CN115708678A - Brain-computer interface experimental method based on functional near infrared - Google Patents
Brain-computer interface experimental method based on functional near infrared Download PDFInfo
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Abstract
The invention is suitable for the technical field of brain-computer interfaces and brain area health examination, and provides a brain-computer interface experimental method based on functional near infrared, which comprises the following steps: receiving a brain picture template and a brain hemodynamic parameter sample collected by a brain-computer interface system, calling the corresponding brain picture template and the corresponding brain hemodynamic parameter template according to the serial numbers, comparing the brain picture template and the brain hemodynamic parameter template with a brain picture and a brain hemodynamic parameter sample of a subject, automatically matching each brain region in the brain picture of the subject with each brain region in the brain picture template, matching the brain region picture with a corresponding brain region picture standard library according to a marked brain region name, outputting a matched standard brain region picture and standard brain region hemodynamic parameters, comparing the marked brain region hemodynamic parameter sample with the standard brain region hemodynamic parameters, and outputting brain region status bar information, wherein the experimental results are more accurate.
Description
Technical Field
The invention relates to the technical field of brain-computer interfaces and brain area health examination, in particular to a brain-computer interface experimental method based on functional near infrared.
Background
The functional near infrared spectroscopy is a completely lossless in-vivo optical detection technology developed in recent years, biological tissues have the characteristics of low absorption and high scattering to light in a near infrared band, and near infrared light can penetrate through the thickness of the biological tissues by several centimeters to detect deep biological tissues. When the brain activates, the oxygen metabolism rate increases, and the cerebral blood flow also increases, causing changes in the concentration of oxygenated hemoglobin (HbO 2) and reduced hemoglobin (Hb). The absorption spectra of HbO2 and Hb in the near infrared band have specificity, so that the brain nerve activity can be indirectly detected by near infrared spectrometry according to the change of emergent light intensity or phase. Compared with other biomedical imaging technologies, the near infrared spectroscopy has the advantages of flexibility in use, portability, low cost and the like, so that the near infrared spectroscopy is widely applied to the field of brain function imaging and detection in recent years, and a new technical means is provided for the development of a brain-computer interface (BCI).
The brain-computer interface is a system which converts the nerve physiological signals in the thinking process into control signals and controls external machines without depending on peripheral nervous systems and muscles. The brain-computer interface not only can help the serious paralyzed patient to communicate with the outside, but also can assist the cerebral apoplexy patient to recover the motor function. Non-invasive brain-computer interfaces have shown broad application prospects because of their relatively easily available signals and broad user population. Many techniques are currently applied in the field of non-invasive brain-computer interfaces, such as electroencephalography (EEG), magnetoencephalography (MEG), functional magnetic resonance (fMRI), and functional near-infrared spectroscopy. The magnetoencephalogram and functional magnetic resonance are only used in scientific research at present due to expensive, complex and huge equipment, and have no practical application prospect. The electrical signal for directly detecting the neural activity by the brain electricity is the most common technology in the field of brain-computer interfaces, and has the advantages of simple use, safety and low cost.
However, in the experimental process of researching the health degree of each brain area (most common including a primary motor cortex and a forehead lobe layer, the former is related to the action of human muscles, and the latter is related to mental arithmetic or audio-video and the like) of a subject based on the technical principle of a functional near-infrared brain-computer interface, the problem that whether the collected brain data of the subject is healthy cannot be automatically judged exists, generally, manual and automatic judgment and comparison are needed, and the problems of low efficiency and large judgment result error occur.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a brain-computer interface experimental method based on functional near infrared to solve the problems in the background technology.
The invention is realized in such a way, and discloses a brain-computer interface experimental method based on functional near infrared, which comprises the following steps:
the brain-computer interface system is adopted to connect the scalp surface of the testee, and the testee completes imagination tasks according to prompts;
acquiring a brain hemodynamic parameter sample and a brain picture of a testee, which are acquired by a brain-computer interface system, wherein the brain picture corresponding to the brain hemodynamic parameter sample of the testee is marked with a serial number;
calling a corresponding brain picture template and a corresponding brain hemodynamic parameter template according to the serial numbers, wherein the brain picture template and the brain hemodynamic parameter template are provided with one or more information frames, and each information frame corresponds to a brain area name;
covering the brain picture template and the brain hemodynamic parameter template above the brain picture and the brain hemodynamic parameter sample of the subject to obtain one or more brain area pictures and brain area hemodynamic parameter samples, wherein each brain area picture and brain area hemodynamic parameter sample is marked with a brain area name;
inputting the brain area picture into a corresponding brain area picture standard library for matching according to the marked brain area name, and outputting a matched standard brain area picture and standard brain area hemodynamic parameters;
matching the marked brain region hemodynamic parameter sample with the standard brain region hemodynamic parameter, and outputting brain region status bar information;
and summarizing the information of the one or more brain area status bars to generate experimental result information.
