Central European Journal of Sport Sciences and Medicine


ISSN: 2300-9705     eISSN: 2353-2807    OAI    DOI: 10.18276/cej.2017.3-09
CC BY-SA   Open Access   DOAJ  DOAJ

Lista wydań / Vol. 19, No. 3/2017
Validation of the New Visual Swimming Pace Control System in Real-Time

Autorzy: Stefan Szczepan
Faculty of Physical Education, Department of Swimming, University School of Physical Education, Wroclaw, Poland

Krystyna Zatoń
Faculty of Physical Education, Department of Swimming, University School of Physical Education, Wroclaw, Poland
Słowa kluczowe: device validation speed control system swimming speed visual information
Data publikacji całości:2017-09
Liczba stron:12 (93-104)
Cited-by (Crossref) ?:

Abstrakt

Controlling swimming speed, i.e. the intensity of physical activity, is an important factor in swimming training. The aim of this study was to validate the new “Swimming Pace Control System” (SPCS) for the control of swimming speed in real time using visual information. Submerged at the bottom of the pool was a system equipped with LEDs and software that informed the swimmer of the appropriate distance and swimming speed. A validation test was completed with an accuracy of ±200ms which compared the predetermined time for the beam of light emitted by the SPCS and the times achieved and recorded by the electronic starting system; “Colorado Time System” (Colorado Time, USA). The average time required to move the beam simulated by the SPCS at fixed distances (150 m, 100 m, 50 m) was within the assumed error of measurement (500 ms). SPCS was proven to be useful for control of swimming speed in real-time with the aid of visual information. The system gives an objective indication of swimming speed, thus it can be used in swimming training and during empirical research.
Pobierz plik

