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Abstract. Myoelectric prosthetic hands aim to serve upper limb amputees. The myoelectric control of the hand grasp action is a kind of real-time or online method. Thus it is of great necessity to carry on a study of online prosthetic hand electrical control. In this paper, the strategy of simultaneous EMG decoding of grasping patterns and grasping force was realized by controlling a virtual multi-degree-freedom prosthetic hand and a real one-degree-freedom prosthetic hand simultaneously. The former realized the grasping patterns from the recognition of the sEMG pattern. The other implemented the grasping force from sEMG force decoding. The results show that the control method is effective and feasible.

Abstract.A prosthetic hand with a self-regulated grip force could achieve different operation modes, which can help the upper limb amputees to fetch objects of different shapes. To get the appropriate grasping force with smaller samples and shorter training time, the method of threshold value judgment in this paper is effective on achieving the estimate of the discrete force basing on the mean absolute value (MAV) of EMG's level. The 10 subjects can be divided into 8 grasping patterns determined through three levels: the small, medium and great of grasping forces in experiments. Experimental results conditioned on small training samples and short training time show that the accuracy of force estimation is 72.91±9.58% and thereby convincing the effectiveness and reality of the proposed method.

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