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Brain-computer interface signal analysis method and system, medium and equipment

A brain-computer interface and analysis method technology, applied in the fields of diagnostic signal processing, computer components, medical science, etc., can solve the problem of difficult detection of stimulus targets, and achieve the effects of increasing modulation dimensions, improving resolution capabilities, and high communication rates

Active Publication Date: 2019-07-05
SHANGHAI ADVANCED RES INST CHINESE ACADEMY OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In view of the above-mentioned shortcomings of the prior art, the purpose of the present invention is to provide a method, system, medium and equipment of a brain-computer interface, which are used to solve the problem of difficulty in detecting stimulus targets in the prior art

Method used

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  • Brain-computer interface signal analysis method and system, medium and equipment
  • Brain-computer interface signal analysis method and system, medium and equipment
  • Brain-computer interface signal analysis method and system, medium and equipment

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Embodiment 1

[0032] This embodiment provides a method for analyzing brain-computer interface signals, including:

[0033] Acquire several stimulation targets, and collect corresponding EEG signals according to the stimulation targets; wherein, several of the stimulation targets have different shapes and have different stimulation frequencies and / or stimulation phases;

[0034] Carrying out one-to-one discriminant analysis of characteristic coefficients of the EEG signal and several prestored expected signals to obtain a discriminant analysis result, the discriminant analysis result including a frequency characteristic coefficient and a spatial intensity distribution coefficient;

[0035] Comparing the spatial intensity distribution coefficient with several pre-stored training data to obtain a spatial characteristic probability coefficient based on the spatial intensity distribution coefficient under the same stimulation target and the training data corresponding to the stimulation target; ...

Embodiment 2

[0080] The present invention provides an analysis system of a brain-computer interface signal, and the analysis system of the brain-computer interface signal includes:

[0081] A signal acquisition module, configured to acquire several stimulation targets, and collect corresponding EEG signals according to the stimulation targets; wherein, several of the stimulation targets have different shapes and have different stimulation frequencies and / or stimulation phases;

[0082] The discriminant analysis module is used to perform one-to-one discriminant analysis of the characteristic coefficients of the EEG signal and several prestored expected signals to obtain a discriminant analysis result, and the discriminant result includes a frequency characteristic coefficient and a spatial intensity distribution coefficient;

[0083] A probability analysis module, configured to compare the spatial intensity distribution coefficient with several pre-stored training data to obtain a spatial ch...

Embodiment 3

[0101] This embodiment provides a device, including: a processor, a memory, a transceiver, a communication interface or / and a system bus; the memory and the communication interface are connected to the processor and the transceiver through the system bus and complete mutual communication, and the memory is used for The computer program is stored, the communication interface is used to communicate with other devices, the processor and the transceiver are used to run the computer program, so that the device executes the steps of the brain-computer interface signal analysis method described in Embodiment 1.

[0102] The system bus mentioned above may be a Peripheral Component Interconnect (PCI for short) bus or an Extended Industry Standard Architecture (EISA for short) bus or the like. The system bus can be divided into address bus, data bus, control bus and so on. The communication interface is used to realize the communication between the database access device and other devic...

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Abstract

The invention provides a brain-computer interface signal analysis method and system, a medium and equipment. The brain-computer interface signal analysis method comprises: acquiring a plurality of stimulating targets, and acquiring corresponding electroencephalogram signals corresponding to the stimulating targets; subjecting the electroencephalogram signals and a plurality of pre-stored expectedsignals to one-to-one corresponding characteristic coefficient judging and analysis to obtain judging and analysis results; comparing spatial intensity distribution coefficient and a plurality of pre-stored training data pieces to obtain a spatial characteristic probability coefficient for the spatial intensity distribution coefficient under the same stimulating target with respect to training data corresponding to the stimulating target; weighting the frequency characteristic coefficients and spatial characteristic probability coefficients of corresponding to the stimulating targets, and using the stimulating target corresponding to the maximum value of the weighting results as a detection result. The invention provides a novel brain-computer interface stimulating paradigm and corresponding detection algorithm design; stimulating targets can be recognized more accurately, so that overall communication rate of a brain-computer interface can be increased.

Description

technical field [0001] The invention belongs to the technical field of intelligent communication, and relates to a brain-computer interface method, in particular to a brain-computer interface signal analysis method, system, medium and equipment. Background technique [0002] The brain-computer interface is a new type of EEG signal collected from the surface of the human skull through translation to achieve information output different from normal language pathways and behavioral pathways. According to the types of extracted EEG signals, several main implementation methods of BCI can be divided into P300 BCI, motor imagery BCI and SSVEP BCI, etc. Among them, the signal-to-noise ratio of the SSVEP signal extracted by the SSVEP brain-computer interface is the largest, and the interface communication rate that can be achieved is the highest. In addition to the acquisition and analysis equipment of EEG signals, the SSVEP brain-computer interface also needs additional visual stim...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0476G06K9/00
CPCA61B5/72A61B5/369G06F2218/12
Inventor 王振宇张敏胡宏林周婷徐天衡欧阳玉玲沈芳菲
Owner SHANGHAI ADVANCED RES INST CHINESE ACADEMY OF SCI