Brain-myoelectricity artificial limb control device and method based on scene steady-state visual evoking

A technology of steady-state visual induction and myoelectric control, which is applied in the field of brain-myoelectric intelligent control devices, can solve problems such as brain-computer interface paradigm research, and achieve the effect of improving flexible use ability

Active Publication Date: 2015-03-11
XI AN JIAOTONG UNIV
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Problems solved by technology

[0004] For the EEG-driven control of disabled prostheses, domestic scholars are still using the EEG signals generated by the process of motor imagery or motion recognition as the c...

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  • Brain-myoelectricity artificial limb control device and method based on scene steady-state visual evoking

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Embodiment Construction

[0023] refer to figure 1 , figure 2 The system involved in the present invention includes an EEG acquisition unit 3 placed on the occipital region 7 of the subject, an electromyography acquisition unit 4 placed on the biceps brachii and triceps 6 of the subject's upper arm, placed on the subject The scene steady-state visual eliciting unit 1 within the visual range of the tester's eyes, the scene steady-state visual eliciting unit may be a display device such as a computer monitor, a TV screen, a mobile phone or a tablet computer. Since brain and EMG signals are both weak signals, the EEG acquisition unit 3 preferentially uses a special portable EEG cap EMOTIV to collect EEG signals in the occipital lobe area, and selects O1 and O2 channel signals under the international standard 10 / 20. And perform amplification and filtering on EMOTIV's own software. The electromyography acquisition unit adopts KMS wireless surface electromyography device to collect the surface electromyog...

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Abstract

The invention discloses a brain-myoelectricity artificial limb control device and method based on scene steady-state visual evoking. The method is characterized by comprising the following steps: stimulating the brain of a subject by adopting a scene steady-state visual evoking unit to induce the generation of an operation intent; picking up the electroencephalogram and myoelectricity signals of an operator respectively by adopting a portable electroencephalogram acquisition unit, a myoelectricity acquisition unit and a wireless Bluetooth technology; transmitting the electroencephalogram and myoelectricity signals onto a microprocessor; performing target action identification through a method for combining the electroencephalogram and myoelectricity signals; and coding an identification result to drive an intelligent artificial limb to finish corresponding actions. The key points are that a certain action is decomposed into a plurality of different scenes; two inverse color pictures with sharp contrast between black and white are obtained respectively after each scene is subjected to gray-scale processing; two inverse color pictures of each scene flicker continuously and alternatively through pulse width modulation of different frequencies to stimulate the brain of the subject in order to induce the generation of the operation intent.

Description

technical field [0001] The invention relates to biomedicine and advanced manufacturing technology, in particular to a brain-myoelectric intelligent control device and method for human artificial limbs. Background technique [0002] With the development of biomechatronics technology, more and more bioelectrical control methods are applied to intelligent prosthetics. According to different control sources, they can be divided into myoelectric control prostheses and EEG control prostheses. The control source processing method of EMG signal is simple, and the signal-to-noise ratio is high, but the measured muscle is prone to fatigue; while the EEG signal does not depend on external environmental conditions, but it has low resolution, strong randomness, and low SNR. insufficient. In recent years, scholars at home and abroad have shown great interest in EEG signals as the drive and control source of external electromechanical devices. In 2011, the University of Pittsburgh succes...

Claims

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Application Information

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IPC IPC(8): A61F2/72
Inventor 张小栋李睿田艳举陈江城郭晋刘畅王贺石强勇
Owner XI AN JIAOTONG UNIV
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