据统计80%的脑卒中运动功能障碍患者患有上肢功能障碍,由于上肢承担了许多精细活动,故其功能恢复难度大。上肢康复训练周期长,很大程度上依赖于治疗师自身的主观经验,而现有用于训练的康复机器人普遍智能性不足,导致其临床效果欠佳。为了减轻治疗师和患者的负担,实现上肢康复训练智能化,智能决策系统成为了康复领域的研究热点之一。该文对近年来上肢康复训练智能决策系统的研究进行了综述,重点对系统知识库构建、特征处理、决策模型搭建方法的优缺点和应用场景进行了分析总结,最后对当前智能决策系统存在的问题和未来发展的趋势展开讨论,以期为相关领域学者提供一定的参考。
According to statistics, 80% of stroke patients with motor dysfunction suffer from upper limb dysfunction. Because the upper limb undertakes many fine activities, it is difficult to recover its function. The period of upper limb rehabilitation training is long, which largely depends on the subjective experience of therapists. However, the existing rehabilitation robots used for training is generally lack of intelligence, which leads to poor clinical effect. In order to reduce the burden on therapists and patients and realize the intelligence of upper limb rehabilitation training, an intelligent decision-making support system has become one of the research hotspots in medical rehabilitation. In this paper, research on intelligent decision-making support system for upper limb rehabilitation training in recent years is reviewed, focusing on the advantages, disadvantages and application range of methods used in knowledge base building, feature processing and model building. Finally, current challenges and future development trends are discussed. It is expected that this paper can provide a reference for researchers in related fields.
康复机器人,运动功能障碍,决策支持系统,智能处方,专家系统, Rehabilitation Robot Motor Dysfunction Decision-Making Support System Intelligent
Prescription Expert System摘要
According to statistics, 80% of stroke patients with motor dysfunction suffer from upper limb dysfunction. Because the upper limb undertakes many fine activities, it is difficult to recover its function. The period of upper limb rehabilitation training is long, which largely depends on the subjective experience of therapists. However, the existing rehabilitation robots used for training is generally lack of intelligence, which leads to poor clinical effect. In order to reduce the burden on therapists and patients and realize the intelligence of upper limb rehabilitation training, an intelligent decision-making support system has become one of the research hotspots in medical rehabilitation. In this paper, research on intelligent decision-making support system for upper limb rehabilitation training in recent years is reviewed, focusing on the advantages, disadvantages and application range of methods used in knowledge base building, feature processing and model building. Finally, current challenges and future development trends are discussed. It is expected that this paper can provide a reference for researchers in related fields.
Keywords:Rehabilitation Robot, Motor Dysfunction, Decision-Making Support System, Intelligent Prescription, Expert System
基于规则的知识库在临床决策支持中较为常见,其概念来源于基于规则的推理(Rule Based Reasoning, RBR),是一种把某种领域的专家经验用规则的形式表现出来,囊括了问题与问题的解决方案的知识库 [25]。在上肢康复医学领域的研究中,一般会对康复医学知识和临床经验进行整理和总结,并以逻辑的形式表达知识从而构建规则库。在早期的上肢康复训练智能决策系统研究中常用规则库作为主要的知识库构建方法,例如Douglas D. Dankel II [12] 开发了卒中后康复专家系统REPS,构建CVA状态量表和MMAS量表评估的规则库,根据评估结果用RBR制定训练方案。基于规则的知识库易于理解、搭建方便,但当知识过于复杂时,需要大量的规则条目去支撑,知识库结果会变得冗杂,且程序设计者可能会对知识理解有偏差导致知识表达错误 [26]。因此,基于规则的方法适用于对内容较为简单、易于拆分成条目的医学知识进行知识库搭建。
马琪琪,郑金钰,贺婉莹,李素姣,倪 伟,喻洪流. 上肢康复训练智能决策支持系统研究进展Research Progress on Intelligent Decision-Making Support System for Upper Limb Rehabilitation Training[J]. 软件工程与应用, 2022, 11(06): 1357-1367. https://doi.org/10.12677/SEA.2022.116139
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