SVM based Chronic Fatigue Syndrome Evaluation for Intelligent Garment
Chronic fatigue syndrome (CFS) also called sub-health is a serious and complex problem for modern people all over the world. But the methods of CFS diagnosis up to now are very elementary. This paper tries to establish a CFS evaluation model based on human bodys vital signals, especially ECG. Firstly, an intelligent garment oriented physiological signal capturing and processing platform is proposed. Then, a multi-class SVM-based strategy to render a diagnosis between various degrees of CFS is constructed. Based on the ISNI-DHU CFS database we set up, the results show that the diagnosis model achieve high classification accuracy, at 97.4％ of average accuracy, and heartbeat parameters can be effectively used to evaluation of CFS.
Chronic fatigue syndrome intelligent garment SVM classifier ECG
Wu Yi-Zhi Xu Hong-An Ding Yong-Sheng Shi Jin-Lan Zhu Bo-Hui
College of Information Sciences and Technology Donghua University Shanghai 201620, China College of Information Sciences and Technology East China Normal University Shanghai 200062, China College of Information Sciences and Technology Engineering Research Center of Digitized Textile & Fa
国际会议
上海
英文
1947-1950
2008-05-16（万方平台首次上网日期，不代表论文的发表时间）