计算机应用与软件2017，Vol.34Issue(7)：182-187,276,7.DOI:10.3969/j.issn.1000-386x.2017.07.034
基于SVM和阈值分析法的摔倒检测系统
FALL DETECTION SYSTEM BASED ON SVM AND THRESHOLD ANALYSIS
摘要
Abstract
With the rapid development of aging population, China's population gradually shows the trend of aging and empty nest phenomenon.Once if the aged fall to the ground, they haven't been discovered soon enough and take reasonable measures immediately;it would bring serious physical and psychological harm to them.In order to solve this problem, we design and implement the fall detection system for the elderly.The system uses the embedded microprocessor K60 core development board as the processing core, the accelerometer MMA7660FC collects the three-axis acceleration information of human body, and the ENC-03 gyroscope gathers the angular velocity information of the two axes.A fall detection algorithm based on SVM and threshold analysis is used to judge whether the old man falls down or not, and it can automatically send the falling alarm information when falling.Experimental results show that the system can effectively distinguish between falls and other daily life behaviour.The algorithm has high accuracy and high real-time performance.关键词
加速度传感器/陀螺仪/支持向量机/阈值分析法/摔倒检测Key words
Accelerometer/ Gyroscope/ Support vector machine/ Threshold analysis/ Fall detection分类
信息技术与安全科学引用本文复制引用
陈玮,周晴,曹桂涛..基于SVM和阈值分析法的摔倒检测系统[J].计算机应用与软件,2017,34(7):182-187,276,7.基金项目
国家重点基础研究发展计划项目(2011CB707104). （2011CB707104）