As a further scheme of the invention: the step of connecting the scalp surface of the testee by adopting the brain-computer interface system specifically comprises the following steps:
the near-infrared detector and the CT equipment are adopted to be close to the scalp surface of the head of the testee and are respectively used for collecting brain hemodynamic parameter samples and brain pictures.
As a further scheme of the invention: the step of obtaining the sample of the hemodynamic parameters of the brain of the human subject collected by the brain-computer interface system specifically comprises the following steps:
the testee completes the imagination task according to the prompt, and the near-infrared detector is used for collecting brain hemodynamic signals;
calculating brain hemodynamic parameters of a tested person by using a signal detection method of a near-infrared brain-computer interface based on independent component analysis and a least square method;
the method comprises the following steps that a testee completes an imagination task for a plurality of times according to prompts, a near-infrared detector collects a plurality of brain hemodynamic signals, and a signal detection method of a near-infrared brain-computer interface based on independent component analysis and least square method is used for calculating a plurality of brain hemodynamic parameters of the testee;
summarizing the plurality of brain hemodynamic parameters to generate a brain hemodynamic parameter sample of the tested person.
As a further scheme of the invention: the step of calling corresponding brain pictures and brain hemodynamic parameter samples according to the serial numbers specifically comprises:
inputting the number corresponding to the brain parameter sample of the tested person into the information frame;
and outputting a corresponding brain picture and a brain hemodynamic parameter sample.
The invention also aims to provide an electric power equipment detection system based on the infrared image.
As a further scheme of the invention: the step of inputting the brain area picture into the corresponding brain area picture standard library for matching according to the marked brain area name specifically comprises:
inputting the brain area pictures into corresponding brain area picture standard libraries according to the marked brain area names for matching, wherein each brain area name corresponds to one brain area picture standard library;
matching the brain area picture marked with the brain area name with a standard brain area picture in a brain area parameter standard library to obtain a plurality of matching values;
and outputting a standard brain area picture with the highest matching value, and outputting standard hemodynamic parameter sample information corresponding to the standard brain area picture.
As a further scheme of the invention: the near-infrared detector comprises a dual-wavelength light source L, a detector D1 and a detector D2, near-infrared light emitted by the dual-wavelength light source L is incident to brain tissues to be detected, the detector D1 is used for detecting hemodynamic signals of a primary motor cortex, and the detector D2 is used for detecting hemodynamic signals of a forehead lobe layer.
As a further scheme of the invention: the method comprises the following steps of respectively calculating and obtaining brain hemodynamic parameter samples of a tested person by using a signal detection method of a near-infrared brain-computer interface based on independent component analysis combined with a least square method, and specifically comprises the following steps:
the testee finishes the imagination task related to muscle action or muscle tension according to the prompt, the detector D1 collects the primary motor cortex hemodynamic change signals, and the primary motor cortex hemodynamic parameters s (k) 1a1 are respectively calculated by using a signal detection method of a near-infrared brain-computer interface based on independent component analysis and least square method;
the testee completes the imagination task related to mental calculation or music intention according to the prompt, the detector D2 collects the primary motor cortex hemodynamic change signals, and forehead lobe layer hemodynamic parameters s (k) 2b1 are respectively calculated by using a signal detection method of a near-infrared brain-computer interface based on independent component analysis and least square method.
A human subject completes an imagination task related to muscle action or muscle tension for a plurality of times according to prompts, a plurality of primary motor cortex hemodynamic parameters are summarized, and a human subject primary motor cortex hemodynamic parameter sample s (k) 1 (a 1.. An) is output;
the testee completes the imagination task related to mental arithmetic or musical intention for a plurality of times according to the prompt, summarizes a plurality of forehead lobe layer hemodynamic parameters, and outputs a forehead lobe layer hemodynamic parameter sample s (k) 2 (b 1.. Bn).
