ArticlePDF Available

Abstract and Figures

The purpose of this study was to compare the active drag values estimated by the MRT-method and the MAD-system. Six male competitive swimmers participated in this study and performed front crawl with arms only condition. The drag was compared at six-staged velocities ranged from 0.9 to 1.4 m/s between MRT-method and MAD-system. The drag estimated by MRT-method showed larger values than that obtained using MAD-system at each velocity (MRT-method/MAD-system: 119% at 1.0 m/s; 133% at 1.2 m/s; 147% at 1.4 m/s). In addition, the stroke length in MRT-method condition decreased with swimming velocity being increased, while that in MAD-system condition was constant. Therefore, swimmers had to increase their stroke frequency in MRT-method condition in order to achieve the same swimming velocities as MAD-system condition, especially at high velocities. It was concluded that the difference in the way of exerting propulsion between MAD-system and MRT-method influenced the active drag which were estimated in two methods.
Content may be subject to copyright.
Proceedings 2018, 2, 287; doi:10.3390/proceedings2060287
Comparison of Active Drag Using the MRT-Method
and the MAD-System in Front Crawl Swimming
Kenzo Narita 1,*, Futoshi Ogita 2, Motomu Nakashima 3 and Hideki Takagi 4
1 Doctoral Program in Physical Education, Health and Sport Sciences, University of Tsukuba,
Tsukuba 305-8574, Japan
2 Department of Sports and Life Sciences, National Institute of Fitness and Sports in Kanoya,
Kanoya 891-2393, Japan;
3 Department of Systems and Control Engineering, Tokyo Institute of Technology, Tokyo 152-8550, Japan;
4 Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba 305-8574, Japan;
* Correspondence:; Tel.: +81-80-4337-4699
Presented at the 12th Conference of the International Sports Engineering Association, Brisbane,
Queensland, Australia, 26–28 March 2018.
Published: 11 February 2018
Abstract: The purpose of this study was to compare the active drag values estimated by the
MRT-method and the MAD-system. Six male competitive swimmers participated in this study and
performed front crawl with arms only condition. The drag was compared at six-staged velocities
ranged from 0.9 to 1.4 m/s between MRT-method and MAD-system. The drag estimated by
MRT-method showed larger values than that obtained using MAD-system at each velocity
(MRT-method/MAD-system: 119% at 1.0 m/s; 133% at 1.2 m/s; 147% at 1.4 m/s). In addition, the
stroke length in MRT-method condition decreased with swimming velocity being increased, while
that in MAD-system condition was constant. Therefore, swimmers had to increase their stroke
frequency in MRT-method condition in order to achieve the same swimming velocities as MAD-
system condition, especially at high velocities. It was concluded that the difference in the way of
exerting propulsion between MAD-system and MRT-method influenced the active drag which were
estimated in two methods.
Keywords: active drag; front crawl; stroke frequency; stroke length; propulsion
1. Introduction
A resistive force in swimming, i.e., active drag, is a main factor of determining the swimming
performance. Swimming velocity depends on a balance between propulsive force and active drag.
When active drag being larger than propulsive force in swimming, the velocity of the swimmer
decreases. Hence, reducing active drag is important to achieve high swimming velocity. Although
various methodologies have been suggested, it is currently impossible to measure active drag
accurately during swimming, and there has been no standard method for measuring active drag.
In front-crawl swimming, which is the fastest human swimming stroke, distances varied from
50 m to 1500 m are adopted as official events in competitions. Since swimmers alter their swimming
velocity depending on the distance, it is necessary to evaluate active drag at various swimming
velocities to provide detailed kinetic information on swimming performances to athletes and coaches.
As a methodology for evaluating active drag at various velocities, Hollander et al. [1] developed the
measuring active drag system (MAD-system). In this method, the swimmer propelled him/herself
forward by pushing the pads which were fixed under the water, and the pushing forces exerted by
the swimmer was measured by a load cell. Then, under the assumption that the swimmer’s
Proceedings 2018, 2, 287 2 of 6
swimming velocity during the measurement is constant, the active drag was evaluated from the
principle that the mean propulsive force exerted by the swimmer (that is, the force for pushing the
pad) was equal to the mean drag in swimming. The drag estimation using MAD-system can only be
applied to front crawl swimming without legs motion due to its methodological characteristics.
