Five-degree-of-freedom upper arm artificial limb control system based on FSM

Abstract

The invention provides a five-degree-of-freedom upper arm artificial limb control system based on an FSM. The system is based on an upper arm artificial limb with five degrees of freedom, employs multi-channel surface electromyographic signals, and can accurately recognize the intention of a user. A BP neural network is used as a classifier to classify the processed electromyographic signals, an encoding module based on a finite state machine is used for conducting secondary classification on the electromyographic signals, motion state codes are generated according to the electromyographic signals obtained after further classification, and the motion of the artificial limb is planned and executed through a motion control module. A series of problems that a traditional artificial limb control system is inconvenient to operate, the training process is long, the control freedom degree is small, and the intention recognition deviation rate is high, and the like are well solved.

Description

technical field [0001] The invention relates to the field of myoelectric prosthesis control, in particular to an FSM-based five-degree-of-freedom upper arm prosthesis control system. Background technique [0002] Myoelectric prosthesis is a rehabilitation device that uses the electromyographic signal (EMG) of the residual limb of the human body as a control signal to control the movement of the prosthetic hand to achieve functions similar to human hands such as grasping, tapping, and rotation. The myoelectric prosthesis recognizes the patient's movement intention by collecting the patient's myoelectric signal, and then controls the movement of the prosthesis. popular research directions. [0003] However, the traditional state-transition-based prosthetic control method usually requires state switching through signal types and durations, which is inconvenient to operate, and in actual use, there are cumbersome and lengthy training processes, less degrees of freedom, insuffic...

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Problems solved by technology

[0003] However, the traditional state-transition-based prosthetic control method usually requires state switching through signal types and durations, which is inconvenient to operate, and in actual use, there are cumbersome and lengthy training processes, less degrees of freedom, insufficient dexterity, and intentional A series of problems such as high recognition deviation rate make users feel bad and have high mental stress, which leads to high abandonment rate of prosthetics

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