Auditory auxiliary evaluation method based on brain-computer interface

Abstract

The invention discloses an auditory auxiliary evaluation method based on a brain-computer interface, and relates to the technical field of brain-computer interfaces, and the method comprises the steps: collecting sound information, adjusting the stimulation information of different sounds in real time through a change function, obtaining the actual receiving state information of the brain-computer interface, and obtaining the receiving gap information; the method comprises the steps of obtaining evaluation values of a brain-computer interface aiming at different sound stimulation information, judging the human body sound receiving degree, dividing stage grades for a method for reducing differences, and analyzing a method for improving the human body sound receiving degree, and has the advantages that the content of a sound stimulation scheme can be randomly replaced by changing functions; therefore, the content sequence and time of each experiment are different, the effect of the user in the sound stimulation scheme experiment is improved, the human body sound receiving degrees of different users can be calculated, then the optimal solution is retrieved according to the human body sound receiving degrees of different users, and the user experience is improved. And the user can better receive the sound information through the brain-computer interface.

Description

Technical Field

[0001] The present invention relates to the technical field of brain-computer interface, and in particular to a method for auditory-assisted evaluation based on a brain-computer interface. Background Art

[0002] Brain-computer interface refers to a direct connection between the human or animal brain and external devices to achieve information exchange between the brain and the device. This concept has actually been around for a long time, but it was not until the 1990s that phased results began to emerge. Brain-computer interface technology is a revolutionary human-computer interaction technology. Its mechanism of action is to bypass peripheral nerves and muscles and directly establish a new communication and control channel between the brain and external devices.

[0003] The common brain-computer interface auditory assistance evaluation method cannot effectively randomly shuffle the experimental content when evaluating the brain-computer interface auditory assistance function, and it is inconvenient to calculate the user's human sound reception degree, and it will not recommend methods to improve human sound reception degree to users. For this reason, we propose a brain-computer interface based auditory assistance evaluation method. Summary of the invention

[0004] The purpose of the present invention is to provide a method for auditory assisted evaluation based on brain-computer interface.

[0005] In order to solve the problems raised in the above background technology, the present invention provides the following technical solution: a method for evaluating auditory assistance based on a brain-computer interface, comprising the following steps:

[0006] Step 1: Collect sound information and extract sound factors that can be received by the brain-computer interface;

[0007] Step 2: formulate a sound stimulation scheme according to the extracted sound factors, formulate a change function for the sound stimulation scheme, use the change function to adjust the stimulation information of different sounds in real time, and record the adjusted sound stimulation scheme information;

[0008] Step 3: Collect the sound stimulation scheme information received by the brain-computer interface to obtain the actual receiving state information of the brain-computer interface;

[0009] Step 4: Analyze the machine reasons that cause the deviation of the sound stimulation scheme information received by the brain-computer interface, obtain the ideal receiving state information of the brain-computer interface, determine the gap between the actual receiving state information and the sound stimulation scheme information, and obtain the receiving gap information;

[0010] Step 5: Evaluate the auditory auxiliary function of the brain-computer interface based on the obtained reception gap information, so as to obtain the evaluation value of the brain-computer interface for different sound stimulation information;

[0011] Step 6: Analyze the effect of the human body receiving the sound stimulation scheme information according to the actual receiving state information and the ideal receiving state information, and determine the human body's sound reception degree;

[0012] Step 7: Collect the differences between the adaptability of different types of brain-computer interfaces and the human body, record the methods to reduce the differences, and divide the methods to reduce the differences into stages;

[0013] Step 8. Analyze the method of improving human sound reception based on the previous method of reducing the difference between the brain-computer interface and any fitness, and show the analyzed method to the user.

[0014] As a further solution of the present invention: in the step one, after collecting the sound information, it is necessary to retrieve the model of the current brain-computer interface, and analyze the types of sounds that the current brain-computer interface can receive based on the information of the current brain-computer interface. At this time, sound factor information is extracted from the sound information based on the types of sounds that the current brain-computer interface can receive, and a brain-computer model database is established at the same time, and the sound factor information that can be received by brain-computer interfaces of different models is recorded in the corresponding brain-computer model database.

