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摘要:Falls have caused extensive interest of the researchers for it becomes the second largest accidental injury to death in the worldAnd there are lots of approaches to fall detection at presentHowever,on account for the complexity of this problem,a preferable effective method for fall detection hasn’t been present so farThis paper adopts a relatively high-predicted and stable SVM classifier to predict falls10 healthy young subjects participated in this study based on the Xsens MVN Biomech systemWith the extraction of feature vectors,as well as the exploration of the best position,it found that the waist would be the best to measure body’s motion,and the simple accelerometer can offer the preferable features for the classifier to determinate the falls wellMeanwhile it can get a high accuracy up to 96% by setting an optimal C and g with five-fold cross-validation testing.
会议名称:

第三届健康信息学国际学术会议(HIS 2014)

会议时间:

2014-04-21

会议地点:

中国广东深圳

  • 专辑:

    电子技术及信息科学

  • 专题:

    自动化技术

  • 分类号:

    TP18

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