Artificial hand using muscle electrical and electroencephalogram cooperative control and controlling method thereof

A collaborative control and prosthetic hand technology, applied in the field of human hand replacement and its control, can solve the problems of poor accuracy and repeatability of information patterns, muscle fatigue, and inability to provide sufficient myoelectric control information, etc.

Inactive Publication Date: 2007-10-24
TIANJIN UNIV
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AI Technical Summary

Problems solved by technology

[0005] However, only using EMG signals as a prosthetic signal source also has certain limitations: the operator works for a long time, and the muscles are prone to fatigue; muscle fatigue, changes in electrode positions, physical energy fluctuations, etc. will change the characteristic values ​​​​of EMG signals, resulting in The accuracy of control and the repeatability of information patterns are not good; in addition, in patients with high amputations or muscle atrophy due to paralysis, insufficient myoelectric control information can be provided

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  • Artificial hand using muscle electrical and electroencephalogram cooperative control and controlling method thereof
  • Artificial hand using muscle electrical and electroencephalogram cooperative control and controlling method thereof

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Embodiment Construction

[0028] The system first collects the EMG signal through the processing module. As shown in Figure 2, the amplification and filtering functions of the acquisition system are realized in four stages. The first stage uses an instrument amplifier to amplify the collected biological signal dozens of times. The second stage adopts a passive double-T notch circuit, and the resistance and capacitance of the circuit are matched to filter out 50Hz interference well. The third stage uses a high-pass filter to filter out the DC potential generated by the polarization potential. The fourth stage uses a low-pass filter to filter out high-frequency interference. The cut-off frequency of the EEG signal is set at 30Hz, and the cut-off frequency of the EMG signal is set at 500Hz. This filter also acts as an anti-aliasing filter before A / D conversion. Considering the safety of the human body, high-speed digital optocoupler isolation is used in the circuit.

[0029] Then feature extraction and ...

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Abstract

The invention relates to an artificial hand controlled by myoelectric and brain, comprising myoelectric and brain electrode, myoelectric and brain signal treatment module, A/ D conversion data collection, myoelectric signal moving module identification and track prediction module, electrical artificial hand, touch and feel sensor, systematic feedback stimulation device, force and speed moderating module. The controlling method comprises following steps: collecting and enlarging myoelectric signal; collecting characteristic and identifying module; checking caught object condition, if the objection is not caught, a certain kind of physical stimulation signal will be sent to operator; checking brain information; outputting information to force and speed moderating module; output information controlling the electrical artificial hand. The invention overcomes limit of only taking myoelectric signal as signal source.

Description

technical field [0001] The invention relates to a substitute for a human hand and a control method thereof, in particular to a prosthetic hand controlled by myoelectricity and brain electricity and a control method thereof. Background technique [0002] Since World War II, prosthetic hand technology has developed significantly, especially myoelectrically controlled prosthetic hands have been widely used. The myoelectric prosthetic hand is a man-machine system controlled by bioelectricity. It controls the opening and closing of the prosthetic hand through the exchange of information between the human body's myoelectric signal and the prosthetic. [0003] The development of myoelectric prosthetic hands at home and abroad has a certain foundation, such as the automatic SUVA sensor hand developed by Otto Bock in Germany, which controls the grip strength and opening and closing speed of the prosthetic hand through the strength of the myoelectric signal, making the grasping action...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61F2/72A61F2/70A61F2/54
Inventor 李醒飞钟莹裘祖荣张国雄向红标朱嘉
Owner TIANJIN UNIV
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