Comparison method and system for event-related potential signals

Abstract

The present invention provides a method and system for comparing event-related potential signals, wherein the method includes: obtaining two event-related potential signals to be compared; determining the sample type of the two related potential signals; wherein the sample type includes an independent sample or a paired sample; comparing the mean functions of the two related potential signals based on the sample type, and obtaining the corresponding comparison result; wherein, when the sample type of the two related potential signals is an independent sample, a first preset comparison method is used to compare the two related potential signals, and when the sample type of the two related potential signals is a paired sample, a second preset comparison method is used to compare the two related potential signals. The above invention can be used to conveniently and effectively complete the comparison of the mean functions of event-related potential signals.

Description

Technical Field

[0001] The present invention relates to the field of electronic information technology, and more specifically, to a method and system for comparing event-related potential signals. Background Art

[0002] Event-related potentials are a special type of EEG data, which refers to the EEG data recorded after a certain stimulus. Event-related potentials have been widely studied in psychology and neuroscience, and a large number of studies have shown that event-related potentials have a certain relationship with human diseases, cognitive levels and other physiological characteristics. To explore these relationships, a major data analysis method is to compare the mean values ​​of the event-related potentials of two samples.

[0003] At present, the mean comparison of two-sample event-related potentials refers to dividing all subjects into two groups according to certain standards (for example, diseased or not, what type of stimulation, etc.), and comparing the mean functions of specific components of event-related potentials (EEG data of a specific time period) measured in these two groups. However, since event-related potentials are essentially a type of functional data, it is difficult to directly compare the mean functions of this type of data under two samples.

[0004] The method adopted by existing research is generally to convert the event-related potential data of different subjects into scalars first, and then perform variance analysis modeling. The existing methods are mainly divided into three categories: averaging the event-related potentials over time and establishing variance analysis modeling; finding the maximum (minimum) value of the event-related potentials over time and establishing a variance analysis model; establishing a variance analysis model for the event-related potentials at each time point. Although the above methods can compress the infinite-dimensional event-related potential data into one dimension so that mean comparison can be carried out, it will inevitably cause the loss of data information, thereby reducing the efficacy of hypothesis testing. To this end, the study hopes to start from the structure of the event-related potentials themselves and directly compare their mean functions, so as to maximize the retention of data information and improve the efficacy of hypothesis testing.

[0005] The existing methods for directly comparing the mean functions of functional data are mainly based on the assumption that data errors are independent and identically distributed. Since EEG data will inevitably be affected by various artifacts during the measurement process, these artifacts are difficult to meet the assumption of independent and identically distributed, making it difficult to directly compare the mean functions of event-related potentials, or the comparison accuracy is poor, which is not conducive to the research and application of event-related potentials in psychology, neuroscience and other fields. Summary of the invention

[0006] In view of the above problems, the purpose of the present invention is to provide a method and system for comparing event-related potential signals to solve the problems that the existing event-related potential signals are difficult to satisfy the independent synchronous distribution assumption during the comparison process, resulting in poor comparison accuracy and difficulty in implementation.

[0007] The event-related potential signal comparison method provided by the present invention includes: obtaining two event-related potential signals to be compared; determining the sample type of the two related potential signals; wherein the sample type includes an independent sample or a paired sample; comparing the mean functions of the two related potential signals based on the sample type, and obtaining the corresponding comparison result; wherein, when the sample type of the two related potential signals is an independent sample, the two related potential signals are compared using a first preset comparison method, and when the sample type of the two related potential signals is a paired sample, the two related potential signals are compared using a second preset comparison method.

[0008] In addition, an optional technical solution is that the first preset comparison method includes: projecting the two related potential signals onto the function space spanned by the B-spline function respectively, determining the first true trajectory estimation value and the second true trajectory estimation value corresponding to the two groups of samples respectively; determining the corresponding first mean function based on the first true trajectory estimation value, and determining the corresponding second mean function based on the second true trajectory estimation value; determining the first covariance function of the first sample based on the first true trajectory estimation value and the first mean function, and determining the second covariance function of the second sample based on the second true trajectory estimation value and the second mean function; wherein the samples of the two related potential signals are the first sample and the second sample respectively; constructing the corresponding test statistic based on the first mean function, the second mean function, the first covariance function and the second covariance function, and determining the P value of the test statistic.

