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This aim of this study was to compare the reliability and validity of seven commercially available devices to measure movement velocity during the bench press exercise. Fourteen men completed two testing sessions. The bench press one-repetition maximum (1RM) was determined in the first session. The second testing session consisted of performing three repetitions against five loads (45-55-65-75-85% of 1RM). The mean velocity was simultaneously measured using an optical motion sensing system (Trio-OptiTrack™; “gold-standard”) and seven commercially available devices: 1 linear velocity transducer (T-Force™), 2 linear position transducers (Chronojump™ and Speed4Lift™), 1 camera-based optoelectronic system (Velowin™), 1 smartphone application (PowerLift™), and 2 inertial measurement units (PUSH™ band and Beast™ sensor). The devices were ranked from the most to the least reliable as follows: (I) Speed4Lift™ (coefficient of variation [CV] = 2.61%), (II) Velowin™ (CV = 3.99%), PowerLift™ (3.97%), Trio-OptiTrack™ (CV = 4.04%), T-Force™ (CV = 4.35%), Chronojump™ (CV = 4.53%), (III) PUSH™ band (CV = 9.34%), and (IV) Beast™ sensor (CV = 35.0%). A practically perfect association between the Trio-OptiTrack™ system and the different devices was observed (Pearson’s product-moment correlation coefficient (r) range = 0.947-0.995; P < 0.001) with the only exception of the Beast sensor (r = 0.765; P < 0.001). These results suggest that linear velocity/position transducers, camera-based optoelectronic systems and the smartphone application could be used to obtain accurate velocity measurements for restricted linear movements, while the inertial measurement units used in this study were less reliable and valid.
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Original Research
Reliability and Concurrent Validity of Seven
Commercially Available Devices for the
Assessment of Movement Velocity at Different
Intensities During the Bench Press
Alejandro erez-Castilla,
1
Antonio Piepoli,
2
Gabriel Delgado-Garc´
ıa,
1
Gabriel Garrido-Blanca,
2
and
Amador Garc´
ıa-Ramos
1,3
1
Department of Physical Education and Sport, Faculty of Sport Sciences, University of Granada, Granada, Spain;
2
Department of
Health Sciences, Faculty of Health Sciences, University of Jaen, Jaen, Spain; and
3
Department of Sports Sciences and Physical
Conditioning, Faculty of Education, CIEDE, Catholic University of the Most Holy Concepci ´on, Concepci ´on, Chile
Abstract
erez-Castilla, A, Piepoli, A, Delgado-Garc´
ıa, G, Garrido-Blanca, G, and Garc´
ıa-Ramos, A. Reliability and concurrent validity of
seven commercially available devices for the assessment of movement velocity at different intensities during the bench press. J
Strength Cond Res XX(X): 000–000, 2019—The aim of this study was to compare the reliability and validity of 7 commercially
available devices to measure movement velocity during the bench press exercise. Fourteen men completed 2 testing sessions.
One-repetition maximum (1RM) in the bench press exercise was determined in the first session. The second testing session
consisted of performing 3 repetitions against 5 loads (45, 55, 65, 75, and 85% of 1RM). The mean velocity was simultaneously
measured using an optical motion sensing system (Trio-OptiTrack; “gold-standard”) and 7 commercially available devices: 1 linear
velocity transducer (T-Force), 2 linear position transducers (Chronojump and Speed4Lift), 1 camera-based optoelectronic system
(Velowin), 1 smartphone application (PowerLift), and 2 inertial measurement units (IMUs) (PUSH band and Beast sensor). The
devices were ranked from the most to the least reliable as follows: (a) Speed4Lift (coefficient of variation [CV] 52.61%); (b) Velowin
(CV 53.99%), PowerLift (3.97%), Trio-OptiTrack (CV 54.04%), T-Force (CV 54.35%), and Chronojump (CV 54.53%); (c) PUSH
band (CV 59.34%); and (d) Beast sensor (CV 535.0%). A practically perfect association between the Trio-OptiTrack system and
the different devices was observed (Pearson’s product-moment correlation coefficient (r) range 50.947–0.995; p,0.001) with the
only exception of the Beast sensor (r50.765; p,0.001). These results suggest that linear velocity/position transducers, camera-
based optoelectronic systems, and the smartphone application could be used to obtain accurate velocity measurements for
restricted linear movements, whereas the IMUs used in this study were less reliable and valid.
Key Words: linear position transducer, linear velocity transducer, smartphone application, inertial measurement units, velocity-
based training, testing
Introduction
Velocity-based resistance training has gained in popularity over
recent years because of the proliferation of different commercially
available devices (e.g., linear position transducers, inertial mea-
surement units [IMUs], smartphone applications, etc.) that are
supposed to accurately measure movement velocity (3,5). It has
been proposed that the monitoring of barbell velocity could be an
appropriate alternative to prescribe the training load as compared
to the traditional approach that requires the determination of the
1 repetition maximum (1RM) (17,32). The use of movement
velocity to prescribe the training load is justified by the strong and
linear relationship that has been reported for multiple exercises
between movement velocity and the %1RM (13,26,31). In this
regard, instead of determining the 1RM through a single maximal
lift or by a set of repetitions to failure, the load can be prescribed
to match the desired velocity (17,34). Despite the encouraging
applications of velocity-based resistance training (6), little
research is available comparing the reliability and validity of
different commercially available devices used in training and re-
search to monitor movement velocity.
From a scientific standpoint, the three-dimensional (3D) mo-
tion capture has been recognized as the gold-standardin-
strument to measure movement velocity (22,36). However,
because this technology is not practical or affordable for strength
and conditioning professionals, other devices are typically used in
practice when implementing the velocity-based resistance training
approach. The linear position transducer has been the most used
device in scientific research (2,5,10,14). The linear position
transducer consists of an isoinertial dynamometer with a cable
that is typically attached to the barbell, and it derives velocity
from the recorded displacement-time data using the inverse dy-
namic approach (18). More recently, a linear velocity transducer
named T-Force(T-Force system; Ergotech, Murcia, Spain) has
been made commercially available, which directly provides ve-
locity measurements through the recording of electrical signals
that are proportional to the cables extension velocity (33). It is
reasonable to speculate that the linear velocity transducer could
be more precise than linear position transducers because it is
Address correspondence to Amador Garc ´
ıa-Ramos, amagr@ugr.es.
Journal of Strength and Conditioning Research 00(00)/1–8
ª2019 National Strength and Conditioning Association
1
Copyright © 2019 National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
known that the successive manipulation of raw data increases
measurement errors (25,30). However, it remains unexplored
whether the reliability of velocity outputs significantly differs
between linear position and linear velocity transducers, as well as
their concurrent validity with respect to the gold-standard3D
motion capture.
