计算机与现代化Issue(8)：30-36,7.DOI:10.3969/j.issn.1006-2475.2024.08.006
老年人跌倒检测技术研究综述
Review of Fall Detection Technologies for Elderly
摘要
Abstract
With the rapidly growing aging population in China,the proportion of the elderly living alone has significantly in-creased,and thus the aging-population-oriented facilities have received increased attention.In a domestic environment,the el-derly are likely to fall down due to different reasons such as lack of care,aging,and sudden illness,which have become one of the main threats to their health.Therefore,monitoring,detecting and predicting fall down behavior of the elderly in real-time can ensure their safety to some extent,while further reducing the life and health risks caused by accidental falling down.Based on a comprehensive overview of the research on human fall detection,we categorize fall detection into two categories:vision-free technologies and computer vision based methods,depending on different kinds of sensors used for data acquisition.We summa-rize and introduce the system composition of different methods and explore the latest relevant research,and discuss their method characteristics and practical applications.In particular,we focus on reviewing the deep learning based schemes which have been developing rapidly in recent years,while analyzing and discussing relevant principles and research results of deep learning based schemes in details.Next,we also introduce public benchmarking datasets for human fall detection,including dataset size and storage format.Finally,we discuss the prospect for the relevant research,and come up with reasonable suggestions in different aspects.关键词
跌倒检测/计算机视觉/机器学习/深度学习Key words
fall detection/computer vision/machine learning/deep learning分类
信息技术与安全科学引用本文复制引用
王梦溪,李峻..老年人跌倒检测技术研究综述[J].计算机与现代化,2024,(8):30-36,7.基金项目
国家自然科学基金资助项目(62173186,61703096) （62173186,61703096）
