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A Linear Optimization Procedure for an EMG-driven NeuroMusculoSkeletal Model Parameters Adjusting: Validation Through a Myoelectric Exoskeleton Control

机译:肌电图驱动的神经肌肉骨骼模型参数调整的线性优化程序:通过肌电外骨骼控制的验证

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This paper presents a linear optimization procedure able to adapt a simplified EMG-driven NeuroMusculoSkeletal (NMS) model to the specific subject. The optimization procedure could be used to adjust a NMS model of a generic human articulation in order to predict the joint torque by using ElectroMyoGraphic (EMG) signals. The proposed approach was tested by modeling the human elbow joint with only two muscles. Using the cross-validation method, the adjusted elbow model has been validated in terms of both torque estimation performance and predictive ability. The experiments, conducted with healthy people, have shown both good performance and high robustness. Finally, the model was used to control directly and continuously a exoskeleton rehabilitation device through EMG signals. Data acquired during free movements prove the model ability to detect the human's intention of movement.
机译:本文提出了一种线性优化程序,能够使简化的EMG驱动的NeuroMusculoSkeletal(NMS)模型适应特定受试者。优化程序可用于调整一般人关节的NMS模型,以便通过使用ElectroMyoGraphic(EMG)信号预测关节扭矩。通过仅用两块肌肉对人体肘关节建模来测试所提出的方法。使用交叉验证方法,已在扭矩估计性能和预测能力方面验证了调整后的肘部模型。对健康人进行的实验显示了良好的性能和较高的鲁棒性。最后,该模型用于通过EMG信号直接连续地控制外骨骼康复设备。自由运动期间获取的数据证明了该模型能够检测人的运动意图。

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