Blana Dimitra, Kirsch Robert F, Chadwick Edward K
Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Med Biol Eng Comput. 2009 May;47(5):533-42. doi: 10.1007/s11517-009-0479-3. Epub 2009 Apr 3.
A functional electrical stimulation controller is presented that uses a combination of feedforward and feedback for arm control in high-level injury. The feedforward controller generates the muscle activations nominally required for desired movements, and the feedback controller corrects for errors caused by muscle fatigue and external disturbances. The feedforward controller is an artificial neural network (ANN) which approximates the inverse dynamics of the arm. The feedback loop includes a PID controller in series with a second ANN representing the nonlinear properties and biomechanical interactions of muscles and joints. The controller was designed and tested using a two-joint musculoskeletal model of the arm that includes four mono-articular and two bi-articular muscles. Its performance during goal-oriented movements of varying amplitudes and durations showed a tracking error of less than 4 degrees in ideal conditions, and less than 10 degrees even in the case of considerable fatigue and external disturbances.
提出了一种功能性电刺激控制器,该控制器在高位损伤的手臂控制中采用前馈和反馈相结合的方式。前馈控制器生成期望运动名义上所需的肌肉激活,反馈控制器校正由肌肉疲劳和外部干扰引起的误差。前馈控制器是一个人工神经网络(ANN),它近似于手臂的逆动力学。反馈回路包括一个与第二个ANN串联的PID控制器,第二个ANN表示肌肉和关节的非线性特性以及生物力学相互作用。该控制器是使用手臂的双关节肌肉骨骼模型设计和测试的,该模型包括四块单关节肌肉和两块双关节肌肉。在不同幅度和持续时间的目标导向运动中,其性能在理想条件下显示跟踪误差小于4度,即使在相当疲劳和存在外部干扰的情况下,跟踪误差也小于10度。