As a further scheme of the invention: the step of matching the brain area picture marked with the brain area name with the standard brain area picture in the brain area parameter standard library specifically comprises:
and respectively calculating the hash values of the primary moving cortex image of the testee and the standard primary moving cortex image by using a hash method based on DCT to obtain h _1 and h _2.
Respectively calculating the hash values of the forehead leaf layer image and the standard forehead leaf layer image of the testee by using a hash method based on DCT (discrete cosine transformation) to obtain h _3 and h _4;
calculating a Hamming distance dis _ h1 between h _1 and h _2, and calculating a Hamming distance dis _ h2 between h _1 and h _2;
and calculating to obtain the similarity between the primary motion cortical image of the subject and the standard primary motion cortical image according to the Hamming distance dis _ h1, calculating to obtain the similarity between the forehead lamina image of the subject and the standard forehead lamina image according to the Hamming distance dis _ h2, wherein the similarity is a matching value.
As a further scheme of the invention: the step of matching the marked sample of hemodynamic parameters of the brain region with the standard hemodynamic parameters of the brain region specifically comprises:
comparing the primary motor cortex hemodynamic change signal sample s (k) 1 (a 1-a 2) and the forehead lobe layer hemodynamic change signal sample s (k) 2 (b 1-b 2) with the brain hemodynamic change signal standard value respectively by using Tanimoto coefficients, and outputting comparison values T1 and T2;
when T1 and T2 are close to 1, outputting information of good state of the brain area;
when T1 and T2 are close to 0, information of poor brain region state is output.
Compared with the prior art, the invention has the beneficial effects that:
in the invention: after receiving a brain picture template and a brain hemodynamic parameter sample acquired by a brain-computer interface system, calling the corresponding brain picture template and brain hemodynamic parameter template according to numbers, wherein the brain picture template and the brain hemodynamic parameter template are respectively corresponding to information frames and are automatically matched with brain areas in the brain picture template of a subject when the brain picture template and the brain hemodynamic parameter template are compared with the brain picture and the brain hemodynamic parameter sample of the subject, so as to obtain one or more brain area pictures, the brain hemodynamic parameter sample is automatically corresponding to the corresponding brain area pictures, the brain hemodynamic parameter sample and the brain area pictures are automatically marked with corresponding names, the brain area pictures are continuously matched with a corresponding brain area picture standard library according to the marked brain area names, matched standard brain area pictures and standard brain hemodynamic parameters are output, the marked brain area hemodynamic parameter is differentiated or similar to the standard brain area hemodynamic parameter, the brain area pictures and the brain area dynamic information can be compared with the standard brain area hemodynamic parameter samples, and the comparison result can be more accurately observed by a person who observes the brain area health information.
Drawings
Fig. 1 is a flowchart of a method for detecting an electrical device based on an infrared image.
Fig. 2 is a flowchart of acquiring a sample of a brain hemodynamic parameter of a subject collected by a brain-computer interface system in an infrared image based power device detection method.
Fig. 3 is a flow chart of a method for detecting signals of a near-infrared brain-computer interface based on an independent component analysis combined with a least square method in an infrared image-based power equipment detection method for respectively calculating and obtaining brain hemodynamic parameter samples of a subject.
Fig. 4 is a flowchart illustrating a method for detecting an electrical device based on an infrared image, in which a brain region image is input into a corresponding brain region image standard library according to a marked brain region name for matching.
Fig. 5 is a flowchart of matching a brain region picture marked with a brain region name with a standard brain region picture in a brain region parameter standard library in an infrared image-based power device detection method.
Fig. 6 is a flowchart of matching labeled brain region hemodynamic parameter samples with standard brain region hemodynamic parameters in an infrared image-based power device detection method.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more clear, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
Specific implementations of the present invention are described in detail below with reference to specific embodiments.
