脑卒中患者异常步态的识别分类技术
Recognition and Classification Technology of Abnormal Gait in Stroke Patients
DOI: 10.12677/AIRR.2023.122012, PDF,   
作者: 黄灶荣*, 韦建军, 余学书, 窦亮亮：广西科技大学，机械与汽车工程学院，广西 柳州；王春宝#：广西科技大学，机械与汽车工程学院，广西 柳州；深圳大学第一附属医院，广东 深圳；深圳市第二人民医院，广东 深圳；广东铭凯医疗机器人有限公司，广东 珠海；刘铨权, 段丽红, 刘 琦：深圳大学第一附属医院，神经内科，广东 深圳；深圳市第二人民医院，神经内科，广东 深圳；张 鑫：深圳大学第一附属医院，神经内科，广东 深圳；深圳市大鹏新区南澳人民医院，康复医学科，广东 深圳
关键词: 脑卒中；异常步态；识别分类；传感器；摄像头；机器学习Stroke； Abnormal Gait； Recognition and Classification； Sensors； Cameras； Machine Learning
摘要: 本文主要介绍了脑卒中患者异常步态的识别分类技术。其中详细介绍了基于可穿戴传感器和基于摄像头的步态识别技术，包括加速度计、陀螺仪、压力传感器和摄像头等相关技术。同时，介绍了基于机器学习的步态识别技术，包括特征提取和分类算法方面。最后讨论了步态识别技术的局限性和未来发展方向，包括技术局限性、研究挑战和未来发展方向等方面。本文旨在为脑卒中康复领域的研究者提供技术支持和发展方向的参考。
Abstract: This paper mainly introduces the recognition and classification techniques for abnormal gait of stroke patients. It details wearable sensor-based and camera-based gait recognition techniques, including technologies such as accelerometers, gyroscopes, pressure sensors, and cameras. Additionally, it introduces machine learning-based gait recognition techniques, including feature extraction and classification algorithms. Finally, the limitations and future development directions of gait recognition technology are discussed, including technological limitations, research challenges, and future development directions. This paper aims to provide technical support and development directions for researchers in the field of stroke rehabilitation.
文章引用：黄灶荣, 王春宝, 韦建军, 余学书, 窦亮亮, 刘铨权, 段丽红, 张鑫, 刘琦. 脑卒中患者异常步态的识别分类技术[J]. 人工智能与机器人研究, 2023, 12(2): 84-96. https://doi.org/10.12677/AIRR.2023.122012

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