Fresh taste synergistic effect evaluation method based on electroencephalogram monitoring technology

Abstract

The invention belongs to the field of food quality evaluation, and provides a delicate flavor synergistic effect evaluation method based on an electroencephalogram monitoring technology. Psychological or physiological factors such as subjective judgment, forced selection or scoring, individual umami cognition and umami sensitivity difference of sensory officers may affect the accuracy of sensory experiment results; the invention discloses methods such as umami sample selection and strength evaluation, electroencephalogram signal acquisition experiment normal form, quantitative evaluation and statistical analysis, feature extraction and response difference analysis, and the like, and the response mechanism of typical umami compounds in the human brain is explored by taking the response of people to umami signals as a research object and taking electroencephalogram signal detection analysis as a main method. A new theoretical basis is provided for quantitative evaluation based on the human palatable taste intensity, and the method is worthy of wide popularization.

Description

Technical Field

[0001] The present invention belongs to the field of food quality evaluation, and particularly relates to a method for evaluating the umami synergistic effect based on electroencephalogram monitoring technology. Background Art

[0002] Taste is one of the important physiological sensations for evaluating food quality. In the past two decades, with the discovery of umami receptors and the development of umami evaluation methods, umami, as one of the five basic tastes, has gradually been accepted by people. Since more and more umami substances and their analogs have been discovered, traditional umami evaluation methods can no longer meet the needs of contemporary food umami evaluation. In traditional sensory evaluation methods, psychological or physiological factors such as the subjective judgment of sensory officers, forced choice or scoring, individual umami perception, and umami sensitivity differences affect the accuracy of sensory experiment results to a certain extent, which poses new problems and challenges to the quantitative evaluation of umami intensity based on humans.

[0003] Currently, methods for umami evaluation include artificial sensory analysis, intelligent sensory analysis, biosensors, etc. Among them, artificial sensory evaluation is the main means for evaluating taste. Commonly used methods include taste descriptive method, triangle test method, scale scoring method, taste dilution analysis method, and comparative taste dilution analysis method, etc. However, the artificial sensory method belongs to a subjective evaluation method, and its experimental results are affected by human subjective factors. Intelligent sensory methods such as electronic tongue are a bionic taste system. Limited by the sample type, they cannot have a strong response signal to all samples, and cannot comprehensively show the true perception of umami by humans for the detection of umami.

[0004] Electroencephalogram is a common method for studying the changes in brain waves during brain activities, and is the overall reflection of the electrophysiological activities of brain nerve cells on the scalp surface. Electroencephalogram has the characteristics of high time-domain resolution, relatively time-saving, digitalization of measurement results, and no interference from human subjective factors. Therefore, electroencephalogram is used to explore the umami perception of the brain. The brain response topology map can show the topological changes in the brain's response to stimuli at different times, and can be used to explore the relevant potential distribution of the brain scalp's response to umami stimuli.

[0005] At present, compound seasonings such as chicken essence are widely used in the market. Its main ingredient is sodium glutamate, which is the sodium salt of glutamic acid and contains a small amount of glutamic acid. Usually, an appropriate amount of disodium inosinate is added to enhance the umami flavor, taking advantage of the synergistic umami enhancement effect between sodium glutamate and disodium inosinate. Some studies have pointed out that disodium inosinate can make the binding between sodium glutamate and the umami receptor more tight at the binding site, and its binding effect in the domain of the active pocket is better, thus playing a synergistic effect. Glutamic acid is an acidic amino acid with two carboxyl groups in its molecule. Its chemical name is α-aminopentanedioic acid. It is abundantly present in cereal proteins and plays an important role in the protein metabolism in organisms. The umami flavor felt by people in their daily diet is not "pure" umami, but the umami flavor enhanced through synergy. Currently, there are few reports on the impact of this synergy on the human brain. Summary of the Invention

[0006] To solve the above technical problems, the present invention provides an evaluation method for umami synergy based on electroencephalogram (EEG) monitoring technology to solve the problems in the prior art. The technical solution adopted by the present invention is as follows:

[0007] An evaluation method for umami synergy based on electroencephalogram (EEG) monitoring technology, comprising the following steps:

[0008] S1: Select umami samples for gustatory brain electrical induction. Use the 0-100 linear scaling method to evaluate the umami intensity of several umami solutions with different concentrations respectively, and use an EEG device to collect the EEG signals under the stimulation of umami solutions with different concentrations.