Therefore, active drag acting on the swimmer during whole body swimming cannot be estimated
with this method. Another problem in MAD-system is that swimmers change their velocity in a
different manner compared with actual swimming condition. Swimming velocity is calculated by the
product of stroke frequency and length. In MAD-system condition, however, stroke length of the
swimmer is constant and the swimming velocity is affected only by the stroke frequency, which is
not the case in reality [2,3]. On the other hand, the drag in various swimming styles can be assessed
by other two methods [4,5]. However, they can only evaluate the drag during maximal effort trials.
The drag during swimming has been mainly assessed by those three methods, and MAD-system is
the only method which is able to evaluate active drag at various velocities among the three.
A methodology for estimating the drag in swimming using measured values of residual thrust
(MRT-method) has recently been developed by Narita et al. [6]. The MRT-method has no restriction
on swimming style and velocity, therefore, the method can evaluate active drag at any velocities as
with MAD-system. Furthermore, unlike the MAD-system approach, this method allows researchers
to verify an influence of stroke frequency and length on active drag. In MRT-method condition, the
swimmer propels his/her body forward by sweeping their arms through the water without the
restriction by the pads. Therefore, with this method, it is possible to investigate the active drag at
various velocities without neglecting the influence of the stroke length. By comparing active drag
evaluated by both MAD-system and MRT-method with the same swimmers, the effect of the way of
generating propulsion on the active drag can be investigated.
The purpose of this study was to compare the active drag values in front crawl swimming with
arms only condition between the MRT-method and the MAD-system.
2. Methods
2.1. Participants
Six male competitive swimmers (age: 20.0 ± 1.0 years; height: 1.71 ± 0.03 m; weight: 67.6 ± 6.2 kg)
participated in this study. They all trained six days a week and had experience in participating in
Japanese national competitions. The test procedures were approved by the University of Tsukuba
Ethics Committee and each participant signed an informed-consent form.
2.2. Experimental Design
Each swimmer performed front crawl using arms only in MRT-method and MAD-system. To
restrict the movement of the swimmer’s legs, we attached a buoyant buoy with the thigh of the
swimmer and fastened a band to the ankle. In all experiments, the swimmers used a snorkel to
eliminate an influence of the breathing motion. Moreover, the swimmers were instructed to wear the
same type of swimsuit in both testing conditions to avoid any potential effects on resistance caused
by different types of swimsuit.
2.2.1. MRT-Method
Trials using MRT-method were conducted in a water flume (Igarashi Industrial Works Co., Ltd.,
Chiba, Japan), which allowed the flow velocity to be controlled precisely. Prior to the measurements,
the swimmers had familiarization period for the flume.
The MRT-method evaluates the active drag from the relationship between the residual thrusts
and the flow velocities. The residual thrust is the difference between the propulsion and drag. This
can be calculated by measuring towing forces exerted by the swimmer by two load cells connected
to wires which are attached to the waist of the swimmer at various flow velocities (U), while the
swimmer maintains the same techniques and kinematics. Thus, to estimate the active drag at a given
velocity = i m/s (VSi), the swimmer has to maintain his/her stroke motion and body position required
Proceedings 2018, 2, 287 3 of 6
to swim at V
even when U was varied. Prior to measuring the residual thrust, each swimmer
self-propelled in the flume with the flow velocity U being set to i m/s. To make it eas y for the swimmer
to maintain his/her stroke at different U, the stroke time (s/stroke) that the swimmer used to propel
himself at i m/s was provided using a small audible waterproof metronome (Tempo trainer Pro;
FINIS, Inc., Livermore, LA, USA). To measure the residual thrust at each U, a belt wrapped around
the swimmer’s waist was connected to load cells using wires (LUX-B-2KN-ID, Kyowa Electronic
Instruments Co. Ltd., Tokyo, Japan). The load cells were located at the front and back of the flume
(Figure 1). The forward and backward towing forces were measured for 10 s, and then the residual
thrust was calculated from their difference between the forces. We measured the residual thrust at
eight points within the range of ±0.2 m/s around V
, changing U by 0.05 m/s each time. Thereafter,
we derived best-fit regression curves for the measured values of residual thrust and U and used them
to calculate the active drag (for further details, see Narita et al. [6]). The drag was estimated in
six-staged velocities from 0.9 to 1.4 m/s. The stroke frequency (SF [Hz]) was calculated from the
inverse of the stroke time (s/stroke), and the stroke length SL was computed by dividing the velocities
derived from the regression curve fitted to the SF.
Figure 1. Top view of MRT-method.
