Method for evaluating attention of alcohol products after drinking based on electroencephalogram signals
Through the evaluation method based on EEG signal, the impact of alcohol products on the subjects' attention was collected and analyzed, and the subjectivity and inaccuracy of traditional evaluation methods were solved, achieving a more scientific and objective evaluation effect.
Patent Information
- Application Number
- CN202411541191.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-31
- Publication Date
- 2025-02-25
AI Technical Summary
The prior art lacks effective methods to evaluate the changes in attention after drinking alcohol products, and traditional expert sensory evaluations have problems with subjectivity and small sample data.
Using an evaluation method based on EEG signal, by determining multiple subjects and different types of liquor samples under the same conditions, the behavioral data and EEG data of the subjects when performing Stroop styling tasks before and after drinking liquor were collected, and statistical analysis was conducted to evaluate the potential impact of liquor products on attention.
It has achieved a more scientific, objective and quantifiable description of the impact of different alcoholic products on attention, and combined with EEG signals and behavioral data to provide more comprehensive and dynamic analysis results.
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Figure CN119513526A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of electroencephalogram signals, and in particular to a method for evaluating attention after drinking alcoholic products based on electroencephalogram signals. Background Art
[0002] In recent years, brain-computer interface technology, cognitive neuroscience, psychology, sensory science, computer science, artificial intelligence and other disciplines have developed rapidly, and related scientific and technological means have become relatively mature. However, there are still relatively few methods using multidisciplinary cross-disciplinary methods to study consumers' comfort after drinking alcoholic products, and the development is relatively slow. At present, with the improvement of living standards and consumers' pursuit of quality of life, the quality of alcoholic products has received unprecedented attention. Among many factors, after-drinking comfort has become a key indicator for evaluating the quality of alcoholic products, directly affecting consumers' purchasing choices and consumption experience. After-drinking comfort refers to the physiological and psychological feelings after drinking, such as whether you feel dry mouth, headache, and whether brain cognitive functions such as attention and memory are significantly affected.
[0003] However, there is still a lack of effective evaluation methods for attention after drinking alcoholic products. Traditional evaluation mainly relies on sensory evaluation by experts. Although experts have advantages in providing detailed and in-depth evaluations, there are also several limitations: first, due to differences in taste perception and preference among individuals, the opinions of experts cannot represent the true feelings of ordinary consumers; second, the sensory evaluation method is highly subjective. Even when evaluating the same content, different individuals will have different understandings of its definition due to differences in their cultural background, life experience, and value judgment, and the threshold of perception and evaluation criteria cannot be completely unified; third, the expert sensory evaluation team is usually composed of a small number of people. Small sample data poses great difficulties for statistical analysis, which limits the universality and generalizability of the conclusions from a mathematical and statistical perspective.
[0004] Therefore, there is an urgent need to develop an effective evaluation method for the after-drinking comfort quality of alcoholic products based on the precise statistics of objective physiological data from the perspective of consumers. Summary of the invention
[0005] The purpose of the present invention is to provide an evaluation method for attention after drinking alcoholic products based on EEG signals, which can solve the inaccurate feedback problem caused by traditional questionnaires and interviews, and achieve a more scientific, objective and quantifiable description of the impact of different alcoholic products on attention.
[0006] To achieve the above object, the technical solution adopted by the present invention is:
[0007] The present invention provides a method for evaluating attention after drinking alcoholic products based on electroencephalogram signals, comprising the following steps:
[0008] S10, determining multiple test subjects under the same conditions and different types of liquor samples to be evaluated;
[0009] S20, collecting behavioral data and EEG data of each subject when performing the Stroop color-word task before and after drinking the liquor sample;
[0010] S30. Conduct statistical analysis on the behavioral data and EEG data of all subjects, compare the performance in the Stroop task and the changes in EEG signals before and after drinking, and evaluate the potential impact of alcohol products on the subjects' attention.
[0011] Furthermore, the behavioral data includes the subjects' reaction time and accuracy in the Stroop color-word task.
[0012] Furthermore, the EEG data includes EEG signals in various frequency bands during the execution of the Stroop task.