[0009] S2: Adopt a quantitative evaluation method to evaluate the umami intensity of different umami solutions and mixed solutions. In the experiment, keep the molar concentrations of single samples and mixed samples consistent. Use a 64-channel EEG device to collect the EEG signals under different stimulations, and then conduct statistical analysis on all samples. The methods used are mixed model variance analysis and Bonferroni post hoc test analysis, where the sensory panelists are used as random factors, and the samples, rhythm waves, and different brain regions are used as fixed factors.

[0010] S3: Select data for a specific time period, extract features for analysis. The features to be extracted include analyzing the energy spectrum response results to explore the position where the maximum signal response appears; and analyzing the brain regions and rhythm waves with gustatory coding responses through the average spectral response signal distribution of the brain combined with the response topological map to explore the response differences of the brain to the synergistic stimulation of different umamis.

[0011] Further, in the step S1, the selected umami samples are typical umami stimulants, including sodium glutamate, disodium succinate, and disodium inosinate.

[0012] Furthermore, in step S1, when using an electroencephalogram device to collect electroencephalogram signals under the stimulation of umami solutions of different concentrations, a 64-channel electroencephalogram device is used to collect electroencephalogram signals under the stimulation of umami solutions of different concentrations; the total time of a single collection is 10 to 20 seconds, the electrode impedance is 5 to 20 kΩ, and the sampling rate is 200 to 1000 Hz;

[0013] When collecting, first rinse your mouth with 8 to 12 mL of water and saline, then taste 8 to 15 mL of umami standard solutions of different umami intensities for 8 to 10 seconds, spit it out after 10 to 15 seconds, rinse your mouth with clean water, rest for 20 to 30 seconds before tasting the next group of solutions. Repeat 3 to 6 times and take the average of the results.

[0014] Furthermore, in the step S1, when evaluating the umami intensity of several umami solutions of different concentrations, the concentration of umami agents of similar sensory intensity is determined by combining the sensory intensity evaluation result of the 0-100 point linear scaling method with the umami intensity quantitative evaluation method.

[0015] Furthermore, in step S3, the frequency and rhythmic wave response are analyzed, including: importing data and electrode positioning, followed by filtering preprocessing, calculating the power spectrum value and analyzing it. The analysis indicators include the energy of each rhythm: delta wave, theta wave, alpha wave, beta wave, and gamma wave, so as to explore the impact of the taste produced by different umami solutions on different rhythmic waves and areas of EEG.

[0016] Furthermore, the step S3 also includes studying the effects of different umami solutions, rhythmic waves, and different brain regions on brain responses by using a significant difference analysis method: using the results of the brain responses to different umami standard solutions and mixed solutions during a specific time period randomly selected from all subjects, thereby obtaining a topological map of the brain to umami stimulation, and analyzing the location and degree of umami response in each activated area;

[0017] Combining different umami solutions, rhythmic waves, and the responses of different brain regions to the brain, we can determine whether the brain can distinguish between different umami standard solutions and mixed solutions;

[0018] Analyze whether there are significant differences in the changes in the brain's response to delta, theta, and alpha waves induced by the umami stimulation of different umami standard solutions and mixed solutions; whether the synergistic effect of umami stimulation on brain response is a simple superposition of rhythmic waves, and whether samples under different rhythmic waves can show synergistic effects;

[0019] Finally, the response between brain regions was analyzed for significance, in order to explore whether there were significant differences in the EEG signal responses between different brain regions. Mathematical statistical analysis was used to compare the taste response signals induced by umami of different frequencies and concentrations with the response differences between different brain regions to be tested and different brain anatomical regions.

