Literature DB >> 28268467

Characterizing muscular activities using non-negative matrix factorization from EMG channels for driver swings in golf.

Yasunori Ozaki, Ryosuke Aoki, Toshitaka Kimura, Youichi Takashima, Tomohiro Yamada.   

Abstract

The goal of this study is to propose a data driven approach method to characterize muscular activities of complex actions in sports such as golf from a lot of EMG channels. Two problems occur in a many channel measurement. The first problem is that it takes a lot of time to check the many channel data because of combinatorial explosion. The second problem is that it is difficult to understand muscle activities related with complex actions. To solve these problems, we propose an analysis method of multi EMG channels using Non-negative Matrix Factorization and adopt the method to driver swings in golf. We measured 26 EMG channels about 4 professional coaches of golf. The results show that the proposed method detected 9 muscle synergies and the activation of each synergy were mostly fitted by sigmoid curve (R2=0.85).

Mesh:

Year:  2016        PMID: 28268467     DOI: 10.1109/EMBC.2016.7590844

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  1 in total

1.  eDRAM: Effective early disease risk assessment with matrix factorization on a large-scale medical database: A case study on rheumatoid arthritis.

Authors:  Chu-Yu Chin; Sun-Yuan Hsieh; Vincent S Tseng
Journal:  PLoS One       Date:  2018-11-26       Impact factor: 3.240

  1 in total

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