[0009] In addition, an optional technical solution is that the second preset comparison method includes: obtaining paired difference data of two related potential signals; projecting the paired difference data to the function space spanned by the B-spline function to obtain the true trajectory estimate corresponding to the paired difference data; determining the mean function of the paired difference data based on the true trajectory estimate; determining the covariance function of the paired difference data based on the true trajectory estimate and the mean function; constructing a corresponding test statistic based on the mean function and the covariance function, and determining the P value of the test statistic.

[0010] In addition, an optional technical solution is to determine the comparison result based on the P value of the test statistic.

[0011] In addition, an optional technical solution is that the expression formula of the event-related potential signal is as follows:

[0012]

[0013] Where d represents the sample group number of the relevant potential signal, N represents the number of measurements of the dth group of samples, and m d (·) represents the mean function of the dth group of samples, ξ di (·) is the random trajectory represented by the ith sample in the dth group, j represents the jth measurement of the ith sample, ∈ dij This indicates measurement error.

[0014] In addition, an optional technical solution is that, in the first preset comparison method, the expression formula of the first true trajectory estimation value or the second true trajectory estimation value is as follows:

[0015]

[0016] in, N represents the number of measurements of the d-th group of samples, r represents the order of the B-spline function, K represents the number of internal nodes corresponding to the B-spline function, B(·) is the vector composed of all K+r B-spline functions, Yi represents the vector spanned by all the data of the i-th sample, and Y i =[Y i1 ,……,Y iN ] T .

[0017] In addition, an optional technical solution is that, in the first preset comparison method, the expression formula of the first covariance function or the second covariance function is as follows:

[0018]

[0019] Where d represents the sample group number of the relevant potential signal, t1,t2∈[0,1], represents the mean function corresponding to the d group of samples, n d represents the number of subjects in the sample of group d, Represents the true trajectory estimate of the i-th sample in the d group of samples.

[0020] In addition, an optional technical solution is that the constructed test statistic is expressed as follows:

[0021]

[0022] The original hypothesis is H0: m1(t) = m2(t), t∈Λ, Λ represents the range of values ​​of the first mean function and the second mean function, n1 represents the number of subjects in the first sample, and n2 represents the number of subjects in the second sample. represents the first mean function, represents the second mean function, represents the first covariance function, represents the second covariance function.

[0023] In addition, an optional technical solution is that the expression formula of the P value of the test statistic is as follows:

[0024]

[0025] Among them, M represents the number of samplings performed by Gauss ζ, and the sample obtained in each sampling is ζ w , w=1,…,M,T represents the test statistic, Gaussian satisfies the mean of 0 and the covariance of represents the first covariance function, Represents the second covariance function, n1 represents the number of subjects in the first sample, and n2 represents the number of subjects in the second sample.

[0026] According to another aspect of the present invention, a system for comparing event-related potential signals is provided, comprising: an event-related potential signal acquisition unit, used to acquire two event-related potential signals to be compared; a sample type judgment unit, used to judge the sample type of the two related potential signals; wherein the sample type includes an independent sample or a paired sample; a comparison result acquisition unit, used to compare the mean functions of the two related potential signals based on the sample type, and acquire the corresponding comparison result; wherein, when the sample type of the two related potential signals is an independent sample, the comparison result acquisition unit adopts a first preset comparison method to compare the two related potential signals; when the sample type of the two related potential signals is a paired sample, the comparison result acquisition unit adopts a second preset comparison method to compare the two related potential signals.

[0027] By utilizing the above-mentioned event-related potential signal comparison method and system, it is possible to obtain the asymptotic distribution of the test statistic based on the functional structure of the event-related potential itself, and to use the theory of functional data to directly perform hypothesis testing on the event-related potential data without losing data information, and to simultaneously compare multiple components of the event-related potential.