[0020] Establish a method for analyzing the umami perception response signal of the human brain based on electroencephalogram spectrum technology combined with mathematical statistical methods, and explore the feasibility of detecting umami response signals by electroencephalogram spectrum.

[0021] The present invention has the following beneficial effects:

[0022] The present invention takes the human response to umami signals as the research object and electroencephalogram signal detection and analysis as the main method to explore the response mechanism of typical umami compounds in the human brain, providing a new theoretical basis for the quantitative evaluation based on human umami intensity, which is worthy of wide promotion. Description of the Drawings

[0023] Figure 1 is the electroencephalogram experiment flow chart in the embodiment of the present invention;

[0024] Figure 2 is the sensory intensity of each umami in the sensory experiment in the embodiment of the present invention;

[0025] Figure 3 is the analysis of variance result of the brain response to monosodium glutamate, disodium succinate and disodium inosinate with different sensory intensities in the embodiment of the present invention;

[0026] Figure 4 is the analysis of variance result of the brain response changes of biological rhythm waves δ, θ and α caused by monosodium glutamate, disodium succinate and disodium inosinate in the embodiment of the present invention;

[0027] Figure 5 is the result of the brain response topology map to different umami stimuli in the embodiment of the present invention. (a) is the result of the brain response topology map of monosodium glutamate with different sensory intensities; (b) is the result of the brain response topology map of monosodium glutamate, disodium succinate and disodium inosinate with similar sensory intensities;

[0028] Figure 6 is the analysis of variance result of the brain response to umami stimuli in different brain regions in the embodiment of the present invention;

[0029] Figure 7 is the analysis of variance result of the umami intensity of different umami sensory analyses in the embodiment of the present invention;

[0030] Figure 8 is the topology map of the brain response to umami stimuli in the embodiment of the present invention: monosodium glutamate, disodium inosinate and the mixture of monosodium glutamate and disodium inosinate;

[0031] Figure 9 is the analysis of variance result of the brain response results of the changes of rhythm waves δ, θ and α caused by different umami monosodium glutamate, disodium inosinate and the mixture of monosodium glutamate and disodium inosinate in the oral cavity in the embodiment of the present invention;

[0032] Figure 10 It is the result of the analysis of variance of the responses of different brain regions to umami stimuli in the embodiments of the present invention;

[0033] Figure 11 They are the topographic maps of each power spectrum at 6 s for different monosodium glutamate, disodium inosinate, and mixtures of monosodium glutamate and disodium inosinate in the embodiments of the present invention. Detailed implementation manners

[0034] Next, in combination with the Figure 1 - Figure 2 in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. If not specifically specified, the technical means used in the embodiments are conventional means well known to those skilled in the art.

[0035] The present invention mainly aims at the problem that in traditional sensory evaluation methods, psychological or physiological factors such as the subjective judgment of sensory officers, forced selection or scoring, individual umami cognition, and umami sensitivity differences may affect the accuracy of sensory experiment results, and proposes a method for evaluating umami synergy based on electroencephalogram monitoring technology. Select umami samples for gustatory brain electroencephalogram induction, and use the 0-100 linear scale method to evaluate the umami intensity of several umami solutions with different concentrations respectively. The specific experimental paradigm for umami stimulation adopted is as follows: Use a 64-channel electroencephalogram device to collect electroencephalogram signals under the stimulation of umami solutions with different concentrations. The total duration of a single collection is 10-20 s. At the beginning of the experiment, first rinse the mouth with 8-12 mL of water and physiological saline for 8-10 s, then taste 8-15 mL of umami standard solutions with different umami intensities for 10-15 s, spit out after 10-15 s, and rinse the mouth with clean water. After resting for 20-30 s, conduct the next group of tastings. The experiment is repeated 3-6 times, and the results are averaged; S2: Adopt a quantitative evaluation method to evaluate the umami intensity of different umami solutions and mixed solutions, and keep the molar concentrations of single samples and mixed samples consistent in the experiment. Use a 64-channel electroencephalogram device to collect electroencephalogram signals under different stimulations. Subsequently, perform a mixed model analysis of variance and Bonferroni post hoc test analysis on all samples, where the sensory officers are used as random factors, and the samples, rhythm waves, and different brain regions are used as fixed factors. S3: Select data for a specific time period such as 5-10 s, extract features for analysis. The feature extraction is mainly reflected in the analysis of the energy spectrum response results to explore the position where the maximum signal response appears; and through the average spectral response signal distribution of the brain combined with the response topology map, analyze the brain regions and rhythm waves with gustatory coding responses, etc., to explore the response differences of the brain to the synergistic stimulation of different umamis.