[0015] As a further solution of the present invention: in the step 2, the change function will formulate each sound factor information in the sound stimulation scheme into an information card, and at the same time formulate the corresponding stimulation time period according to the number of sound factors in the sound stimulation scheme, and then formulate the stimulation time period information into a time card again, and then shuffle the formulated information cards and time cards respectively according to the shuffling method, and then match the shuffled information cards and time cards in sequence to obtain the adjusted sound stimulation scheme information, and then use the adjusted sound stimulation scheme information to perform sound stimulation on the user.

[0016] As a further solution of the present invention: in the step three, when collecting the sound stimulation scheme information received by the user's brain-computer interface, the user's EEG signals are synchronously collected, and then the collected EEG signals are preprocessed to remove irrelevant interference and noise, and then the sound stimulation scheme is feature extracted according to the sound factors, and the relevant sound stimulation scheme information is extracted from the EEG signals based on the extracted features. At this time, the sound stimulation scheme information actually received by the user is analyzed in combination with the sound stimulation scheme information received by the user's brain-computer interface.

[0017] As a further solution of the present invention: in the step four, after obtaining the machine reason that causes the deviation in the sound stimulation scheme information received by the brain-computer interface, the influence ratio of the machine reason on the sound stimulation scheme received by the brain-computer interface will be analyzed, and the sound stimulation scheme information received by the brain-computer interface under the ideal state will be analyzed according to the influence ratio. At this time, the ideal receiving state information can be obtained, and then the actual receiving state information is compared with the ideal receiving state information to obtain the gap between the actual receiving state information and the ideal receiving state information, thereby obtaining the receiving gap information.

[0018] As a further solution of the present invention: in the step five, when evaluating the auditory assistive function of the brain-computer interface, the actual receiving state information and the ideal receiving state information can be converted into numerical values, and then the difference between the actual receiving state information numerical value and the ideal receiving state information numerical value is calculated. At this time, the auditory assistive function of the brain-computer interface is evaluated according to the calculated numerical ratio. At the same time, when evaluating the auditory assistive function of the brain-computer interface, behavioral test information can also be added, and then the user is asked to complete a series of hearing-related tasks while using the brain-computer interface hearing device, and then the accuracy and reaction time of the user in completing the task are recorded, so that the auditory assistive function of the brain-computer interface can be comprehensively evaluated.

[0019] As a further solution of the present invention: in the step six, when analyzing the effect of the sound stimulation scheme information received by the human body, a calculation model can be added to improve the efficiency of the calculation of the human body's sound reception degree. When establishing the calculation model, it is necessary to consider the human body's perception accuracy, reaction time measurement, EEG analysis, subjective evaluation, behavioral performance analysis and information compared with normal hearing. At the same time, the user can input known information into the calculation model, and the user's unknown information that affects the human body's reception of the sound stimulation scheme can be filled in by the calculation model. The unknown information filled in by the calculation model is the average impact parameter calculated by the calculation model after obtaining the previous human body reception sound stimulation scheme information.

[0020] As a further solution of the present invention: in the step seven, when recording the method of reducing the difference, the difference between the brain-computer interface and the human body's fitness can be divided into stage levels, and a difference stage-by-stage reduction clip can be established at the same time, and the reduction method of each stage level can be recorded in the corresponding stage-by-stage reduction clip, and then the difference features in the difference between the brain-computer interface and the human body's fitness can be extracted, and the difference features can be recorded in the stage-by-stage reduction clip.

[0021] As a further solution of the present invention: in step eight, when analyzing the method of improving the human body's sound receptivity, it is necessary to first obtain the information on the human body's sound receptivity, and then analyze the receptivity value in the human body's sound receptivity information, analyze the stage level of the human body's sound receptivity information according to the human body's sound receptivity value, and then extract the method of reducing the difference in adaptability between the brain-computer interface and the human body recorded in the corresponding stage level.

