Recruitment of small synergistic movement makes a good pianist

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages242-245
Number of pages4
ISBN (Electronic)9781424492718
DOIs
Publication statusPublished - 4 Nov 2015
Externally publishedYes
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: 25 Aug 201529 Aug 2015

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2015-November
ISSN (Print)1557-170X

Conference

Conference37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Country/TerritoryItaly
CityMilan
Period25/08/1529/08/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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