It should be acknowledged that linear position/velocity trans-
ducers are not always practical or affordable. The need to attach
the cable to the barbell restricts exercise selection to the ones
predominantly performed in a vertical direction (5). Another
common drawback of linear position/velocity transducers is their
high price (2,000 US dollars), which may limit their use to
laboratory-based or professional sport settings (7,23,24). How-
ever, it should be noted that a new linear position transducer
named Speed4Lift(Speed4Lift
AU1 ; Madrid, Spain) has appeared
on the market with a considerably lower price (340 US dollars),
although there are no available data regarding its reliability and
validity. As an alternative to linear position/velocity transducers,
wearable technologies are increasingly gaining popularity in the
field of strength training and conditioning (3,5,12,28).
One of the wearable devices that have recently appeared on the
market is named Velowin(Velowin; DeporTeC, Murcia,
Spain). Velowin is a camera-based optoelectronic system
designed to measure movement velocity by the tracking of an
infrared reflective marker placed in the barbell. A high reliability
and concurrent validity of the Velowin to measure movement
velocity has been reported during the free-weight back squat ex-
ercise (12,21). The main advantage of Velowin as compared to
linear position/velocity transducers is that it does not require to be
attached to the barbell through a cable and, therefore, this would
eliminate the risk of cable rupture (21). However, the Velowin
cost (625 US dollars) and limited portability (e.g., a PC software
is needed) could limit its use for many strength and conditioning
professionals. Many practitioners can only afford more practical
devices such as smartphone applications or IMUs (2,28).
A smartphone application named PowerLifthas been
designed to monitor movement velocity by the manual inspection
of a slow motion video recording by the smartphone high-speed
camera (4). The high reliability and validity of PowerLift to
monitor mean velocity has been confirmed in exercises such as the
bench press, full-squat, and hip-thrust (3,4). However, the main
limitation of PowerLift is that it does not provide real-time ve-
locity feedback because coaches are required to indicate manually
the start and end of the concentric phase. The PUSH band (PUSH
band, PUSH, Inc., Toronto, Canada) and Beast sensor (Beast
sensor, Beast Technologies Srl., Brescia, Italy), which are com-
posed by the combination of 3-axis accelerometers and 3-axis
gyroscopes, are 2 of the IMUs most commonly used in research
and practice (3,5). An advantage of IMUs is that they are able to
account for the anteroposterior displacement that is frequent
during free-weight exercises (28), whereas linear position/velocity
transducer cannot distinguish the direction of the cable dis-
placement. However, owing to the discrepancies found between
the studies that have evaluated the validity of the PUSH band
(3,5,36) and owing to the scarce number of studies that have
examined the reliability and validity of the Beast sensor (3), more
research is needed to explore the feasibility of both IMU devices.
To address the existing gaps in the literature, this study was
designed to provide a comprehensive analysis of different devices
(i.e., linear velocity transducer, linear position transducers,
camera-based optoelectronic system, smartphone application,
and IMUs) that are being used in practice for the measurement of
movement velocity during resistance training. Specifically, the
objective of this study was to compare the reliability and validity
of 7 commercially available devices to measure movement ve-
locity during the bench press exercise. We hypothesized that the
devices would be ranked from the most to the least reliable and
valid as follows: (a) linear velocity transducer; (b) linear position
transducers; (c) camera-based optoelectronic device; (d) smart-
phone application; and (e) IMUs. The results of this study should
provide practical information for strength and conditioning
coaches regarding the reliability and concurrent validity of dif-
ferent devices that can be used in practice for the assessment of
movement velocity.
Methods
Experimental Approach AU2to the Problem
This study was designed to explore the reliability and concurrent
validity of 7 commercially available devices for the measurement
of movement velocity. Subjects completed 2 testing sessions sep-
arated by 4872 hours. The 1RM in the bench press exercise was
determined in the first testing session. The second testing session
consisted of performing 3 repetitions against 5 different loads (45,
55, 65, 75, and 85% of 1RM). The mean velocity of the barbell
was measured using an optical motion sensing system (V120:
Trio, OptiTrack; NaturalPoint, Inc. AU3, USA) that was considered
the gold standard in this study (27,38). In addition, the mean
velocity was also measured by 7 commercially available devices: 1
linear velocity transducer (T-Force system, Ergotech), 2 linear
position transducers (Chronojump; Boscosystem, Barcelona,
Spain; and Speed4Lift), 1 camera-based optoelectronic system
(Velowin, DeporTeC), 1 smartphone application (PowerLift),
and 2 IMUs (PUSH band; PUSH, Inc., and Beast sensor; Beast
Technologies Srl.). The 2 repetitions with higher mean velocity
recorded by the Trio-OptiTrack at each load were used for cal-
culating intrasession reliability (3,21), whereas only the repetition
with the highest mean velocity recorded at each load by the Trio-
OptiTrack was used for validity analyses.
Subjects
Fourteen physically AU4active men (age: 22.9 61.6 years; body
height: 1.76 60.06 m; body mass: 76.9 67.8 kg; bench AU5press
1RM: 86.1 611.9 kg) volunteered to participate in this study.
Subjects were recruited from a fitness center, and all of them AU6were
familiarized with the bench press exercise before the beginning of
the study. None of them suffered from physical limitations, health
problems, or musculoskeletal injuries that could compromise
tested performance. Subjects were instructed to avoid any stren-
uous exercise 2 days before each testing session. They were in-
formed of the study procedures and signed a written informed
consent form before initiating the study. The study protocol ad-
hered to the tenets of the Declaration of Helsinki and was ap-
proved by the institutional review board.
Testing Procedures AU7.The first testing session was used for an-
thropometric measures and to determine the 1RM during the
concentric-only bench press exercise following an incremental
loading test (11). The standardized warm-up consisted of jogging,
self-selected dynamic stretching and joint mobilization exercises,
and 1 set of 5 repetitions performed against external load of 17 kg
(mass of the unloaded Smith machine barbell) during the bench
press exercise. Thereafter, the external load was incremented
from 10 AU8to 1 kg until the 1RM load was reached. The average
Feasibility of Seven Devices to Measure Velocity (2019) 00:00
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number of loads tested was 8.9 61.3. The interset rest was set to 4
minutes, and 12 repetitions were performed with each load.
The second testing session beganwiththesamewarm-up
described for session 1. Afterward, subjects performed the
concentric-only bench press exercise against 5 relative loads
(45, 55, 65, 75, and 85% of 1RM) that were implemented in an
incremental order. Lower loads (i.e., ,45%of1RM)werenot
tested because they are generally not used in training with the
bench press exercise, whereas higher loads (i.e., .85% of
1RM) were excluded to avoid high fatigue that could com-
promise reliability analyses. Three repetitions were executed
with each load. Interrepetition rest was set to 15 seconds, and
interset rest was fixed to 4 minutes. The barbell was held by the
safety stops of the Smith machine during the recovery periods.
