IEEE Trans Neural Syst Rehabil Eng. 2023;31:3384-3396. doi: 10.1109/TNSRE.2023.3306201. Epub 2023 Aug 25.
Soft rehabilitation exoskeletons have gained much attention in recent years, striving to assist the paralyzed individuals restore motor functions. However, it is a challenge to promote human-robot interaction property and satisfy personalized training requirements. This article proposes a soft elbow rehabilitation exoskeleton for the multi-mode training of disabled patients. An adaptive cooperative admittance backstepping control strategy combined with surface electromyography (sEMG)-based joint torque estimation and neural network compensation is developed, which can induce the active participation of patients and guarantee the accomplishment and safety of training. The proposed control scheme can be transformed into four rehabilitation training modes to optimize the cooperative training performance. Experimental studies involving four healthy subjects and four paralyzed subjects are carried out. The average root mean square error and peak error in trajectory tracking test are 3.18° and 5.68°. The active cooperation level can be adjusted via admittance model, ranging from 4.51 °/Nm to 10.99 °/Nm. In cooperative training test, the average training mode value and effort score of healthy subjects (i.e., 1.58 and 1.50) are lower than those of paralyzed subjects (i.e., 2.42 and 3.38), while the average smoothness score and stability score of healthy subjects (i.e., 3.25 and 3.42) are higher than those of paralyzed subjects (i.e., 1.67 and 1.71). The experimental results verify the superiority of proposed control strategy in improving position control performance and satisfying the training requirements of the patients with different hemiplegia degrees and training objectives.
近年来，软体康复外骨骼受到了广泛关注，致力于帮助瘫痪患者恢复运动功能。然而，促进人机交互性能并满足个性化训练需求仍然是一个挑战。本文提出了一种用于残疾患者多模式训练的软肘康复外骨骼。开发了一种自适应协同导纳反步控制策略，结合基于表面肌电（sEMG）的关节转矩估计和神经网络补偿，可诱导患者积极参与，并保证训练的完成和安全性。所提出的控制方案可以转换为四种康复训练模式，以优化协同训练性能。进行了涉及四名健康受试者和四名瘫痪受试者的实验研究。在轨迹跟踪测试中，平均均方根误差和峰值误差分别为 3.18°和 5.68°。通过导纳模型可以调整主动协作水平，范围从 4.51°/Nm 到 10.99°/Nm。在协同训练测试中，健康受试者的平均训练模式值和努力评分（即 1.58 和 1.50）低于瘫痪受试者（即 2.42 和 3.38），而健康受试者的平均平滑度评分和稳定性评分（即 3.25 和 3.42）高于瘫痪受试者（即 1.67 和 1.71）。实验结果验证了所提出的控制策略在提高位置控制性能和满足不同偏瘫程度和训练目标患者的训练需求方面的优越性。
