基于可穿戴设备的跌倒检测算法综述  

Fall detection algorithms based on wearable device: a review

作　　者：忽丽莎 王素贞[1] 陈益强[2] 高晨龙 胡春雨[2] 蒋鑫龙[2] 陈振宇[3] 高兴宇 HU Li-sha;HU Li-sha;CHEN Yi-qiang;GAO Chen-long;HU Chun-yu;JIANG Xin-long;CHEN Zhen-yu;GAO Xing-yu(Institute of Information Technology,Hebei University of Economics and Business,Shijiazhuang 050061,China;Institute of Information Technology,Hebei University of Economics and Business,Shijiazhuang 050061,China;China Electric Power Research Institute,Beijing 100192,China;Institute of Microelectronics,Chinese Academy of Sciences,Beijing 100029,China)

机构地区：[1]河北经贸大学信息技术学院,石家庄050061 [2]中国科学院计算技术研究所,北京100190 [3]中国电力科学研究院,北京100192 [4]中国科学院微电子研究所,北京100029

出　　处：《浙江大学学报（工学版）》2018年第9期1717-1728,共12页Journal of Zhejiang University：Engineering Science

基　　金：国家自然科学基金资助项目(61702491);国家电网公司总部科技资助项目(5442DZ170019);河北省高等学校科学技术研究资助项目(QN2018116;QN2018105;ZD2018205);河北经贸大学校内科研基金资助项目(2016KYZ05)

摘　　要：综述2013-2018年基于穿戴式惯性传感器的跌倒检测研究工作.从跌倒的定义出发,阐述常规跌倒行为的几种状态、跌倒的分类方式及其类别.以可穿戴跌倒检测系统框架为基础,依次从数据采集、预处理、特征提取、模型构建等角度分别展开介绍当前的研究工作.归纳用于跌倒检测性能评估的一系列技术指标,展示9个跌倒检测的公开数据集,以及当前跌倒检测研究工作在这些数据集上的检测精度.旨在为后续开展可穿戴跌倒检测工作提供借鉴与参考.Fall detection methods based on wearable inertial devices were elaborated from 2013 to 2018.First of all,the definition of fall,conventional phases contained within a fall,classification and categories of falls were fully introduced.Secondly,current research works were introduced with respect to modules such as data collection,preprocessing,feature extraction and model construction of the wearable fall detection system framework.A series of widely-used technical criteria were induced for evaluating the performance of fall detection methods.At last,nine public fall detection datasets were described,as well as the predictive performance based on those datasets,which is helpful for future research in fall detection research area.

关 键 词：可穿戴设备 跌倒检测 健康监护 机器学习 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]