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智能控制策略在机器人辅助康复中的有效性——系统评价。

Effectiveness of Intelligent Control Strategies in Robot-Assisted Rehabilitation-A Systematic Review.

出版信息

IEEE Trans Neural Syst Rehabil Eng. 2024;32:1828-1840. doi: 10.1109/TNSRE.2024.3396065. Epub 2024 May 10.

DOI:10.1109/TNSRE.2024.3396065
PMID:38696295
Abstract

This review aims to provide a systematic analysis of the literature focused on the use of intelligent control systems in robotics for physical rehabilitation, identifying trends in recent research and comparing the effectiveness of intelligence used in control, with the aim of determining important factors in robot-assisted rehabilitation and how intelligent controller design can improve them. Seven electronic research databases were searched for articles published in the years 2015 - 2022 with articles selected based on relevance to the subject area of intelligent control systems in rehabilitation robotics. It was found that the most common use of intelligent algorithms for control is improving traditional control strategies with optimization and learning techniques. Intelligent algorithms are also commonly used in sensor output mapping, model construction, and for various data learning purposes. Experimental results show that intelligent controllers consistently outperform non-intelligent controllers in terms of transparency, tracking accuracy, and adaptability. Active participation of the patients and lowered interaction forces are consistently mentioned as important factors in improving the rehabilitation outcome as well as the patient experience. However, there are limited examples of studies presenting experimental results with impaired participants suffering limited range of motion, so the effectiveness of therapy provided by these systems is often difficult to quantify. A lack of universal evaluation criteria also makes it difficult to compare control systems outside of articles which use their own comparison criteria.

摘要

本综述旨在对专注于将智能控制系统应用于物理康复机器人的文献进行系统分析,确定近期研究趋势,并比较控制中使用的智能的有效性,以期确定机器人辅助康复中的重要因素,以及智能控制器设计如何改善这些因素。检索了 2015 年至 2022 年发表的文章,从与康复机器人智能控制系统相关的主题领域中选择文章。结果发现,智能算法最常用于控制的方法是利用优化和学习技术改进传统控制策略。智能算法还常用于传感器输出映射、模型构建以及各种数据学习目的。实验结果表明,智能控制器在透明度、跟踪精度和适应性方面始终优于非智能控制器。患者的积极参与和降低的交互力被一致认为是改善康复效果和患者体验的重要因素。然而,很少有研究呈现出实验结果,涉及运动受限的受损参与者,因此,这些系统提供的治疗效果往往难以量化。缺乏通用的评估标准也使得难以在使用自身比较标准的文章之外比较控制系统。

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引用本文的文献

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Effective unilateral/bilateral robot-assisted training for upper limb motor function rehabilitation: a cross-sectional study.有效的单侧/双侧机器人辅助上肢运动功能康复训练:一项横断面研究。
Front Hum Neurosci. 2025 Jun 18;19:1571624. doi: 10.3389/fnhum.2025.1571624. eCollection 2025.