2.2.2. MAD-System
In testing using MAD-system, each swimmer swam 25 m with pushing pads. The pads were
attached to a 23 m rod, which was mounted 0.8 m below the water surface and connected to a force
transducer, and a 1.30 m interval (Figure 2). The force by pushing off pads were measured at a
frequency of 100 Hz. Mean active drag was determined to be equal to the mean propulsive force
under the assumption that the velocity of the swimmer was constant throughout the trial. To establish
the relationship between the active drag and the velocity, each subject completed ten trials at different
selected velocities with approximately 3 min rest between trials. We chose six out of the ten trials
which showed similar velocity as U
that was calculated for the same swimmer in MRT-method.
The SF was calculated by dividing the swimming velocity by the SL (which is constantly 2.6 m with
Figure 2. Top view of MAD-system.
Proceedings 2018, 2, 287 4 of 6
2.3. Data Analysis
To compare the values of active drag which were evaluated with MRT-method and
MAD-system at various velocities, the drag/velocity data were fitted to the function: D = k vn (D: drag,
v: velocity) to obtain coefficient k and degree n for each swimmer, and the active drag for 1.0, 1.2 and
1.4 m/s were calculated by the aforementioned equation with obtained k and n values being
2.4. Statistical Analysis
We compared the active drag calculated by MRT-method and MAD-system using a paired t-
test. To investigate the influence of stroke parameters on the swimming velocity and the active drag
in MRT-method and MAD-system, we obtained by Pearson’s correlation coefficients (r) between
swimming velocity/active drag and SF/SL of all swimmers. All statistical analyses were conducted at
a significance level of p < 0.05 using SPSS ver. 22.0 (SPSS, Inc., Chicago, IL, USA).
3. Results
Table 1 indicates the values of k and n obtained in MRT-method and MAD-system. Significant
differences between the two methods were observed in k (t (5) = 4.96, p < 0.01) and n (t (5) = 2.76,
p = 0.04). The average values of all swimmer’s active drag at 1.0, 1.2 and 1.4 m/s were shown in
Figure 3. There were also significant differences in active drag values at 1.0 (t (5) = 4.96, p < 0.01), 1.2
(t (5) = 5.00, p < 0.01) and 1.4 m/s (t (5) = 3.90, p = 0.01).
Table 1. Coefficient k and degree n in each swimmer obtained by MRT-method and MAD-system.
Swimmer MRT-Method MAD-System
k n k n
A 37.8 3.28 30.5 1.73
B 34.1 2.30 28.2 1.85
C 32.2 2.34 27.1 2.06
D 38.9 2.16 29.6 2.10
E 33.0 2.83 31.3 1.85
F 31.1 2.23 27.6 1.84
Mean 34.5 2.53 29.1 1.90
SD 2.9 0.40 1.5 0.13
Figure 3. The average values of active drag at 1.0, 1.2 and 1.4 m/s in MRT-method (blue) and MAD-
system (orange). Asterisk (*) indicates a significant difference between MRT-method and MAD-
system, p < 0.05.
1.0 1.2 1.4
Active drag (N)
Velocity (m/s)
: MRT-method : MAD-system
Proceedings 2018, 2, 287 5 of 6
Figure 4 present the relationships between swimming velocity/active drag and stroke frequency.
In MRT-method, SF had a significant positive correlation with swimming velocity (r = 0.797, p < 0.01)
and active drag (r = 0.808, p < 0.01), whereas SL showed a significant negative correlation with
swimming velocity (r = 0.401, p = 0.02) and active drag (r = 0.452, p < 0.01). On the other hand, in
MAD-system, there was a significant positive correlation between SF and swimming velocity (r =
0.999, p < 0.01)/active drag (r = 0.970, p < 0.01), besides, the relationship between SL and active
drag/velocity could not be evaluated because SL was constant.
Figure. 4 The relationship between each variables in MRT-method (blue) and MAD-system (orange)
for all swimmers. (a) The relationship between swimming velocity and stroke frequency; (b) the
relationship between stroke frequency and active drag.