Subjects were encouraged to lift the barbell at the maximum
possible velocity.
The standard 5-point body contact position technique (head,
upper back, and buttocks firmly on the bench with both feet flat
on the floor) was followed in the 2 testing sessions. Subjects self-
selected the grip width, which was measured and kept constant on
every lift. The barbell was held by the safety stops of the Smith
machine 12 cm above the subjectschest at the level of the
sternum. From that position, subjects were instructed to perform
a concentric-only movement as fast as possible until their elbows
reached full extension. Two spotters were responsible for low-
ering the barbell after each repetition.
Measurement Equipment and Data Acquisition. The measure-
ment devices were not synchronized, and they separately collected
the mean velocity of the same repetitions (
½F1Figure 1). The specific
characteristics of each device are provided below:
Trio-OptiTrack. Trio-OptiTrack (V120:Trio; OptiTrack, Natu-
ralPoint, Inc.) is an optical motion sensing system, which included
3 infrared and precalibrated cameras fixed on a rectangular frame
that gives 3D position data of a reflective marker at a sampling
rate of 120 Hz. Raw data of marker position in space were ac-
quired using the software Motive v.1.5.0 (OptiTrack, Natural-
Point, Inc.) and then analyzed in Microsoft Excel (Microsoft,
Seattle, WA, USA). Instantaneous velocity was calculated by the
differentiation of the displacement data with respect to time. The
reflective marker was placed on the left side of the barbell, and the
Trio-OptiTrack was positioned at a distance of 2.5 m from the
marker.
T-Force. T-Force (T-Force system, Ergotech) is an isoinertial dy-
namometer that consists of a cable-extension linear velocity
transducer interfaced with a personal computer by means of a 14-
bit resolution analog-to-digital data acquisition board. In-
stantaneous velocity was automatically calculated at a sampling
rate of 1,000 Hz by the custom software v.2.28. The cable was
vertically attached to the right side of the barbell using a Velcro
strap.
Chronojump. Chronojump (Chronojump Boscosystem, Barce-
lona, Spain) is an isoinertial dynamometer that consists of a cable-
extension linear position transducer attached to the barbell
interfaced with a personal computer at a sampling rate of 1,000
Hz. Raw data were exported from the custom software v.1.6.2
and then analyzed in Microsoft Excel (Microsoft). Instantaneous
velocity was calculated by the differentiation of the displacement
data with respect to time. The cable was vertically attached to the
right side of the barbell using a Velcro strap.
Speed4Lift. Speed4Lift (Speed4Lift) is an isoinertial dynamome-
ter that consists of a cable-extension linear position transducer
attached to the barbell. Data were directly recorded by the dif-
ferentiation of the displacement data with respect to time at
a sampling rate of 1,000 Hz through Wi-Fi connection with an
Android smartphone using Speed4Lift application v.4.1. The
cable was vertically attached to the left side of the barbell using
a Velcro strap.
Velowin. Velowin (Velowin; DeporTeC) is an optoelectronic
system, which included an infrared camera interfaced with
a personal computer that measured displacement of a reflector
fixed to the barbell. Data were directly recorded from the custom
software v.1.6.314 by the differentiation of the displacement data
with respect to time at a sampling rate of 500 Hz. The Velowin
was placed at a distance of 1.7 m from the infrared reflector, and it
was calibrated according to the manufacturers instructions.
PowerLift. PowerLift is a smartphone v.6.0.1 application that
involves a frame-by-frame manual inspection of a slow motion
video recording by the smartphone high-speed camera at a fre-
quency of 240 frames per second and a quality of 720 pixels. The
mean velocity was computed as the individual range of motion
(i.e., vertical displacement of the barbell from the initial [1cm
above the subjects chest] to the final [elbows at full extension]
position) divided by the lifting time (i.e., time between 2 frames
selected by the user). The smartphone (iPhone; Apple, Inc., CA,
USA) was held by a researcher in a portrait position and
recorded each lift from the front of the subject at approxi-
mately 1.5 m.
PUSH Band. PUSH band (PUSH band, PUSH, Inc.) is a wearable
wireless IMUs that consist of a 3-axis accelerometer and a gyro-
scope that provided 6 degrees of freedom in its coordinate system
(2). Data were directly recorded by the integration of the accel-
eration data with respect to time at a sampling rate of 200 Hz
through Bluetooth 4.0 LE connection with a smartphone (iPhone,
Apple, Inc.) using PUSH application v.1.1.26. The PUSH band
Figure 1. Distribution of the measurement devices during the
testing protocol: (1) Trio-OptiTrack, (2) T-Force, (3) Chro-
nojump, (4) Speed4Lift, (5) Velowin, (6) PowerLift, (7) PUSH
band, and (8) Beast sensor.
Feasibility of Seven Devices to Measure Velocity (2019) 00:00 |www.nsca.com
3
Copyright © 2019 National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
was worn on the subjects dominant forearm immediately inferior
to the elbow crease with the main button located proximally (2,5).
Beast Sensor. Beast sensor (Beast sensor, Beast Technologies Srl.)
is a wearable wireless IMUs that included a 3-axis accelerometer,
gyroscope, and magnetometer. Data were directly recorded by the
integration of the vertical acceleration with respect to time at
a sampling rate of 50 Hz through Bluetooth 4.0 LE connection
with a smartphone (iPhone, Apple, Inc.) using Beast application
v.2.3.7. The Beast sensor was placed on the barbell using a built-
in magnet (3).
Statistical Analyses
Descriptive data are presented as means and SDs, whereas the
coefficient of variation (CV) of the 5 loads is presented through
their median value. Reliability was assessed for each individual
load by the CV and the intraclass correlation coefficient (ICC
model 3,1). Acceptable reliability was determined as a CV ,10%
and an ICC .0.70 (8). The median CV value of the 5 loads was
calculated to compare the reliability between the 8 devices ex-
amined in this study. To interpret the magnitude of differences
observed between 2 CVs, a criterion for the smallest important
ratio was established as higher than 1.15 (37). Bland-Altman
plots were constructed to explore the concurrent validity of the 7
commercially available devices with respect to the Trio-
OptiTrack system. Because we observed proportional bias in 6
of 7 comparisons (r
2
.0.1) (1), the data were log transformed
before calculating the Pearsons product-moment correlation
coefficients (r) (19). The criteria to interpret the strength of the r
coefficients were as follows: trivial (,0.1), small (0.10.3),
moderate (0.30.5), high (0.50.7), very high (0.70.9), or
practically perfect (.0.9) (19). Statistical significance was ac-
cepted at the p,0.05 level, and confidence limits were set at
95%. All reliability assessments were performed by means of
a custom spreadsheet (20), whereas other statistical analyses were
performed using the software package SPSS (IBM SPSS version
22.0, Chicago, IL, USA).