As shown in fig. 1, an embodiment of the present invention provides a brain-computer interface experimental method based on functional near infrared, including the following steps:
s100, connecting the scalp surface of the testee by adopting a brain-computer interface system, and finishing imagination tasks by the testee according to prompts;
s200, acquiring a brain hemodynamic parameter sample and a brain picture of the testee, which are acquired by a brain-computer interface system, wherein the brain picture corresponding to the brain hemodynamic parameter sample of the testee is marked with a serial number;
s300, calling corresponding brain picture templates and brain hemodynamic parameter templates according to the numbers, wherein the brain picture templates and the brain hemodynamic parameter templates are provided with one or more information frames, and each information frame corresponds to a brain area name;
s400, covering the brain picture template and the brain hemodynamic parameter template above the brain picture and the brain hemodynamic parameter sample of the subject to obtain one or more brain area pictures and brain area hemodynamic parameter samples, wherein each brain area picture and brain area hemodynamic parameter sample is marked with a brain area name;
s500, inputting the brain area picture into a corresponding brain area picture standard library for matching according to the marked brain area name, and outputting a matched standard brain area picture and standard brain area hemodynamic parameters;
s600, matching the marked brain region hemodynamic parameter sample with a standard brain region hemodynamic parameter, and outputting brain region status bar information;
and S700, summarizing the one or more brain area status bar information to generate experimental result information.
It should be noted that functional near infrared spectroscopy is a completely lossless in vivo optical detection technology developed in recent years, biological tissues have low absorption and high scattering properties for light in a near infrared band, and near infrared light can penetrate through the biological tissues by a thickness of several centimeters to detect deep biological tissues. When the brain activates, the oxygen metabolism rate increases, and the cerebral blood flow also increases, causing changes in the concentration of oxygenated hemoglobin (HbO 2) and reduced hemoglobin (Hb). The absorption spectra of HbO2 and Hb in the near infrared band have specificity, so that the near infrared spectroscopy can indirectly detect brain nerve activity according to the change of emergent light intensity or phase. Compared with other biomedical imaging technologies, the near infrared spectroscopy has the advantages of flexibility in use, portability, low cost and the like, so that the near infrared spectroscopy is widely applied to the field of brain function imaging and detection in recent years, and a new technical means is provided for the development of a brain-computer interface (BCI).
The brain-computer interface is a system which converts the neurophysiological signals in the thinking process into control signals and controls external machines without depending on peripheral nervous systems and muscles. The brain-computer interface not only can help the serious paralyzed patient to communicate with the outside, but also can assist the cerebral apoplexy patient to recover the motor function. Non-invasive brain-computer interfaces have shown broad application prospects because of their relatively easily available signals and broad user population. Many techniques are currently applied in the field of non-invasive brain-computer interfaces, such as electroencephalography (EEG), magnetoencephalography (MEG), functional magnetic resonance (fMRI), and functional near-infrared spectroscopy. The magnetoencephalogram and functional magnetic resonance are only used in scientific research at present due to expensive, complex and huge equipment, and have no practical application prospect. The electrical signal for directly detecting the neural activity by the brain electricity is the most common technology in the field of brain-computer interfaces, and has the advantages of simple use, safety and low cost. However, the electroencephalogram has the disadvantages that the spatial resolution is low, the location of the active brain area cannot be carried out, and the further improvement of the brain-computer interface identification precision is limited. And the brain-computer interface based on the brain electricity has the phenomenon of brain-computer interface illiterate, namely some users can not operate the brain-computer interface system in any way. Therefore, it is necessary to develop a technology to make up for the shortage of electroencephalogram to expand the field of brain-computer interfaces.
In the embodiment of the invention, the brain picture template and the brain hemodynamic parameter template are determined to meet the health requirement before the experiment is carried out, one or more information frames can appear on each brain picture and brain hemodynamic parameter sample of a tested person, the corresponding brain area name is displayed in each information frame, after the brain picture template and the brain hemodynamic parameter sample collected by the brain-computer interface system are received, the corresponding brain picture template and the corresponding brain hemodynamic parameter template can be called according to the number, because the brain comprises a plurality of brain areas, the brain picture template and the brain hemodynamic parameter template are provided with one or more information frames, each information frame is corresponding to the brain area name, when the brain picture template and the brain hemodynamic parameter template are covered on the brain picture and the brain hemodynamic parameter sample of the tested person, each brain area in the brain picture of the tested person can be automatically matched with each brain area in the brain picture template, so as to obtain one or more brain area pictures, the brain area hemodynamic parameter sample can be automatically corresponding to the corresponding brain area picture, and the brain area hemodynamic parameter sample and the brain area picture can be automatically marked with corresponding names, the brain area pictures are continuously input into the corresponding brain area picture standard library according to the marked brain area names for matching, matched standard brain area pictures and standard brain area hemodynamic parameters are output, the standard brain area pictures and the standard brain area hemodynamic parameters refer to the brain area pictures and the brain area hemodynamic parameters meeting the health requirements, the marked brain area hemodynamic parameter sample and the standard brain area hemodynamic parameters are subjected to differentiation or similarity comparison, the comparison result can output brain area status bar information after coming out, and the staff of being convenient for through observing brain area status bar information knows the health degree in each brain area of the person under test, and the experimental result also can be more accurate moreover.