[0022] By adopting the above technical solution, compared with the prior art, the beneficial effects of the present invention are:

[0023] 1. The present invention can randomly change the content of the sound stimulation program by changing the setting of the function when the user conducts an experiment on the sound stimulation program information, so that the content sequence and time of each experiment are different, preventing the user from summarizing the sequence of the sound stimulation program content, thereby improving the effect of the user's sound stimulation program experiment, and can calculate the human body sound reception degree of different users. At this time, the best solution can be retrieved according to the human body sound reception degree of different users, so that the user can better receive sound information through the brain-computer interface;

[0024] 2. The present invention establishes a brain-computer interface database. When a user uses the brain-computer interface, the sound factor information that the brain-computer interface can receive can be retrieved more quickly, thereby improving the retrieval efficiency. The relevant sound stimulation scheme information can be extracted from the EEG signal according to the extracted features. In this way, the sound stimulation scheme information can be extracted from the EEG signal more accurately, thereby better obtaining the sound stimulation scheme information actually received by the user;

[0025] 3. The present invention analyzes the ideal reception state information, so as to eliminate the influence of machine reasons on the user's reception of sound stimulation program information, so as to better judge the user's human sound reception degree through different brain-computer interfaces, and record the establishment of the calculation model. When the user has a lot of unknown information that affects the human body's reception of the sound stimulation program, the user's human sound reception degree can still be calculated more accurately, so as to better judge the method of improving the user's human sound reception degree. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 Schematic diagram of the method steps in an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The specific embodiments of the present invention will be further described below in conjunction with the accompanying drawings. It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention.

[0028] In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0029] Please see attached Figure 1 The present invention is based on a brain-computer interface auditory assisted evaluation method, comprising the following steps:

[0030] Step 1: Collect sound information and extract sound factors that can be received by the brain-computer interface;

[0031] Step 2: formulate a sound stimulation scheme according to the extracted sound factors, formulate a change function for the sound stimulation scheme, use the change function to adjust the stimulation information of different sounds in real time, and record the adjusted sound stimulation scheme information;

[0032] Step 3: Collect the sound stimulation scheme information received by the brain-computer interface to obtain the actual receiving state information of the brain-computer interface;

[0033] Step 4: Analyze the machine reasons that cause the deviation of the sound stimulation scheme information received by the brain-computer interface, obtain the ideal receiving state information of the brain-computer interface, determine the gap between the actual receiving state information and the sound stimulation scheme information, and obtain the receiving gap information;

[0034] Step 5: Evaluate the auditory auxiliary function of the brain-computer interface based on the obtained reception gap information, so as to obtain the evaluation value of the brain-computer interface for different sound stimulation information;

[0035] Step 6: Analyze the effect of the human body receiving the sound stimulation scheme information according to the actual receiving state information and the ideal receiving state information, and determine the human body's sound reception degree;

[0036] Step 7: Collect the differences between the adaptability of different types of brain-computer interfaces and the human body, record the methods to reduce the differences, and divide the methods to reduce the differences into stages;

[0037] Step 8. Analyze the method of improving human sound reception based on the previous method of reducing the difference between the brain-computer interface and any fitness, and show the analyzed method to the user.

[0038] In one embodiment of the present invention: in step one, after collecting sound information, it is necessary to retrieve the model of the current brain-computer interface, analyze the types of sounds that the current brain-computer interface can receive based on the information of the current brain-computer interface, then extract sound factor information from the sound information based on the types of sounds that the current brain-computer interface can receive, and establish a brain-computer model database at the same time, and record the sound factor information that different models of brain-computer interfaces can receive in the corresponding brain-computer model database.

[0039] In one embodiment of the present invention: in step two, the change function will formulate each sound factor information in the sound stimulation scheme into an information card, and at the same time formulate the corresponding stimulation time period according to the number of sound factors in the sound stimulation scheme, and then formulate the stimulation time period information into a time card again, and then shuffle the formulated information cards and time cards respectively according to the shuffling method, and then match the shuffled information cards and time cards in sequence to obtain the adjusted sound stimulation scheme information, and then use the adjusted sound stimulation scheme information to perform sound stimulation on the user.