4. Discussion
Active drag in front-crawl swimming without legs motion assessed by MRT-method was larger
than the drag estimated using MAD-system at all velocities. In MAD-system, due to its mechanical
structure, swimmers propels their body by pushing fixed pads under the water. Thus, swimmers can
utilize all reaction force acquired by pushing the fixed pads by the hands as the propulsive force. On
the other hand, during the actual swimming, the force swimmers obtain from the water are divided
into propulsive force and force which does not contribute to propulsion [7]. Therefore, propulsive
force is probably generated more efficiently by swimmers with MAD-system compared with the
actual swimming and MRT-method condition at the same velocities. The swimming velocity is
determined by the balance between propulsive force and active drag. It means that when the
swimmer achieves a given swimming velocity with a small propulsive force, the drag acting on the
swimmer is also small. In this study, the SL, which was adopted as a simple index of swimming
efficiency, was constant regardless the swimming velocity in MAD-system condition. However, in
MRT-method, it decreased with the velocity being increased. Therefore, MRT-method required the
swimmers to achieve the same swimming velocities as they did with MAD-system by increasing their
SF, especially at high velocity conditions. On the other hand, SF and active drag were positively
correlated in both methods. However, the resistance force is strongly influenced by the velocity, as
well as SF. Hence, in order to investigate a relationship between SF and the drag with minimizing
the influence of the velocity, we calculated an active drag coefficient and conducted a correlation
analysis. A significant positive correlation was observed between these variables in MRT-method
(r = 0.44, p < 0.01), while no significant correlation was found in MAD-system (r = 0.10, p = 0.57). In
front-crawl swimming, swimmers repeatedly move their arms and legs around the water surface.
Therefore, it is expected that additional drags from waves and splashes are generated in each stroke
cycle. Therefore, it is possible that the active drag in high SF conditions was affected by those drags
more than that in low SF conditions.
0.8 1.0 1.2 1.4
Stroke frequency (Hz)
Velocity (m/s)
r= .797, p< .01
r= .999, p< .01
0.2 0.4 0.6 0.8 1.0
Active drag (N)
Stroke frequency (Hz)
r= .808, p< .01
r= .970, p< .01
Proceedings 2018, 2, 287 6 of 6
On the other hand, since present study did not conduct a motion analysis, the influence of the
difference in the motion of the swimmer between each method on the active drag was unclear.
Obtaining information on the path and speed of upper limbs and pitch/yaw of the body of swimmers
in each method will be helpful for better understanding of the influence of these variables on the
difference of the drag between the two methods. Therefore, further investigations including the
motion analysis are needed for detailed analysis of the effect of the difference of each methodology
on active drag.
5. Conclusions
The present study compared the active drag using the MRT-method and the MAD-system in
front crawl swimming without kicking motion. As a result, the active drag values estimated using
MRT-method was higher than those obtained by MAD-system. In addition, SL in MAD-system
condition was constant, while that in MRT-method condition decreased with swimming velocity
being increased. Therefore, swimmers had to increase their SF in MRT-method condition in order to
achieve the same swimming velocities as MAD-system condition, especially in high velocity
conditions. It is probable that the different ways to generate propulsive force by upper limbs between
the two methods influence the stroke parameters, consequently, the active drag.
Acknowledgments: This research was supported in part by the Ministry of Education, Culture, Sports, Science
and Technology (MEXT) for the Human High Performance Project (2014–2018) and by a grant from Advanced
Research Initiative for Human High Performance (ARIHHP), University of Tsukuba.
Conflicts of Interest: There are no conflicts of interest to declare.
1. Hollander, A.P.; De Groot, G.; van Ingen Schenau, G.; Toussaint, H.M.; De Best, H.; Peeters, W.;
Meulemans, A.; Schreurs, A.W. Measurement of active drag during crawl arm stroke swimming. J. Sports
Sci. 1986, 4, 21–30.
2. Craig, A.B.; Skehan, P.L.; Pawelczyk, J.A.; Boomer, W.L. Velocity, stroke rate, and distance per stroke
during elite swimming competition. Med. Sci. Sports Exerc. 1985, 17, 625–634.
3. Seifert, L.; Toussaint, H.M.; Alberty, M.; Schnitzler, C.; Chollet, D. Arm coordination, power, and swim
efficiency in national and regional front crawl swimmers. Hum. Mov. Sci. 2010, 29, 426–439.
4. Kolmogorov, S.; Duplishcheva, O. Active drag, useful mechanical power output and hydrodynamic force
coefficient in different swimming strokes at maximal velocity. J. Biomech. 1992, 25, 311–318.
5. Formosa, D.P.; Mason, B.; Burkett, B. The force–time profile of elite front crawl swimmers. J. Sports Sci.
2011, 29, 811–819.
6. Narita, K.; Nakashima, M.; Takagi, H. Developing a methodology for estimating the drag in front-crawl
swimming at various velocities. J. Biomech. 2017, 54, 123–128.
7. Toussaint, H.M. Differences in propelling efficiency between competitive and triathlon swimmers. Med.
Sci. Sports Exerc. 1990, 22, 409–415.
