energy loss. African runners expressed higher vertical stiffness and higher step rate, which might lead to a lower CoM vertical displacement, and furthermore reduce mechanical energy loss.
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... In contrast the SEMs were quite high. In the case of running time the mean was 30 min and the SEM 4.5 min, meaning that only changes of at least 9 min can be attributed to factors other than random measurement error (Gouttebarge et al., 2015). ...
Reproducibility of the Evolution of Stride Biomechanics During Exhaustive Runs
Article
Full-text available
Running biomechanics and its evolution that occurs over intensive trials are widely studied, but few studies have focused on the reproducibility of stride evolution in these runs. The purpose of this investigation was to assess the reproducibility of changes in eight biomechanical variables during exhaustive runs, using three-dimensional analysis. Ten male athletes (age: 23 ± 4 years; maximal oxygen uptake: 57.5 ± 4.4 ml0 2 ·min ⁻¹ ·kg ⁻¹ ; maximal aerobic speed: 19.3 ± 0.8 km·h ⁻¹ ) performed a maximal treadmill test. Between 3 to 10 days later, they started a series of three time-to-exhaustion trials at 90% of the individual maximal aerobic speed, seven days apart. During these trials eight biomechanical variables were recorded over a 20-s period every 4 min until exhaustion. The evolution of a variable over a trial was represented as the slope of the linear regression of these variables over time. Reproducibility was assessed with intraclass correlation coefficients and variability was quantified as standard error of measurement. Changes in five variables (swing duration, stride frequency, step length, centre of gravity vertical and lateral amplitude) showed moderate to good reproducibility (0.48 ≤ ICC ≤ 0.72), while changes in stance duration, reactivity and foot orientation showed poor reproducibility (-0.71 ≤ ICC ≤ 0.04). Fatigue-induced changes in stride biomechanics do not follow a reproducible course across the board; however, several variables do show satisfactory stability: swing duration, stride frequency, step length and centre of gravity shift.
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... To our knowledge, only one other study has investigated the validity of GCT measures for a torso-mounted accelerometer device. 22 These authors reported errors greater than 100 milliseconds, far in excess to the results of the current study, and intraclass correlation coefficients near 0.50, for a device attached to the pelvis. The device in the current study exhibited a maximum average error of 17 milliseconds, which is comparable to previous studies that have used a shank-mounted accelerometer, and also reported a similar effect of speed. ...
Use of baseline pelvic acceleration during running for classifying response to muscle strengthening treatment in patellofemoral pain: A preliminary study
Article
Background: Objectively identifying patients at baseline who may not respond well to a generic muscle strengthening intervention could improve clinical practice by optimizing treatment strategies. The purpose of this study was to determine whether pelvic acceleration measures during running, and clinical and demographic variables could classify patellofemoral pain patients according to their response to a 6-week hip/core and knee exercise-based rehabilitation protocol. Methods: Forty-one individuals with patellofemoral pain participated in a 6-week exercise intervention program and were sub-grouped into treatment Responders (n = 28) and Non-responders (n = 13) based on self-reported pain and function measures. Baseline pelvic acceleration measures were reduced using a principal component analysis and combined with patient reported outcome measures and demographic variables in a support vector machine to retrospectively classify patient treatment response. Findings: The final classification model had 85.4% classification accuracy, which was significantly better than treatment success rate, with excellent detection rates for Responders (recall: 96.4%), but 23.1% of misclassifications among Non-responders (precision: 90.0%). Thus, it resulted in an F1-score of 0.93 and a Matthews correlation coefficient of 0.69. Interpretation: Overall, the classifier successfully separated patellofemoral pain patients into exercise-based treatment Responders and Non-responders based on a combination of three components of the pelvic accelerations. While this model requires independent validation, it has the potential for further development and to be applied in clinical practice and improve treatment strategies for patellofemoral pain.
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Validity and reliability of the Myotest Pro wireless accelerometer in squat jumps
Article
Full-text available
  • May 2013
BACKGROUND: Portable and cost-effective accelerometers can yield instantaneous results of force, power, and velocity, with minimum set-up time to assess muscle power. However, such devices must also produce both valid and reliable data. OBJECTIVE: The current study assessed the validity and reliability of the Myotest Pro wireless accelerometer (ACC). METHODS: Thirty physically active males performed two squat jump, on two separate sessions. The jump was recorded simultaneously by a force platform and ACC, which was attached to a barbell resting on the subjects' shoulders. Validity was determined using Pearson correlation coefficient (r) and t-test between the maximum force platform (F _{FP} ) and ACC (F _{ACC} ) force. Between session reliability of F _{ACC} , power (P _{ACC} ) and velocity (V _{ACC} ) from the ACC were assessed with t-test, intraclass correlation coefficient (ICC), and coefficient of variation (CV). RESULTS: F _{ACC} correlated highly to F _{FP} (r=0.815, p< 0.05), but there was a proportionate ratio bias of 0.81. There was no difference between sessions (p> 0.05) for any variable. High ICCs were found for all variables (F _{ACC} 0.90; P _{ACC} 0.80; V _{ACC} 0.84). Low CV was found for F _{ACC} (2.1%), P _{ACC} (3.3%) and V _{ACC} (3.2%). CONCLUSIONS: ACC is a valid and reliable tool to use for assessing barbell movement, but caution in power data interpretation is needed.