[0040] In one embodiment of the present invention: in step three, when collecting the sound stimulation scheme information received by the user's brain-computer interface, the user's EEG signals are synchronously collected, and then the collected EEG signals are preprocessed to remove irrelevant interference and noise, and then the sound stimulation scheme is feature extracted according to the sound factors, and the relevant sound stimulation scheme information is extracted from the EEG signals based on the extracted features. At this time, the sound stimulation scheme information actually received by the user is analyzed in combination with the sound stimulation scheme information received by the user's brain-computer interface.

[0041] In one embodiment of the present invention: in step four, after obtaining the machine reason that causes the deviation in the sound stimulation scheme information received by the brain-computer interface, the influence ratio of the machine reason on the sound stimulation scheme received by the brain-computer interface will be analyzed, and the sound stimulation scheme information received by the brain-computer interface under ideal conditions will be analyzed according to the influence ratio. At this time, the ideal receiving state information can be obtained, and then the actual receiving state information is compared with the ideal receiving state information to obtain the gap between the actual receiving state information and the ideal receiving state information, thereby obtaining the receiving gap information.

[0042] In one embodiment of the present invention: In step five, when evaluating the auditory assistive function of the brain-computer interface, the actual receiving state information and the ideal receiving state information can be converted into numerical values, and then the difference between the actual receiving state information numerical value and the ideal receiving state information numerical value is calculated. At this time, the auditory assistive function of the brain-computer interface is evaluated according to the calculated numerical ratio. At the same time, when evaluating the auditory assistive function of the brain-computer interface, behavioral test information can also be added, and then the user is asked to complete a series of hearing-related tasks while using the brain-computer interface hearing device, and then the accuracy and reaction time of the user in completing the task are recorded, so that the auditory assistive function of the brain-computer interface can be comprehensively evaluated.

[0043] In one embodiment of the present invention: in step six, when analyzing the effect of the sound stimulation scheme information received by the human body, a calculation model can be added to improve the efficiency of the calculation of the human body's sound reception. When establishing the calculation model, it is necessary to consider the human body's perception accuracy, reaction time measurement, EEG analysis, subjective evaluation, behavioral performance analysis and information compared with normal hearing. At the same time, the user can input known information into the calculation model, and the user's unknown information that affects the human body's reception of the sound stimulation scheme can be filled in by the calculation model. The unknown information filled in by the calculation model is the average impact parameter calculated by the calculation model after obtaining the previous human body reception sound stimulation scheme information.

[0044] In one embodiment of the present invention: In step seven, when recording the method of reducing the difference, the difference between the brain-computer interface and the human body's fitness can be divided into stage levels, and a difference stage-by-stage reduction clip can be established at the same time, and the reduction method of each stage level can be recorded in the corresponding stage-by-stage reduction clip, and then the difference features in the difference between the brain-computer interface and the human body's fitness can be extracted, and the difference features can be recorded in the stage-by-stage reduction clip.

[0045] In one embodiment of the present invention: In step eight, when analyzing the method of improving human sound reception, it is necessary to first obtain the information on human sound reception, and then analyze the reception value in the human sound reception information, analyze the stage level of the human sound reception information according to the human sound reception value, and then extract the method of reducing the difference in adaptability between the brain-computer interface and the human body recorded in the corresponding stage level.

[0046] Example 1, please refer to the attached Figure 1 When the sound factor information is recorded in the corresponding brain-computer model database, the sound factor information can also be stored using data structures such as hash tables, B-trees, or B+, and the data can be partitioned. Then, the sound factor information can be partitioned and stored according to the frequency of use of different brain-computer interfaces. The use of data compression can further reduce the data space occupied by the sound factor information.

[0047] Example 2, please refer to the attached Figure 1 At the same time, when the information in the sound stimulation scheme is shuffled, a number can be randomly assigned to the information in each sound stimulation scheme, and then sorted according to the size of the random number. After the sorting, the sound stimulation scheme uses the hash mapping method to randomly map the information in the two sound stimulation schemes, and the two mapped information are exchanged, thereby improving the randomness of the information in the sound stimulation scheme.

