中国医疗设备2016，Vol.31Issue(5)：43-46,53,5.DOI:10.3969/j.issn.1674-1633.2016.05.010
基于SVM算法的红外测量皮下脂肪厚度模型研究
Study of the Model for Infrared Measurement of Subcutaneous Fat Thickness Based on SVM Algorithm
王玉 1郝冬梅 2安峥1
作者信息
- 1. 中日友好医院 医学工程处，北京100026
- 2. 北京工业大学 生命科学与生物工程学院，北京100124
- 折叠
摘要
Abstract
This paper established a model for infrared measurement of subcutaneous fat thickness based on Support Vector Machine (SVM) algorithm. 40 cases of human experiment were designed and completed. The subcutaneous thickness of 20 body parts of each subject was measured. 6 regression models were established with nonlinear methods (including whole data, segment data, date excepted for shoulder blade, upper limb data, lower limb data, and abdomen data). The prediction value of each model was analyzed in comparison with the ultrasound measurement value. The results indicated that the segment model predicted more accurately than the whole data model. The upper limb model was most ideal, whose correlation coefficient with B ultrasound was 0.9. The results showed the SVM model, was more suitable for accurate and rapid measurement of subcutaneous adipose tissue thickness.关键词
SVM算法/皮下脂肪厚度/红外测量Key words
support vector machine algorithm/subcutaneous fat thickness/infrared measurement分类
医药卫生引用本文复制引用
王玉,郝冬梅,安峥..基于SVM算法的红外测量皮下脂肪厚度模型研究[J].中国医疗设备,2016,31(5):43-46,53,5.
