Gait Classification of Young Adults, Elderly Non-Fallers, and Elderly Fallers Using Micro-Doppler Radar Signals: Simulation Study

被引：34

作者：

Saho, Kenshi ^{[1
]}

Fujimoto, Masahiro ^{[2
]}

Masugi, Masao ^{[1
]}

Chou, Li-Shan ^{[3
]}

机构：

[1] Ritsumeikan Univ, Coll Sci & Engn, Kusatsu, Shiga 5258577, Japan

[2] Ritsumeikan Univ, Coll Sport & Hlth Sci, Kusatsu, Shiga 5258577, Japan

[3] Univ Oregon, Dept Human Physiol, Eugene, OR 97403 USA

来源：

IEEE SENSORS JOURNAL | 2017年 / 17卷 / 08期

关键词：

Micro-Doppler radar; gait classification; falls; elderly; principal component analysis; WALKING; RISK;

D O I：

10.1109/JSEN.2017.2678484

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This letter presents a gait classification technique for the identification of individuals with different gait patterns using simulated micro-Doppler radar remote sensing data. Proposed feature parameters for the classification are principal components of velocities extracted via micro-Doppler radar signals generated using motion capture-based kinematic data. Distinct differences were found in the proposed parameters among three groups of subjects with different gait patterns: healthy young and elderly adults, and elderly adults with a history of falls (elderly fallers).

引用

页码：2320 / 2321

页数：2

共 6 条

[1] Radar Signal Processing for Elderly Fall Detection The future for in-home monitoring [J].