gender prediction by gait analysis based on time series variation of joint positions
Clicks: 155
ID: 251729
2015
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Emerging Content
30.0
/100
155 views
22 readers
AI Quality Assessment
Not analyzed
Readership in this journal
EmergingRanked #34 of 40 articles by views in gastric cancer : official journal of the international gastric cancer association and the japanese gastric cancer association
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
In this paper, a novel gender prediction scheme based on a gait analysis is proposed. For the gait analysis, we propose a novel feature extraction scheme that uses the time series vari- ation in the joint positions directly. Here, normalization by linear interpolation is adopted to set the number of samples of a walking period as the same constant for all target hu- mans. The classifier for gender prediction is constructed with a support vector machine using the feature extraction scheme. To evaluate our proposal, we carried out an experiment for gender prediction using six male and six female humans who are in their twenties. The experimental results show that the classification accuracy is 99.12% when three-dimensional co- ordinates are used directly for feature extraction and 99.12% if two-dimensional features are used in the best case.
| Reference Key |
miyamoto2015journalgender
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Ryusuke Miyamoto;Risako Aoki |
| Journal | gastric cancer : official journal of the international gastric cancer association and the japanese gastric cancer association |
| Year | 2015 |
| DOI |
DOI not found
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.