Sep 7, 2009
Quantitative Classification of Pedaling Skill of Power-Assisted Bicycles Using Discriminant Analysis based on Mahalanobis Distance
IEICE technical report
- ,
- ,
- ,
- Volume
- 109
- Number
- 194
- First page
- 1
- Last page
- 6
- Language
- Japanese
- Publishing type
- Publisher
- The Institute of Electronics, Information and Communication Engineers
In this report, we evaluated pedaling skills from muscle activation patterns of both vastus lateralis of agonist and biceps femoris of antagonist, to classify them quantitatively. To this end, four parameters to classify muscle activation were prepared by means of calculating cross-correlation coefficients between the above two muscles. In the four-parameter space, we classified the pedaling skills into four groups in terms of the discriminant analysis based on Mahalanobis distances. As a result, the classification method presented in this report corresponded about 70.6% accuracy with a qualitative classification based on the human subjectivity. Furthermore, the groups classified by this method were statistically more significant than the qualitative classification.
- Link information
-
- CiNii Articles
- http://ci.nii.ac.jp/naid/110007387366
- CiNii Books
- http://ci.nii.ac.jp/ncid/AN1001320X
- URL
- http://id.ndl.go.jp/bib/10390264
- ID information
-
- ISSN : 0913-5685
- CiNii Articles ID : 110007387366
- CiNii Books ID : AN1001320X