Network Approach to Inducing Coordinative Structures of Skillful Movements

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.