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Electric artificial hand combined controlled by brain electricity and muscle electricity and control method

A technology of joint control and EEG, applied in the field of information and control, can solve the problems of handicapped injury, low signal-to-noise ratio of surface EMG signal aliasing, difficulty in recognizing multi-modal movements, etc. Reliable motion control and improved bionic performance

Inactive Publication Date: 2010-03-24
HANGZHOU DIANZI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Recognition of multimodal actions from few-channel surface EMG signals is difficult due to the weak nature, aliasing, and low signal-to-noise ratio of SEMG signals
Although the single-degree-of-freedom myoelectric prosthetic hand with two action modes obtained from two surface electromyographic signals has been practical, the commercialization of the real-time-controlled multi-degree-of-freedom myoelectric prosthetic hand is not ideal. The key problem is the real-time processing of multi-degree-of-freedom modes. The accuracy needs to be further improved
At present, the correct rate of 85% of the pattern processing of the three-degree-of-freedom myoelectric prosthetic hand is difficult to put into practical application, because any uncertain movement of the prosthetic hand may cause unexpected damage to the disabled

Method used

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  • Electric artificial hand combined controlled by brain electricity and muscle electricity and control method
  • Electric artificial hand combined controlled by brain electricity and muscle electricity and control method
  • Electric artificial hand combined controlled by brain electricity and muscle electricity and control method

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Embodiment Construction

[0026] Such as figure 1 As shown, the electric prosthetic hand controlled by EEG combined with electromyography includes four electromyographic pickup sensors placed on the skin surface corresponding to the extensor carpi ulnaris, flexor carpi ulnaris, finger extensors, and pronator quadratus of the residual arm 1 and two EEG pick-up sensors 2 placed in the center of the top of the human head at the positions C3 and C4 determined according to the 10-20 lead system. Each myoelectric pickup sensor 1 includes three myoelectric pickup electrodes placed on the residual arm of the human body and the localized myoelectric primary amplifying circuit connected with the myoelectric pickup electrode signal; the output terminal of the myoelectric primary amplifying circuit Respectively connected to the corresponding myoelectric secondary processing circuit 3, the secondary processing circuit 3 includes a 10-500 Hz band-pass filter and a 50 Hz notch wave to obtain an effective frequency my...

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Abstract

The invention relates to a power-driven artificial hand controlled by the combination of brain electricity and myoelectricity and a control method thereof. The pattern treatment of a current 3-DOF myoeletricity artificial hand has poor accuracy. The power-driven artificial hand comprises a plurality of myoelectricity picking-up sensors and brain electricity picking-up sensors. The output end of asecondary processing circuit in the myoelectricity picking-up sensors and the brain electricity picking-up sensors is connected with the input end of an A / D switching circuit. Three electrical motorsare connected with a driving circuit respectively. A micro processor is connected with the output end of the A / D switching circuit and the input end signal of the driving circuit respectively. The myoelectricity picking-up sensors and the brain electricity picking-up sensors collect surface myoelectric signals from the points of a disabled arm and brain electricity signals from the top of a head and an ear. After being amplified, filtered and processed by A / D switching, the surface myoelectric signals and the brain electricity signals are input into the micro processor for further processing so as to control a 3-DOF power-driven artificial hand. The power-driven artificial hand performs control by the combination of the myoelectric signals and the brain electricity signals and module recognition, so that the accuracy is high and the control of action is reliable.

Description

technical field [0001] The invention belongs to the field of information and control technology, and relates to a technology for controlling artificial hand with scalp EEG and surface EMG information. Specifically, after merging EEG / EMG signals, multiple patterns of artificial hand movements can be identified and realized. An electric prosthetic hand controlled in real time with multiple degrees of freedom and a control method. Background technique [0002] Electromyogram (EMG for short) is a kind of bioelectrical signal accompanying muscle activity, which is the source of electrical signal of muscle activity, which contains various information of muscle activity, including body movement patterns corresponding to muscle activity. Surface Electromyogram (SEMG for short) is the combined effect of the EMG of the superficial muscles and the electrical activity of the nerve trunk on the skin surface. Because SEMG has non-invasive characteristics in measurement, it is painless an...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61F2/72
Inventor 罗志增孟明
Owner HANGZHOU DIANZI UNIV
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