[0028] In order to achieve the above and related purposes, one or more aspects of the present invention include the features that will be described in detail later. The following description and the accompanying drawings describe some exemplary aspects of the present invention in detail. However, these aspects indicate only some of the various ways in which the principles of the present invention can be used. In addition, the present invention is intended to include all these aspects and their equivalents. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] By referring to the following description in conjunction with the accompanying drawings, and with a more comprehensive understanding of the present invention, other objects and results of the present invention will become more apparent and easy to understand. In the accompanying drawings:

[0030] Figure 1 is a flow chart of a method for comparing event-related potential signals according to an embodiment of the present invention;

[0031] Figure 2 4 is a block diagram of a system for comparing event-related potential signals according to an embodiment of the present invention.

[0032] The same reference numerals throughout the drawings indicate similar or corresponding features or functions. DETAILED DESCRIPTION

[0033] In the following description, for the purpose of illustration, in order to provide a comprehensive understanding of one or more embodiments, many specific details are set forth. However, it is apparent that these embodiments may also be implemented without these specific details. In other examples, for ease of describing one or more embodiments, known structures and devices are shown in the form of block diagrams.

[0034] To describe the event-related potential signal comparison method and system of the present invention in detail, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0035] Figure 1 The flowchart of the method for comparing event-related potential signals according to an embodiment of the present invention is shown.

[0036] like Figure 1 As shown, the event-related potential signal comparison method of the embodiment of the present invention mainly includes:

[0037] S100: Acquire two event-related potential signals to be compared.

[0038] Among them, the jth measurement of the event-related potential signal of the i-th subject in the d-th group of samples can be recorded as Y dij , for Y dij The expression formula of the event-related potential signal after the model is established is as follows:

[0039]

[0040] Where d represents the sample group number of the relevant potential signal. When two groups of samples are compared, d = 1 or 2, N represents the number of measurements of the dth group of samples, and m d (·) represents the mean function of the dth group of samples, ξ di (·) is the random trajectory represented by the ith sample in the dth group, j represents the jth measurement of the ith sample, ∈ dij This indicates measurement error.

[0041] In the process of processing two groups of samples, the number of subjects in the two groups of samples can be recorded as n1 and n2. The present invention performs a hypothesis test on the mean functions m1(·) and m2(·) of the two groups of samples to check whether they are equal. In mathematical language, it can be expressed as: the original hypothesis H0: m1(t) = m2(t), t∈Λ., the alternative hypothesis H1: m1(t)≠m2(t), Among them, Λ represents the range of values ​​of interest for whether the mean functions of two samples are equal. Our goal is to construct a statistic for this hypothesis test problem and determine the probability of rejecting the null hypothesis based on the statistic.

[0042] S200: Determine the sample type of two related potential signals; wherein the sample type includes an independent sample or a paired sample.

[0043] Among them, there are two situations in the comparison process of the event-related potential signals of the two groups of samples. Based on the sample type, they can be divided into independent samples and paired samples. That is, in the comparison process, we must first determine the sample type of the two related potential signals, and then perform corresponding comparison operations based on the sample type.

[0044] Specifically, independent samples mainly refer to the fact that the artifacts in the two groups are independent of each other. For example, the division of groups is based on gender, and the subjects in different groups will not affect each other. Paired samples mainly refer to the fact that the event-related potentials of the two groups of samples are not independent, but come from the same group of subjects. For example, the event-related potentials generated by the same group of subjects given two different groups of stimuli.

[0045] S300: Compare the mean functions of two related potential signals based on the sample type and obtain the corresponding comparison results; wherein, when the sample types of the two related potential signals are independent samples, the two related potential signals are compared using a first preset comparison method, and when the sample types of the two related potential signals are paired samples, the two related potential signals are compared using a second preset comparison method.

[0046] When the sample types of the two related potential signals are independent samples, the process of using the first preset comparison method to compare the two related potential signals includes:

[0047] S310: Projecting the two related potential signals to the function space spanned by the B-spline function respectively, and determining the first true trajectory estimation value and the second true trajectory estimation value corresponding to the two groups of samples respectively.

