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多模态人体动作表示识别及其正骨康复训练应用综述 被引量:3

A review on multi-modal human motion representation recognition and its application in orthopedic rehabilitation training
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摘要 人体动作识别(HAR)是智慧医疗、体育训练、视频监控等众多领域的技术基础,受到社会各界的广泛关注。本文概述了HAR的研究进展及意义,将其归纳为动作捕捉和基于深度学习的动作分类两个过程。首先,详细介绍了基于视频、基于深度相机以及基于惯性传感器的三种主流动作捕捉方式,列举了常用的动作数据集。其次,从特征自动提取及多模态特征融合两方面来描述基于深度学习的HAR,并介绍了正骨康复训练中如何通过HAR实现监督锻炼和模拟训练。最后,讨论了HAR的精准动作捕捉、多模态特征融合方法,以及在正骨康复训练应用中的重点和难点。本文通过总结以上内容旨在快速地引导研究人员了解HAR的研究现状及其在正骨康复训练中的应用。 Human motion recognition(HAR)is the technological base of intelligent medical treatment,sports training,video monitoring and many other fields,and it has been widely concerned by all walks of life.This paper summarized the progress and significance of HAR research,which includes two processes:action capture and action classification based on deep learning.Firstly,the paper introduced in detail three mainstream methods of action capture:video-based,depth camera-based and inertial sensor-based.The commonly used action data sets were also listed.Secondly,the realization of HAR based on deep learning was described in two aspects,including automatic feature extraction and multi-modal feature fusion.The realization of training monitoring and simulative training with HAR in orthopedic rehabilitation training was also introduced.Finally,it discussed precise motion capture and multi-modal feature fusion of HAR,as well as the key points and difficulties of HAR application in orthopedic rehabilitation training.This article summarized the above contents to quickly guide researchers to understand the current status of HAR research and its application in orthopedic rehabilitation training.
作者 邢蒙蒙 魏国辉 刘静 张俊忠 杨锋 曹慧 XING Mengmeng;WEI Guohui;LIU Jing;ZHANG Junzhong;YANG Feng;CAO Hui(School of Science and technology,Shandong University of Traditional Chinese Medicine,Jinan 250355,P.R.China)
出处 《生物医学工程学杂志》 EI CAS CSCD 北大核心 2020年第1期174-178,184,共6页 Journal of Biomedical Engineering
基金 国家自然科学基金资助项目(81473708,81973981) 山东省研究生导师指导能力提升项目(SDYY17119) 山东省研究生教育优质课程建设项目(SDYKC17065) 山东省重点研发计划项目(2018GSF118105) 山东省中医药科技发展计划项目(2017-016)
关键词 动作捕捉 动作特征提取 深度学习 动作识别 正骨康复训练 action capture action feature extraction deep learning action recognition orthopedic rehabilitation training
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