基于贝叶斯优化的机器人辅助踝关节康复的用户自适应变阻抗控制

IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL
Gautham Manoharan;Hyunglae Lee
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引用次数: 0

摘要

本文提出了一种用于机器人辅助康复的用户自适应可变阻抗控制方法,首先关注脚踝康复应用。控制器根据用户的运动意图动态调整阻抗参数,从而在运动任务中提供个性化的帮助。贝叶斯优化是用来提高速度和准确性,在电机任务中,通过最小化目标函数制定的用户的运动学数据。优化过程采用高斯过程作为替代模型来解决人类行为固有的不确定性。此外,将基于Student-t过程的离群值拒绝方法与贝叶斯优化相结合,增强了贝叶斯优化的鲁棒性。为了评估所提出的控制方法的有效性,使用可穿戴式踝关节机器人对15名健康参与者进行了一项目标导向的目标达到研究。使用速度、精度、任务完成时间和用户努力的性能指标来比较优化的可变阻抗控制器与未优化的对应物。结果表明,与未优化控制器相比,优化后的控制器平均速度提高了9.9%,与目标轨迹的偏差降低了7.6%。此外,优化后的控制器将任务完成时间缩短了6.6%,同时保持了类似的用户工作量。值得注意的是,每个个体的最优参数变化显著,突出了用户自适应方法的重要性。总体而言,本研究证明了所提出的最优可变阻抗控制方法在机器人辅助康复应用中的有效性和可行性,特别是在踝关节康复的背景下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
User-Adaptive Variable Impedance Control Using Bayesian Optimization for Robot-Aided Ankle Rehabilitation
This paper presents a user-adaptive variable impedance control approach for robot-aided rehabilitation, initially focusing on an ankle rehabilitation application. The controller dynamically adjusts the impedance parameters based on the user’s motion intent, thereby providing personalized assistance during motor tasks. Bayesian optimization is employed to enhance speed and accuracy during the motor tasks by minimizing an objective function formulated from the user’s kinematic data. The optimization process incorporates a Gaussian process as a surrogate model to address uncertainties inherent in human behaviors. Furthermore, an outlier rejection method based on the Student-t process is integrated into Bayesian optimization to enhance its robustness. To evaluate the effectiveness of the proposed control approach, a goal-directed target-reaching study was conducted with 15 healthy participants using a wearable ankle robot. The performance metrics of speed, accuracy, task completion time, and user effort were used to compare the optimized variable impedance controller against an unoptimized counterpart. Results showed that the optimized controller achieved an average speed improvement of 9.9% and a 7.6% decrease in deviation from the target trajectory compared to the unoptimized controller. Additionally, the optimized controller reduced task completion time by 6.6% while maintaining a similar level of user effort. Notably, the optimal parameters for each individual varied significantly, highlighting the significance of the user-adaptive approach. Overall, this study demonstrates the effectiveness and feasibility of the proposed optimal variable impedance control approach for robot-aided rehabilitation applications, particularly in the context of ankle rehabilitation.
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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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