[0048] Specifically, the expression formula of the first true trajectory estimation value and the second true trajectory estimation value is the same, as shown below:

[0049]

[0050] in, N represents the number of measurements of the d-th group of samples, r represents the order of the B-spline function, K represents the number of internal nodes corresponding to the B-spline function, B(·) is the vector composed of all K+r B-spline functions, Yi represents the vector spanned by all the data of the i-th sample, and Y i =[Y i1 ,……,Y iN ] T .

[0051] Where r is the order of the selected B-spline function, K is the number of internal nodes corresponding to the B-spline function, and the present invention adopts the equidistant node segmentation method to obtain K+r spline functions in the interval [0, 1], denoted as {B l,r (·), 1≤l≤K+r}. Let B(·) be the vector composed of all K+r B-spline functions, that is, B(·)=[B 1,r (·),B 2,r (·),……,B K+r,r (·)] T , where T represents the matrix transpose, and the matrix can be further defined Based on the least squares estimation, the true trajectory estimate or the true rule spline function approximation for each sample is where Y i is the vector of all data of the i-th sample, that is, Y i =[Y i1 ,……,Y iN ] T .

[0052] S320: Determine a corresponding first mean function based on the first true trajectory estimation value, and determine a corresponding second mean function based on the second true trajectory estimation value.

[0053] Among them, the expression formula of the first mean function or the second mean function is:

[0054]

[0055] Where d represents the sample group number of the relevant potential signal. When two groups of samples are compared, d can take the value of 1 or 2. represents the true trajectory estimate corresponding to the mean function, n d Represents the number of subjects in the sample group d.

[0056] S330: Determine a first covariance function of a first sample based on a first true trajectory estimate and a first mean function, and determine a second covariance function of a second sample based on a second true trajectory estimate and a second mean function; wherein the samples of the two correlated potential signals are the first sample and the second sample, respectively.

[0057] The expression formula of the first covariance function or the second covariance function is as follows:

[0058]

[0059] Where d represents the sample group number of the relevant potential signal, t1,t2∈[0,1], represents the mean function corresponding to the d group of samples, n d represents the number of subjects in the sample of group d, Represents the true trajectory estimate of the i-th sample in the d group of samples.

[0060] S340: constructing a corresponding test statistic based on the first mean function, the second mean function, the first covariance function, and the second covariance function, and determining a P value of the test statistic.

[0061] Among them, the expression formula of the constructed test statistic is as follows:

[0062]

[0063] The original hypothesis is H0: m1(t) = m2(t), t∈Λ, Λ represents the range of values ​​of the first mean function and the second mean function, n1 represents the number of subjects in the first sample, and n2 represents the number of subjects in the second sample. represents the first mean function, represents the second mean function, represents the first covariance function, represents the second covariance function.

[0064] Furthermore, the expression formula of the P value of the test statistic is as follows:

[0065]

[0066] Among them, M represents the number of samplings performed by Gauss ζ, and the sample obtained in each sampling is ζ w , w=1,…,M,T represents the test statistic, Gaussian satisfies the mean of 0 and the covariance of represents the first covariance function, Represents the second covariance function, n1 represents the number of subjects in the first sample, and n2 represents the number of subjects in the second sample.

[0067] It should be noted that, since the distribution of the constructed test statistic T is related to a Gaussian process, it is necessary to sample the Gaussian process and obtain its empirical quantile. In the present invention, the sampled Gaussian process is denoted as ζ, which satisfies the mean of 0 and the covariance of Then, the P value of the hypothesis test can be obtained, and the final comparison result can be determined based on the P value.

[0068] In another specific embodiment of the present invention, when the sample types of the two related potential signals are paired samples, the process of using the second preset comparison method to compare the two related potential signals includes:

[0069] S350: Acquire paired difference data of two related potential signals.