As a preferred embodiment of the present invention, the step of connecting the scalp surface of the subject with the brain-computer interface system specifically includes:
a near infrared detector and a CT device are adopted to be close to the scalp surface of the head of a testee and are respectively used for acquiring a brain hemodynamic parameter sample and a brain picture.
In the embodiment of the invention, the near infrared detector and the CT equipment are fixedly installed.
As shown in fig. 2, as a preferred embodiment of the present invention, the step of obtaining a sample of a brain hemodynamic parameter of a subject collected by a brain-computer interface system specifically includes:
s201, completing a imagination task by a testee according to a prompt, wherein the near-infrared detector is used for collecting a brain hemodynamic signal;
s202, calculating brain hemodynamic parameters of the testee by using a signal detection method of a near-infrared brain-computer interface based on independent component analysis and a least square method;
s203, completing a imagination task for a plurality of times according to prompts by a testee, collecting a plurality of brain hemodynamic signals by a near-infrared detector, and calculating a plurality of brain hemodynamic parameters of the testee by using a signal detection method of a near-infrared brain-computer interface based on independent component analysis combined with a least square method;
and S204, summarizing the plurality of brain hemodynamic parameters to generate a brain hemodynamic parameter sample of the tested person.
In the embodiment of the invention, the existing main technologies comprise electroencephalogram, magnetoencephalogram, positron emission tomography and functional magnetic resonance. Based on a certain relation among activity of neurons, local energy metabolism and local hemodynamics, by measuring the absorption characteristics of brain tissues to near-infrared light waves, the hemodynamic change based on information such as the concentration of oxygenated hemoglobin and reduced hemoglobin can be provided. Therefore, the near infrared spectrum technology is used for measuring the optical parameters, the blood oxygen and the hemodynamic parameter information of the region, the functional response of the cerebral cortex during stimulation excitation of limb movement, vision, hearing, touch, language and the like can be obtained, the method is used for researching a brain-computer interface, when a testee completes an imagination task according to prompts, the near infrared detector is used for collecting signals used for brain hemodynamics, and the method based on independent component analysis and least square method is a means for calculating the brain hemodynamics parameters according to the change of the brain hemodynamics signals in the prior art and is not repeated.
As a preferred embodiment of the present invention, the step of calling the corresponding brain picture template and the corresponding brain hemodynamic parameter template according to the number specifically includes:
inputting the number corresponding to the brain parameter sample of the tested person into the information frame;
and outputting the corresponding brain picture template and the brain hemodynamic parameter template.
In the embodiment of the invention, the corresponding brain picture template and the corresponding brain hemodynamic parameter template are called according to the numbers, and the brain comprises a plurality of brain areas, so that the brain picture template and the brain hemodynamic parameter template are provided with one or more information frames, and each information frame is corresponding to a brain area name.
As shown in fig. 4, an embodiment of the present invention further provides a brain-computer interface experimental method based on functional near infrared, where the step of inputting a brain region picture into a corresponding brain region picture standard library according to a marked brain region name for matching specifically includes:
s501, inputting the brain area pictures into corresponding brain area picture standard libraries for matching according to the marked brain area names, wherein each brain area name corresponds to one brain area picture standard library;
s502, matching the brain area picture marked with the brain area name with a standard brain area picture in a brain area parameter standard library to obtain a plurality of matching values;
and S503, outputting a standard brain area picture with the highest matching value, and simultaneously outputting standard hemodynamic parameter sample information corresponding to the standard brain area picture.