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (
... In other words, this method can be applied to any swimming stroke at submaximal and maximal swimming velocities. Therefore, the assessment of the MRT-method's reliability and validity are of interest in research groups world-wide (Gonjo et al., 2020;Narita et al., 2018aNarita et al., , 2018b. Particularly, the assumption that swimmers can reproduce the same motion regardless of the environmental change (i.e., flow velocity and the special condition of swimming in a flume) should be further explored. ...
... The MAD-System also revealed significantly greater mean active drag values (66.9N) than the VPM (53.2N) (Toussaint et al., 2004). The MRT method was found to have greater active drag values than the MAD-System (Narita et al., 2018a). For the HRM method, there are no direct comparisons with other solutions, but published data point to higher values (~80 to 90 N for front crawl Olympic champions). ...
... Despite the evidence on EMG similarity between MAD swimming and free front crawl (Clarys et al., 1988), the hand contact with a rigid object in the MAD-System may also alter regular stroke mechanics, compared with displacing water during regular stroke cycles. As Narita et al. (2018a) hypothesised, the propulsive force generation is likely more efficient when in contact with fixed pads than when the hand moves through water. Additionally, the use of a pull buoy during MAD-System data collection eliminates the effect of kicking on the axial rotation of the body (Andersen & Sanders, 2018;Yanai, 2001) and, consequently, the potentially beneficial or adverse effects on hydrodynamic resistance. ...
Free-swimming performance depends strongly on the ability to develop propulsive force and minimise resistive drag. Therefore, estimating resistive drag (passive or active) may be important to understand how free-swimming performance can be improved. The purpose of this narrative overview was to describe and discuss experimental methods of measuring or estimating active and passive drag relevant to competitive swimming. Studies were identified using a mixed-model approach comprising a search of SCOPUS and Web of Science data bases, follow-up of relevant studies cited in manuscripts from the primary search, and additional studies identified by the co-authors based on their specific areas of fluid dynamics expertise. The utility and limitations of active and passive drag methods were critically discussed with reference to primary research domains in this field, 'swimmer morphology' and 'technique analysis'. This overview and the subsequent discussions provide implications for researchers when selecting an appropriate method to measure resistive forces (active or passive) relevant to improving performance in free-swimming.
... Comparison studies were conducted, but only based on drag procedures and for active drag alone (Formosa et al., 2012;Narita et al., 2018b;Toussaint et al., 2004). However, the overall trend reported in the literature is that the active drag output presents significant differences when measured by different methods. ...
... The authors argued that the kicking absence in the MAD system might partially explain such a large difference (Formosa et al., 2012). More recently, Narita et al. (2018b) compared the MAD and the MRT systems without the kicking motion. The active drag values estimated using the MRT method were significantly higher than those obtained by the MAD system. ...
... The active drag values estimated using the MRT method were significantly higher than those obtained by the MAD system. The authors argued that the MAD system implied stroke mechanics constrictions because swimmers must propel themselves by pushing fixed pads underwater (Narita et al., 2018b). Thus, it seems that for this type of measurements, allowing swimmers to move as under "free swimming" conditions represents a key factor. ...
Full-text available
The aim of this study was to analyze the agreement of the active drag coefficient measured through drag and propulsion methods. The sample was composed of 18 swimmers (nine boys: 15.9 ± 0.9 years; nine girls: 15.3 ± 1.2 years) recruited from a national swimming team. The velocity perturbation method was used as the drag measurement system and the Aquanex system as the propulsion system. For both sexes combined, the frontal surface area was 0.1128 ± 0.016 m 2 , swim velocity 1.54 ± 0.13 m•s-1 , active drag 62.81 ± 11.37 N, propulsion 68.81 ± 12.41 N. The level of the active drag coefficient agreement was calculated based on the mean values comparison, simple linear regression, and Bland Altman plots. The mean data comparison revealed non-significant differences (p > 0.05) between methods to measure the active drag coefficient. Both the linear regression (R 2 = 0.82, p < 0.001) and Bland Altman plots revealed a very high agreement. The active drag coefficient should be the main outcome used in the interpretation of the swimmers' hydrodynamic profile, because it is less sensitive to swimming velocity. Coaches and researchers should be aware that the active drag coefficient can also be calculated based on propulsion methods and not just based on drag methods. Thus, the swimming community can now use different equipment to measure the hydrodynamics of their swimmers.
... The main difference between the two is that the ATM produces D a profiles and intra-course propulsion, rather than just an average measure of D a (Formosa et al., 2012). The MRT method, which was recently developed, allows the estimation of drag in swimming using measured values of residual thrust (Narita et al., 2017;Narita et al., 2018b;Gonjo et al., 2020). Through this method, it is possible to investigate D a at various speeds without neglecting the influence of stroke length. ...