[0070] Among them, for paired samples, n1=n2=n, that is, the number of subjects in the sample is the same. For the i-th subject, the data Y of the event-related potential signal in the first sample is 1i (·) and the event-related potential signal data Y in the second group 2i (·) is subtracted to obtain the difference data of paired samples. The expression formula is as follows:

[0071] D i (·)=Y 1i (·)-Y 2i (·),1≤i≤n

[0072] S360: Projecting the paired difference data to the function space spanned by the B-spline function to obtain a true trajectory estimation value corresponding to the paired difference data.

[0073] S370: Determine a mean function of the paired difference data based on the true trajectory estimate.

[0074] Among them, the paired difference (or difference data, the same below) of the i-th sample is D i (·), project it to the function space spanned by the B-spline function, and obtain its true trajectory estimate Then according to We can further obtain the estimated value of the mean function of the paired difference The calculation formula of the true trajectory estimation value may refer to the acquisition method in the first preset comparison method, and will not be described in detail here.

[0075] S380: Determine the covariance function of the paired difference data based on the true trajectory estimate and the mean function.

[0076] Among them, the true trajectory estimate obtained in the previous step and mean function The covariance function of the paired difference G(t1,t2), t1,t2∈[0,1] can be estimated. The corresponding covariance function is expressed as follows:

[0077]

[0078] Where n represents the number of subjects in the two groups of samples. represents the mean function in the first sample, represents the mean function in the second sample, t1,t2∈[0,1], represents the true trajectory estimate of the i-th sample in the first sample, represents the true trajectory estimate of the i-th sample in the second sample.

[0079] S390: Based on the mean function and the covariance function, construct a corresponding test statistic, and determine the P value of the test statistic.

[0080] The expression formula of the constructed test statistic is as follows:

[0081]

[0082] Among them, Λ represents the value range of the mean function, represents the mean function when t1=t2, Represents the covariance function when t1=t2.

[0083] Furthermore, the expression formula of the P value of the test statistic is as follows:

[0084]

[0085] Among them, M represents the number of samplings performed by Gauss ζ, and the sample obtained in each sampling is ζ w , w=1,…,M,T represents the test statistic, Gaussian satisfies the mean of 0 and the covariance of represents the covariance function.

[0086] Finally, based on the P value of the test statistic obtained above, the comparison result can be determined to make a decision on the test question, that is, whether the event-related potential mean functions of the two groups of samples are considered equal. If the conclusion is negative, the neural mechanism behind the difference in mean function can be further explored, and the difference can be used for clinical auxiliary judgment.

[0087] As a specific example, first obtain the data set to be processed, which includes event-related potential data of 28 subjects under four stimuli. Each subject will be presented with 4 types of phrases as stimuli (1, 2, 3 and 4), and the subject needs to make different responses according to this type of phrase. These four types of phrases represent dialectical self, dialectical non-self, non-dialectical self and non-dialectical non-self situations. The goal of this study is to explore the physiological mechanism of the brain's processing of contradictory information by analyzing the differences in event-related potentials under these four types of stimuli. The recording of EEG signals begins after the stimulus (i.e., different word pairs) is applied and lasts for 1 second.

[0088] The results of the comparison of event-related potential signals based on the above conditions are shown in the following table:

[0089] Stimulus contrast 1vs 2 1vs 3 1vs 4 2vs 3 2vs 4 3vs 4 The p value obtained by the present invention is <0.001 0.462 0.901 <0.001 <0.001 0.572 Take the mean and perform ANOVA on the p value 0.002 0.398 0.796 <0.001 <0.001 0.497 Take the maximum value for the p value of variance analysis <0.001 0.500 0.526 <0.001 0.003 0.192

[0090] As shown in the above table, for the null hypothesis that there is no difference in the mean functions of the three components N1 (EEG data 80-180ms after the stimulus occurs), N2 (EEG data 250-350ms after the stimulus occurs) and N450 (EEG data 350-500ms after the stimulus occurs) under stimulus 1 and 4, that is, there is a high probability that this null hypothesis cannot be rejected, while the traditional method requires hypothesis testing of multiple components one by one to obtain the result; in addition, since the present method utilizes more data information when calculating the p value, the performance of the event-related potential signal comparison method provided by the present invention is better than that of the traditional method in more complex situations.

