Upper limb multi-joint synchronous proportional electromyography control method and system based on muscle synergy

Abstract

The invention discloses an upper limb multi-joint synchronous proportional electromyography control method and system based on muscle synergy. The method includes first collecting and preprocessing asurface electromyography signal of joint motion related muscles, providing a semi-supervised non-negative matrix factorization synergic analysis method according to a muscle synergic contraction modelto decouple the electromyography signal and effectively extract joint motion related muscle synergy elements and activation coefficient sequences; second constructing a synergic activation model of activation coefficients and joint angles through support vector regression and adopting a brainstorming algorithm to optimize model parameters to achieve synchronous estimation of multiple joint motionangle information of upper limbs; finally constructing an upper limb multi-joint synchronous proportional electromyography control system based on muscle synergy by combining the multi-degree-of-freedom parallel proportional electromyography control strategy to convert the estimated multi-joint motion angle information into multi-degree-of-freedom operation displacement of a rehabilitation aid device and provide a smooth stable motion control instruction for the rehabilitation aid device.

Description

technical field [0001] The invention belongs to the field of myoelectric signal processing and myoelectric control, and relates to a muscle synergy analysis method and a multi-joint synchronous continuous motion estimation method based on a synergistic activation model, in particular to an upper limb multi-joint synchronous proportional myoelectric control method and system based on muscle synergy. Background technique [0002] Surface Electromyography (sEMG) is widely used in the fields of rehabilitation robots, intelligent prosthetics, and human-computer interaction because of its anti-interference ability, easy acquisition, and rich motion control information. The rich information contained in the sEMG signal can reflect the movement intention and state of the limbs, and provide a variety of different modes of motion control instructions for intelligent rehabilitation auxiliary equipment. Compared with other auxiliary equipment that rely on buttons or artificial voice cont...

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Problems solved by technology

However, most of these studies are aimed at the sequential motion of single joint and single degree of freedom, while the natural motion of the human body is often a synchronous motion of multiple joints and multiple degrees of freedom.

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