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The Optimization of Running Technique: What Should Runners Change and How Should They Accomplish it?
Article
Full-text available
  • Jan 2013
Aim To gather knowledge about interventions (i.e., training programs, running technique methods) aimed to enhance or optimise the running technique in recreational runners by means of reviewing the scientific literature and (2) to identify the barriers and facilitators that are related to learning and applying a natural running technique. Methods A systematic search of the scientific literature (Medline and SPORTDiscus) was conducted to identify relevant original studies. Subsequently, a qualitative research was conducted focusing on a specific and widely available natural running technique (Chi Running). Information was gathered from recreational runners who followed a Chi Running course by means of interviews and from Chi Running instructors participating in a focus group discussion. Results Based on 7 original studies identified, step frequency, in combination with other running technique elements (step length and foot strike pattern), the Pose method, and visual feedback about tibial acceleration were found to have a positive effect on ground reaction force, contact time foot-ground, compartment pressures, mechanical power-consumption and self-reported pain. None of the retrieved studies investigated the sustainability of the learned technique aspects. From the interviews and focus group discussion, several barriers in learning and applying a new running technique emerged. The barriers were related to the individual runner (such as a lack of patience), the running technique method itself (such as being too extensive to learn), and the environment (such as adverse reactions from coaches). Conclusion This study presents technique elements which could be beneficial for runners. Facilitators and barriers in learning and applying a running technique method were explored. This information is valuable in designing evidence-based interventions aimed at optimising running technique in recreational runners.
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Validity and reliability of the Myotest Pro wireless accelerometer
Conference Paper
Full-text available
  • Nov 2010
Assessing strength and power is crucial for evaluating muscular performance and function. As laboratory testing can be time-consuming or inaccessible to many athletes, portable accelerometers have been developed to assess strength and power on the field. Recently, a wireless accelerometer was introduced to allow for even greater flexibility in assessment. Nevertheless, any assessment tool must be valid and reliable. The aim of the current study was to assess the validity and reliability of a commercially available accelerometer. Forty-eight physically active subjects (males: n=32: age 30±9 years, height 1.79±0.12 m, body mass 82.0±14.3 kg; females: n=16: age 27±6 years, height 1.71±0.06 m, body mass 63.8±7.4 kg) completed two countermovement jump squats on a force plate (FP) with at least 1-min rest, on two separate occasions. The accelerometer was secured on a lightweight bar, which rested on the subjects' shoulders while jumping. The jump with the highest force generation was selected from each occasion for further analysis. Validity was determined from the Pearson correlation coefficient (r) between the accelerometer and the FP. Bias was also calculated, using a t test. Reliability was assessed by the intraclass correlation coefficient (ICC) and coefficient of variation (CV), while test-retest differences were examined with a t test. The accelerometer demonstrated significant and high correlation to the FP (p=0.001, r=0.85), while it overestimated force production by 7.8% (p=0.001). Repeatability for both devices was the same (ICC=0.87), with small CV (accelerometer=7.5%, FP=6.1%) and test-retest differences (accelerometer=0.1%, FP=1.1%). The results indicate that the Myotest Pro accelerometer is a valid and reliable tool for assessing force in the field. However, caution needs to be exercised when the results are compared to data obtained from a FP, as the Myotest Pro calculation method overestimates the maximum force produced.
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What are the Main Running-Related Musculoskeletal Injuries? A Systematic Review
Article
Full-text available
  • Jul 2012
Background: Musculoskeletal injuries occur frequently in runners and despite many studies about running injuries conducted over the past decades it is not clear in the literature what are the main running-related musculoskeletal injuries (RRMIs). Objective: The aim of this study is to systematically review studies on the incidence and prevalence of the main specific RRMIs. Methods: An electronic database search was conducted using EMBASE (1947 to October 2011), MEDLINE (1966 to October 2011), SPORTDiscus(1975 to October 2011), the Latin American and Caribbean Center on Health Sciences Information (LILACS) [1982 to October 2011] and the Scientific Electronic Library Online (SciELO) [1998 to October 2011] with no limits of date or language of publication. Articles that described the incidence or prevalence rates of RRMIs were considered eligible. Studies that reported only the type of injury, anatomical region or incomplete data that precluded interpretation of the incidence or prevalence rates of RRMIs were excluded. We extracted data regarding bibliometric characteristics, study design, description of the population of runners, RRMI definition, how the data of RRMIs were collected and the name of each RRMI with their rates of incidence or prevalence. Separate analysis for ultra-marathoners was performed. Among 2924 potentially eligible titles, eight studies (pooled n = 3500 runners) were considered eligible for the review. In general, the articles had moderate risk of bias and only one fulfilled less than half of the quality criteria established. Results: A total of 28 RRMIs were found and the main general RRMIs were medial tibial stress syndrome (incidence ranging from 13.6% to 20.0%; prevalence of 9.5%), Achilles tendinopathy (incidence ranging from 9.1% to 10.9%; prevalence ranging from 6.2% to 9.5%) and plantar fasciitis (incidence ranging from 4.5% to 10.0%; prevalence ranging from 5.2% to 17.5%). The main ultra-marathon RRMIs were Achilles tendinopathy (prevalence ranging from 2.0% to 18.5%) and patellofemoral syndrome (prevalence ranging from 7.4% to 15.6%). Conclusion: This systematic review provides evidence that medial tibia stress syndrome, Achilles tendinopathy and plantar fasciitis were the main general RRMIs, while Achilles tendinopathy and patellofemoral syndrome were the most common RRMIs for runners who participated in ultra-marathon races.
