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Intelligent wheelchair control method and system based on human brain movement intention

A motion intention and control method technology, which is used in vehicle rescue, patient chairs or special transportation tools, medical transportation, etc., can solve the problem of potential interference corresponding to motion intention, inaccurate EEG signal processing, and poor real-time wheelchair control. and other problems, to ensure the concentration of attention, avoid poor real-time performance, not easy to noise and baseline interference

Active Publication Date: 2018-05-04
郑州布恩科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The object of the present invention is: the present invention provides a kind of intelligent wheelchair control method and system based on human brain movement intention, solves the problem that in the prior art, only local brain regions are analyzed, which leads to inaccurate EEG signal processing and thus makes the control accuracy of the wheelchair Poor, motor intention corresponding potential is affected by interference, resulting in poor real-time wheelchair control

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  • Intelligent wheelchair control method and system based on human brain movement intention
  • Intelligent wheelchair control method and system based on human brain movement intention
  • Intelligent wheelchair control method and system based on human brain movement intention

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Embodiment 1

[0041] A kind of intelligent wheelchair control method based on human brain motion intention, comprises the following steps:

[0042] Step 1: Construct the EEG brain network through the collected EEG signals;

[0043] Step 2: Classify the state of attention according to the node characteristics of the EEG brain network, and judge whether the subject is in a state of concentration. If so, start the wheelchair walking mode and skip to step 3; if not, skip to step 1;

[0044] Step 3: Extract the motor readiness potential, ERD features and eye-closing rhythm features of the collected EEG signals, and control the wheelchair according to the instructions of turning left, turning right, going straight and stopping going straight.

[0045] An intelligent wheelchair control system based on human brain motion intention, including an acquisition and amplification unit, a wireless transmission unit, an analysis unit and an intelligent wheelchair, wherein

[0046] The acquisition and ampl...

Embodiment 2

[0051] Step 1.1: After using the electrode cap to collect the EEG signal, use a notch filter to remove the power frequency interference on the EEG signal, use the template matching method to eliminate the oculoelectric artifact, and use the band-pass filter to remove the motion artifact to obtain the preprocessed EEG signal;

[0052] Step 1.2: Obtain EEG data based on the preprocessed EEG signal, define the electrode leads of the EEG data as the nodes of the EEG brain network, and define the coherence coefficient calculated based on the EEG data between the electrode pairs as the edge of the EEG brain network to complete Construct EEG brain network;

[0053] Step 2.1: Construct a weighted network according to the edges and nodes of the EEG brain network to calculate the node degree, and use the support vector machine classifier to classify the attention state with the node degree feature to judge whether it is a state of high concentration of attention. If so, skip to step 2.2 ...

Embodiment 3

[0059] Use dry electrodes to collect EEG signals and wirelessly transmit them to the analysis unit via Bluetooth; in the actual implementation, the electrode cap with 32 dry electrodes is worn on the patient's head, and the electrodes are arranged according to the international standard 10-20 standard. The weak EEG signals recorded by the 32 conductive electrodes are converted into digital signals after being amplified by the amplifier, and wirelessly transmitted to the computer equipped with the analysis unit through the bluetooth interface.

[0060] Construct the EEG brain network after preprocessing the collected EEG signals: In the specific implementation, the notch filter is used to filter out the power frequency interference in the EEG signals, and the template matching method is used to eliminate the ocular artifacts in the EEG signals. The band-pass filter method removes the motion artifacts in the EEG signal; the EEG data is obtained based on the preprocessed EEG signa...

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Abstract

The invention discloses an intelligent wheelchair control method and system based on the human brain movement intention, and relates to the field of intelligent wheelchairs. The method comprises the following steps that 1, through collected electroencephalograms, an EEG brain network is built; 2, according to node characteristics of the EEG brain network, attentional states are classified, whetheror not a tested object is in a focused state is judged, if yes, a wheelchair walking mode is started, the step 3 is executed, and if not, the step 1 is executed; 3, movement preparation potentials, ERD characteristics and eye closing rhythm characteristics of the collected electroencephalograms are executed, and according to the movement preparation potentials, the ERD characteristics and the eyeclosing rhythm characteristics of the collected electroencephalograms, left steering, right steering, straight going and straight going stopping instructions are generated to control a wheelchair. Bymeans of the method and the system, the problems are solved that in the prior art, only local brain areas are analyzed, so that electroencephalogram processing is not correct, and then the control precision of the wheelchair is poor; the effects of improving the precision and the real-time capability of wheelchair control are achieved.

Description

technical field [0001] The invention relates to the field of intelligent wheelchairs, in particular to an intelligent wheelchair control method and system based on human brain motion intention. Background technique [0002] In recent years, the rapid development of brain-computer interface technology has made the idea of ​​using human brain signals to directly control external devices a reality, bringing hope for the improvement of the quality of life of disabled patients with partial quadriplegia but normal brain functions. Among them, the most promising The technology is an intelligent wheelchair based on brain-computer interface control, which can decode the EEG signals of disabled patients and use it to control the walking of intelligent wheelchairs, greatly expanding the living space of patients; the currently developed brain for controlling intelligent wheelchairs There are three main types of machine interface: motor imagery, P300 potential and steady-state visual evo...

Claims

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Application Information

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IPC IPC(8): A61G5/04A61G5/10
CPCA61G5/04A61G5/10A61G2203/18
Inventor 张锐
Owner 郑州布恩科技有限公司