In the embodiment of the invention, when the brain picture template and the brain hemodynamic parameter template are covered above the brain picture and the brain hemodynamic parameter sample of the subject, each brain area in the brain picture of the subject can be automatically matched with each brain area in the brain picture template, so that one or more brain area pictures can be obtained, the brain hemodynamic parameter sample can automatically correspond to the corresponding brain area picture, and the brain hemodynamic parameter sample and the brain area picture can be automatically marked with corresponding names.
As a preferred embodiment of the present invention, the near infrared detector is composed of a dual-wavelength light source L, a detector D1 and a detector D2, the dual-wavelength light source L emits near infrared light to be incident on the brain tissue to be detected, the detector D1 is used for detecting the hemodynamic signal of the primary motor cortex, and the detector D2 is used for detecting the hemodynamic signal of the prefrontal lamina.
In this embodiment, the near-infrared light emitted from the near-infrared probe is incident on the brain tissue to be measured, the detector D1 is capable of sensing hemodynamic changes of the primary motor cortex, and the detector D2 is capable of sensing hemodynamic changes of the frontal lobe layer.
As shown in fig. 3, as a preferred embodiment of the present invention, the step of respectively calculating and obtaining the brain hemodynamic parameter samples of the subject by using the signal detection method of the near-infrared brain-computer interface based on the independent component analysis combined with the least square method specifically includes:
s2031, a subject completes the imagination task related to muscle action or muscle tension according to the prompt, a detector D1 collects primary motor cortex hemodynamics change signals, and primary motor cortex hemodynamics parameters S (k) 1a1 are respectively calculated by a signal detection method of a near-infrared brain-computer interface based on an independent component analysis combined least square method;
s2032, the testee completes the imagination task related to mental calculation or music intention according to the prompt, the detector D2 collects the primary motor cortex hemodynamics change signal, and calculates the forehead lamina hemodynamics parameters S (k) 2b1 by the signal detection method of the near-infrared brain-computer interface based on the independent component analysis and the least square method;
s2033, the testee completes the imagination task related to muscle action or muscle tension for a plurality of times according to the prompt, summarizes a plurality of primary motor cortex hemodynamic parameters, and outputs a sample S (k) 1 (a 1.. An) of the primary motor cortex hemodynamic parameters of the testee;
s2034, the subject completes the imagination task related to mental arithmetic or musical intention several times according to the prompt, collects several forehead lamina hemodynamic parameters, and outputs a forehead lamina hemodynamic parameter sample S (k) 2 (b 1.. Bn).
In the embodiment of the invention, the formula for solving the hemodynamic signals in the brain-computer interface signals based on the independent component analysis and the least square method is as follows: s (k) = bl (k) + c, a1.. An and b1.. Bn denote the number of experiments, and the number of experiments is not particularly limited and is not limited.
As shown in fig. 5, as a preferred embodiment of the present invention, the step of matching the brain region image marked with the brain region name with the standard brain region image in the brain region parameter standard library specifically includes:
s5021, respectively calculating the hash values of the primary moving cortex image and the standard primary moving cortex image of the testee by using a hash method based on DCT to obtain h _1 and h _2;
s5022, respectively calculating hash values of the forehead leaf layer image and the standard forehead leaf layer image of the testee by using a hash method based on DCT to obtain h _3 and h _4;
s5023, calculating a Hamming distance dis _ h1 between h _1 and h _2, and calculating a Hamming distance dis _ h2 between h _1 and h _2;
s5024, calculating according to the Hamming distance dis _ h1 to obtain the similarity between the primary motion cortical image of the testee and the standard primary motion cortical image, calculating according to the Hamming distance dis _ h2 to obtain the similarity between the forehead lamina image of the testee and the standard forehead lamina image, wherein the similarity is a matching value.
In the embodiment of the invention, a DCT-based hash method is used for identifying a picture as an AI picture identification method in the prior art, the DCT-based hash method uses discrete cosine transform to extract low-frequency components of the picture, the picture is firstly converted into a gray-scale image with standard size, then DCT transformation is carried out on the gray-scale image, a 64-bit hash value is extracted from a coefficient matrix to serve as a fingerprint, then a Hamming distance dis _ h between h _1 and h _2 is calculated, and the similarity between a primary moving cortex image of a testee and a standard primary moving cortex image and the similarity between a forehead leaf image of the testee and the standard forehead leaf image are calculated according to the Hamming distance dis _ h, and the method for calculating the similarity between the two pictures is the prior art and is not described in detail herein.