[0013] Furthermore, the EEG data were collected using a 64-channel NeuroScan system, the amplifier model was SynAmps II; the electrodes were arranged using the international 10-20 standard; the reference electrode for online collection was CZ, the sampling rate was 500 Hz, and the impedance was kept below 10 kilo-ohms.
[0014] Furthermore, the step S20 also includes: recording two physiological indicators, skin temperature and heart rate, of each subject when performing the Stroop color-word task before and after drinking the liquor sample.
[0015] Furthermore, the step S20 further includes: preprocessing the EEG data; the preprocessing process includes:
[0016] Independent component analysis algorithm is used to remove artifacts in the data;
[0017] The continuous EEG data were bandpass filtered at 1-45 Hz;
[0018] The segmented time periods included: 200 ms before stimulus presentation and 1000 ms after stimulus presentation, and the data segment of 200 ms before stimulus presentation was used as the baseline for signal correction.
[0019] Furthermore, in step S30, the statistical analysis includes:
[0020] The variance analysis method was used for the two physiological indicators of skin temperature and heart rate to determine the differences in changes in skin temperature and heart rate caused by different amounts of alcohol consumption.
[0021] Furthermore, in step S30, the statistical analysis includes:
[0022] A paired t-test was performed on the P200 component of the FCZ electrode site of all subjects, with the EEG data in the time window of 180–220 ms, and the FDR method was used for multiple correction;
[0023] It was determined that different alcohol samples had different inhibitory effects on the amplitude of the P200 component, a key indicator of attention, in the Stroop color-word task.
[0024] Compared with the prior art, the present invention has the following beneficial effects:
[0025] 1. Comprehensive evaluation: Combining EEG signals and behavioral data makes the evaluation of attention after drinking alcohol products more comprehensive and can reflect both physiological and behavioral changes.
[0026] 2. Real-time monitoring: Through EEG technology, the subject's brain electrical activity can be monitored in real time, instantaneous changes in attention can be captured in time, and more dynamic analysis results can be provided.
[0027] 3. Detailed signal analysis: Using advanced data preprocessing technologies such as independent component analysis (ICA) and bandpass filtering to effectively remove artifact interference, improve signal quality, and ensure the accuracy of analysis results.
[0028] 4. Standardized method: Using the international 10-20 standard electrode arrangement ensures the consistency and comparability of EEG data collection, increasing the credibility of the research results.
[0029] 5. Innovation of statistical methods: The FDR method is introduced for multiple corrections, which controls the false positive rate, improves the reliability of statistical analysis, and makes the results more scientific.
[0030] 6. Flexible applicability: This method is not only applicable to liquor, but can also be extended to other types of alcoholic products, with good adaptability and promotion value. BRIEF DESCRIPTION OF THE DRAWINGS
[0031] Figure 1 This is a flow chart of the method for evaluating attention after drinking alcoholic products based on EEG signals;
[0032] Figure 2 This is a curve chart showing the changes in alcohol consumption and skin temperature;
[0033] Figure 3 This is a curve chart showing changes in alcohol consumption and heart rate;
[0034] Figure 4 It is a bar graph showing the correlation between drinking liquor sample 1 and the obtained accuracy rate.
[0035] Figure 5 It is a bar graph showing the correlation between drinking liquor sample 2 and the obtained accuracy rate.
[0036] Figure 6 It is a bar graph showing the correlation between drinking liquor sample 1 and reaction time.
[0037] Figure 7 It is a bar graph showing the correlation between drinking liquor sample 2 and reaction time.
[0038] Figure 8 The ERP waveforms of the P200 amplitude at the FCZ electrode of the two samples in the pre-drinking and post-drinking stages under three experimental conditions.
[0039] Fig. 9 The graph shows the changes in P200 amplitude of the two samples under three experimental conditions before and after drinking. DETAILED DESCRIPTION
[0040] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.
[0041] In the description of the present invention, it should be noted that the terms "upper", "lower", "inner", "outer", "front end", "rear end", "two ends", "one end", "the other end" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.
[0042] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "provided with", "connected", etc. should be understood in a broad sense. For example, "connected" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.