[0048] Example 3, please refer to the attached Figure 1When evaluating the human body's sound reception, subjective evaluations such as the sound quality, sound clarity, and comfort level relative to the user receiving the sound stimulation scheme information when the user receives the sound stimulation information can also be added to the human body's sound reception evaluation. At this time, a comprehensive judgment can be made on the human body's sound reception.

[0049] Specifically, by changing the setting of the function, when the user conducts an experiment on the sound stimulation plan information, the content of the sound stimulation plan can be randomly changed, so that the content sequence and time of each experiment are different, preventing the user from summarizing the sequence of the sound stimulation plan content, thereby improving the effect of the user's sound stimulation plan experiment, and being able to calculate the human sound reception degree of different users. At this time, the best solution can be retrieved according to the human sound reception degree of different users, so that the user can better receive sound information through the brain-computer interface.

[0050] Specifically, through the establishment of a brain-computer interface database, when a user uses a brain-computer interface, the sound factor information that the brain-computer interface can receive can be retrieved more quickly, thereby improving the retrieval efficiency, and the relevant sound stimulation scheme information can be extracted from the EEG signal based on the extracted features. In this way, the sound stimulation scheme information can be extracted from the EEG signal more accurately, thereby better obtaining the sound stimulation scheme information actually received by the user.

[0051] Specifically, through the analysis of ideal reception state information, it is possible to eliminate the influence of machine reasons on the user's reception of sound stimulation plan information, so as to better judge the user's human sound reception through different brain-computer interfaces, and record the establishment of the calculation model. When the user has a lot of unknown information that affects the human body's reception of sound stimulation plans, the user's human sound reception can still be calculated more accurately, so as to better judge methods to improve the user's human sound reception.

[0052] Working principle:

[0053] Step 1: Collect sound information and extract sound factors that can be received by the brain-computer interface, and establish a brain-computer model database. Record the sound factor information that can be received by different models of brain-computer interfaces in the corresponding brain-computer model database, formulate a sound stimulation plan based on the extracted sound factors, and formulate a change function for the sound stimulation plan. Use the change function to adjust the stimulation information of different sounds in real time, and record the adjusted sound stimulation plan information;

[0054] Step 2: Collect the sound stimulation scheme information received by the brain-computer interface, and combine it with the electroencephalogram signal to obtain the actual receiving state information of the brain-computer interface, analyze the machine reasons that cause the deviation of the sound stimulation scheme information received by the brain-computer interface, analyze the influence ratio of the machine reasons on the sound stimulation scheme received by the brain-computer interface, obtain the ideal receiving state information of the brain-computer interface, judge the gap between the actual receiving state information and the sound stimulation scheme information, obtain the receiving gap information, evaluate the auditory auxiliary function of the brain-computer interface according to the obtained receiving gap information, and record the accuracy and reaction time of the user to complete the task, so as to comprehensively evaluate the auditory auxiliary function of the brain-computer interface;

[0055] Step three, analyze the effect of the human body receiving the sound stimulation scheme information according to the actual receiving state information and the ideal receiving state information, judge the human body's sound reception, and add a calculation model to improve the efficiency of the human body's sound reception calculation. The user can input known information into the calculation model, and the user's unknown information that affects the human body's reception of the sound stimulation scheme can be filled in by the calculation model. The difference between different types of brain-computer interfaces and human fitness in the past is collected, and the method of reducing the difference is recorded, and the method of reducing the difference is divided into stage levels. According to the previous method of reducing the difference between the brain-computer interface and any fitness, the method of improving the human body's sound reception is analyzed, and the analyzed method is displayed to the user. At this point, the entire workflow is completed.

[0056] At the same time, the present application uses specific words to describe the embodiments of the present application. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of the present application. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of the present application can be appropriately combined.

