single-jc.php

JACIII Vol.15 No.8 pp. 988-996
doi: 10.20965/jaciii.2011.p0988
(2011)

Paper:

Network Approach to Inducing Coordinative Structures of Skillful Movements

Masanori Tsujino, Tsutomu Fujinami, and Keisuke Nagai

Japan Advanced Institute of Science and Technology

Received:
February 21, 2011
Accepted:
May 15, 2011
Published:
October 20, 2011
Keywords:
coordinative structure, network, correlation, motion capture, drum performance
Abstract

Even though coordination is the key to explaining skillful movement, as advocated by Bernstein, analyzing the coordinative structure of body parts remains yet to be fully addressed. Pattern matching applied to analyzing skillful movement cannot describe the coordinative structure. A correlation network is useful for identifying the most influential factor in the web of correlations among factors. The correlation network is thus thought to be effective in analyzing coordinative structures because it enables us to identify the body partmost influential in skillful movement. As an example of skillful movement, we investigated traditional Japanese Heike-daiko drumming to see if we could describe the coordinative structure through this approach. We created correlation networks among body parts involved in playing the Heike-daiko. We asked a Heike-daiko player to play a rhythmic pattern typical of traditional drumming and collected data on movement using a motion capture device. We split the performance sequence into 10 sections, each exhibiting a unique characteristic of the player. It was difficult for onlookers to distinguish these 10 patterns because differences were too subtle to recognize visually. By applying our method to data, we found overlaps among the 10 sections in that the same set of body parts tends to form a network through the sequence. Results suggest that movement similarities and differences can be captured by comparing correlation networks among body parts. We also found two classes of coordinative structure, one reflecting our anatomical structure and the other quite different from it. We found that second class classifies skillful movement.

Cite this article as:
Masanori Tsujino, Tsutomu Fujinami, and Keisuke Nagai, “Network Approach to Inducing Coordinative Structures of Skillful Movements,” J. Adv. Comput. Intell. Intell. Inform., Vol.15, No.8, pp. 988-996, 2011.
Data files:
References
  1. [1] N. A. Bernstein, “Dexterity and its development,” Lawrence Erlbaum Assoc Inc, 1996.
  2. [2] T. Miura, K. Mitobe, T. Yukawa, T. Kaiga, T. Taniguchi, and H. Tamamoto, “Adaptation of Grouping Structure Analysis in GTTM to Hierarchical Segmentation of Dance Motion,” Trans. of Information Processing Society of Japan, 51:2354-2374, 2010.
  3. [3] T. Mizuno, H. Takayasu, and M. Takayasu, “Correlation Networks among Currencies,” Physica A, 364:336-342, 2005.
  4. [4] C. H. Papadimitriou and K. Steiglitz, “Combinatorial optimization : algorithms and complexity,” Dover Publications, 1998.
  5. [5] D. B. West, “Introduction to Graph Theory,” Prentice-Hall, 2001.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Mar. 05, 2021