Results
Mean velocity values only reached an acceptable reliability at all
loads for the Trio-OptiTrack system, the linear velocity/position
transducers, and the smartphone application (CV ,6.24% and
ICC .0.73) (
½T1Table 1). Based on the comparison of the median
CVs of the 5 loads, the devices were ranked from the most to the
least reliable as follows: (a) Speed4Lift (CV 52.61%); (b) Velo-
win (CV 53.99%), PowerLift (3.97%), Trio-OptiTrack (CV 5
4.04%), T-Force (CV 54.35%), and Chronojump (CV 5
4.53%); (c) PUSH band (CV 59.34%); and (d) Beast sensor (CV
535.0%).
Bland-Altman plots revealed low systematic bias and random
errors (#0.05 m·s
21
) for the T-Force, Chronojump, Speed4Lift,
Velowin, and PowerLift as compared to the Trio-OptiTrack
system (
½F2Figure 2). Both IMUs showed larger random errors
(PUSH band 50.06 m·s
21
and Beast sensor 50.21 m·s
21
).
Heteroscedasticity of the errors was observed for all devices with
the only exception of the Speed4Lift (r
2
50.007). A practically
perfect association between the Trio-OptiTrack system and the
different devices was observed (rrange 50.9470.995; p,
0.001) with the only exception of the Beast sensor (r50.765; p,
0.001) (
½F3Figure 3).
Discussion
This study compared the reliability and concurrent validity of 7
commercially available devices for the measurement of movement
velocity during the bench press exercise performed in a Smith
machine. The different devices were ranked from the most to the
least reliable as follows: (a) Speed4Lift; (b) Velowin, PowerLift, T-
Force, and Chronojump; (c) PUSH band; and (d) Beast sensor.
The concurrent validity of the T-Force, Chronojump, Speed4Lift,
Velowin, and PowerLift with respect to the Trio-OptiTrack sys-
tem was practically perfect. The 2 IMUs, especially the Beast
sensor, showed the lowest concurrent validity (i.e., lower rcoef-
ficients and larger random errors) as compared to the Trio-
OptiTrack system. The Speed4Lift was the only device that did
not report heteroscedasticity of errors. The results of this study
speak in favor of the Speed4Lift as the most reliable and valid
device for the measurement of movement velocity during the
Table 1
Reliability of mean velocity values obtained from the Trio-
OptiTrack method and 7 commercially available devices at
different loads during the bench press exercise.*
Device
Load
(%1RM)
Mean velocity
(m·s
21
) CV (95% CI) ICC (95% CI)
Trio-OptiTrack 45 0.84 60.05 3.47 (2.52–5.59) 0.73 (0.35–0.90)
55 0.71 60.05 2.22 (1.57–3.76) 0.93 (0.79–0.98)
65 0.58 60.05 4.04 (2.93–6.50) 0.84 (0.57–0.95)
75 0.46 60.05 4.15 (2.98–6.85) 0.83 (0.54–0.95)
85 0.35 60.05 4.64 (3.37–7.48) 0.88 (0.67–0.96)
T-Force 45 0.83 60.06 2.48 (1.78–4.09) 0.90 (0.70–0.97)
55 0.70 60.05 1.82 (1.32–2.93) 0.95 (0.84–0.98)
65 0.59 60.05 4.35 (3.15–7.01) 0.78 (0.45–0.93)
75 0.49 60.05 4.78 (3.43–7.89) 0.77 (0.40–0.92)
85 0.37 60.05 4.90 (3.55–7.90) 0.87 (0.64–0.96)
Chronojump 45 0.90 60.05 2.31 (1.67–3.72) 0.87 (0.64–0.96)
55 0.76 60.05 2.09 (1.51–3.36) 0.90 (0.71–0.97)
65 0.60 60.07 6.24 (4.47–10.3) 0.72 (0.31–0.90)
75 0.47 60.06 4.53 (3.25–7.48) 0.85 (0.58–0.95)
85 0.34 60.05 5.65 (4.05–9.32) 0.86 (0.60–0.95)
Speed4Lift 45 0.88 60.06 2.61 (1.80–4.77) 0.87 (0.55–0.96)
55 0.75 60.04 2.39 (1.73–3.85) 0.84 (0.57–0.94)
65 0.63 60.05 2.42 (1.69–4.25) 0.93 (0.78–0.98)
75 0.51 60.05 3.92 (2.81–6.47) 0.81 (0.49–0.94)
85 0.38 60.05 3.41 (2.38–5.98) 0.94 (0.78–0.98)
PowerLift 45 0.79 60.04 2.85 (2.02–4.83) 0.84 (0.55–0.95)
55 0.70 60.06 3.97 (2.81.6.74) 0.85 (0.57–0.96)
65 0.58 60.05 4.91 (3.48–8.33) 0.74 (0.32–0.92)
75 0.51 60.05 3.69 (2.58–6.48) 0.87 (0.58–0.96)
85 0.40 60.04 4.97 (3.47–8.71) 0.85 (0.54–0.96)
Velowin 45 0.91 60.06 2.89 (2.09–4.65) 0.83 (0.56–0.94)
55 0.77 60.05 3.27 (2.35–5.40) 0.79 (0.45–0.93)
65 0.64 60.06 3.99 (2.86–6.59) 0.83 (0.53–0.94)
75 0.51 60.05 6.01 (4.36–9.69) 0.68 (0.26–0.89)
85 0.38 60.06 7.64 (5.54–12.3) 0.69 (0.27–0.89)
PUSH band 45 0.79 60.07 5.02 (3.56–8.52) 0.69 (0.22–0.89)
55 0.63 60.07 7.84 (5.39–14.3) 0.46 (20.27–0.81)
65 0.46 60.08 9.34 (6.77–15.0) 0.78 (0.45–0.92)
75 0.31 60.06 14.6 (10.0–26.6) 0.50 (20.21–0.82)
85 0.24 60.06 19.1 (13.7–31.5) 0.47 (20.09–0.80)
Beast sensor 45 0.82 60.32 33.4 (23.5–58.9) 0.29 (20.42–0.72)
55 0.70 60.27 24.2 (15.6–53.2) 0.64 (20.28–0.89)
65 0.51 60.21 35.0 (22.6–77.1) 0.30 (20.91–0.77)
75 0.34 60.16 40.2 (28.1–70.5) 0.31 (20.40–0.73)
85 0.23 60.15 54.9 (38.9–93.2) 0.27 (20.38–0.70)
*1RM 51 repetition maximum; CV 5coefficient of variation; 95% CI 595% confidence interval;
ICC 5intraclass correlation coefficient.