[0057] Some aspects of the present application may be performed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above hardware or software may be referred to as "data blocks", "modules", "engines", "units", "components" or "systems". The processor may be one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DAPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or combinations thereof. In addition, various aspects of the present application may be expressed as computer products located in one or more computer-readable media, which include computer-readable program codes. For example, computer-readable media may include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, tapes ...), optical disks (e.g., compact disks CDs, digital versatile disks DVDs ...), smart cards, and flash memory devices (e.g., cards, sticks, key drives ...).

[0058] A computer-readable medium may include a propagated data signal containing computer program code, such as in baseband or as part of a carrier wave. The propagated signal may have a variety of manifestations, including electromagnetic, optical, etc., or a suitable combination. A computer-readable medium may be any computer-readable medium other than a computer-readable storage medium, which may be connected to an instruction execution system, device or apparatus to communicate, propagate or transmit a program for use. The program code on the computer-readable medium may be propagated through any suitable medium, including radio, cable, fiber optic cable, radio frequency signal, or similar medium, or a combination of any of the above mediums.

[0059] Similarly, it should be noted that in order to simplify the description disclosed in this application, so as to help understand one or more embodiments of the invention, in the above description of the embodiments of the present application, sometimes multiple features are merged into one embodiment, drawings or descriptions thereof. However, this disclosure method does not mean that the features required by the object of the present application are more than the features mentioned in the claims. In fact, the features of the embodiment are less than all the features of the single embodiment disclosed above. In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "approximately", "approximately" or "substantially" in some examples. Unless otherwise specified, "approximately", "approximately" or "substantially" indicate that the number allows a variation of ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may change according to the characteristics required by individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining the digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of the present application are approximate values, in specific embodiments, such numerical settings are as accurate as possible within the feasible range.

[0060] Although the present invention is disclosed as above in terms of preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications without departing from the spirit and scope of the present invention. Therefore, any modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the scope of protection defined by the claims of the present invention.

Claims

1. A method for evaluating auditory assistance based on a brain-computer interface, characterized in that: The following steps are involved: Step 1: Collect sound information and extract sound factors that can be received by the brain-computer interface; Step 2: formulate a sound stimulation scheme according to the extracted sound factors, formulate a change function for the sound stimulation scheme, use the change function to adjust the stimulation information of different sounds in real time, and record the adjusted sound stimulation scheme information; Step 3: Collect the sound stimulation scheme information received by the brain-computer interface to obtain the actual receiving state information of the brain-computer interface; Step 4: Analyze the machine reasons that cause the deviation of the sound stimulation scheme information received by the brain-computer interface, obtain the ideal receiving state information of the brain-computer interface, determine the gap between the actual receiving state information and the sound stimulation scheme information, and obtain the receiving gap information; Step 5: Evaluate the auditory auxiliary function of the brain-computer interface based on the obtained reception gap information, so as to obtain the evaluation value of the brain-computer interface for different sound stimulation information; Step 6: Analyze the effect of the human body receiving the sound stimulation scheme information according to the actual receiving state information and the ideal receiving state information, and determine the human body's sound reception degree; Step 7: Collect the differences between the adaptability of different types of brain-computer interfaces and the human body, record the methods to reduce the differences, and divide the methods to reduce the differences into stages; Step 8. Analyze the method of improving human sound reception based on the previous method of reducing the difference between the brain-computer interface and any fitness, and show the analyzed method to the user.

2. The method for hearing-assisted assessment based on brain-computer interface according to claim 1, characterized in that: In the step one, after collecting the sound information, it is necessary to retrieve the model of the current brain-computer interface, and analyze the types of sounds that the current brain-computer interface can receive based on the information of the current brain-computer interface. At this time, sound factor information is extracted from the sound information based on the types of sounds that the current brain-computer interface can receive, and a brain-computer model database is established at the same time, and the sound factor information that can be received by brain-computer interfaces of different models is recorded in the corresponding brain-computer model database.

