ABSTRACT
In this paper we introduce the concept of a wearable assistant for swimmer, called SwimMaster. The SwimMaster consists of acceleration sensors with micro-controllers and feedback interface modules that swimmer wear while swimming. With four different evaluation studies and a total of 22 subjects we demonstrate the functionality and power of the SwimMaster system. We show how a wide range of swim parameters can be monitored and used for a continuous swim performance evaluation. These parameters include the time per lane, the swimming velocity and the number of strokes per lane. Also swim style specific factors like the body balance and the body rotation are extracted. Finally three feedback modalities are tested and evaluated. With these means we show the ability of the SwimMaster to assist a swimmer in achieving the desired exercise goals by constantly monitoring his/her swim performance and providing the necessary feedback to achieve the desired workout goals.
- R. Anderson, A. Harrison, and G.M. Lyons. Accelerometry-based feedback -- can it improve movement consistency and performance in rowing? Sports Biomechanics, 4(2):179--195, 2005.Google ScholarCross Ref
- B. Auvinet, E. Gloria, G. Renault, and E. Barrey. Runner's stride analysis: comparison of kinematic and kinetic analyses under field conditions. Science&Sports 2002, 17:92--4, 2002.Google ScholarCross Ref
- M. Bächlin, D. Roggen, and G. Tröster. Context-aware platform for long-term life style management and medical signal analysis. In Proceedings of the 2nd Sensation International Conference, Chania, Greece, 2007.Google Scholar
- D. Bannach, K. Kunze, P. Lukowicz, and O. Amft. Distributed modular toolbox for multi-modal context recognition. In ARCS 2006: Proceedings of the 19th International Conference on Architecture of Computing Systems., pages 99--113, March 2006. Google ScholarDigital Library
- M. Beetz, B. Kirchlechner, and M. Lames. Computerized real-time analysis of football games. IEEE Pervasive Computing, 4(3):33--39, 2005. Google ScholarDigital Library
- M. Beetz, N.v. Hoyningen-Huene, J. Bandouch, B. Kirchlechner, S. Gedikli, and A. Maldonado. Camera-based observation of football games for analyzing multi-agent activities. In AAMAS '06: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems, pages 42--49, New York, NY, USA, 2006. ACM. Google ScholarDigital Library
- A.J. Callaway. A comparison of video and accelerometer based approaches applied to performance monitoring in swimming. International Journal of Sports Science and Coaching, 4:139--153(15), March 2009.Google ScholarCross Ref
- R. Chan. Swimming lap counter, December 2007.Google Scholar
- A.J. Craig and D. Pendergast. Relationships of stroke rate, distance per stroke, and velocity in competitive swimming. Med Sci Sports, 11(3):278--83, 1979.Google Scholar
- N.P. Davey, M.E. Anderson, and D.A. James. An accelerometer-based system for elite athlete swimming performance analysis. volume 5649, pages 409--415. Society of Photo-Optical Instrumentation Engineers (SPIE) Conference, 2005.Google Scholar
- K. Förster, M. Bächlin, and G. Tröster. Non-interrupting user interfaces for electronic body-worn swim devices. In Proceedings of the 2nd International Conference on PErvasive Technologies Related to Assistive Environments, June 2009. Google ScholarDigital Library
- J. Hey and S. Carter. Pervasive computing in sports training. Pervasive Computing, IEEE, 4(3):54--, July-Sept. 2005. Google ScholarDigital Library
- D. James, N. Davey, and T. Rice. An accelerometer based sensor platform for insitu elite athlete performance analysis. Sensors, 2004. Proceedings of IEEE, pages 1373--1376 vol.3, 24-27 Oct. 2004.Google ScholarCross Ref
- G.J. Maw and S. Volkers. Measurement and application of stroke dynamics during training in your own pool. Australian Swim. Coach, 12(3):34--38, 1996.Google Scholar
- F. Michahelles and B. Schiele. Sensing and monitoring professional skiers. IEEE Pervasive Computing, 4(3):40--46, 2005. Google ScholarDigital Library
- Y. Ohgi. Microcomputer-based acceleration sensor device for sports biomechanics -- stroke evaluation by using swimmer's wrist acceleration. Sensors, 2002. Proceedings of IEEE, 1:699--704, 2002.Google ScholarCross Ref
- D. Roggen, N.B. Bharatula, M. Stäger, P. Lukowicz, and G. Tröster. From sensors to miniature networked sensorbuttons. In In Proc. of the 3rd Int. Conf. on Networked Sensing Systems (INSS06), pages 119--122, 2006.Google Scholar
- S.E. Slawson, L.M. Justham, A.A. West, P.P. Conway, M.P. Caine, and R. Harrison. Accelerometer profile recognition of swimming strokes. The Engineering of Sport, 7:81--87, Aug. 2008.Google Scholar
- S. Tarpinian. The Triathlete's Guide to Swim Training. VeloPress, 2005.Google Scholar
Index Terms
- SwimMaster: a wearable assistant for swimmer
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