[0036] Such as Figure 1, A method for evaluating the umami synergistic effect based on electroencephalogram monitoring technology, comprising the following steps:

[0037] S1: Select umami samples for gustatory brain electroencephalogram induction, and use the 0-100 linear scale method to evaluate the umami intensity of several umami solutions with different concentrations respectively. Use a 64-channel electroencephalogram device to collect the electroencephalogram signals under the stimulation of umami solutions with different concentrations. The total duration of a single collection is 10-20 s.

[0038] S2: Adopt a quantitative evaluation method to evaluate the umami intensity of different umami solutions and mixed solutions. In the experiment, the molar concentrations of single samples and mixed samples are kept consistent. Use a 64-channel electroencephalogram device to collect the electroencephalogram signals under different stimulations. Subsequently, perform a mixed model analysis of variance and Bonferroni post hoc test analysis on all samples, where the sensory officers are used as random factors, and the samples, rhythm waves, and different brain regions are used as fixed factors.

[0039] S3: Select data for a specific time period, such as 5-10 s, extract features for analysis. The feature extraction is mainly reflected in analyzing the energy spectrum response results to explore the position where the maximum signal response appears; and analyzing the brain regions and rhythm waves with gustatory coding responses through the average spectral response signal distribution of the brain combined with the response topology map. To explore the response differences of the brain to the synergistic stimulation of different umamis.

[0040] Specifically, in S2, the mixed model analysis of variance (Mixed Model ANOVA) and Bonferroni post hoc test (Bonferroni Post Hoc Test) are commonly used analysis methods in statistics for processing data in complex experimental designs, especially in the case of repeated measurements or multi-factor interactions.

[0041] The mixed model analysis of variance is applicable to experimental designs that simultaneously contain fixed effects and random effects. Fixed effects refer to the experimental conditions (such as different treatment groups) that the researcher is interested in and can control, while random effects refer to the uncontrollable and randomly varying factors in the experiment (such as individual differences among subjects). The Bonferroni post hoc test is a multiple comparison correction method used to further compare the differences between groups after a significant analysis of variance.

[0042] The present invention combines the mixed model analysis of variance and the Bonferroni post hoc test. First, determine whether the experimental conditions (fixed effects) or time points (repeated measurements) have a significant impact on the outcome variable through the mixed model analysis of variance. After finding a significant effect, then use the Bonferroni post hoc test to perform pairwise comparisons between groups to determine the specific sources of differences.

[0043] Further, in the step S1, the selected taste stimulus sample is a typical umami stimulus, specifically including but not limited to sodium glutamate, disodium succinate, disodium inosinate, etc.

[0044] Furthermore, in the step S1, the established experimental paradigm for umami stimulation is as follows: Use a 64-channel electroencephalogram (EEG) device to collect EEG signals under the stimulation of umami solutions with different concentrations. The total duration of a single collection is 10 - 20 s, the electrode impedance is 5 - 20 kΩ, and the sampling rate is 200 - 1000 Hz. At the beginning of the experiment, first rinse the mouth with 8 - 12 mL of water and physiological saline for 8 - 10 s, then taste 8 - 15 mL of umami standard solutions with different umami intensities for 10 - 15 s and then spit them out, and rinse the mouth with clean water. After resting for 20 - 30 s, conduct the next group of tastings. The experiment is repeated 3 - 6 times, and the results are averaged.

