Comparative Analysis of Active Drag Using the MAD System and an Assisted Towing Method in Front Crawl Swimming

2012 ◽  
Vol 28 (6) ◽  
pp. 746-750 ◽  
Author(s):  
Danielle P. Formosa ◽  
Huub M. Toussaint ◽  
Bruce R. Mason ◽  
Brendan Burkett
Keyword(s):  
Time Profile ◽  
Maximum Speed ◽  
Free Swimming ◽  
Front Crawl ◽  
Two Systems ◽  
The Mean ◽  
Force Time ◽  
Swimming Style ◽  
Swimming Technique ◽  
Active Drag

The measurement of active drag in swimming is a biomechanical challenge. This research compared two systems: (i) measuring active drag (MAD) and (ii) assisted towing method (ATM). Nine intermediate-level swimmers (19.7 ± 4.4 years) completed front crawl trials with both systems during one session. The mean (95% confidence interval) active drag for the two systems, at the same maximum speed of 1.68 m/s (1.40–1.87 m/s), was significantly different (p= .002) with a 55% variation in magnitude. The mean active drag was 82.3 N (74.0–90.6 N) for the MAD system and 148.3 N (127.5–169.1 N) for the ATM system. These differences were attributed to variations in swimming style within each measurement system. The inability to measure the early catch phase and kick, along with the fixed length and depth hand place requirement within the MAD system generated a different swimming technique, when compared with the more natural free swimming ATM protocol. A benefit of the MAD system was the measurement of active drag at various speeds. Conversely, the fixed towing speed of the ATM system allowed a natural self-selected arm stroke (plus kick) and the generation of an instantaneous force-time profile.

Swimming Style Classification Based on Ensemble Learning and Adaptive Feature Value by Using Inertial Measurement Unit

2017 ◽  
Vol 21 (4) ◽  
pp. 616-631 ◽  
Author(s):  
Yuto Omae ◽  
Yoshihisa Kon ◽  
Masahiro Kobayashi ◽  
Kazuki Sakai ◽  
Akira Shionoya ◽  
...  
Keyword(s):  
Ensemble Learning ◽  
Test Data ◽  
Mean Value ◽  
Measurement Unit ◽  
Front Crawl ◽  
The Mean ◽  
Feature Values ◽  
Swimming Style ◽  
Learning Data ◽  
F Measure

We have been constructing a swimming ability improvement support system. One of the issues to be addressed is the automatic classification of swimming styles (backstroke, breaststroke, butterfly, and front crawl). The mainstream swimming style classification technique of conventional researches is based on non-ensemble learning; in their classification, breaststroke and butterfly are mixed up with each other. To improve its generalization performance, we need to use better classifiers and more adaptive feature values than previously considered. Therefore, this research has introduced (1) random forest technique, one of ensemble learning techniques, and (2) feature values specific to breaststroke and butterfly to construct a four-swimming-style classifier that has resolved this issue. From subjects with 7 to 20 years history of swimming races, we have obtained their sensor data during swimming and have divided the data into learning data and test data. We have also converted them into feature values that represent their body motions. We have selected from those body-motion-representing feature values the important data to classify four swimming styles and feature values specific to breaststroke and butterfly. We have used the learning data to construct a swimming style classifier, and the test data to evaluate its classification accuracy. The evaluation results show that (1’) the introduction of ensemble learning has improved the mean value of F-measure for breaststroke and butterfly by 0.053, and (2’) the introduction of feature values specific to breaststroke and butterfly has improved the mean value of F-measure for breaststroke and butterfly by 0.121 as compared with (1’). The proposed swimming style classifier has performed a mean F-measure of 0.981 for the four swimming styles as well as good classification accuracies for front crawl and backstroke. Therefore, we have concluded that the swimming style classifier we have constructed has resolved the problem of mixing up breaststroke and butterfly, as well as can properly classify all different swimming styles.

The force–time profile of elite front crawl swimmers

2011 ◽  
Vol 29 (8) ◽  
pp. 811-819 ◽  
Author(s):  
Danielle P. Formosa ◽  
Bruce Mason ◽  
Brendan Burkett
Keyword(s):  
Time Profile ◽  
Front Crawl ◽  
Force Time

scholarly journals Monitoring Master Swimmers’ Performance and Active Drag Evolution along a Training Mesocycle

2021 ◽  
Vol 18 (7) ◽  
pp. 3569
Author(s):  
Henrique P. Neiva ◽  
Ricardo J. Fernandes ◽  
Ricardo Cardoso ◽  
Daniel A. Marinho ◽  
J. Arturo Abraldes
Keyword(s):  
Aerobic Training ◽  
Training Period ◽  
Velocity Variation ◽  
Hydrodynamic Drag ◽  
Swimming Training ◽  
Front Crawl ◽  
Maximal Intensity ◽  
Before And After ◽  
Active Drag