[0043] The present invention provides a method for evaluating attention after drinking alcoholic products based on electroencephalogram signals, wherein attention is an important quality dimension of comfort after drinking alcoholic products. It is a complex brain cognitive process that aims to optimize resource allocation, improve information processing efficiency, and enable humans to better adapt to the living environment. In the field of neuroscience, attention is defined as the ability of the brain to selectively process external stimuli while ignoring other irrelevant interference information. Alcohol will have a certain degree of influence on attention, and this influence is usually negative. After consuming alcohol, inhibitory neurotransmitters (GABA) increase, while excitatory neurotransmitters (glutamate) decrease. This change inhibits the activity of related brain areas (such as the prefrontal lobe) responsible for the allocation and regulation of attention resources, thereby reducing the ability of individuals to concentrate, which is manifested in behavior as a slower speed of processing information and a decrease in reaction accuracy. Under the premise of drinking in moderation, high-quality alcohol products should not have a significant negative impact on attention, an important cognitive function, so evaluating the degree of change in consumer attention before and after drinking can objectively reflect the quality of comfort after drinking alcoholic products.
[0044] In the related technology, the Stroop color-word task is a classic paradigm in the field of psychology for evaluating selective attention and cognitive control ability. In 1935, psychologist Dr. John Ridley Stroop found that most people's reactions would be significantly slower when the meaning of the word was inconsistent with the printed color (for example, the printed color of the word "blue" was red). This is the famous Stroop effect. A large amount of subsequent work further expanded this research and used the accuracy (or error rate) of the response as an important indicator for measuring the handling of cognitive conflicts. In addition, the Stroop task is also widely used and studied in the assessment and diagnosis of clinical psychiatric and neurological diseases, such as attention deficit hyperactivity disorder (ADHD), Alzheimer's disease, post-traumatic stress disorder (PTSD), etc.
[0045] Recently, EEG technology has attracted increasing attention in consumer science research and has shown great application potential. EEG technology can non-invasively measure the weak current generated by the synchronous electrical activity of a group of brain neurons with a time resolution of milliseconds. It is suitable for studying a variety of cognitive functions and states such as attention, memory and emotion. Alvino et al. (2020) used EEG to explore consumers' behavior and preferences during the experience of wine products; and found that the higher the preference for wine, the greater the decrease in the oscillation of beta waves (Alvino et al., 2018). The EEG power was used to predict consumers' decisions when watching mobile phone product advertisements with an accuracy rate of more than 87% (Golnar-Nik et al., 2019). In addition, Moore and colleagues (2012) used the Stroop task as a measure of attention control and found that the EEG characteristics 160-240 milliseconds after the stimulus presentation reflected the improvement of attention after meditation training. Heidlmayr et al. (2020) reviewed that the N2 component reflects the conflict monitoring process of the Stroop task, the N400 reflects the interference inhibition process, and the LSP (late sustained potential) component may reflect the conflict resolution process. However, the effects of acute drinking on the relevant ERPs in the Stroop task remain poorly understood, and it is even less clear whether the effects of different types of alcohol differ significantly.
[0046] The present invention uses the Stroop task to test the degree of change in consumers' attention before and after drinking, so as to objectively reflect the comfort quality of alcoholic products after drinking. To achieve this goal, consumers perform the Stroop color-word task before and after drinking different types of liquor, and simultaneously record their continuous EEG signals. We assume that different types of liquor have different degrees of influence on the behavioral performance of the Stroop task; in addition, they also have different degrees of influence on the EEG N200 component.
[0047] Reference Figure 1 As shown, the present invention provides a method for evaluating attention after drinking alcoholic products based on EEG signals, comprising:
[0048] S10, determining multiple test subjects under the same conditions and different types of liquor samples to be evaluated;
[0049] S20, collecting behavioral data and EEG data of each subject when performing the Stroop color-word task before and after drinking the liquor sample;
[0050] S30. Conduct statistical analysis on the behavioral data and EEG data of all subjects, compare the performance in the Stroop task and the changes in EEG signals before and after drinking, and evaluate the potential impact of alcohol products on the subjects' attention.