[0045] Furthermore, in the step S1, the umami intensity of several umami solutions with different concentrations is evaluated as follows: The determination of the concentration of umami agents with similar sensory intensities is obtained through the umami intensity quantitative evaluation method combined with the sensory intensity evaluation results of the 0 - 100 linear scale method.

[0046] Furthermore, in the step S3, the analysis of frequency and rhythm wave responses is as follows: Import the data and electrode positioning, and then perform preprocessing such as filtering to exclude noise interference, removing electrooculogram (EOG), and rereferencing. Further calculate the power spectral values and conduct analysis. The analysis indicators include the energies of each rhythm: δ, θ, α, β, and γ, so as to explore the effects of the taste generated by different umami solutions on different rhythm waves and regions of the EEG.

[0047] Furthermore, in the step S3, select data for a specific time period such as 5 - 10 s for data analysis, process the EEG signal data, import the data and electrode positioning, and then perform preprocessing such as filtering to exclude noise interference, removing EOG, and rereferencing. Further calculate the power spectral values and conduct analysis. The analysis indicators include the energies of each rhythm: δ, θ, α, β, and γ; that is, delta wave (δ 1 - 4 Hz), theta wave (θ 4 - 8 Hz), alpha wave (α 8 - 13 Hz), beta wave (β 13 - 30 Hz), gamma wave (γ 30 - 45 Hz); δ, θ, α, β, and γ are the main frequency bands of the electroencephalogram (EEG), and each frequency band corresponds to different brain activities and physiological states. They correspond to different wave bands respectively.

[0048] Further, the significance difference analysis method was used to study the effects of different umami solutions, rhythm waves, and different brain regions on the brain response. Based on the results of the brain response to different umami standard solutions and mixed solutions during a specific time period randomly selected from all subjects, the topological map of the brain response to umami stimuli was obtained, and the umami response positions and degrees in each activated region were analyzed. Further, combined with the responses of different umami solutions, rhythm waves, and different brain regions to the brain, it was judged whether the brain could distinguish different umami standard solutions and mixed solutions. Further analysis was carried out to determine whether there were significant differences (p<0.05) in the response changes of the brain to δ, θ, and α waves induced by the umami stimuli of different umami standard solutions and mixed solutions; whether the synergistic effect of umami stimuli on the brain response was a simple superposition between rhythm waves, and whether there was a synergistic effect between samples under different rhythm waves; finally, a significance analysis was performed on the responses between brain regions to explore whether there were significant differences (p<0.005) in the electroencephalogram signals between different brain regions. That is, mathematical statistical analysis was used to compare the taste response signals induced by umami with different frequencies and concentrations with the response differences between different brain regions to be measured and different brain anatomical regions. A method for analyzing the umami perception response signal of the human brain based on electroencephalogram spectrum technology combined with mathematical statistical methods was established, and the feasibility of detecting umami response signals by electroencephalogram spectrum was explored.