[0091] According to another aspect of the present invention, a system for comparing event-related potential signals is provided.

[0092] Specifically, Figure 2 A schematic logic diagram of a comparison system for event-related potential signals according to an embodiment of the present invention is shown.

[0093] like Figure 2 As shown, the event-related potential signal comparison system 200 according to the embodiment of the present invention includes:

[0094] An event-related potential signal acquisition unit 210, used to acquire two event-related potential signals to be compared;

[0095] The sample type determination unit 220 is used to determine the sample type of two related potential signals; wherein the sample type includes an independent sample or a paired sample;

[0096] The comparison result acquisition unit 230 is used to compare the mean functions of the two related potential signals based on the sample type and obtain the corresponding comparison result; when the sample type of the two related potential signals is an independent sample, the comparison result acquisition unit 230 uses a first preset comparison method to compare the two related potential signals; when the sample type of the two related potential signals is a paired sample, the comparison result acquisition unit 230 uses a second preset comparison method to compare the two related potential signals.

[0097] It should be noted that the embodiments of the above-mentioned event-related potential signal comparison system can refer to the description in the embodiment of the event-related potential signal comparison method, which will not be described in detail here.

[0098] The method and system for comparing event-related potential signals provided by the present invention can solve the problem that the existing comparison methods compress infinite-dimensional event-related potential data into one dimension, causing loss of data information, thereby reducing the effectiveness of hypothesis testing. Starting from the functional structure of the event-related potential itself, the asymptotic distribution of the test statistic is obtained, and the theory of functional data is used to directly perform hypothesis testing on the event-related potential data without losing data information, and multiple components of the event-related potential can be compared simultaneously.

[0099] As described above, the event-related potential signal comparison method and system according to the present invention are described by way of example with reference to the accompanying drawings. However, it should be understood by those skilled in the art that various improvements can be made to the event-related potential signal comparison method and system proposed by the present invention without departing from the content of the present invention. Therefore, the protection scope of the present invention should be determined by the content of the attached claims.

Claims

1. A method for comparing event-related potential signals, characterized in that: include: Obtain two event-related potential signals to be compared; Determining the sample types of the two related potential signals; wherein the sample types include independent samples or paired samples; The mean functions of the two related potential signals are compared based on the sample type, and a corresponding comparison result is obtained; wherein, When the sample types of the two related potential signals are independent samples, the two related potential signals are compared using a first preset comparison method, and when the sample types of the two related potential signals are paired samples, the two related potential signals are compared using a second preset comparison method; the first preset comparison method includes: Projecting the two related potential signals respectively to the function space spanned by the B-spline function, and determining a first true trajectory estimation value and a second true trajectory estimation value corresponding to the two groups of samples respectively; Determine a corresponding first mean function based on the first true trajectory estimate value, and determine a corresponding second mean function based on the second true trajectory estimate value; Determine a first covariance function of a first sample based on the first true trajectory estimate and the first mean function, and determine a second covariance function of a second sample based on the second true trajectory estimate and the second mean function; wherein the samples of the two related potential signals are the first sample and the second sample, respectively; Based on the first mean function, the second mean function, the first covariance function and the second covariance function, a corresponding test statistic is constructed, and a P value of the test statistic is determined; the second preset comparison method includes: Acquiring paired difference data of the two related potential signals; Projecting the paired difference data to a function space spanned by a B-spline function to obtain a true trajectory estimation value corresponding to the paired difference data; Determine a mean function of the paired difference data based on the true trajectory estimate; Determining a covariance function of the paired difference data based on the true trajectory estimate and the mean function; Based on the mean function and the covariance function, construct a corresponding test statistic, and determine a P value of the test statistic; Determining the comparison result based on the P value of the test statistic; The expression formula of the event-related potential signal is as follows: Where d represents the sample group number of the relevant potential signal, N represents the number of measurements of the dth group of samples, and m d (·) represents the mean function of the dth group of samples, ξ di (·) is the random trajectory represented by the ith sample in the dth group, j represents the jth measurement of the ith sample, ∈ dij This indicates measurement error.