[0051] Among them, in step S10, the selection of subjects and samples: determining multiple subjects under the same conditions and different types of liquor samples to be evaluated.
[0052] In step S20, data collection: before and after drinking the liquor sample, collect the behavioral data (including reaction time and accuracy) and EEG data (including EEG signals of each frequency band) of each subject when performing the Stroop color-word task. In addition, record the subject's skin temperature and heart rate as two physiological indicators.
[0053] And data preprocessing is also required: preprocessing the collected EEG data, including:
[0054] Independent component analysis was used to remove artifacts from the data.
[0055] The continuous EEG data were band-pass filtered at 1-45 Hz.
[0056] The time segments were divided into 200 milliseconds before and 1000 milliseconds after stimulus presentation, and the data segment of the first 200 milliseconds was used as the baseline for signal correction.
[0057] Finally, in step S30, statistical analysis is performed on the behavioral data and EEG data of all subjects to compare the performance in the Stroop task and the changes in EEG signals before and after drinking, and to evaluate the potential impact of alcoholic products on the subjects' attention.
[0058] Variance analysis was performed on the changes in skin temperature and heart rate to determine the differences in changes in physiological indicators caused by different amounts of alcohol consumption.
[0059] A paired t-test was performed on the P200 component of the FCZ electrode site (time window of 180-220 milliseconds), and the FDR method was used for multiple correction to determine the amplitude suppression effect of different alcohol samples on the P200 component. Among them, FCZ is a position in the electroencephalogram (EEG) electrode arrangement, representing the "frontal central Z" (Frontal Central Z). It is located in the center of the frontal region and is often used to measure brain electrical activity related to cognition, emotion, and attention. This position is standardized in the international 10-20 system, which helps to ensure the consistency and comparability of the data.
[0060] The embodiment of the present invention provides a new perspective for evaluating the impact of alcoholic products on attention by combining EEG signals and behavioral data. This method not only improves the accuracy of the research, but also lays a foundation for future related research.
[0061] The technical solution of the present invention is described in detail below by taking examples:
[0062] 1. Subjects
[0063] 21 subjects (7 females, average age M = 24.9, standard deviation SD = 4.3), that is, the average age of the 21 subjects participating in the experiment was 24.9 years old, and the age fluctuation range was about 4.3 years old, participated in this experiment. The subjects were all right-handed, healthy, without neurological or mental diseases, and not allergic to alcohol. The subjects had normal vision or corrected vision and were not color blind. All subjects signed an informed consent form before the experiment and received a certain amount of monetary compensation after the experiment. The data of all subjects participated in behavioral and physiological analysis, and the data of 2 subjects were not included in the EEG analysis due to technical problems.
[0064] 2. Materials
[0065] During the study, the subjects drank two different types of 53-proof liquor, one was elegant liquor (sample 1), priced at RMB 1,699; the other was fragrant liquor (sample 2), priced at RMB 68. The prices of the two samples came from the same shopping website and were easily available (Alvino et al., 2020). The two samples were stored in the same environment to ensure the consistency of the test conditions. Each subject consumed the appropriate amount of alcohol calculated based on his or her weight each time (0.7g alcohol / kg body weight / day) (Kranzler et al., 2008), with an average drinking amount of 45-75mL, and the method and speed of consuming liquor were unified. In order to avoid possible interference of brand effects on the experimental results, both samples were provided in the same unmarked container, and the subjects were not informed of the information about the samples during the experiment.
[0066] 3. Stimulation
[0067] The subjects performed the Stroop color-word task during the experiment. Words of three different colors (red, green, and blue) were presented on the computer screen in a pseudo-random manner. One category of words was words that expressed color meanings, such as "red", "green", and "blue", and the other category of words was words that had no specific meanings, such as "such as", "then", and "it". Under the consistent experimental conditions, the printed color and meaning of the words were consistent, such as "blue" in blue print and "red" in red print; under the inconsistent experimental conditions, the printed color and meaning of the words were inconsistent, such as "red" in blue print and "blue" in red print; under the control conditions, the words themselves had no specific meaning, only color information. Each stimulus was presented for 500ms, and the interstimulus interval (ISI) was 1500-2000ms, with an average of 2000ms. Matlab (MathWorks, version 2019a) and Psychotoolbox3.0.16 (Brainard, 1997) toolkits were used to present stimuli and record the keystroke responses of the subjects.