As shown in fig. 6, as a preferred embodiment of the present invention, the step of matching the labeled sample of the hemodynamic parameters of the brain region with the standard hemodynamic parameters of the brain region specifically includes:
s601, comparing a primary motor cortex hemodynamic change signal sample S (k) 1 (a 1-a 2) and a forehead lobe layer hemodynamic change signal sample S (k) 2 (b 1-b 2) with a brain hemodynamic change signal standard value respectively by using a Tanimoto coefficient, and outputting comparison values T1 and T2;
s602, outputting information of good brain area state when T1 and T2 are close to 1;
and S603, outputting information of poor brain area state when T1 and T2 are close to 0.
In the embodiment of the present invention, the Tanimoto coefficient is used as an algorithm for calculating the similarity between two sets of data, when several sets of measurement results in the sample s (k) 1 (a 1-a 2) of the hemodynamic change signal of the primary motor cortex are compared with the labeled value of the hemodynamic change signal of the primary motor cortex, the similarity is close to 1, which indicates that the health state of the primary motor cortex is good, and the similarity is close to 0, which indicates that the health state of the primary motor cortex is poor, and the same applies to the frontal lobe layer.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of steps in various embodiments may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed alternately or alternatingly with other steps or at least a portion of sub-steps or stages of other steps.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a non-volatile computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the program is executed. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice in the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (9)
1. A brain-computer interface experimental method based on functional near infrared is characterized by comprising the following steps:
a brain-computer interface system is adopted to connect the scalp surface of the testee, and the testee completes imagination tasks according to prompts;
acquiring a brain hemodynamic parameter sample and a brain picture of a subject collected by a brain-computer interface system, wherein the brain picture corresponding to the brain hemodynamic parameter sample of the subject is marked with a serial number;
calling a corresponding brain picture template and a corresponding brain hemodynamic parameter template according to the serial numbers, wherein the brain picture template and the brain hemodynamic parameter template are provided with one or more information frames, and each information frame corresponds to a brain area name;
covering the brain picture template and the brain hemodynamic parameter template above the brain picture and the brain hemodynamic parameter sample of the subject to obtain one or more brain area pictures and brain area hemodynamic parameter samples, wherein each brain area picture and brain area hemodynamic parameter sample is marked with a brain area name;
inputting the brain area picture into a corresponding brain area picture standard library for matching according to the marked brain area name, and outputting a matched standard brain area picture and standard brain area hemodynamic parameters;
matching the marked brain region hemodynamic parameter sample with the standard brain region hemodynamic parameter, and outputting brain region status bar information;
and summarizing the information of the one or more brain area status bars to generate experimental result information.
2. The brain-computer interface experimental method based on functional near infrared as claimed in claim 1, wherein the step of connecting the scalp surface of the subject with the brain-computer interface system specifically comprises:
the near-infrared detector and the CT equipment are adopted to be close to the scalp surface of the head of the testee and are respectively used for collecting brain hemodynamic parameter samples and brain pictures.
3. The brain-computer interface experimental method based on functional near infrared according to claim 2, wherein the step of obtaining the sample of the hemodynamic parameter of the brain of the subject collected by the brain-computer interface system specifically comprises:
the testee completes the imagination task according to the prompt, and the near-infrared detector is used for collecting brain hemodynamic signals;
calculating the brain hemodynamic parameters of the testee by using a near-infrared brain-computer interface signal detection method based on independent component analysis and a least square method;
the method comprises the following steps that a testee completes an imagination task for a plurality of times according to prompts, a near-infrared detector collects a plurality of brain hemodynamic signals, and a signal detection method of a near-infrared brain-computer interface based on independent component analysis and least square method is used for calculating a plurality of brain hemodynamic parameters of the testee;
summarizing the plurality of brain hemodynamic parameters to generate a brain hemodynamic parameter sample of the tested person.
