• DocumentCode
    3683922
  • Title

    Recruitment of small synergistic movement makes a good pianist

  • Author

    Beth Jelfs;Shengli Zhou;Bernard K.Y. Wong;Chung Tin;Rosa H.M. Chan

  • Author_Institution
    Department of Electronic Engineering and the Centre for Biosystems, Neuroscience, and Nanotechnology (CBNN), City University of Hong Kong, Hong Kong
  • fYear
    2015
  • Firstpage
    242
  • Lastpage
    245
  • Abstract
    Time-varying synergies from kinematic data can be used to discern fundamental patterns of movement. We show through simultaneous extraction of synergies from both novice and experienced pianists that movement common to both groups can be identified. The extracted synergies successfully allow for the majority of the variability of the data to be accounted for by a limited number of components. Furthermore, classification of the weightings representing the recruitment of each of the synergies accurately distinguishes between the piano playing of the two groups of subjects. However, the major differences between the two groups lie not in the synergies representing the majority of the variance of the data but in the recruitment of smaller synergies.
  • Keywords
    "Joints","Thumb","Indexes","Presses","Recruitment","Data mining","Kinematics"
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Electronic_ISBN
    1558-4615
  • Type

    conf

  • DOI
    10.1109/EMBC.2015.7318345
  • Filename
    7318345