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Alternative TitleExercise Training and Interactive Control with a Horizontal Exoskeleton for Lower Limb Rehabilitation
Thesis Advisor侯增广
Degree Grantor中国科学院大学
Place of Conferral中国科学院自动化研究所
Degree Discipline控制理论与控制工程
Keyword下肢康复机器人 运动训练 交互控制 生物医学信号 Lower Limb Rehabilitation Robot Exercise Training Interactive Control Biomedical Signal
Abstract由于中风和脊髓损伤的高发病率和致残率,肢体瘫痪患者的数量与日俱增。在经过诸如外科手术等急性期的临床处理后,运动康复成为针对瘫痪患者的一种主要治疗手段,它能够在一定程度上帮助患肢恢复运动功能,重新学习日常生活活动,从而尽最大可能地帮助患者回归正常生活。但是康复通常都是一个相当长期的持续过程,有时甚至可能贯穿患者一生的时间。相对于传统的理疗,使用机器人辅助康复训练能够提高效率,降低成本,减少理疗师的人员和体力消耗,因此节省了康复医疗资源,并且可以完成更加多样的主被动训练策略,从而提高了康复效果。本文介绍了一套由作者所在课题组自主研发的下肢康复机器人系统——iLeg。 本文研究工作的主要创新点如下: 1. 针对坐卧式外骨骼下肢康复机器人系统,建立了患者-机器人混合系统的动力学模型,在强约束和高度非线性的条件下,采用粒子群算法和最小二乘估计对动力学参数进行辨识,进而估计出了康复训练运动过程中下肢的肌肉收缩力矩。 2. 实现了被动训练过程中的交互控制。与现有被动训练策略的纯位置控制方法相比,该交互控制方法结合阻抗控制和运动规划,实现了被动训练过程中的主动柔顺性,避免了康复训练过程中可能出现的下肢痉挛、抖动等异常的肌肉活动造成下肢与机构之间过度对抗进而导致下肢与机器人系统的损伤,确保了康复运动训练的安全。 3. 提出了一种用于任务导向式主动训练的交互控制方法。与现有方法相比,该方法直接以主动运动意图为依据,实时调节运动阻抗,建立了一个自适应触觉反馈接口:当患者意图对抗指定的运动任务时,阻抗增大,为患者提供消极的触觉反馈;当主动运动意图与运动任务相符合时,阻抗减小,为患者提供积极的触觉反馈。因此,该方法不仅激励了患者的主动参与意识,同时能够引导患者正确地参与到运动训练任务中来。 4. 实现了基于表面肌电信号的单关节主动训练策略。相较于力矩信号,表面肌电信号随机性较大,抗干扰性弱,信噪比较低,但有着更好的灵敏性和辨识度,能反映出特定肌肉群的活动状态。本研究利用表面肌电信号提取患者的主动运动意图,设计了阻尼式和弹簧式两种单关节主动训练策略。 5. 利用脑电信号实现了肢体动作分类。对于完全脊髓损伤患者来说,肢体的运动功能基本全部丧失,无法产生主动力矩和肌电信号,但是其大脑功能是健全的,因此,本研究为完全脊髓损伤患者提供了一种潜在的主动训练策略。本研究采用了一种基于脉冲神经网络的脑电信号处理方法——NeuCube,将大脑活动进行了可视化,并且提高了分类精度。
Other AbstractThe number of paralytic sufferers is currently growing huge because of the high incidence and disability rate of stroke and spinal cord injury (SCI). Exercise rehabilitation becomes a primary therapy to the paralytic sufferers after instant treatment like surgery, an approach that helps patients return to normal life as much as possible by regaining locomotor function of affected limbs and relearning ADL. However, rehabilitation for patients with paralysis is usually a long-time process, which may continue throughout most of their entire lifetimes. Compared to traditional physiotherapy, rehabilitation with the assistance of robots can reduce the cost and time consumed, and less labor intensity is required. Moreover, training strategies are variously provided by robots, so that rehabilitation effect can be improved. This paper introduces a lower limb rehabilitation robot named iLeg which is developed at our laboratory. The main contributions of the dissertation are as follows: 1. The human-robot hybrid system is built with respect to patients and iLeg, and the dynamic equation is derived to model the hybrid system. In order to estimate the torque that is generated by lower limb muscles, particle swam optimization and least square method are used to identify the dynamic parameters, with strong constraints and high nonlinearity. 2. An interactive control is proposed and implemented during passive training with iLeg. Compared to existing methods, the proposed method achieves active compliant behavior using impedance control and motion planing, to protect the lower limb from secondary injury that may be caused by excessive contact force between mechanism and lower limb from abnormal muscle activities such as spasm and trembling. Hence, the safety is promised during the passive training. 3. An interactive control is proposed to implement the task-oriented active training with iLeg. Compared to existing methods, the proposed method adjusts motion impedance in real time directly based on the voluntary motion intention of patients, which establishes an adaptive haptic interface. Impedance increases when patients intend to resist the predefined motion task. Impedance decreases when the voluntary motion intention agrees with the motion task. Hence, the proposed method not only motivates patients' voluntary participation but also supervises patients to contributes to the training task. 4. sEMG-based single joint active training is proposed and implemented wit...
Other Identifier201118014628008
Document Type学位论文
Recommended Citation
GB/T 7714
胡进. 坐卧式外骨骼下肢康复机器人的运动训练策略和交互控制方法[D]. 中国科学院自动化研究所. 中国科学院大学,2014.
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