2. The method for comparing event-related potential signals according to claim 1, characterized in that: In the first preset comparison method, the expression formula of the first true trajectory estimation value or the second true trajectory estimation value is as follows: in, N represents the number of measurements of the d-th group of samples, r represents the order of the B-spline function, K represents the number of internal nodes corresponding to the B-spline function, B(·) is a vector composed of all K+r B-spline functions, Yi represents the vector spanned by all data of the i-th sample, and Y i =[Y i1 ,……,Y iN ] T .

3. The method for comparing event-related potential signals according to claim 2, characterized in that: In the first preset comparison method, the expression formula of the first covariance function or the second covariance function is as follows: Where d represents the sample group number of the relevant potential signal, t1,t2∈[0,1], represents the mean function corresponding to the d group of samples, n d represents the number of subjects in the sample of group d, Represents the true trajectory estimate of the i-th sample in the d group of samples.

4. The method for comparing event-related potential signals according to claim 3, characterized in that: The expression formula of the constructed test statistic is as follows: Wherein, the null hypothesis is H0:m1(t)=m2(t), t∈Λ, Λ represents the value range of whether the first mean function and the second mean function are equal, n1 represents the number of subjects in the first sample, n2 represents the number of subjects in the second sample, represents the first mean function, represents the second mean function, represents the first covariance function, Denotes the second covariance function.

5. The method for comparing event-related potential signals according to claim 4, characterized in that: The expression formula of the P value of the test statistic is as follows: Among them, M represents the number of samplings performed by Gauss ζ, and the sample obtained in each sampling is ζ w , w = 1, ..., M, T represents the test statistic, the Gaussian satisfies the mean of 0 and the covariance of represents the first covariance function, represents the second covariance function, n1 represents the number of subjects in the first sample, and n2 represents the number of subjects in the second sample.

6. A system for comparing event-related potential signals, characterized in that: include: An event-related potential signal acquisition unit, used for acquiring two event-related potential signals to be compared; A sample type determination unit, used to determine the sample type of the two related potential signals; wherein the sample type includes an independent sample or a paired sample; A comparison result acquisition unit is used to compare the mean functions of the two related potential signals based on the sample type and acquire the corresponding comparison result; wherein, When the sample types of the two related potential signals are independent samples, the comparison result acquisition unit uses a first preset comparison method to compare the two related potential signals; when the sample types of the two related potential signals are paired samples, the comparison result acquisition unit uses a second preset comparison method to compare the two related potential signals; The first preset comparison method includes: Projecting the two related potential signals respectively to the function space spanned by the B-spline function, and determining a first true trajectory estimation value and a second true trajectory estimation value corresponding to the two groups of samples respectively; Determine a corresponding first mean function based on the first true trajectory estimate value, and determine a corresponding second mean function based on the second true trajectory estimate value; Determine a first covariance function of a first sample based on the first true trajectory estimate and the first mean function, and determine a second covariance function of a second sample based on the second true trajectory estimate and the second mean function; wherein the samples of the two related potential signals are the first sample and the second sample, respectively; Based on the first mean function, the second mean function, the first covariance function and the second covariance function, a corresponding test statistic is constructed, and a P value of the test statistic is determined; the second preset comparison method includes: Acquiring paired difference data of the two related potential signals; Projecting the paired difference data to a function space spanned by a B-spline function to obtain a true trajectory estimation value corresponding to the paired difference data; Determine a mean function of the paired difference data based on the true trajectory estimate; Determining a covariance function of the paired difference data based on the true trajectory estimate and the mean function; Based on the mean function and the covariance function, construct a corresponding test statistic, and determine a P value of the test statistic; Determining the comparison result based on the P value of the test statistic; The expression formula of the event-related potential signal is as follows: Where d represents the sample group number of the relevant potential signal, N represents the number of measurements of the dth group of samples, and m d (·) represents the mean function of the dth group of samples, ξ di (·) is the random trajectory represented by the ith sample in the dth group, j represents the jth measurement of the ith sample, ∈ dij This indicates measurement error.

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