[0068] 4. Procedure
[0069] Each subject tasted one sample on the first visit and the second sample on the second visit within a week. The order of testing the two samples was randomized among all subjects. At the beginning of each experimental session, the behavioral data and EEG data of each subject when performing the Stroop color-word task before drinking were collected as the baseline data for the pre-test. They were required to selectively pay attention to the color of the word when seeing the stimulus on the screen, ignore its meaning, and press the button of the corresponding color as quickly and accurately as possible. The three experimental conditions included a total of 180 trials. Then, under the supervision and guidance of the experimenter, the subject took 1 / 3 of the alcohol every 10 minutes, and recorded two physiological indicators: skin temperature and heart rate. The subject was required to complete the specified amount of alcohol intake within 30 minutes, and then began to perform the Stroop task after drinking. The experimental procedure was exactly the same as the pre-test. Their continuous EEG data were recorded simultaneously during the whole process.
[0070] 5.EEG Recording and Analysis
[0071] EEG data were collected using a 64-channel NeuroScan system, and the amplifier model was SynAmps II. The electrodes were arranged using the international 10-20 standard. The reference electrode for online collection was CZ, with a sampling rate of 500 Hz and an impedance of less than 10 kilo-ohms. The subjects were required to keep their bodies and heads still during the Stroop task before and after drinking, and to swallow and blink as much as possible during the stimulation interval to reduce the interference of various artifacts on the EEG data. The independent component analysis algorithm was used to remove artifact interference in the data. The continuous EEG data was then bandpass filtered at 1-45 Hz. The time period for epoch segmentation was 200 ms before and 1000 ms after the stimulus presentation, and the data segment 200 ms before the stimulus presentation was used as the baseline for correction. According to the conclusions of existing literature, the electrode site used for analysis was FCZ.
[0072] 6. Statistics
[0073] In order to evaluate the effect of different sample intake on physiological indicators (skin temperature and heart rate), a two-factor repeated measures ANOVA was used. One factor was intake, which had 4 levels: stage 1 (before drinking), stage 2 (1 / 3 of the amount consumed within 10 minutes), stage 3 (2 / 3 of the amount consumed within 20 minutes), and stage 4 (the entire amount consumed within 30 minutes); the other factor was sample type, which had 2 levels, sample 1 and sample 2. Mauchly was used to test the sphericity assumption, and if violated, Greenhouse-Geisser was used for correction. Tukey's Honest Significant Difference (HSD) was used for post hoc analysis.
[0074] The statistical methods used in analyzing behavioral and EEG data were based on clear pre-planned tests. Paired t-tests were used to analyze the differences in behavioral indicators (accuracy and reaction time) and EEG P200 amplitude before and after drinking in the same subjects under consistent conditions, control conditions, and inconsistent conditions.
[0075] 7. Physiological Results
[0076] Figure 2 , Figure 3 The changes of the subjects' physiological indicators (skin temperature and heart rate) with the amount of alcohol consumed were shown. The effects of alcohol consumption and sample type on skin temperature and heart rate were explored by two-factor repeated measures ANOVA. Figure 2 In the figure, temperature is the vertical axis, which indicates the temperature; consumption is the horizontal axis, which indicates the amount of alcohol consumed; Figure 3In the figure, heartrate is the vertical axis, which represents the heart rate; consumption is the horizontal axis, which represents the amount of alcohol consumed; sample1 represents sample 1, and sample2 represents sample 2.
