Gait Analysis and Machine Learning Classification on Healthy Subjects in Normal Walking

被引：1

作者：

Shirakawa, Tomohiro ^{[1
]}

Sugiyama, Naruhisa ^{[2
]}

Sato, Hiroshi ^{[1
]}

Sakurai, Kazuki ^{[1
]}

Sato, Eri ^{[1
]}

机构：

[1] Natl Def Acad Japan, Sch Elect & Comp Engn, Dept Comp Sci, Yokosuka, Kanagawa 2398686, Japan

[2] Horinouchi Chiropract, Yokosuka, Kanagawa 2380014, Japan

来源：

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2014 (ICNAAM-2014) | 2015年 / 1648卷

关键词：

gait analysis; accelerometry; machine learning; healthy subject; normal walking; KNOCK KNEES; ACCELEROMETRY; PARAMETERS;

D O I：

10.1063/1.4912817

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Walking is one of the most fundamental activities of human, and there have already been many studies on human walking. However, most of the studies so far mainly focus on the impaired gait of the patients with some disease or injury, and thus there are not many studies on the gait patterns of healthy subjects. In this study, we performed a gait analysis on 113 healthy subjects in normal walking and tried to classify their walking patterns by using cluster analysis and principal component analysis. As a result, we got the basic data on the body movement of healthy walkers and the criteria for the evaluation and classification of unimpaired gait patterns.

引用

页数：4

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