This study aimed to analyze the effects of a swimming training mesocycle in master swimmers’ performance and active drag. Twenty-two 39.87 ± 6.10 year-old master swimmers performed a 25 m front crawl at maximal intensity before and after a typical four-week training mesocycle. Maximum, mean and minimum speeds, speed decrease and hip horizontal intra-cyclic velocity variation were assessed using an electromechanical speedometer, and the active drag and power to overcome drag were determined using the measuring active drag system. Maximum, mean and minimum front crawl speeds improved from pre- to post-training (mean ± 95% CI: 3.1 ± 2.8%, p = 0.04; 2.9 ± 1.6%, p = 0.01; and 4.6 ± 3.1%, p = 0.01; respectively) and the speed decrease along the 25 m test lowered after the training period (82.5 ± 76.3%, p = 0.01). The training mesocycle caused a reduction in the active drag at speeds corresponding to 70% (5.0 ± 3.9%), 80% (5.6 ± 4.0%), and 90% (5.9 ± 4.0%), but not at 100% (5.9 ± 6.7%), of the swimmers’ maximal exertions in the 25 m test. These results showed that four weeks of predominantly aerobic training could improve master swimmers’ performance and reduce their hydrodynamic drag while swimming mainly at submaximal speeds.

scholarly journals Basic Swimming Style Crawl Engineering Skills Survey in Athletes Ages 10-12

2021 ◽  
Vol 1 (02) ◽  
pp. 115-124
Author(s):  
Puput Widodo ◽  
Fatma Zainul Yunida
Keyword(s):  
Skills Training ◽  
Average Standard Deviation ◽  
Descriptive Data ◽  
Frequency Table ◽  
Minimum Data ◽  
Research Plan ◽  
The Right ◽  
Basic Motion ◽  
Swimming Style ◽  
Swimming Technique

This study aims to: 1.To know the basic technique skills of crawl style swimming in the Kebumen swimming club association students. 2. Knowing the factors of difficulty experienced by students in learning the basic motion skills of crawl style swimming 3. Students are able to apply the basic movements of swimming with the right steps. This research was conducted on the students of the Kebumen swimming club association in Gossi Kebumen. The research plan is carried out in November 2021. The sample referred to in this study is 20 students in the 10-12 year age group who take part in basic swimming skills training. Descriptive data analysis was entered to get an overview of the data including the average, standard deviation, maximum data, minimum data, range, frequency table and graphs. Based on the results of the research that has been carried out, it can be concluded: 1. Freestyle swimming skills measured using a stopwatch on students aged 10-12 years at the swimming club association in Kebumen showed that 50% of students had very poor swimming skills, 25% students have poor swimming skills and 25% of students have sufficient skills. 2. The category of skills that dominates the most in students is very low ability. Contributing to further research is to conduct research on more intense exercises on crawl swimming style techniques need to be done by athletes and also strategies to improve the ability of athletes in crawl style swimming.Keywords: Swimming, Crawl Style, Basic Swimming Technique

scholarly journals An operational solar wind prediction system transitioning fundamental science to operations

2018 ◽  
Vol 8 ◽  
pp. A39 ◽  
Author(s):  
Jingjing Wang ◽  
Xianzhi Ao ◽  
Yuming Wang ◽  
Chuanbing Wang ◽  
Yanxia Cai ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Solar Wind ◽  
Arrival Time ◽  
Space Environment ◽  
Maximum Speed ◽  
Source Surface ◽  
Prediction System ◽  
Fundamental Science ◽  
Cone Model ◽  
The Mean

We present in this paper an operational solar wind prediction system. The system is an outcome of the collaborative efforts between scientists in research communities and forecasters at Space Environment Prediction Center (SEPC) in China. This system is mainly composed of three modules: (1) a photospheric magnetic field extrapolation module, along with the Wang-Sheeley-Arge (WSA) empirical method, to obtain the background solar wind speed and the magnetic field strength on the source surface; (2) a modified Hakamada-Akasofu-Fry (HAF) kinematic module for simulating the propagation of solar wind structures in the interplanetary space; and (3) a coronal mass ejection (CME) detection module, which derives CME parameters using the ice-cream cone model based on coronagraph images. By bridging the gap between fundamental science and operational requirements, our system is finally capable of predicting solar wind conditions near Earth, especially the arrival times of the co-rotating interaction regions (CIRs) and CMEs. Our test against historical solar wind data from 2007 to 2016 shows that the hit rate (HR) of the high-speed enhancements (HSEs) is 0.60 and the false alarm rate (FAR) is 0.30. The mean error (ME) and the mean absolute error (MAE) of the maximum speed for the same period are −73.9 km s−1 and 101.2 km s−1, respectively. Meanwhile, the ME and MAE of the arrival time of the maximum speed are 0.15 days and 1.27 days, respectively. There are 25 CMEs simulated and the MAE of the arrival time is 18.0 h.

