Abstract This study presents an event driven automatic controller to regulate the movement of a mobile lower limb active orthosis (LLAO) triggered with the information obtained from electromyographic (EMG) signals, which are captured from the user’s triceps and biceps muscles. The proposed controller has an output feedback realization including a velocity estimator algorithm based on a high order sliding mode observer. The output feedback controller implements a class of decentralized super-twisting algorithm. The controller must enforce the movement of the orthosis articulations following some defined reference trajectories. This strategy realizes a time-window dependent event driven controller for the active orthosis. The controller selects among four different routines to be executed by a patient. A differential neural network classifies the different patterns of muscle movements. This classifier succeeds in defining the correct EMG class in a 95% of the tested signals. This work senses the EMG signals from the biceps and triceps, considering a possible injury in the patient to be obtained from the quadriceps. Therefore, four upper limb routines are established to generate the corresponding classes and the four different main therapies for the LLAO. A fully instrumented and self-designed orthosis is constructed to evaluate the proposed controller including three rotational joints per leg and a mobile robot to execute translation movements.

中文翻译：

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基于连续神经网络肌电信号分类器的下肢外骨骼事件驱动滑模控制

摘要 本研究提出了一种事件驱动的自动控制器，用于通过从用户的肱三头肌和肱二头肌捕获的肌电图 (EMG) 信号中获得的信息触发来调节移动下肢主动矫形器 (LLAO) 的运动。所提出的控制器具有输出反馈实现，包括基于高阶滑模观测器的速度估计器算法。输出反馈控制器实现了一类分散超扭算法。控制器必须按照一些定义的参考轨迹强制矫形器关节的运动。该策略实现了主动矫形器的时间窗口相关事件驱动控制器。控制器在四个不同的程序中进行选择，由患者执行。差分神经网络对肌肉运动的不同模式进行分类。该分类器成功地在 95% 的测试信号中定义了正确的 EMG 类别。考虑到从股四头肌获得的患者可能的损伤，这项工作检测来自二头肌和三头肌的 EMG 信号。因此，建立了四个上肢例程来为 LLAO 生成相应的类和四种不同的主要疗法。构建了一个完全仪器化和自行设计的矫形器来评估所提出的控制器，包括每条腿的三个旋转关节和一个执行平移运动的移动机器人。考虑到从股四头肌获得的患者可能受伤。因此，建立了四个上肢例程来为 LLAO 生成相应的类和四种不同的主要疗法。构建了一个完全仪器化和自行设计的矫形器来评估所提出的控制器，包括每条腿的三个旋转关节和一个执行平移运动的移动机器人。考虑到从股四头肌获得的患者可能受伤。因此，建立了四个上肢例程来为 LLAO 生成相应的类和四种不同的主要疗法。构建了一个完全仪器化和自行设计的矫形器来评估所提出的控制器，包括每条腿的三个旋转关节和一个执行平移运动的移动机器人。