基于姿态融合的实时跌倒检测系统研究  

Research on Real Time Fall Detection System Based on Attitude Fusion

作　　者：徐甲栋 陈强[1] 王洪杰 XU Jia-dong;CHEN Qiang;WANG Hong-jie(School of Electric and Electronic Engineering,Shanghai University of Engineering Science,Shanghai 201620,China;State Grid Linyi Power Supply Company,Linyi 276000,China)

机构地区：[1]上海工程技术大学电子电气工程学院,上海201620 [2]国网临沂供电公司,山东临沂276000

出　　处：《软件导刊》2022年第4期144-150,共7页Software Guide

基　　金：国家自然科学基金项目(61705127);上海市科技委员会重点项目(18511101600)。

摘　　要：为降低老人跌倒的伤残率和死亡率,通过可穿戴式装置采集运动数据,结合阈值法与模式识别算法的优点提出一种基于姿态融合的联立判别跌倒检测算法,并引入云技术与微信小程序设计一种便捷可行的跌倒检测系统。该系统首先通过互补滤波对原始数据进行预处理,解决因陀螺仪低频特性差和加速度计高频特性差导致解算姿态不准确的问题,然后通过阈值法对可疑跌倒行为进行判断,过滤掉大部分日常活动,当检测到可疑行为时,再启动SVM算法进行跌倒识别。实验结果表明,采用该系统进行跌倒检测识别的正确率达到90.1%,灵敏度达到91.2%,特异度达到89.4%,且漏报率与误报率较低,分别只有8.8%和10.6%。In order to reduce the disability rate and mortality rate of the elderly caused by falls,collect motion data through wearable devices,combine the advantages of threshold method and pattern recognition algorithm,propose a simultaneous discriminant fall detection algorithm based on posture fusion,and introduce cloud technology and WeChat small program to design a convenient and feasible fall detection system.Firstly,the original data is preprocessed by complementary filtering to solve the problem of inaccurate attitude calculation caused by poor lowfrequency characteristics of gyroscope and poor high-frequency characteristics of accelerometer.Then,the suspicious fall behavior is judged by threshold method to filter out most of daily activities.When suspicious behavior is detected,SVM algorithm is started for fall recognition.The experimental results show that the accuracy,sensitivity and specificity of the algorithm are 90.1%,91.2%and 89.4%respectively,and the missing and false alarm rates are only 8.8%and 10.6%respectively.

关 键 词：跌倒检测 姿态融合 互补滤波 陀螺仪 加速度计 SVM 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]