Nunes Polyana F, Ostan Icaro, Siqueira Adriano A G
Rehabilitation Robotics Laboratory, Department of Mechanical Engineering, São Carlos School of Engineering, University of São Paulo, São Carlos, Brazil.
Front Robot AI. 2020 Dec 16;7:575217. doi: 10.3389/frobt.2020.575217. eCollection 2020.
In order to assist after-stroke individuals to rehabilitate their movements, research centers have developed lower limbs exoskeletons and control strategies for them. Robot-assisted therapy can help not only by providing support, accuracy, and precision while performing exercises, but also by being able to adapt to different patient needs, according to their impairments. As a consequence, different control strategies have been employed and evaluated, although with limited effectiveness. This work presents a bio-inspired controller, based on the concept of motor primitives. The proposed approach was evaluated on a lower limbs exoskeleton, in which the knee joint was driven by a series elastic actuator. First, to extract the motor primitives, the user torques were estimated by means of a generalized momentum-based disturbance observer combined with an extended Kalman filter. These data were provided to the control algorithm, which, at every swing phase, assisted the subject to perform the desired movement, based on the analysis of his previous step. Tests are performed in order to evaluate the controller performance for a subject walking actively, passively, and at a combination of these two conditions. Results suggest that the robot assistance is capable of compensating the motor primitive weight deficiency when the subject exerts less torque than expected. Furthermore, though only the knee joint was actuated, the motor primitive weights with respect to the hip joint were influenced by the robot torque applied at the knee. The robot also generated torque to compensate for eventual asynchronous movements of the subject, and adapted to a change in the gait characteristics within three to four steps.
为了帮助中风后个体恢复运动能力，研究中心已开发出下肢外骨骼及其控制策略。机器人辅助治疗不仅可以在进行锻炼时提供支撑、准确性和精确性，还能够根据患者的损伤情况适应不同的患者需求。因此，尽管效果有限，但已采用并评估了不同的控制策略。这项工作提出了一种基于运动原语概念的仿生控制器。所提出的方法在一种下肢外骨骼上进行了评估，其中膝关节由串联弹性驱动器驱动。首先，为了提取运动原语，通过基于广义动量的干扰观测器结合扩展卡尔曼滤波器来估计用户扭矩。这些数据被提供给控制算法，该算法在每个摆动阶段，根据对受试者上一步的分析，协助其执行期望的运动。进行测试以评估控制器在受试者主动行走、被动行走以及这两种情况相结合时的性能。结果表明，当受试者施加的扭矩小于预期时，机器人辅助能够补偿运动原语的重量不足。此外，尽管仅对膝关节进行驱动，但相对于髋关节的运动原语权重受到在膝关节处施加的机器人扭矩的影响。机器人还产生扭矩以补偿受试者最终的异步运动，并在三到四步内适应步态特征的变化。