Full-text available
Introduction: In swimming, it is necessary to understand and identify the main factors that are important to reduce active drag and, consequently, improve the performance of swimmers. However, there is no up-to-date review in the literature clarifying this topic. Thus, a systematic narrative review was performed to update the body of knowledge on active drag in swimming through numerical and experimental methods. Methods: To determine and identify the most relevant studies for this review, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach was used. Results: 75 studies related to active drag in swimming and the methodologies applied to study them were analyzed and kept for synthesis. The included studies showed a high-quality score by the Delphi scale (mean score was 5.85 ± 0.38). Active drag was included in seven studies through numerical methods and 68 through experimental methods. In both methods used by the authors to determine the drag, it can be concluded that the frontal surface area plays a fundamental role. Additionally, the technique seems to be a determining factor in reducing the drag force and increasing the propulsive force. Drag tends to increase with speed and frontal surface area, being greater in adults than in children due to body density factors and high levels of speed. However, the coefficient of drag decreases as the technical efficiency of swimming increases (i.e., the best swimmers (the fastest or most efficient) are those with the best drag and swimming hydrodynamics efficiency). Conclusion: Active drag was studied through numerical and experimental methods. There are significantly fewer numerical studies than experimental ones. This is because active drag, as a dynamical phenomenon, is too complex to be studied numerically. Drag is greater in adults than in children and greater in men than in women across all age groups. The study of drag is increasingly essential to collaborate with coaches in the process of understanding the fundamental patterns of movement biomechanics to achieve the best performance in swimming. Although most agree with these findings, there is disagreement in some studies, especially when it is difficult to define competitive level and age. The disagreement concerns three main aspects: 1 ) period of the studies and improvement of methodologies; 2 ) discrimination of methodologies between factors observed in numerical vs. experimental methods; 3 ) evidence that drag tends to be non-linear and depends on personal, technical, and stylistic factors. Based on the complexity of active drag, the study of this phenomenon must continue to improve swimming performance.
... Ⅰ 緒 言 競泳競技において,推進力や抵抗力は競技成績 を決定する主要な要因であることから,水泳に関 する研究では,古くから泳者の身体に働く抵抗 力や,泳者が発揮する推進力を定量化する試み がなされてきた (Formosa et al., 2011;Hollander et al., 1986;Kolmogorov and Duplishcheva, 1992;Kudo et al., 2008;Morouço et al., 2011;Narita et al., 2018aNarita et al., , 2018bSchleihauf et al., 1983; 清 水 ほ か,2000; Takagi and Wilson, 1999;Tsunokawa et al., 2015;角 川ほか,2012;Xin-Feng et al., 2007 (Hollander et al., 1986;Toussaint et al., 1988;Van der Vaart et al., 1987) (Kudo et al., 2008;Takagi and Wilson, 1999;Tsunokawa et al., 2015 Ceccon, S., Ceseracciu, E., Sawacha, Z., Gatta, G., Cortesi, ...
Full-text available
Through pressure measurement and underwater motion capture analysis, the aim of this study was to clarify how propulsive forces, Froude efficiency, and stroke parameters change with swimming velocity during front-crawl swimming. Eight male swimmers performed 2 trials, once using pressure measurement and underwater motion capture analysis and once using a MAD system. In the analysis using pressure measurement and underwater motion capture, each swimmer performed 16-m front-crawl swimming 10 times at various velocities. During the trials, pressure forces acting on the hand and hand kinematics were analyzed to obtain the hand propulsive forces at each velocity. In the analysis using the MAD system, each swimmer performed 25-m front-crawl swimming 10 times at various velocities while pushing the pad set under the water, and the propulsive force at each velocity was obtained from the pushing force of the pad. This revealed that the mean propulsive force increased exponentially with the increase in mean swimming velocity, and the propulsive index n was 2.62 on average for the 8 participants. Maximal propulsive forces and maximal propulsive powers at maximum were significantly correlated with the results obtained using the MAD system. Froude efficiency varied considerably among the participants, being 0.54 ± 0.05 on average for all trials.
