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.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。.