4. The brain-computer interface experimental method based on functional near infrared according to claim 3, wherein the step of calling the corresponding brain picture template and the corresponding brain hemodynamic parameter template according to the number specifically comprises:
inputting the number corresponding to the brain parameter sample of the testee into an information frame;
and outputting the corresponding brain picture template and the corresponding brain hemodynamic parameter template.
5. The brain-computer interface experimental method based on functional near infrared according to claim 4, wherein the step of inputting the brain area picture into the corresponding brain area picture standard library for matching according to the marked brain area name specifically comprises:
inputting the brain area pictures into corresponding brain area picture standard libraries for matching according to the marked brain area names, wherein each brain area name corresponds to one brain area picture standard library;
matching the brain area picture marked with the brain area name with a standard brain area picture in a brain area parameter standard library to obtain a plurality of matching values;
and outputting a standard brain area picture with the highest matching value, and outputting standard hemodynamic parameter sample information corresponding to the standard brain area picture.
6. The brain-computer interface experimental method based on functional near infrared as claimed in claim 2, wherein the near infrared detector is composed of a dual-wavelength light source L, a detector D1 and a detector D2, the dual-wavelength light source L emits near infrared light to be incident on the brain tissue to be detected, the detector D1 is used for detecting the hemodynamic signal of the primary motor cortex, and the detector D2 is used for detecting the hemodynamic signal of the frontal lobe layer.
7. The brain-computer interface experimental method based on functional near infrared according to claim 6, wherein the step of calculating and obtaining the brain hemodynamic parameter samples of the subject by using the signal detection method of the near infrared brain-computer interface based on the independent component analysis combined with the least square method comprises:
the tester completes the imagination task related to muscle action or muscle tension according to the prompt, the detector D1 collects the primary motor cortex hemodynamics change signals, and the primary motor cortex hemodynamics parameters s (k) 1a1 are respectively calculated by using a signal detection method of a near-infrared brain-computer interface based on an independent component analysis combined with a least square method;
a testee completes an imagination task related to mental calculation or musical intention according to a prompt, a detector D2 collects a primary motor cortex hemodynamic change signal, and forehead lobe layer hemodynamic parameters s (k) 2b1 are respectively calculated by using a signal detection method of a near-infrared brain-computer interface based on independent component analysis and least square method;
a human subject completes an imagination task related to muscle action or muscle tension for a plurality of times according to prompts, a plurality of primary motor cortex hemodynamic parameters are summarized, and a human subject primary motor cortex hemodynamic parameter sample s (k) 1 (a 1.. An) is output;
the testee completes imagination tasks related to mental arithmetic or musical intention for a plurality of times according to prompts, summarizes a plurality of forehead lobe layer hemodynamic parameters, and outputs forehead lobe layer hemodynamic parameter samples s (k) 2 (b 1.
8. The brain-computer interface experimental method based on functional near infrared according to claim 7, wherein the step of matching the brain region picture marked with the brain region name with the standard brain region picture in the brain region parameter standard library specifically comprises:
respectively calculating the hash values of the primary moving cortex image of the testee and the standard primary moving cortex image by using a hash method based on DCT to obtain h _1 and h _2;
respectively calculating the hash values of the forehead leaf layer image and the standard forehead leaf layer image of the tested person by using a hash method based on DCT to obtain h _3 and h _4;
calculating a Hamming distance dis _ h1 between h _1 and h _2, and calculating a Hamming distance dis _ h2 between h _1 and h _2;
and calculating according to the Hamming distance dis _ h1 to obtain the similarity between the primary motion cortical image of the testee and the standard primary motion cortical image, calculating according to the Hamming distance dis _ h2 to obtain the similarity between the forehead leaf level image of the testee and the standard forehead leaf level image, wherein the similarity is a matching value.
9. The brain-computer interface experimental method based on functional near infrared according to claim 8, wherein the step of matching the labeled brain region hemodynamic parameter sample with the standard brain region hemodynamic parameter specifically comprises:
comparing the primary motor cortex hemodynamic change signal sample s (k) 1 (a 1-a 2) and the forehead lobe layer hemodynamic change signal sample s (k) 2 (b 1-b 2) with the brain hemodynamic change signal standard value respectively by using Tanimoto coefficients, and outputting comparison values T1 and T2;
when T1 and T2 are close to 1, outputting information of good state of the brain area;
when T1 and T2 are close to 0, information of poor brain region state is output.
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