Artificial hand control system and method

Abstract

The invention discloses an artificial hand control system and an artificial hand control method. The system comprises a signal acquisition module, a feedback module, a data storage module, a digital signal processing module and a driving module, wherein a master control module is connected with the signal acquisition module, the feedback module, the data storage module, the digital signal processing module and the driving module respectively; the master control module is used for cooperatively managing the signal acquisition module, the feedback module, the data storage module, the digital signal processing module and the driving module; and the signal acquisition module is connected with eight electrodes for recording electroencephalogram (EEG) and two electrodes for recording surface electromyography (SEMG). The system can integrate the EEG and SEMG information, and decodes the speed, accelerated speed and track of hand motion in real time; therefore, an artificial hand is flexibly controlled; moreover, the system is natural to use and convenient to maintain and does not need any implanted electrode.

Description

technical field [0001] The invention relates to hand motion parameter prediction technology, in particular to a prosthetic hand control system and a control method thereof. Background technique [0002] Prediction of hand motion parameters (including velocity, acceleration, and trajectory) is a difficult point in the realization of prosthetic hand control. At present, there are two main types of prosthetic hand control systems based on the prediction of hand motion parameters: (1) By analyzing the action potentials emitted by the muscles of the residual limbs, extracting effective features that reflect the willingness of the hand to move, thereby establishing feature vectors and hand motion parameters The control function is realized by the mapping relationship between them. The system is limited by the decoding ability of myoelectricity, and the degree of freedom of controlling the movement of the prosthetic hand is not high. (2) Implant electrodes to record nerve signals ...

AI Technical Summary

Problems solved by technology

At present, there are two main types of prosthetic hand control systems based on the prediction of hand motion parameters: (1) By analyzing the action potentials emitted by the muscles of the residual limbs, extracting effective features that reflect the willingness of the hand to move, thereby establishing feature vectors and hand motion parameters The control function is realized by the mapping relationship between them. The system is limited by the decoding ability of myoelectricity, and the degree of freedom to control the movement of the prosthetic hand is not high.

(2) Implant electrodes to record nerve signals of the brain or upper limbs, and predict hand movement parameters. This system is natural to use and has good control effects, but it has surgical risks and is not easy to maintain

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