Feasibility of Seven Devices to Measure Velocity (2019) 00:00
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bench press exercise performed in a Smith machine. Collectively,
the results of this study suggest that all devices, with the exception
of the IMUs (especially the Beast sensor), could be used to obtain
accurate velocity measurements for restricted linear movements.
However, strength and conditioning professionals should be
aware of the presence of heteroscedasticity between these devices,
which could limit the interchangeable use of different devices.
Linear position/velocity transducers have been routinely used
for training and testing purposes (5,16,29). These devices have
been considered the gold-standardto measure barbell velocity
Figure 2. Bland-Altman plots for the measurement of mean velocity between the Trio-OptiTrack system and
the 7 commercially available devices: T-Force (upper-left panel), Chronojump (upper-right panel), Speed4Lift
(upper middle-left panel), Velowin (upper middle-right panel), PowerLift (lower middle-left panel), PUSH band
(lower middle-right panel), and Beast sensor (lower panel). Each plot depicts the averaged difference and
95% limits of agreement (dashed lines), along with the regression line (solid line).
Feasibility of Seven Devices to Measure Velocity (2019) 00:00 |www.nsca.com
5
Copyright © 2019 National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
in many studies (2,3,5). Specifically, the linear velocity transducer
used in this study (T-Force) has been frequently used to validate
other devices that were designed to measure movement velocity
(2,14,15). The preferential use of linear velocity transducers as
compared to linear position transducers could be justified because
the direct measurement of movement velocity is expected to
provide more accurate velocity outputs (30). However, there is
scarce information regarding the comparison of the reliability of
velocity outputs between linear velocity and linear position
transducers. Contrary to our hypothesis, the linear velocity
Figure 3. Relationship of mean velocity values between the Trio-OptiTrack system and the 7 com-
mercially available devices: T-Force (upper-left panel), Chronojump (upper-right panel), Speed4Lift
(upper middle-left panel), Velowin (upper middle-right panel), PowerLift (lower middle-left panel), PUSH
band (lower middle-right panel), and Beast sensor (lower panel). The Pearson’s correlation coefficient (r)
was calculated using the log transformation because the assumption of homoscedasticity was violated.
Feasibility of Seven Devices to Measure Velocity (2019) 00:00
6
Copyright © 2019 National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
transducer (i.e., T-Force) was not more reliable than the 2 linear
position transducers used in this study (i.e., Chronojump and
Speed4Lift). In addition, to the best of our knowledge, this is the first
scientific article that has provided data regarding the validity of the
Chronojump and Speed4Lift. It should be noted that the Speed4Lift
was the most reliable device and the only device that did not report
heteroscedasticity of errors with respect to the Trio-OptiTrack sys-
tem. These results together with its lower price (340 US dollars)
and excellent portability (the software is installed in a smartphone
app that is wirelessly connected with the hardware) place the
Speed4Lift as an accurate, cost-effective, and practical device for
the measurement of movement velocity. It is worth noting that the
heteroscedasticity of errors observed for the other devices com-
promises their interchangeability. The T-Force and PowerLift
showed progressively larger values than the Trio-OptiTrack with
increasing velocities, whereas opposite results were observed for the
Chronojump, Velowin, PUSH band, and Beast sensor.
The Velowin has been recently developed as a more affordable
and practical device to measure movement velocity during re-
sistance training exercises. However, to date, only 2 studies have
examined its reliability and concurrent validity to measure move-
ment velocity. Garc´
ıa-Ramos et al. (12) found a comparable re-
liability (CV 54.294.60%) and high validity (r50.970.98)
between the T-Force and Velowin systems during the free-weight
back-squat exercise. Laza-Cagigas et al (21). also observed a high
validity (concordant correlation coefficient 50.96) and reliability
(CV 57.3% and ICC 50.97)oftheVelowinsystemtomeasure
mean velocity during the free-weight back-squat exercise with re-
spect to a 3D system. In line with these findings, our results showed
a high and comparable reliability and validity of the Velowin system
as compared to the data provided by linear position/velocity
transducers during the bench press exercise performed in a Smith
machine. More recently, an affordable (11 US dollars) smart-
phone application named PowerLift has been made commercially
available to measure movement velocity. The results of this study
corroborate the findings of Balsalobre-Fern ´
andez et al. who showed
a comparable reliability (ICC 50.930.99) and high validity (r5
0.940.98) of PowerLift with respect to the data provided by a lin-
ear position transducer (SmartCoach Europe, Stockholm, Sweden)
during free-weight exercises (3,4). Although it should be acknowl-
edged that it is possible to obtain accurate measurements of mean
velocity with PowerLift, the necessity of individually selecting the
start and end points of each repetition may be unpractical when
many athletes need to be assessed. In addition, the no provision of
real-time velocity feedback should also be considered a limitation
compared with the other devices analyzed in this study (39).
Wearable technologies such as the PUSH band and Beast sensor
are being increasingly used in the strength and conditioning field.
These 2 IMUs have been recently validated to measure movement
velocity during a variety of resistance training exercises (2,3,5,36). In
line with our results, the PUSH band provided highly valid meas-
urements of mean velocity when the data of several loads were
combined for the analysis during the bench press performed in
a Smith machine and during the free-weight shoulder press and
biceps/arm curl exercises (r.0.86) (2,36). However, the validity of
the PUSH band seems to be compromised when the data of in-
dividual loads are analyzed separately (specially for loads $80% of
1RM) (5). The PUSH band device should be therefore considered
with some caution given the controversial results and the lower re-
liability reported in this study. Regarding the Beast sensor, to the best
of our knowledge, only 1 study has investigated the reliability and
validity of this device with respect to the data provided by a linear
position transducer (SmartCoach Europe), reporting both a very
high reliability (ICC .0.95) and validity (r.0.98) during the bench
press, full-squat, and hip-thrust exercises (3). On the contrary, our
results suggest that the Beast sensor is the least reliable and valid
device among all the commercially available devices analyzed in this
study. It is plausible that the lower sampling frequencies of the IMUs
or the need to integrate acceleration-time data to obtain velocity
values could have caused their lower reliability (5,28). Therefore,
more evidence about the feasibility of wearable technology in the
field of velocity-based resistance training is needed.
Several limitations and directions for future research should be
considered. First, it should be noted that the mean velocity is not
the only velocity variable used in practice. The mean propulsive
velocity (i.e., average velocity from the start of the concentric
phase until the acceleration of the bar is lower than gravity) and
maximum velocity (i.e., maximum instantaneous velocity value
reached during the concentric phase) have been commonly rec-
ommended for training and testing (9,35). Therefore, future
studies should consider expanding the analysis of the reliability
and validity of different devices to these variables. It should be
noted that the mean velocity was the only variable analyzed in this
study because it was the only common variable for the 8 devices
analyzed. Second, the PUSH band was placed on the subjects
forearm, whereas the other devices were attached to the barbell.
