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
Link To Document :
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