基于三轴加速度传感器人体姿态识别的特征选择

doi:10.3969/j.issn.0255-8297.2019.03.013

应用科学学报 ›› 2019, Vol. 37 ›› Issue (3): 427-436.doi: 10.3969/j.issn.0255-8297.2019.03.013

• 信号与信息处理 • 上一篇

基于三轴加速度传感器人体姿态识别的特征选择

范书瑞¹, 贾雅亭¹, 刘晶花^1,2

1. 河北工业大学电子信息工程学院, 天津 300401;
2. 中国科学院大学电子学研究所, 北京 100190

收稿日期:2018-09-14 修回日期:2018-10-24 出版日期:2019-05-31 发布日期:2019-05-31
作者简介:范书瑞,副教授,研究方向:边缘计算和人工智能,E-mail:fansr@hebut.edu.cn
基金资助:
教育部春晖计划合作课题基金（No.Z2017016）；教育部产学合作协同育人项目基金（No.201801335014）资助

Feature Selection of Human Activity Recognition Based on Tri-axial Accelerometer

FAN Shurui¹, JIA Yating¹, LIU Jinghua^1,2

1. College of Electronic Information Engineering, Hebei University of Technology, Tianjin 300401, China;
2. Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China

Received:2018-09-14 Revised:2018-10-24 Online:2019-05-31 Published:2019-05-31

摘要/Abstract

摘要： 为解决人体运动模式识别中姿态分类问题，详细研究了人体姿态识别的特征选择.通过统计三轴加速度传感器的x轴、y轴、z轴等信号，获得标准差、偏度和峰度等117种特征.将Fisher score、relief-F和Chi square 3种算法与层次分类方法相结合选择出特征子集，采用支持向量机对动作进行分类.实验表明，利用3种特征选择算法所选择出的特征集有助于较高精度地识别站立、坐和躺3种静态动作以及走、上楼、下楼3种动态动作，且有利于后续进行低复杂度在线识别方法研究.

关键词: 特征选择, 人体姿态识别, 支持向量机, 三轴加速度传感器

Abstract: In order to solve the problem of activity classification in human motion pattern recognition, the feature selection of human activity recognition is studied in detail. By taking signal statistics on the x-axis, y-axis and z-axis, 117 features such as standard deviation, skewness and kurtosis are obtained. The three algorithms of Fisher score, Relief-F and Chi square are combined with the hierarchical classification method to select the feature subset, and the action classification is conducted by using the support vector machine (SVM). Experiments showed that the feature set selected by the three feature selection algorithms helps to identify three static movements of standing, sitting and lying and three dynamic movements of walking, going upstairs and downstairs with high precision, which is conducive to the subsequent research on low complexity online identification method.

Key words: human activity recognition, tri-axial accelerometer, feature selection, support vector machine (SVM)

中图分类号:

TP391

范书瑞, 贾雅亭, 刘晶花. 基于三轴加速度传感器人体姿态识别的特征选择[J]. 应用科学学报, 2019, 37(3): 427-436.

FAN Shurui, JIA Yating, LIU Jinghua. Feature Selection of Human Activity Recognition Based on Tri-axial Accelerometer[J]. Journal of Applied Sciences, 2019, 37(3): 427-436.

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基于三轴加速度传感器人体姿态识别的特征选择

Feature Selection of Human Activity Recognition Based on Tri-axial Accelerometer

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