An asynchronous real-time brain control method driven by weak myoelectricity artifact micro-expression electroencephalogram signals

Abstract

The invention discloses an asynchronous real-time brain control method driven by weak myoelectricity artifact micro-expression electroencephalogram signals. The method includes: taking a 100ms electroencephalogram signal as a single signal source, and carrying out brain control micro-expression attribute judgment by utilizing myoelectricity artifact energy proportion; Executing brain control statestart / stop brain control micro-expression detection and effectiveness judgment thereof; and starting a brain control state after judging that the brain control micro-expression is true, performing brain control micro-expression recognition and validity judgment after judging that the brain control micro-expression attribute is in the brain control state, and generating a brain control instructionfor controlling a controlled object or stopping the brain control state after judging that the brain control micro-expression is true. Start / stop of a brain control state and action operation of eight controlled objects are achieved based on brain control micro expressions, the real-time performance, flexibility and accuracy of the brain control method are effectively improved, asynchronous braincontrol interface detection and brain control micro expression effectiveness judgment are increased, the practical value of the brain control method is improved, and the brain control method can be widely applied to various brain control systems.

Description

technical field [0001] The invention relates to the technical field of brain-computer interface, in particular to an asynchronous real-time brain control method driven by weak myoelectric artifacts and micro-expression EEG signals. Background technique [0002] Brain Computer Interface (BCI) technology, which uses the user's EEG signal as the signal source, uses advanced computer information processing technology to decode the user's intention, and avoids the possible damage of the user's peripheral nerves / The muscular system establishes direct communication between the user's consciousness and peripherals. It has great application value in rehabilitation medicine, high-risk operations, game entertainment, aerospace military and other fields. [0003] Traditional brain-computer interfaces are mostly implemented based on the Steady State Visual Evoked Potential (SSVEP) and Motor Imagery (MI) paradigms. Among them, SSVEP has the advantages of high accuracy and many recogniza...

AI Technical Summary

Problems solved by technology

[0003] Traditional brain-computer interfaces are mostly implemented based on the Steady State Visual Evoked Potential (SSVEP) and Motor Imagery (MI) paradigms. Among them, SSVEP has the advantages of high accuracy and many recognizable categories. However, due to its Constrained by paradigm principles, additional visual stimulators and visual stimulation time are required, and there are problems of equipment redundancy and limited real-time response in terms of brain control; MI has the advantage of conforming to the spontaneous EEG generation process of the human brain, but due to imaginary movement It is difficult to implement, requires additional time for subjects to adapt, and has problems of low user-friendliness and limited identifiable categories on brain control issues

Moreover, most of the existing research is based on the synchronous brain-computer interface, which only allows the user to send commands during the specific time period set by the system, and cannot provide the user with the authority to control the time of sending control commands autonomously. limit

[0004] In order to solve the above problems of redundancy and low user-friendliness of traditional brain-computer interface devices, Chinese patent 201510423224 and Chinese patent 201510423398 all disclose brain control methods based on the expression-driven brain-computer interface paradigm

The expression-driven brain control method involved in it does not consider the difference between it and other daily facial expressions in the actual application process and the aesthetics of the user's use process in terms of expression movements; in terms of EEG signal channel selection, it only includes forehead The lobar cortex and limbic system ignore facial expressions as a kind of facial muscle action in the information expression of the motor cortex of the brain; in terms of the brain-controlled expression actions provided, it is only suitable for operations within 4 kinds of control targets, and the number of control targets is limited; In the working process of the brain control interface, the asynchronous brain control interface is not introduced, and the automatic start / stop of the user's brain control state cannot be realized, which lacks practical application value

[0005] The brain-control methods derived from the above-mentioned brain-computer interface technology have low real-time performance (low frequency of control command output), redundancy of additional stimulators, and lack of asynchronous brain-computer interface (brain control interface) functions to varying degrees. , low user friendliness, etc.

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