期刊文献+

骨关节角度数字化测量与功能评估系统设计 被引量:1

Design of joint angle digital measuring and functional assessing system
下载PDF
导出
摘要 为了实现对骨关节空间角度的数字化测量与功能客观评价,建立了骨关节角度数字化测量与功能评估系统。对该系统所采用的骨关节空间角度测量、功能评估算法进行研究。首先,根据Kinect数据采集原理及空间向量计算方法介绍了骨关节空间角度测量算法,即在Kinect深度数据流基础上将骨关节点空间位置信息转换为对应的三维空间坐标,根据空间向量夹角公式计算骨关节空间角度。然后,在分析比较分类评价方法的性能基础上,说明了采用K-means聚类方法进行骨关节功能评估的算法。实验结果表明,系统可以为用户提供骨关节的数字化测量与功能评估结果,评估指标purity、RI与F-meaures等能稳定在0.8及其以上,基本满足骨关节功能评价的非接触、客观高效、适应能力强、准确度高、操作简便和成本低等要求。 In order to realize digital measurement and objective function assessment for joint angle, an joint angle digital measuring and functional assessing system is established and its applied algorithms is investigated. Firstly, based on Kinect data acquisition principles and calculation method of space vectors, the joint angle measuring algorithm is presented. The space points of joint on the basis of the depth data of Kinect are converted to the corresponding three-dimensional coordinates which will be used to calcu-late the Euclidean distance between each key point, and the joint space angles are calculated according to the angle formula of space vector. Then after the performance of several clustering methods is compared, the algorithm of function assessing by K-means is analyzed. Experimental results indicate that the system can realize the digital measuring and assessing, and the precision of the clustering indexes of purity, RI and F-meaures can be stabled in 0. 8 and above. It can satisfy the system requirements of non-contact, objective, effective, higher precision and strong adaptability, as well as user-friendly control and low cost.
作者 方艳红 杨雪梅 张红英 王学渊 Fang Yanhong;Yang Xuemei;Zhang Hongying;Wang Xueyuan(School of Information Engineering,Southwest University of Science and Technology-,Mianyang 621010,China)
出处 《电子技术应用》 2018年第8期126-129,共4页 Application of Electronic Technique
基金 国家自然科学基金项目(11472297) 四川省科技厅科技创新平台建设项目(2017TJPT0200)
关键词 Kinect数据采集 骨关节角度测量 功能评估 K-MEANS聚类算法 Kinect data acquisition joint angle measurement function assessment K-means clustering algorithm
  • 相关文献

参考文献5

二级参考文献44

  • 1向培素.聚类算法综述[J].西南民族大学学报(自然科学版),2011,37(S1):112-114. 被引量:14
  • 2张惟皎,刘春煌,李芳玉.聚类质量的评价方法[J].计算机工程,2005,31(20):10-12. 被引量:60
  • 3Titterington D M, Smith A F M, Makov U E. Statistical Analysis of Finite Mixture Distribution[M]. New York, USA: Wiley, 1985.
  • 4Solomon K. Information Theory and Statistics[M]. New York, USA: Dover Publications Inc., 1968.
  • 5Hershey J R, Olsen P A. Approximating the Kullback Leibler Divergence Between Gaussian Mixture Models[C]//Proc. of ICASSP'07. [S. L]: IEEE Press, 2007: 317-320.
  • 6Penny W D. Kullback-Liebler Divergences of Normal, Gamma, Dirichlet and Wishart Densities[C]//Proc. of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. New York, USA: ACM Press, 2001.
  • 7Chau M, Cheng R, Kao Ben, et al. Uncertain Data Mining: An Example in Clustering Location Data[C]//Proc. of PAKDD'06. [S.L]: IEEE Press, 2006: 199-204.
  • 8Ng R, Han Jiawei. Efficient and Effective Clustering Methods for Spatial Data Mining[C]//Proc. of the 20th International Conference on Very Large Data Bases. San Francisco, USA: Morgan Kaufmann Publishers Inc., 1994:144-155.
  • 9Thinkstock[EB/OL]. (2011-02-18). http://www.hemera.com/hem era/Corel.
  • 10Greenspan H, Goldberger J, Ridel L. A Continuous Probabilistic Framework for Image Matching[J]. Computer Vision and Image Understanding, 2001, 84(3): 384-406.

共引文献72

同被引文献12

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部