Plik artykułu

Bibliografia

1.Åstrand, P.O., Rodahl, K., Dahl, H., Stromme, S.B. (2003). Textbook of Work Physiology. Physiological Bases of Exercise (4 ed.). Champaign, Illinois: Human Kinetics.
2.Bächlin, M., Tröster, G. (2012). Swimming performance and technique evaluation with wearable acceleration sensors. Pervasive and Mobile Computing, 8 (1), 68–81.
3.Barbosa, T., Keskinen, K., Fernandes, R., Colaço, P., Lima, A., Vilas-Boas, J.P. (2005). Energy cost and intracyclic variation of the velocity of the centre of mass in butterfly stroke. European Journal of Applied Physiology, 93, 519–523.
4.Callaway, A.J., Cobb, J.E., Jones, I. (2009). A comparison of video and accelerometer based approaches applied to performance monitoring in swimming. International Journal of Sports Science & Coaching, 4 (1), 139–153.
5.Carroll, W., Bandura, A. (1990). Representational guidance of action production in observational learning: A causal analysis. Journal of Motor Behavior, 22, 85–97.
6.Chinnasamy, C., St Clair Gibson, A., Micklewright, D. (2013). Effect of spatial and temporal cues on athletic pacing in schoolchildren. Medicine & Science in Sports & Exercise, 45 (2), 395–402.
7.Chow, J.W., Carlton, L.G., Ekkekakis, P., Hay, J.G. (2000). A web-based video digitizing system for the study of projectile motion. Physics Teacher, 38, 37–40.
8.Costill, D.L., Thomas, R., Robergs, R.A., Pascoe, D., Lambert, C., Barr, S., Fink, W.J. (1991). Adaptations to swimming training: influence of training volume. Medicine and Science in Sports and Exercise, 23, 371–377.
9.Davey, N.P., Anderson, M.E., James, D.A. (2005). An Accelerometer-Based System for Elite Athlete Swimming Performance Analysis. In: S.F. Al Sarawi (ed.), Smart Structures, Devices, and System II (pp. 409–415). Sydney, Australia: Proceedings of the SPIE, 5649.
10.Eskofier, B., Kugler, P., Melzer, D., Kuehner, P. (2012). Embedded Classification of the Perceived Fatigue State of Runners: Towards a Body Sensor Network for Assessing the Fatigue State during Running. In: Guang-Zhong Yang (ed.), Proc. 9th International Conference on Wearable Implantable Body Sensor Network (pp. 113–117). London: IEEE.
11.Fernandes, R.J., Cardoso, C.S., Soares, S.M., Ascensão, A., Colaço, P.J., Vilas-Boas, J.P. (2003). Time limit and VO2 slow component at intensities corresponding to VO2max in swimmers. International Journal of Sports Medicine, 24 (8), 576–581.
12.Gonzalez, V., Sanchis, E., Villalobos, M., Brizuela, G., Llana, S., Tella, V. (2002). A new electronic system for the control of swimming speed. In: J.C. Chatard (ed.), Book of abstract: Biomechanics and Medicine in Swimming IX (pp. 67–69). France: Publications de l’Université de Saint-Étienne.
13.Hay, J.G. (2002). Cycle rate, length and speed of progression in human locomotion. Journal of Applied of Biomechanics, 18, 257–270.
14.Hohmann, A., Fehr, U., Kirsten, R., Krueger, T. (2008). Biomechanical analysis of the backstroke of the start technique in swimming. E-Journal Bewegung und Training, 2, 28–33.
15.Lees, A. (2002). Technique analysis in sports: a critical review. Journal of Sports Sciences, 20, 813–828.
16.Micklewright, D., Angus, C., Suddaby, J., St Clair Gibson, A., Sandercock, G., Chinnasamy, C. (2012). Pacing strategy in schoolchildren differs with age and cognitive development. Medicine & Science in Sports Exercise, 44 (2), 362–369
17.Ohgi, Y. (2002). Microcomputer-based acceleration sensor device for sports biomechanics, Sensors, 1, 699–704.
18.Pelayo, P., Moretto, P., Robin, H., Sidney, M., Gerbeaux, M., Latour, M.G., Marc-Lavoie, J. (1995). Adaptation of maximal aerobic and anaerobic tests for disabled swimmers. European Journal of Applied Physiology Occupational Physiology, 71, 512–517.
19.Pérez, P., Llana, S., Brizuela, G., Encarnación, A. (2009). Effects of three feedback conditions on aerobic swim speeds. Journal of Sports Science and Medicine, 8, 30–36.
20.Proteau, L., Isabelle, G. (2002). On the role of visual afferent information for the control of aiming movements toward targets of different sizes. Journal of Motor Behavior, 34 (4), 367–384.
21.Scruton, A., Baker, J., Roberts, J., Basevitch, I., Merzbach, V., Gordon, D. (2015). Pacing accuracy during an incremental step test in adolescent swimmers. Journal of Sports Medicine, 6, 249–257.
22.Seat, J.E., Wrisberg, C.A. (1996). The visual instruction system. Research Quarterly for Exercise and Sport, 67, 106–108.
23.Slawson, S.E., Justham, L.M., West, A.A., Conway, P.P., Caine, M.P., Harrison, R., (2008). Accelerometer profile recognition of swimming strokes. The Engineering of Sport, 7, 81–87.
24.Szczepan, S., Zatoń, K., Klarowicz, A. (2016). The effect of concurrent visual feedback on the controlled swimming speed. Polish Journal of Sport and Tourism. Polish Journal of Sport Tourism, 23, 3–6.
25.Tanabe, S., Ito, A. (2007). A three-dimensional analysis of the contributions of upper limb joint movements to horizontal racket head velocity at ball impact during tennis serving, Sports Biomechanics, 6 (3), 418–433.
26.Toussaint, H.M., Truijens, M. (2005). Biomechanical aspects of peak performance in human swimming. Animal Biology, 55 (1), 17–40.
27.Turner, A., Smith, T., Coleman, S.G. (2008). Use of an audio-paced incremental swimming test in young national-level swimmers. International Journal of Sports Physiology and Performance, 3, 68–70.
28.Wilmore, J.H., Costill, D., Kenney, W.L. (2008). Physiology of Sport and Exercise. Champaign, Illinois: Human Kinetics.
29.Zamparo, P., Pendergast, D., Mollendorf, J., Termin, A., Minetti, A. (2005). An energy balance of front crawl. European Journal ofApplied Physiology, 94, 134–144.
30.Zatoń, K., Kędrak, M., Rejman, M. (2016). Synchronized feedback (mirror image) and learning of symmetrical movement activities in breaststroke-kick swimming – pilot study. In: S. Szczepan (ed.), Book of Abstract: The 8th International Symposium Science & Swimming (pp. 54–55). Wroclaw: Ata-Druk.
31.Zatoń, K., Szczepan, S. (2014). The Impact of Immediate Verbal Feedback on the Improvement of Swimming Technique. Journal of Human Kinetics, 41, 129–137.