Training, Speed and Stamina in Trout

1962 ◽  
Vol 39 (4) ◽  
pp. 537-555 ◽  
Author(s):  
RICHARD BAINBRIDGE
Keyword(s):  
Respiratory Rate ◽  
Behavioural Response ◽  
Wild Fish ◽  
Maximum Speed ◽  
Considerable Variability ◽  
Experimental Conditions ◽  
Percentage Improvement ◽  
The Mean ◽  
Better Than

1. A number of trout (Salmo irideus) were kept continuously swimming for a period of 12 months in experimental tanks in which the water was made to rotate at a mean speed of 25 cm./sec. 2. These fish become available for study in the ‘Fish Wheel’ and measurements were made of the maximum speed they sustained for periods of swimming of different duration. 3. For bursts of swimming of up to 20 sec. duration the mean accomplishments of these fish were identical with those of the unexercised trout studied previously. 4. Considerable variability was found amongst the specimens tested and the best of the present exercised fish were appreciably better than the best of the previous unexercised ones. The biggest improvement was 36 % at the 10 sec. period of swimming; the mean percentage improvement for all periods was 11 %. 5. Some specimens were found better at swimming for short periods and others at swimming for longer. 6. In the absence of comparable figures for the earlier fish, the measurements of cruising speeds sustained for periods up to 1½ hr. were compared with other figures in the literature and found to be about half some of these for wild fish. 7. The implications of the results are considered and two interpretations stressed. First, it is assumed that there is a real identity of accomplishment for short periods of swimming, values being determined perhaps solely by gross mass of muscle; while for longer periods of swimming differences dependent upon respiratory rate etc. may well occur. Secondly, for such longer periods the discrepancies reported here may well be accounted for by differing degrees of stimulus and behavioural response under varied experimental conditions.

scholarly journals Front Crawl Is More Efficient and Has Smaller Active Drag Than Backstroke Swimming: Kinematic and Kinetic Comparison Between the Two Techniques at the Same Swimming Speeds

2020 ◽  
Vol 8 ◽  
Author(s):  
Tomohiro Gonjo ◽  
Kenzo Narita ◽  
Carla McCabe ◽  
Ricardo J. Fernandes ◽  
João Paulo Vilas-Boas ◽  
...  
Keyword(s):  
Front Crawl ◽  
Active Drag

Comparison of the Mean Time Between Failures for Two Systems Under Short Tests

2009 ◽  
Vol 58 (4) ◽  
pp. 589-596 ◽  
Author(s):  
Y.H. Michlin ◽  
G.Y. Grabarnik ◽  
E. Leshchenko
Keyword(s):  
Mean Time Between Failures ◽  
Time Between Failures ◽  
Two Systems ◽  
The Mean ◽  
Mean Time

Performance of Young Male Swimmers in the 100-Meters Front Crawl

2010 ◽  
Vol 22 (2) ◽  
pp. 278-287 ◽  
Author(s):  
Fabrício de Mello Vitor ◽  
Maria Tereza Silveira Böhme
Keyword(s):  
Critical Speed ◽  
Swimming Performance ◽  
Anaerobic Power ◽  
Young Male ◽  
Front Crawl ◽  
Physiological Factors ◽  
Average Speed ◽  
Technical Factors ◽  
Swimming Technique

Youth swimming performance may be influenced by anthropometric, physiology and technical factors. The present paper examined the role of these factors in performance of 100m freestyle in swimmers 12–14 years of age (n = 24). Multiple regression analysis (forward method) was used to examine the variance of the 100 meters front crawl. Anaerobic power, swimming index and critical speed explained 88% (p < .05) of the variance in the average speed of 100 meters front crawl among young male pubertal swimmers. To conclude, performance of young swimmers in the 100 meters front crawl is determined predominantly by physiological factors and swimming technique.

Propelling efficiency of front-crawl swimming

1988 ◽  
Vol 65 (6) ◽  
pp. 2506-2512 ◽  
Author(s):  
H. M. Toussaint ◽  
A. Beelen ◽  
A. Rodenburg ◽  
A. J. Sargeant ◽  
G. de Groot ◽  
...  
Keyword(s):  
Kinetic Energy ◽  
Energy Expenditure ◽  
Mechanical Efficiency ◽  
Total Efficiency ◽  
Extended Version ◽  
O2 Uptake ◽  
Free Swimming ◽  
Front Crawl ◽  
Propelling Efficiency ◽  
The Relationship

In this study the propelling efficiency (ep) of front-crawl swimming, by use of the arms only, was calculated in four subjects. This is the ratio of the power used to overcome drag (Pd) to the total mechanical power (Po) produced including power wasted in changing the kinetic energy of masses of water (Pk). By the use of an extended version of the system to measure active drag (MAD system), Pd was measured directly. Simultaneous measurement of O2 uptake (VO2) enabled the establishment of the relationship between the rate of the energy expenditure (PVO2) and Po (since when swimming on the MAD system Po = Pd). These individual relationships describing the mechanical efficiency (8-12%) were then used to estimate Po in free swimming from measurements of VO2. Because Pd was directly measured at each velocity studied by use of the MAD system, ep could be calculated according to the equation ep = Pd/(Pd + Pk) = Pd/Po. For the four top class swimmers studied, ep was found to range from 46 to 77%. Total efficiency, defined as the product of mechanical and propelling efficiency, ranged from 5 to 8%.

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