Full-text available
A novel method aimed at evaluating the active drag profile during front-crawl swimming is proposed. Fourteen full trials were conducted with each trial using a stationary load cell set-up and a commercial resistance trainer to record the tension force in a rope, caused by an athlete swimming. Seven different stroke cycles in each experiment were identified for resampling time dependent data into position dependent data. Active drag was then calculated by subtracting resistance trainer force data away from the stationary load cell force data. Mean active drag values across the stroke cycle were calculated for comparison with existing methods, with mean active drag values calculated between 76 and 140 N depending on the trial. Comparing results with established active drag methods, such as the Velocity Perturbation Method (VPM), shows agreement in the magnitude of the mean active drag forces. Repeatability was investigated using one athlete, repeating the load cell set-up experiment, indicating results collected could range by 88 N depending on stroke cycle position. Variation in results is likely due to inconsistencies in swimmer technique and power output, although further investigation is required. The method outlined is proposed as a representation of the active drag profile over a full stroke cycle.
Full-text available
In this study, we used recently developed technology to determine the force-time profile of elite swimmers, which enabled coaches to make informed decisions on technique modifications. Eight elite male swimmers with a FINA (Federation Internationale de Natation) rank of 900+ completed five passive (streamline tow) and five net force (arms and leg swimming) trials. Three 50-Hz cameras were used to video each trial and were synchronized to the kinetic data output from a force-platform, upon which a motorized towing device was mounted. Passive and net force trials were completed at the participant's maximal front crawl swimming velocity. For the constant tow velocity, the net force profile was presented as a force-time graph, and the limitation of a constant velocity assumption was acknowledged. This allowed minimum and maximum net forces and arm symmetry to be identified. At a mean velocity of 1.92+0.06 m s⁻¹, the mean passive drag for the swimmers was 80.3+4.0 N, and the mean net force was 262.4+33.4 N. The mean location in the stroke cycle for minimum and maximum net force production was at 45% (insweep phase) and 75% (upsweep phase) of the stroke, respectively. This force-time profile also identified any stroke asymmetry.
Full-text available
The mean velocity of 9 out of 10 women's events during the U.S. Olympic Swimming Trials was greater in 1984 as compared to 1976. Three of the 10 men's events showed improvement. In 9 out of these 12 events, the increased velocity was accounted for by increased distance per stroke (range, -3 to -13%). In the women's 100-m butterfly and 100-m backstroke, increased velocity was due solely to faster stroke rates. The finalists in each event were compared to those whose velocities were 3-7% slower. In almost all events and stroke styles, the finalists achieved greater distances per stroke than did the slower group. In the men's events increased distance per stroke was associated with decreased stroke rate, except in the backstroke, in which both were increased for the finalists. Although the faster women swimmers generally had greater distances per stroke, they were more dependent than men on faster stroke rates to achieve superiority. The profile of velocity for races of 200 m and longer indicated that as fatigue developed the distance per stroke decreased. The faster swimmers compensated for this change by maintaining or increasing stroke rate more than did their slower competitors. This study indicates that improvements and superiority in stroke mechanics are reflected in the stroke rate and distance per stroke used to swim a race.
We aimed to develop a new method for evaluating the drag in front-crawl swimming at various velocities and at full stroke. In this study, we introduce the basic principle and apparatus for the new method, which estimates the drag in swimming using measured values of residual thrust (MRT). Furthermore, we applied the MRT to evaluate the active drag (Da) and compared it with the passive drag (Dp) measured for the same swimmers. Da was estimated in five-stages for velocities ranging from 1.0 to 1.4 m s−1; Dp was measured at flow velocities ranging from 0.9 to 1.5 m s−1 at intervals of 0.1 m s−1. The variability in the values of Da at MRT was also investigated for two swimmers. According to the results, Da (Da = 32.3 v3.3, N = 30, R2 = 0.90) was larger than Dp (Dp = 23.5 v2.0, N = 42, R2 = 0.89) and the variability in Da for the two swimmers was 6.5% and 3.0%. MRT can be used to evaluate Da at various velocities and is special in that it can be applied to various swimming styles. Therefore, the evaluation of drag in swimming using MRT is expected to play a role in establishing the fundamental data for swimming.
