基于hill型肌肉模型的功能电刺激指尖预测力控制。

IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL
Junyun Fu;Chengyu Lin;Jinxin Sun;Kong Hoi Cheng;Yuquan Leng;Chenglong Fu
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引用次数: 0

摘要

功能性电刺激(FES)是恢复或增强神经损伤患者手部运动功能的一种有效技术,例如中风或脊髓损伤恢复期。虽然许多研究使用现象学模型来研究FES的控制,但很少有研究同时使用这两种方法来研究手指输出力。本研究旨在利用Hill模型和多关节手指模型准确预测不同当前条件下手指输出力。Hill模型描述了肌肉的力学特性,建立了肌肉激活和关节运动之间的关系。在本研究中,为每个参与者定制个性化的Hill模型,并通过比较预期力和实际力输出来验证模型的准确性。实验结果表明,在最优条件下,测量力与目标力之间的归一化均方根误差可降至最大目标力的5.1%。此外,该方法实现了多个手指的协调控制,便于各种抓取任务。该方法为改善FES在手部康复和辅助机器人中的应用提供了巨大的潜力,为瘫痪患者康复中的精确力控制提供了一种有前途的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive Force Control of Fingertip Induced by Functional Electrical Stimulation Based on a Hill-Type Muscle Model
Functional electrical stimulation (FES) is an effective technique for restoring or enhancing hand motor function in patients with neurological impairments, such as those recovering from stroke or spinal cord injuries. Although many studies have used phenomenological models to investigate the control of FES, few studies have simultaneously employed both methods to study finger output force. This study aims to accurately predict finger output force using the Hill model and a multi-joint finger model under different current conditions. The Hill model describes the mechanical properties of muscles and establishes the relationship between muscle activation and joint motion. In this study, personalized Hill models were customized for each participant, and the accuracy of the models was validated by comparing expected forces with actual force outputs. The experimental results show that under optimal conditions the normalized root mean square error between the measured force and the target force can be reduced to 5.1% of the maximum target force. Furthermore, this method enabled coordinated control of multiple fingers, facilitating a variety of grasping tasks. The proposed method offers significant potential for improving FES applications in hand rehabilitation and assistive robotics, providing a promising approach for precise force control in the rehabilitation of paralyzed patients.
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来源期刊
CiteScore
8.60
自引率
8.20%
发文量
479
审稿时长
6-12 weeks
期刊介绍: Rehabilitative and neural aspects of biomedical engineering, including functional electrical stimulation, acoustic dynamics, human performance measurement and analysis, nerve stimulation, electromyography, motor control and stimulation; and hardware and software applications for rehabilitation engineering and assistive devices.
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