[0049] In this embodiment, the electroencephalogram acquisition device is a 64-channel electroencephalogram acquisition system. The experimental paradigm is as Figure 1 shown. First, the collected electroencephalogram signals were preprocessed, and a significance difference analysis was carried out to explore the influence results of sodium glutamate as umami stimuli on the δ-γ wave frequency (1-100Hz) and the response of sodium glutamate concentration. The results are shown in Figure 2 . With frequency, sodium glutamate concentration, and electrode position as fixed factors, three-factor analysis of variance and Bonferroni post hoc test were used to obtain the brain response positions of umami. Two-factor analysis of variance and Bonferroni post hoc test were used to analyze the response differences of the left, middle, and right regions to umami stimuli with the brain response region and concentration of sodium glutamate as fixed factors (significance level α = 0.05). The results are as Figure 3 shown. It can be seen that the brain can distinguish different types and different intensities of the same type of umami stimuli (p<0.05), and can partially distinguish sodium glutamate, disodium succinate, and disodium inosinate with different sensory intensities. In addition, the response to disodium succinate and disodium inosinate stimuli is more sensitive than that to sodium glutamate; the brain has different sensitivities to different umamis with similar umami intensities, and the response sensitivities to low and high umami intensities are higher than those to medium umami intensities. Compared with the results of sensory experiments, the electroencephalogram experiment differences are more significant; as Figure 4 shown, all three umamis can significantly enhance the brain response to δ, θ, and α waves (p<0.05). Among them, the response change of α wave is the largest, and the enhancement of disodium succinate and disodium inosinate on the brain response α wave is relatively large; asFigure 5 , 6 As shown, different regions of the brain respond differently to umami stimuli. There are significant differences between the parieto-occipital region, the prefrontal region and other regions (p < 0.001), and the parieto-occipital region > the prefrontal region > the left temporal region, the central region, and the right temporal region, while there are no significant differences among the left temporal region, the central region, and the right temporal region.

[0050] In this embodiment, further based on the signal response peak near 5 s of sodium glutamate and disodium succinate, and considering that the action potential during the first 5 s of tasting may interfere with the electroencephalogram (EEG) signal response, the EEG signals in a specific time period are selected and then statistically analyzed. Three-way analysis of variance and Bonferroni post hoc test are used to analyze and compare the effects of different umamis on the response frequency band and region of the brain; the relationship between the change of EEG response and umami intensity; and the relationship between the change of EEG response and different types of umamis. The results are as Figure 7 , 8 shown. It can be seen that the brain can distinguish between sodium glutamate and disodium inosinate, and the mixture of sodium glutamate and disodium inosinate, but cannot distinguish between disodium inosinate and the mixture of sodium glutamate and disodium inosinate. The brain has partial discrimination ability for sodium glutamate, disodium inosinate and the mixture of sodium glutamate and disodium inosinate, and it may be related to the latency and the levels of different brain regions. As Figure 9 shown, there are significant differences (p < 0.05) in the response changes of the umami stimuli of sodium glutamate, disodium inosinate, and the mixture of sodium glutamate and disodium inosinate to the δ, θ, and α waves in the brain; the synergistic effect of umami stimuli on the brain response is not a simple superposition between rhythm waves, and its principle is relatively complex. In the α3 wave (12 - 13 Hz), the mixture of sodium glutamate and disodium inosinate shows the synergistic effect of sodium glutamate and disodium inosinate, while in the α1 wave (8 - 9 Hz) and the α2 wave (9 - 12 Hz), no synergistic effect is found; further results are shown in Figure 10 , there are significant differences between the parieto-occipital region and all other regions including the prefrontal region, the left temporal region, the central region, and the right temporal region, and there are significant differences between the prefrontal region and the left temporal region, and between the prefrontal region and the right temporal region (p < 0.005); there are also significant differences between the central region and the left temporal region, and between the central region and the right temporal region (p < 0.005). When the mixture of sodium glutamate and disodium inosinate is stimulated for 6 s, a significant enhancement of the orbitofrontal cortex can also be observed, as shown in Figure 11 . Compared with sodium glutamate or disodium inosinate, the response area of the mixture of sodium glutamate and disodium inosinate is significantly increased, and the average power is increased.

[0051] The embodiments described above are only descriptions of the preferred embodiments of the present invention, and do not limit the scope of the present invention. Without departing from the design spirit of the present invention, various deformations, variations, modifications, and substitutions made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. An evaluation method for umami synergistic effect based on electroencephalogram monitoring technology, characterized in that, It includes the following steps: S1: Select umami samples for gustatory EEG induction. Use the 0-100 linear scale method to evaluate the umami intensity of several umami solutions with different concentrations respectively, and use EEG equipment to collect the EEG signals under the stimulation of umami solutions with different concentrations; S2: Adopt a quantitative evaluation method to evaluate the umami intensity of different umami solutions and mixed solutions. In the experiment, keep the molar concentrations of single samples and mixed samples consistent. Use a 64-channel EEG equipment to collect the EEG signals under different stimulations, and then conduct statistical analysis on all samples. The methods used are mixed model variance analysis and Bonferroni post hoc test analysis, where the sensory officers are used as random factors, and the samples, rhythm waves, and different brain regions are used as fixed factors; S3: Select data for a specific time period, extract features for analysis. The extracted features include analyzing the energy spectrum response results to explore the position where the maximum signal response appears; and analyzing the brain regions and rhythm waves with gustatory coding responses through the average spectral response signal distribution of the brain combined with the response topology map to explore the response differences of the brain to the synergistic stimulation of different umamis.