The effects of skill level on index of arm coordination (IdC), mechanical power output (P(d)), and swim efficiency were studied in front crawlers swimming at different speeds. Seven national and seven regional swimmers performed an arms-only intermittent graded speed test on the MAD-system and in a free condition. The MAD-system measured the drag (D) and P(d). Swimming speed (v), stroke rate (SR), stroke length (SL), stroke index (SI), relative entry, pull, push, and recovery phase durations, and IdC were calculated. Swim efficiency was assessed from SI, the coefficient of variation of calculated hip intra-cyclic velocity variations (IVV), and the efficiency of propulsion generation, i.e., the ratio of v(2) to tangential hand speed squared (u(2)). Both groups increased propulsive continuity (IdC) and hand speed (u) and applied greater P(d) to overcome active drag with speed increases (p<.05). This motor organization adaptation was adequate because SI, IVV, and v(2)/u(2) were unchanged. National swimmers appeared more efficient, with greater propulsive continuity (IdC) and P(d) to reach higher v than regional swimmers (p<.05). The regional swimmers exhibited a higher u and lower SI, IVV, and v(2)/u(2) compared to national swimmers (p<.05), which revealed lower effectiveness to generate propulsion, suggesting that technique is a major determinant of swimming performance.
By comparing the time of the same distance swum with and without an added resistance, under the assumption of an equal power output in both cases, the drag of 73 top swimmers was estimated. The active drag Fr(a.d.) at maximal swimming velocities varied considerably across strokes and individuals. In the females Fr(a.d.) ranged from 69.78 to 31.16 N in the front-crawl, from 83.04 to 37.78 N in dolphin, from 93.56 to 45.19 N in breaststroke, and from 65.51 to 37.79 N in back-stroke. In the males Fr(a.d.) ranged from 167.11 to 42.23 N in front-crawl, from 156.09 to 46.95 N in dolphin, from 176.87 to 55.61 N in breaststroke, and from 146.28 to 46.36 N in back-stroke. Also, the ratio of Fr(a.d.) to the passive drag Fr(a.d.) as determined for the analogical velocity in a tugging condition (in standard body position-front gliding) shows considerable individual variations. In the female swimmers variations in Fr(a.d.)/Fr(p.d.) ranged from 145.17 to 59.94% in front-crawl, from 192.39 to 85.57% in dolphin, from 298.03 to 124.50% in breaststroke, and from 162.87 to 85.61% in back-stroke. In the male swimmers variations in Fr(a.d.)/Fr(p.d.) ranged from 162.24 to 62.39% in front-crawl, from 191.70 to 70.38% in dolphin, from 295.57 to 102.83% in breaststroke, and from 198.82 to 74.48% in back-stroke. The main reason for such variations is found in the individual features of swimming technique and can be quantitatively estimated with the hydrodynamic force coefficient, which thus provides an adequate index of technique.
Two highly trained groups, competitive swimmers (N = 6) and triathletes (N = 5), were compared to evaluate the significance of the propelling efficiency as a performance determining factor in swimming. Using regression equations, the groups were compared at equal power input (1000 W). The groups did not differ in gross efficiency, stroke frequency, and work per stroke. There was a difference in distance per stroke (1.23 m vs 0.92 m) and mean swimming velocity (1.17 m.s-1) vs 0.95 m.s-1). The difference in swimming speed between the two groups can be explained by the fact that the competitive swimmers used a much higher proportion of their power output to overcome drag (49 W vs 35 W). At the same time, the competitive swimmers expended less power in moving water backwards (32 W vs 45 W). This difference in apportionment of the power output was characterized as the propelling efficiency (power used to overcome drag/total power output). Mean (+/- SD) propelling efficiency for the competitive swimmers was 61 +/- 6% but was only 44 +/- 3% for the triathletes. The results suggest that on average the better swimmer distinguishes himself from the poorer one by a greater distance per stroke rather than a higher stroke frequency. It is concluded that triathletes should focus their attention on their swimming technique rather than their ability to do work. The distance per stroke might be a simple criterion to evaluate the improvement in skill.
In order to measure active drag during front crawl swimming a system has been designed, built and tested. A tube (23 m long) with grips is fixed under the water surface and the swimmer crawls on this. At one end of the tube, a force transducer is attached to the wall of the swimming pool. It measures the momentary effective propulsive forces of the hands. During the measurements the subjects' legs are fixed together and supported by a buoy. After filtering and digitizing the electrical force signal, the mean propulsive force over one lane at constant speeds (ranging from about 1 to 2 m s-1) was calculated. The regression equation of the force on the speed turned out to be almost quadratic. At a mean speed of 1.55 m s-1 the mean force was 66.3 N. The accuracy of this force measured on one subject at different days was 4.1 N. The observed force, which is equal to the mean drag force, fits remarkably well with passive drag force values as well as with values calculated for propulsive forces during actual swimming reported in the literature. The use of the system does not interfere to any large extent with normal front crawl swimming; this conclusion is based on results of observations of film by skilled swim coaches. It was concluded that the system provides a good method of studying active drag and its relation to anthropometric variables and swimming technique.