Therefore, although the measurement of the PUSH could be af-
fected by anteroposterior movements, the displacement of the
other devices was restricted to the vertical direction. Another
factor that could have promoted the lower reliability and validity
of the IMUs is their lower sampling frequency. In this regard, it is
plausible that the reliability and validity of the PUSH could be
improved with the current 2.0 version, which has a higher sam-
pling frequency (1,000 Hz), and it can be directly attached to the
barbell. Future studies should examine whether our findings
could be applicable to free-weight exercises in which the dis-
placement of the barbell is not restricted to the vertical direction.
Finally, because one of the main applications of the use of velocity
during resistance training is the prediction of the 1RM
(13,26,31), future studies should examine the precision of dif-
ferent commercially available devices for predicting the 1RM
during basic resistance training exercises.
Practical Applications
The devices were ranked from the most to the least reliable as
follows: (a) Speed4Lift; (b) Velowin, PowerLift, T-Force, and
Chronojump; (c) PUSH band; and (d) Beast sensor. All devices
presented a high concurrent validity with respect to the Trio-
OptiTrack system with the only exception of the Beast sensor,
whereas the Speed4Lift was the only device that did not report
heteroscedasticity of errors. Taken together, these results
suggest that the Speed4Lift is the most appropriate device for
the measurement of movement velocity during the bench press
exercise performed in a Smith machine. Note that linear ve-
locity transducers, linear position transducers, camera-based
optoelectronic systems, and smartphone application could all
be used to obtain accurate measurements of mean velocity
during the bench press exercise performed in a Smith machine,
although the presence of heteroscedasticity of errors should be
in mind. The 2 IMUs present a lower reliability and validity
and, consequently, more caution should be taken when using
PUSH band and Beast sensor devices for implementing
velocity-based resistance training programs.
Feasibility of Seven Devices to Measure Velocity (2019) 00:00 |www.nsca.com
7
Copyright © 2019 National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
Acknowledgments
The authors thank all the participants who selflessly participated in the
study. This study was supported by the Spanish Ministry of Education,
Culture and Sport under a predoctoral grant (FPU15/03649) awarded
to A.P.C. and by the University of Granada under a postdoctoral grant
(perfeccionamiento de doctores) awarded to A.G.R.
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Copyright © 2019 National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
... Eighteen physically active eumenorrheic women volunteered to participate in this study (mean ± standard deviation [SD]: age = 23.4 ± 2.7 years [range: [20][21][22][23][24][25][26][27][28][29]; body height = 1.64 ± 0.09 m; body mass = 62.7 ± 9.2 kg). One subject dropped out of the study due to a negative urine LH surge, and two subjects did not complete one of the three testing sessions. ...
... The fastest mean velocity collected under the different loading conditions was used for modeling the individualized L-V relationships by means of a linear regression model, and the back-squat 1-RM was estimated as the load associated with a mean velocity of 0.33 m/s [20]. A validated linear velocity transducer (T-Force system; Ergotech, Murcia, Spain) was used to collect the mean velocity of all repetitions throughout the study [21]. Subjects immediately received verbal velocity performance feedback after completing each repetition to encourage maximal effort. ...
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... Systematic bias in mean velocity values has been observed across various devices commonly used to measure movement velocity during RT [8,[49][50][51][52][53]. These findings indicate that generalized L-V relationships may also be contingent upon the choice of measurement tools. ...
... Factor 8 -Velocity monitoring device Linear position transducers are widely recognized as the goldstandard technology for implementing the different applications of VBT [8]. Of note is that different studies have revealed systematic bias in mean velocity values across various linear position transducers [49][50][51][52][53]. However, the only study that directly compared the accuracy of individualized L-V relationships to estimate the 1RM among different brands of linear position transducers found similar levels of accuracy across all devices [79]. ...
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Resistance training intensity is commonly quantified as the load lifted relative to an individual's maximal dynamic strength. This approach, known as percent-based training, necessitates evaluating the one-repetition maximum (1RM) for the core exercises incorporated in a resistance training program. However, a major limitation of rigid percent-based training lies in the demanding nature of directly testing the 1RM from technical, physical and psychological perspectives. A potential solution that has gained popularity in the last two decades to facilitate the implementation of percent-based training involves the estimation of the 1RM by recording the lifting velocity against submaximal loads. This review examines the three main methods for prescribing relative loads (%1RM) based on lifting velocity monitoring: (i) velocity zones, (ii) generalized load-velocity relationships, and (iii) individualized load-velocity relationships. The article concludes by discussing a number of factors that should be considered for simplifying the testing procedures while maintaining the accuracy of individualized L-V relationships to predict the 1RM and establish the resultant individualized %1RM-velocity relationship: (i) exercise selection, (ii) type of velocity variable, (iii) regression model, (iv) number of loads, (v) location of experimental points on the load-velocity relationship, (vi) minimal velocity threshold, (vii) provision of velocity feedback, and (viii) velocity monitoring device.
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This study aimed to assess the validity of three commercial devices in recording mean velocity (MV) and peak velocity (PV) during a unilateral resistance exercise. 18 strength-trained and healthy males performed repetitions of Bulgarian split squats at loads ranging from 40% to 90% of their one-repetition maximum. The MV and PV were simultaneously recorded by GymAware, PUSH, My Lift and compared to Vicon for all repetitions. Concurrent validity was assessed through a linear mixed model, as well as mean difference (MD), mean absolute error (MAE) and Hedge's g effect sizes. GymAware was found to be valid in MV (MD = -0.02 to -0.01 m/s, MAE = 0.02 to 0.03 m/s, g = -0.08 to -0.19) and PV (MD = 0.01 to 0.05 m/s, MAE = 0.05 to 0.07 m/s, g = -0.06 to -0.22) recordings. Significant differences were identified between GymAware, PUSH, My Lift and Vicon for both MV (p < 0.01) and PV (p < 0.01) assessments. Moreover, when comparing the MV and PV recorded by PUSH and My Lift to Vicon, larger MD and MAE, and trivial to moderate effects were also evident. Therefore, our findings suggest that GymAware could be an alternative for recording MV and PV during unilateral resistance exercises.
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An individualised F-Vimb training programme improved sport-specific actions after 8 weeks in basketball athletes.Improvements were specific to the orientation worked on, with vertical jumping and sprint actions being the most sensitive to change after just 4 weeks of individualised F-Vimb intervention.In complex actions such as COD, it would be recommended to optimise the F-V profile, emphasising a vertical force-orientation for at least 8 weeks.
