Application of fuzzy modeling to rowing motion analysis

Kanta Tachibana*, Takeshi Furuhashi, Manabu Shimoda, Yasuo Kawakami, Tetsuo Fukunaga

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)


Fuzzy modeling has distinct features, which are applicability to nonlinear systems and ability to extract knowledge. Fuzzy neural network (FNN) enables automatic acquisition of knowledge. The authors have proposed an uneven division of input space for the FNN which reduces the number of fuzzy rules without sacrificing the precision of the model. In many sports, nonlinear factors affect the performance. In rowing competitions, the performance criterion is the boat speed. In this paper, fuzzy modeling is applied to reveal the relationships between the supplied power and the boat speed. The forces and the angles of on-water rowing are measured. The subjects are candidates of Japanese national team members. The total propulsive work, consistency and uniformity of the propulsive power were calculated from the force and the angle data. The relationships between these factors and the performance were identified with fuzzy modeling. Comparing to linear regression, more precise and more comprehensive model was obtained.

Original languageEnglish
Pages (from-to)VI-190 - VI-195
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Publication statusPublished - 1999
Externally publishedYes
Event1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics' - Tokyo, Jpn
Duration: 1999 Oct 121999 Oct 15

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture


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