脑卒中患者上肢功能智能评估系统研究进展  

Research progress on intelligent assessment system for upper limb function of stroke patients

作　　者：李素姣[1,2,3] 吴坤 孟巧玲(综述)[1,2,3] 喻洪流(审校) LI Sujiao;WU Kun;MENG Qiaoling;YU Hongliu(Institute of Rehabilitation Engineering and Technology,University of Shanghai for Science and Technology,Shanghai 200093,P.R.China;Shanghai Engineering Research Center of Assistive Devices,Shanghai 200093,P.R.China;Key Laboratory of Neural-functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs,Shanghai 200093,P.R.China)

机构地区：[1]上海理工大学康复工程与技术研究所,上海200093 [2]上海康复器械工程技术研究中心,上海200093 [3]民政部神经功能信息与康复工程重点实验室,上海200093

出　　处：《生物医学工程学杂志》2022年第3期620-626,632,共8页Journal of Biomedical Engineering

基　　金：国家自然科学基金资助项目(61903255);国家重点研发计划资助项目(2020YFC2007902)。

摘　　要：目前临床上常采用量表方法评估脑卒中患者的上肢功能,但这种方法存在耗时长、评估结果一致性差、需康复医师参与度高等问题。为克服量表方法的短板,结合传感器和机器学习算法的上肢功能智能评估系统成为了近年来的研究热点之一。本文首先对常用的临床上肢功能评估方法做了分析总结,随后对近年来智能评估系统的研究进行了综述,重点对智能评估系统中数据采集和数据处理部分使用的技术及其优缺点进行了分析总结,最后对目前智能评估系统面临的挑战和未来的发展方向展开讨论,以期为相关领域的研究学者提供有价值的参考信息。At present, the upper limb function of stroke patients is often assessed clinically using a scale method,but this method has problems such as time-consuming, poor consistency of assessment results, and high participation of rehabilitation physicians. To overcome the shortcomings of the scale method, intelligent upper limb function assessment systems combining sensors and machine learning algorithms have become one of the hot research topics in recent years.Firstly, the commonly used clinical upper limb functional assessment methods are analyzed and summarized. Then the researches on intelligent assessment systems in recent years are reviewed, focusing on the technologies used in the data acquisition and data processing parts of intelligent assessment systems and their advantages and disadvantages. Lastly, the current challenges and future development directions of intelligent assessment systems are discussed. This review is hoped to provide valuable reference information for researchers in related fields.

关 键 词：脑卒中 上肢 功能评估 智能评估 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] R743.3[自动化与计算机技术—控制科学与工程]