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Purpose: This study examined the relationships between different loading intensities and movement velocities in the bench-press exercise (BP) in Paralympic powerlifters. Methods: Seventeen National Paralympic powerlifters performed maximum dynamic strength tests to determine their BP one-repetition maximum (1RM) in a Smith-machine device. A linear position transducer was used to measure the movement velocity over a comprehensive range of loads. Linear regression analysis was performed to establish the relationships between the different bar-velocities and the distinct percentages of 1RM (%1RM). Results: Overall, the correlations between bar-velocities and %1RM were strong over the entire range of loads (R² values ranged from 0.80 to 0.91), but the precision of the predictive equations (expressed as mean differences [%] between actual and predicted 1RM values) were higher at heavier loading intensities (~20% for loads ≤ 70% 1RM, and ~5% for loads ≥ 70%1RM). In addition, it seems that these very strong athletes (e.g., 1RM relative in the BP = 2.22 ± 0.36 kg.kg-1, for male participants) perform BP 1RM assessments at lower velocities than those previously reported in the literature. Conclusions: The load-velocity relationship was strong and consistent in Paralympic powerlifters, especially at higher loads (≥ 70% 1RM). Therefore, Paralympic coaches can use the predictive equations and the reference values provided here to determine and monitor the BP loading intensity in National Paralympic powerlifters.
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The objective of this study was to explore the reliability and concurrent validity of the Velowin optoelectronic system to measure movement velocity during the free-weight back squat exercise. Thirty-one men (age = 27.5 ± 3.2 years; body height = 1.76 ± 0.15 m; body mass: 78.3 ± 7.6 kg) were evaluated in a single session against five different loads (20, 40, 50, 60 and 70 kg) and three velocity variables (mean velocity [MV], mean propulsive velocity [MPV] and maximum velocity [Vmax]) were recorded simultaneously by a linear velocity transducer (T-Force; gold-standard) and a camera-based optoelectronic system (Velowin). The main findings revealed that (1) the three velocity variables were determined with a high and comparable reliability by both the T-Force and Velowin systems (median coefficient of variation of the five loads: T-Force: MV = 4.25%, MPV = 4.49% and Vmax = 3.45%; Velowin: MV = 4.29%, MPV = 4.60% and Vmax = 4.44%), (2) the Vmax was the most reliable variable when obtained by the T-force (p < 0.05), but no significant differences in the reliability of the variables were observed for the Velowin (p > 0.05), and (3) high correlations were observed for the values of MV (r = 0.976), MPV (r = 0.965) and Vmax (r = 0.977) between the T-Force and Velowin systems. Collectively, these results support the Velowin as a reliable and valid system for the measurement of movement velocity during the free-weight back squat exercise.
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With the spreading of motion analysis decisions to invest into a new system demand scientific reference applications. The aim of the present systematic review is to reveal the biomechanical scientific applications of OptiTrack motion capture systems and to overview documented usage conditions and purposes. Six major scientific literature databases were used (PubMed, PubMed Central, ScienceDirect, IEEE Xplore, PLOS and Web Of Science). An OptiTrack camera system had to be used for human or biologically related motion capture. A total of 85 articles were included, 4 out of which dealt with the validation of OptiTrack systems and 81 utilized the system for biomechanical analyses. The data analysed and extracted from the system validation studies included: description of the validated and the reference system, measured features and observed errors. The data extracted from the utilizing studies also included: OptiTrack application, camera type and frequency, marker size, camera number, data processing software and the motion studied. The review offers a broad collection of biomechanical applications of OptiTrack motion capture systems as scientific references for certain motion studies. The review also summarizes findings on the accuracy of the systems. It concludes that the method descriptions of system usage are often underspecified.
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This study examined the validity and reliability of a wearable inertial sensor to measure velocity and power in the free-weight back squat and bench press. Twenty-nine youth rugby league players (18 ± 1 years) completed 2 test-retest sessions for the back squat followed by 2 test-retest sessions for the bench press. Repetitions were performed at 20, 40, 60, 80, and 90% of 1 repetition maximum (1RM) with mean velocity, peak velocity, mean power (MP), and peak power (PP) simultaneously measured using an inertial sensor (PUSH) and a linear position transducer (GymAware PowerTool). The PUSH demonstrated good validity (Pearson's product-moment correlation coefficient [r]) and reliability (intraclass correlation coefficient [ICC]) only for measurements of MP (r = 0.91; ICC = 0.83) and PP (r = 0.90; ICC = 0.80) at 20% of 1RM in the back squat. However, it may be more appropriate for athletes to jump off the ground with this load to optimize power output. Further research should therefore evaluate the usability of inertial sensors in the jump squat exercise. In the bench press, good validity and reliability were evident only for the measurement of MP at 40% of 1RM (r = 0.89; ICC = 0.83). The PUSH was unable to provide a valid and reliable estimate of any other criterion variable in either exercise. Practitioners must be cognizant of the measurement error when using inertial sensor technology to quantify velocity and power during resistance training, particularly with loads other than 20% of 1RM in the back squat and 40% of 1RM in the bench press.
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Objectives The velocity of a barbell can provide important insights on the performance of athletes during strength training. The aim of this work was to assess the validity and reliably of four simple measurement devices that were compared to 3D motion capture measurements during squatting. Nine participants were assessed when performing 2 × 5 traditional squats with a weight of 70% of the 1 repetition maximum and ballistic squats with a weight of 25 kg. Simultaneously, data was recorded from three linear position transducers (T-FORCE, Tendo Power and GymAware), an accelerometer based system (Myotest) and a 3D motion capture system (Vicon) as the Gold Standard. Correlations between the simple measurement devices and 3D motion capture of the mean and the maximal velocity of the barbell, as well as the time to maximal velocity, were calculated. Results The correlations during traditional squats were significant and very high (r = 0.932, 0.990, p < 0.01) and significant and moderate to high (r = 0.552, 0.860, p < 0.01). The Myotest could only be used during the ballistic squats and was less accurate. All the linear position transducers were able to assess squat performance, particularly during traditional squats and especially in terms of mean velocity and time to maximal velocity. Electronic supplementary material The online version of this article (10.1186/s13104-017-3012-z) contains supplementary material, which is available to authorized users.
