A rehabilitation robot control method based on electromyography feedback type impedance self-adaption

Abstract

The invention provides a rehabilitation robot control method based on electromyography feedback type impedance self-adaption. The method comprises the steps of identifying the joint extension and flexion states of a training object based on electromyography signal characteristics values, plantar pressure signals and angular velocity signals, determining limb movement intention, and giving electromyography signal characteristic quantities used for describing the active level of the muscles of an affected side by using a method of affected side-mirroring-unaffected side; setting a target impedance equation, describing the function relation between extremity movement track differences and extremity stress, and establishing an impedance function capable of self-adaptive adjustment according to the active level of the muscles of the affected side and joint angles; according to initial anticipated static balance force, analyzing electromyography signals to obtain fatigue degree levels, and finely adjusting the anticipated static balance force. Self-adaptive tracking of anticipated tracks of a lower limb rehabilitation robot is realized by using a position controller. By establishing the self-adaptive adjustment impedance function and adjusting the static balance force by level, rehabilitation training processes can adapt to individuals and control processes are more natural, smooth and reliable and safer.

Description

technical field [0001] The invention relates to the field of adaptive control of rehabilitation robots, in particular to a control method for rehabilitation robots based on myoelectric feedback impedance self-adaptation. Background technique [0002] At present, the control methods of rehabilitation robots mainly fall into two categories: passive control and active control. The passive control method realizes the motion control of the rehabilitation robot by setting the desired trajectory and tracking the desired trajectory by position control. However, the passive control method has poor individual adaptability, and lacks the active participation of the training object in the whole rehabilitation training process; the active control method is also called interactive control. According to the different interactive signals, active control is divided into two categories: Interactive control of feedback signals. The most commonly used method is the impedance control method, w...

AI Technical Summary

Problems solved by technology

However, its reliability cannot be effectively guaranteed, and it is prone to accidents leading to secondary injuries

[0003] In summary, there is still a lack of a better control method for rehabilitation robots

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