2. The evaluation method for umami synergistic effect based on electroencephalogram monitoring technology according to claim 1, characterized in that, In the step S1, the selected umami samples are typical umami stimulants, including sodium glutamate, disodium succinate, and disodium inosinate.

3. The umami synergistic effect evaluation method based on electroencephalogram monitoring technology according to claim 1, wherein In the step S1, when using EEG equipment to collect the EEG signals under the stimulation of umami solutions with different concentrations, use a 64-channel EEG equipment to collect the EEG signals under the stimulation of umami solutions with different concentrations; the total duration of a single collection is 10-20 s, the electrode impedance is 5-20 kΩ, and the sampling rate is 200-1000 Hz; During collection, first rinse the mouth with 8-12 mL of water and physiological saline for 8-10 s, then taste 8-15 mL of umami standard solutions with different umami intensities, spit out after 10-15 s, rinse the mouth with water, rest for 20-30 s, and then conduct the next group of tastings, repeating 3-6 times, and take the average value of the results.

4. The umami synergistic effect evaluation method based on electroencephalogram monitoring technology according to claim 1, characterized in that In the step S1, when evaluating the umami intensity of several umami solutions with different concentrations, it includes: the determination of the concentration of umami agents with similar sensory intensities is obtained through the sensory intensity evaluation results of the umami intensity quantitative evaluation method combined with the 0-100 linear scale method.

5. The umami synergistic effect evaluation method based on electroencephalogram monitoring technology according to claim 1, characterized in that, In the step S3, when analyzing the frequency and rhythm wave responses, it includes: importing data and electrode positioning, then preprocessing through filtering, calculating the power spectrum values and conducting analysis. The analysis indicators include the energy of each rhythm: delta wave, theta wave, alpha wave, beta wave, gamma wave, so as to explore the effects of the taste generated by different umami solutions on different rhythm waves and regions of the brain.

6. The umami synergistic effect evaluation method based on electroencephalogram monitoring technology according to claim 1, characterized in that, In the step S3, it also includes studying the effects of different umami solutions, rhythm waves, and different brain regions on the brain response through the significance difference analysis method: based on the results of the brain's response to different umami standard solutions and mixed solutions between specific time periods randomly selected from all subjects, and then obtaining the topology map of the brain's response to umami stimulation, and analyzing the umami response positions and degrees of each activation area; Based on the responses of the brain to different umami solutions, rhythm waves, and different brain regions, determine whether the brain can distinguish different umami standard solutions and mixed solutions; Analyze whether there are significant differences in the response changes of the brain to δ, θ, and α waves induced by the umami stimuli of different umami standard solutions and mixed solutions; whether the synergistic effect of umami stimuli on the brain response is a simple superposition between rhythm waves, and whether the samples under different rhythm waves can exhibit a synergistic effect; Finally, perform a significance analysis on the responses between brain regions to explore whether there are significant differences in the electroencephalogram (EEG) signal responses between different brain regions. Use mathematical statistical analysis to compare the response differences between the taste response signals induced by umami of different frequencies and concentrations and different brain regions to be measured and different brain anatomical regions; Establish a method for analyzing the umami perception response signal of the human brain based on electroencephalogram (EEG) spectrum technology combined with mathematical statistical methods, and explore the feasibility of detecting umami response signals using EEG spectrum.

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