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The purpose of this study was to analyze the validity, reliability, and accuracy of new wearable and smartphone-based technology for the measurement of barbell velocity in resistance training exercises. To do this, 10 highly trained powerlifters (age = 26.1 ± 3.9 years) performed 11 repetitions with loads ranging 50–100% of the 1-Repetition maximum in the bench-press, full-squat, and hip-thrust exercises while barbell velocity was simultaneously measured using a linear transducer (LT), two Beast wearable devices (one placed on the subjects' wrist –BW–, and the other one directly attached to the barbell –BB–) and the iOS PowerLift app. Results showed a high correlation between the LT and BW (r = 0.94–0.98, SEE = 0.04–0.07 m • s −1), BB (r = 0.97–0.98, SEE = 0.04–0.05 m • s −1), and the PowerLift app (r = 0.97–0.98, SEE = 0.03–0.05 m • s −1) for the measurement of barbell velocity in the three exercises. Paired samples T-test revealed systematic biases between the LT and BW, BB and the app in the hip-thrust, between the LT and BW in the full-squat and between the LT and BB in the bench-press exercise (p < 0.001). Moreover, the analysis of the linear regression on the Bland-Altman plots showed that the differences between the LT and BW (R 2 = 0.004–0.03), BB (R 2 = 0.007–0.01), and the app (R 2 = 0.001–0.03) were similar across the whole range of velocities analyzed. Finally, the reliability of the BW (ICC = 0.910–0.988), BB (ICC = 0.922–0.990), and the app (ICC = 0.928–0.989) for the measurement of the two repetitions performed with each load were almost the same than that observed with the LT (ICC = 0.937–0.990). Both the Beast wearable device and the PowerLift app were highly valid, reliable, and accurate for the measurement of barbell velocity in the bench-press, full-squat, and hip-thrust exercises. These results could have potential practical applications for strength and conditioning coaches who wish to measure barbell velocity during resistance training.
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It is unknown whether instantaneous visual feedback of resistance training outcomes can enhance barbell velocity in younger athletes. Therefore, the purpose of this study was to quantify the effects of visual feedback on mean concentric barbell velocity in the back squat, and to identify changes in motivation, competitiveness, and perceived workload. In a randomised-crossover design (Feedback vs. Control) feedback of mean concentric barbell velocity was or was not provided throughout a set of 10 repetitions in the barbell back squat. Magnitude-based inferences were used to assess changes between conditions, with almost certainly greater differences in mean concentric velocity between the Feedback (0.70 ±0.04 m·s) and Control (0.65 ±0.05 m·s) observed. Additionally, individual repetition mean concentric velocity ranged from possibly (repetition number two: 0.79 ±0.04 vs. 0.78 ±0.04 m·s) to almost certainly (repetition number 10: 0.58 ±0.05 vs. 0.49 ±0.05 m·s) greater when provided feedback, while almost certain differences were observed in motivation, competitiveness, and perceived workload, respectively. Providing adolescent male athletes with visual kinematic information while completing resistance training is beneficial for the maintenance of barbell velocity during a training set, potentially enhancing physical performance. Moreover, these improvements were observed alongside increases in motivation, competitiveness and perceived workload providing insight into the underlying mechanisms responsible for the performance gains observed. Given the observed maintenance of barbell velocity during a training set, practitioners can use this technique to manipulate training outcomes during resistance training.
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Purpose: This study aimed to compare the load-velocity relationship between four variants of the bench press (BP) exercise. Methods: The full load-velocity relationship of 30 men were evaluated by means of an incremental loading test starting at 17 kg progressing to the individual one-repetition maximum (1RM) in four BP variants: concentric-only BP, concentric-only bench press throw (BPT), eccentric-concentric BP, and eccentric-concentric BPT. Results: A strong and fairly linear relationship between mean velocity (MV) and %1RM was observed for the four BP variants (r(2) > 0.96 for pooled data and r(2) > 0.98 for individual data). The MV associated with each %1RM was significantly higher in the eccentric-concentric technique compared to the concentric-only technique. The only significant difference between the BP and BPT variants was the higher MV with the light-moderate loads (20%1RM-70%1RM) in the BPT using the concentric-only technique. Mean test velocity was significantly and positively correlated between the four BP variants (r = 0.44-0.76), which suggests that the subjects with higher velocities for each %1RM in one BP variant also tend to have higher velocities for each %1RM in the three remaining BP variants. Conclusions: these results highlight (1) the need for obtaining specific equations for each BP variant, and (2) the existence of individual load-velocity profiles.
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Previous studies have revealed that the velocity of the bar can be used to determine the intensity of different resistance training exercises. However, the load-velocity relationship seems to be exercise dependent. This study aimed to compare the load- velocity relationship obtained from two variations of the half-squat exercise (traditional vs. ballistic) using two execution techniques (eccentric-concentric vs. concentric-only). Twenty men performed a submaximal progressive loading test in four half-squat exercises: eccentric-concentric traditional-squat, concentric-only traditional-squat, countermovement jump (i.e. ballistic squat using the eccentric-concentric technique), and squat jump (i.e. ballistic squat using the concentric-only technique). Individual linear regressions were used to estimate the one-repetition maximum (1RM) for each half-squat exercise. Thereafter, another linear regression was applied to establish the relationship between relative load (%RM) and mean propulsive velocity (MPV). For all exercises, a strong relationship was observed between %RM and MPV: eccentric- concentric traditional-squat (R2 = 0.949), concentric-only traditional-squat (R2 = 0.920), countermovement jump (R2 = 0.957), and squat jump (R2 = 0.879). The velocities associated with each %RM were higher for the ballistic variation and the eccentric-concentric technique than for the traditional variation and concentric-only technique, respectively. Differences in velocity among the half-squat exercises decreased with the increment in the relative load. These results demonstrate that the MPV can be used to predict exercise intensity in the four half-squat exercises. However, independent regressions are required for each half-squat exercise since the load-velocity relationship proved to be task specific. Keywords: velocity-based training; traditional; ballistic; jump squat; eccentric-concentric technique; concentric-only technique.
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This study analysed the validity and reliability of a new optoelectronic device (Velowin) for the measurement of vertical displacement and velocity as well as to estimate force and mechanical power. Eleven trained males with Mean (SD) age = 27.4 (4.8) years, completed an incremental squat exercise test with 5 different loads (<30–90% of their 1−repetition maximum) while displacement and vertical velocity of the barbell were simultaneously measured using an integrated 3D system (3D motion capture system + force platform) and Velowin. Substantial to almost perfect correlation (concordance correlation coefficient = 0.75–0.96), root mean square error as coefficient of variation ±90% confidence interval ≤10% and good to excellent intraclass correlation coefficient = 0.84–0.99 were determined for all the variables. Passing and Bablock regression methods revealed no differences for average velocity. However, significant but consistent bias were determined for average or peak force and power while systematic and not proportional bias was found for displacement. In conclusion, Velowin, in holds of some potential advantages over traditionally used accelerometer or linear transducers, represents a valid and reliable alternative to monitor vertical displacement and velocity as well as to estimate average force and mechanical power during the squat exercise.