3. The method for hearing-assisted assessment based on brain-computer interface according to claim 1, characterized in that: In the step 2, the change function will formulate each sound factor information in the sound stimulation scheme into an information card, and formulate the corresponding stimulation time period according to the number of sound factors in the sound stimulation scheme, and then formulate the stimulation time period information into a time card again, and then shuffle the formulated information cards and time cards respectively according to the shuffling method, and then match the shuffled information cards and time cards in order to obtain the adjusted sound stimulation scheme information, and then use the adjusted sound stimulation scheme information to perform sound stimulation on the user.

4. The method for hearing-assisted assessment based on brain-computer interface according to claim 1, characterized in that: In the step three, when collecting the sound stimulation scheme information received by the user's brain-computer interface, the user's EEG signals are synchronously collected, and then the collected EEG signals are preprocessed to remove irrelevant interference and noise, and then the sound stimulation scheme is feature extracted according to the sound factors, and the relevant sound stimulation scheme information is extracted from the EEG signals based on the extracted features. At this time, the sound stimulation scheme information actually received by the user is analyzed in combination with the sound stimulation scheme information received by the user's brain-computer interface.

5. The method for hearing-assisted assessment based on brain-computer interface according to claim 1, characterized in that: In the step four, after obtaining the machine reason that causes the deviation in the sound stimulation scheme information received by the brain-computer interface, the influence ratio of the machine reason on the sound stimulation scheme received by the brain-computer interface will be analyzed, and the sound stimulation scheme information received by the brain-computer interface under the ideal state will be analyzed according to the influence ratio. At this time, the ideal receiving state information can be obtained, and then the actual receiving state information is compared with the ideal receiving state information to obtain the gap between the actual receiving state information and the ideal receiving state information, thereby obtaining the receiving gap information.

6. The method for hearing-assisted assessment based on brain-computer interface according to claim 1, characterized in that: In step five, when evaluating the auditory assistive function of the brain-computer interface, the actual receiving state information and the ideal receiving state information can be converted into numerical values, and then the difference between the actual receiving state information numerical value and the ideal receiving state information numerical value is calculated. At this time, the auditory assistive function of the brain-computer interface is evaluated according to the calculated numerical ratio. At the same time, when evaluating the auditory assistive function of the brain-computer interface, behavioral test information can also be added, and then the user is asked to complete a series of hearing-related tasks while using the brain-computer interface hearing device, and then the accuracy and reaction time of the user in completing the task are recorded, so that the auditory assistive function of the brain-computer interface can be comprehensively evaluated.

7. The method for hearing-assisted assessment based on brain-computer interface according to claim 1, characterized in that: In step six, when analyzing the effect of the sound stimulation scheme information received by the human body, a calculation model can be added to improve the efficiency of the calculation of the human body's sound reception. When establishing the calculation model, it is necessary to consider the human body's perception accuracy, reaction time measurement, EEG analysis, subjective evaluation, behavioral performance analysis and information compared with normal hearing. At the same time, the user can input known information into the calculation model, and the user's unknown information that affects the human body's reception of the sound stimulation scheme can be filled in by the calculation model. The unknown information filled in by the calculation model is the average impact parameter calculated by the calculation model after obtaining the previous human body reception sound stimulation scheme information.

8. The method for hearing-assisted assessment based on brain-computer interface according to claim 1, characterized in that: In step seven, when recording the method of reducing the difference, the difference between the brain-computer interface and the human body's fitness can be divided into stage levels, and a difference stage-by-stage reduction clip can be established. The reduction method of each stage level can be recorded in the corresponding stage-by-stage reduction clip, and then the difference features in the difference between the brain-computer interface and the human body's fitness can be extracted, and the difference features can be recorded in the stage-by-stage reduction clip.

9. The method for hearing-assisted assessment based on brain-computer interface according to claim 1, characterized in that: In step eight, when analyzing the method of improving the human body's sound reception, it is necessary to first obtain the information on the human body's sound reception, and then analyze the reception value in the human body's sound reception information, analyze the stage level of the human body's sound reception information according to the human body's sound reception value, and then extract the method of reducing the difference in adaptability between the brain-computer interface and the human body recorded in the corresponding stage level.

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