Simultaneous and Continuous Estimation of Shoulder and Elbow Kinematics from Surface EMG Signals - Zhang, Qin; Liu, Runfeng; Chen, Wenbin; Xiong, Caihua (Frontiers in Neuroscience, 2017)
In this paper, we present a simultaneous and continuous kinematics estimation method for multiple DoFs across shoulder and elbow joint. Although simultaneous and continuous kinematics estimation from surface electromyography (EMG) is a feasible way to achieve natural and intuitive human-machine interaction, few works investigated multi-DoF estimation across the significant joints of upper limb, shoulder and elbow joints. This paper evaluates the feasibility to estimate 4-DoF kinematics at shoulder and elbow during coordinated arm movements. Considering the potential application of this method in exoskeleton, prosthetics and other upper limb rehabilitation techniques, the estimation performance is presented with different muscle activity decomposition and learning strategies. Principle component analysis (PCA) and independent component analysis (ICA) are respectively employed for EMG mode decomposition with artificial neural network (ANN) for electromechanical association learning. Four joint angles across shoulder and elbow are estimated from EMG simultaneously and continuously. With 70-s inter-cross validation and 2-min intra-cross validation, the feasibility, effectiveness and robustness of the proposed myoelectric decoding are presented.