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An Rn Surface to Describe Sport Performance in Women's Basketball Using Kohonen Nets on ECG Signals

Published:18 October 2017Publication History

ABSTRACT

In this paper, we describe a procedure to create a surface based on R29 information, each vector corresponds to information taken from players of women basketball team of Universidad Militar Nueva Granada, those data include frequency data from ECG, statistic data from heart rate variability, and anatomic information as age and height. A close following was done for each player conforming the team, a total of 96 registers from every single player were acquired and used for create a 29 vector to characterize each player in a specific date.

Konohen net technique was employed to make a mapping between high dimensional data and 2 dimensional system of coordinates and nodes, after that, information resulting from Kohonen net was used to represent the performance on the complete team, and groups were detected into the map that can describe and even predict some performance characteristics of a new player.

References

  1. D. E. R. James Mc Clelland, Parallel Distributed Processing, The MIT Press, 1986.Google ScholarGoogle Scholar
  2. P. C. PK. Sharpe, "Self organising maps for the investigation of clinical data: a case study," Neural Comput Appl, vol. 7, pp. 65--70, 1998.Google ScholarGoogle ScholarCross RefCross Ref
  3. S. Malek, A. Salleh and S. A. Sharifah Mumtazah, "Analysis of Algal Growth using Kohonen Self Organizing Feature Map (SOM) and its Prediction using Rule Based Expert System," in International Conference on Information Management and Engineering, Xi'an, China, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. M. S. S. B. J. Koh, "A multilayer self organizing feature map for range image segmentation," Neural Netw, vol. 8, no. 1, pp. 67--86, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. J. Vesanto, "SOM-Based Visualisation Methods," Intelligent Data, vol. 3, pp. 111--126, 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. A. A. Pastukhov and A. A. Prokofiev, "Kohonen self-organizing map application to representative sample formation in the training of the multilayer perceptron," St. Petersburg Polytechnical University Journal: Physics and Mathematics, vol. 2, pp. 134--143, 2016.Google ScholarGoogle ScholarCross RefCross Ref
  7. H. Bauer and W. Schöllhorn, "Self-organizing maps for the analysis of complex movement patterns," Neural Processing Letters, vol. 5, pp. 193--199, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. A. Lees and G. Barton, "A characterisation of technique in the soccer kick using a Kohonen neural network analysis," Science and Football V., pp. 83--88, 2005.Google ScholarGoogle Scholar
  9. My EKG, "Derivaciones Cardiacas, significado," 15 Junio 2016. {Online}. Available: http://www.my-ekg.com/generalidades-ekg/derivaciones-cardiacas.html. {Accessed 1 Julio 2016}.Google ScholarGoogle Scholar
  10. R. Desai and F. Lin, "Medical Diagnosis with a Kohonen LVQ2 Neural Network (PDF Download Available)," 1 Agosto 2014. {Online}. Available: https://www.researchgate.net/publication/237738026_Medical_Diagnosis_with_a_Kohonen_LVQ2_Neural_Network. {Accessed 26 Mayo 2016}.Google ScholarGoogle Scholar
  11. a. t. study, "ECG Rules," 2012. {Online}. Available: http://www.ambulancetechnicianstudy.co.uk/rules.html#.V3a75rjhBdg. {Accessed 1 Julio 2016}Google ScholarGoogle Scholar

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      cover image ACM Other conferences
      ICCBB '17: Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics
      October 2017
      115 pages
      ISBN:9781450353229
      DOI:10.1145/3155077

      Copyright © 2017 ACM

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      Publication History

      • Published: 18 October 2017

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