Gait Classification of Healthy Young and Elderly Adults Using Micro-Doppler Radar Remote Sensing

被引：5

作者：

Okinaka, Hiroaki ^{[1
]}

Saho, Kenshi ^{[2
]}

Fujimoto, Masahiro ^{[3
]}

Go, Seiken ^{[1
]}

Masugi, Masao ^{[1
]}

Sugano, Kouki ^{[2
]}

Uemura, Kazuki ^{[4
]}

Matsumoto, Michito ^{[5
]}

机构：

[1] Ritsumeikan Univ, Dept Elect & Comp Engn, Kusatsu, Shiga, Japan

[2] Toyama Prefectural Univ, Dept Intelligent Robot, Imizu, Toyama, Japan

[3] Ritsumeikan Univ, Coll Sport & Hlth Sci, Kusatsu, Shiga, Japan

[4] Toyama Prefectural Univ, Liberal Arts & Sci, Imizu, Toyama, Japan

[5] Toyama Coll Welf Sci, Dept Social Welf, Imizu, Toyama, Japan

来源：

2018 JOINT 10TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 19TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS) | 2018年

关键词：

radar remote sensing; micro-Doppler classification; gait recognition; balance ability; ACCURATE; WALKING;

D O I：

10.1109/SCIS-ISIS.2018.00193

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a radar-based technique for the gait classification of healthy young and elderly adults based on the difference in their balance ability. We propose a method for extracting the velocity parameters related to the balance ability during walking via micro-Doppler radar gait measurement. The experimental results show that significant gait differences between young and elderly adults exist in the extracted parameters. In particular, the effectiveness of the parameters related to leg motions in both stance and swing phases is verified. By using the extracted parameters, a support vector machine-based approach shows that two groups can be effectively classified.

引用

页码：1222 / 1226

页数：5

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