Fuzzy SVM-based chronic fatigue syndrome evaluation embedded in intelligent garment Online publication date: Tue, 27-Oct-2009
by YiZhi Wu, Yong Sheng Ding, HongAn Xu, Hong Fan, BoHui Zhu
International Journal of Modelling, Identification and Control (IJMIC), Vol. 8, No. 2, 2009
Abstract: Intelligent garment (IG), which is embedded with electrical vital signal capturing and analysis model, can be used to offer personal health monitoring anytime and anywhere. Chronic fatigue syndrome (CFS) is a serious and complex problem for people all over the world. But the methods of CFS diagnosis up to now have been very elementary. In this paper, we present the architecture and design consideration of IG embedded in an online CFS evaluation system based on our previous work. To meet the system needs, we perfect the schema by decreasing feature space using principal component analyses (PCA) and by diagnosing CFS more accurately using fuzzy multiclass SVM. Using the ISNI-DHU CFS database we set up, two series of experiments are done and the results show that the RR interval and R amplitude are the most important features and the fuzzy SVM achieved 93.3% of average sensitivity.
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