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Clinical Gait Analysis
Article
  • Jan 2006
The study of human gait is vital to the work of podiatrists, physiotherapists, orthotists and many others, yet due to its complexity it can appear daunting to the non-expert. Clinical Gait Analysis takes a fresh look at the subject, founded on the authors long experience of teaching and researching biomechanics. In the course of a comprehensive review of biomechanical principles, techniques and clinical approaches to the assessment of walking disorders, Dr Kirtley strips away the dryness and obscurity that often accompanies such surveys and provides a clear, informed and stimulating account. Both theory and practice are brought into focus, and currently contentious issues are highlighted in order to encourage critical thinking. The multiple choice questions scattered throughout the book provide the reader with the opportunity to test their knowledge of some of the more challenging sections. Comprehensive, stimulating and highly readable Written with student needs to the fore Unites theory and practice Authored by an MD PhD Contains test-yourself quizzes.
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Measurement in Medicine: A Practical Guide
Article
  • Sep 2011
The success of the Apgar score demonstrates the astounding power of an appropriate clinical instrument. This down-to-earth book provides practical advice, underpinned by theoretical principles, on developing and evaluating measurement instruments in all fields of medicine. It equips you to choose the most appropriate instrument for specific purposes. The book covers measurement theories, methods and criteria for evaluating and selecting instruments. It provides methods to assess measurement properties, such as reliability, validity and responsiveness, and interpret the results. Worked examples and end-of-chapter assignments use real data and well-known instruments to build your skills at implementation and interpretation through hands-on analysis of real-life cases. All data and solutions are available online. This is a perfect course book for students and a perfect companion for professionals/researchers in the medical and health sciences who care about the quality and meaning of the measurements they perform. © H. C. W. de Vet, C. B. Terwee, L. B. Mokkink and D. L. Knol 2011.
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What We Can Learn About Running from Barefoot Running
Article
  • Dec 2011
Abstract Barefoot running, which was how people ran for millions of years, provides an opportunity to study how natural selection adapted the human body to run. Because humans evolved to run barefoot , a barefoot running style that minimizes impact peaks and ...
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Stide frequency in relation to oxygen consumption in experienced and novice runners
Article
Abstract We hypothesised that experienced runners would select a stride frequency closer to the optimum (minimal energy costs) than would novice runners. In addition, we expected that optimal stride frequency could simply be determined by monitoring heart rate without measuring oxygen consumption ([Formula: see text]O2). Ten healthy males (mean±s: 24±2 year) with no running training experience and 10 trained runners of similar age ran at constant treadmill speed corresponding to 80% of individual ventilatory threshold. For two days, they ran at seven different stride frequencies (self-selected stride frequency±18%) imposed by a metronome. Optimal stride frequency was based on the minimum of a second-order polynomial equation fitted through steady state [Formula: see text]O2 at each stride frequency. Running cost (mean±s) at optimal stride frequency was higher (P < 0.05) in novice (236±31 ml O2·kg(-1.)km(-1)) than trained (189±13 ml O2·kg(-1.)km(-1)) runners. Self-selected stride frequency (mean±s; strides(.)min(-1)) for novice (77.8±2.8) and trained runners (84.4±5.3) were lower (P < 0.05) than optimal stride frequency (respectively, 84.9±5.0 and 87.1±4.8). The difference between self-selected and optimal stride frequency was smaller (P < 0.05) for trained runners. In both the groups optimal stride frequency established with heart rate was not different (P > 0.3) from optimal stride frequency based on [Formula: see text]O2. In each group and despite limited variation between participants, optimal stride frequencies derived from [Formula: see text]O2 and heart rate were related (r > 0.7; P < 0.05). In conclusion, trained runners chose a stride frequency closer to the optimum for energy expenditure than novices. Heart rate could be used to establish optimal stride frequency.
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