[0077] The results of the analysis of skin temperature showed that the main effect of alcohol consumption was significant, F(3,60)=20.1045, p<0.0001, η2=0.060. The F value calculated in the analysis of variance (ANOVA) is used to compare the ratio of between-group variation to within-group variation. A higher F value indicates that the difference between groups is larger than the within-group variation, and the difference between groups may be statistically significant. This indicates that there is a significant difference in the change of body temperature between different levels of alcohol consumption. The main effect of sample type was not significant, F(1,20)=0.0075, p=0.9319, η2=0.00003; the interaction between alcohol consumption and sample type was also not significant F(3,60)=0.3050, p=0.8217, η2=0.122. Post hoc multiple comparisons Tukey HSD showed that compared with before drinking, body temperature changed significantly when consuming 2 / 3 of the amount (p=0.0036) and after drinking all the alcohol (p=0.001), while no significant differences were found in other stages (ps>0.05).
[0078] The results of the analysis of heart rate showed that the main effect of drinking amount was significant, F(3,60)=17.0967, p<0.0001, η2=0.120; the main effect of sample type was not significant, F(1,20)=0.8302, p=0.3731, η2=0.002; the interaction between the two was also not significant, F(3,60)=0.9719, p=0.4120, η2=0.251. Post hoc multiple comparisons Tukey HSD showed that except for the heart rate between 1 / 3 intake and before drinking, 1 / 3 intake and 2 / 3 intake, there were significant differences between the other stages (ps<0.05).
[0079] The results of physiological analysis showed that the main factor affecting skin temperature and heart rate during drinking is the amount of alcohol consumed; and the two samples had similar effects on these physiological indicators, with no statistically significant differences.
[0080] 8. Behavioral Results
[0081] Table 1 shows the results of the subjects' accuracy and reaction time in the consistent, control and inconsistent conditions of the Stroop color-word task before and after drinking.
[0082] Table 1: The accuracy and reaction time results of the two samples under different experimental conditions before and after drinking
[0083]
[0084] Paired t-tests were performed on the pre-test and post-test results of the behavioral indicators, and the FDR method was used for multiple correction. Figure 4 , Figure 5 As shown in the figure, accuracy means the correct rate; Pre means before drinking, Post means after drinking; congruent means consistent, control means control condition; incongruent means inconsistent.
[0085] Sample 1 under the same conditions (t(20) = 2.2258, p corrected =0.0282) and control condition (t(20) = 2.4398, p corrected =0.0282) was statistically significant; however, the reduction under the inconsistent condition was not significant t(20) = 0.5462, p corrected =0.2955; the accuracy of sample 2 decreased significantly in the post-drinking phase under all conditions (consistent: t(20)=1.7369, p corrected =0.0489; control: t(20)=2.7944, p corrected =0.0168; Inconsistency: t(20)=2.4491, p corrected =0.0177). One-sided paired t-test was performed with multiple correction for FDR, and the significance level was 0.05. * indicates p<0.05.
[0086] The analysis results of the reaction are as follows Figure 6 and Figure 7 As shown, response time refers to the reaction time. The reaction time of sample 1 in all conditions increased in the post-drinking stage, but the statistical difference was not significant (consistent: t(20) = -0.5091, p corrected =0.6919; control: t(20)=0.9100, p corrected =0.5604; Inconsistency: t(20) = 0.0601, p corrected =0.6919); similarly, the increase in the reaction time of sample 2 under all conditions was not significant (consistent: t(20) = -0.5526, p corrected =0.7067; control: t(20)=0.3495, p corrected =0.6269; Inconsistency: t(20)=0.2100, p corrected =0.6269).
[0087] The results of behavioral analysis show that drinking may affect the accuracy of subjects in performing the Stroop color-word task. The accuracy will decrease after drinking compared to before drinking, but the effects caused by different products are different. Specifically, under inconsistent conditions, the impact of product 1 is not statistically significant, while product 2 causes a statistically significant difference.
[0088] 9. EEG results
[0089] Here we choose to report the analysis results of the FCZ electrode. The FCZ electrode is located in the prefrontal cortex area, which plays a key role in attention monitoring. Therefore, FCZ is sufficient to represent the core target of the present invention.
[0090] Figure 8 The EEG waves of the three experimental conditions, before and after drinking, are shown. The yellow shaded part in the figure is the P200 component, and the corresponding time window is 180-220ms; the vertical axis amplitude represents the amplitude. It can be seen intuitively from the figure that compared with before drinking, the EEG amplitude of the three experimental conditions in the post-drinking stage showed a downward trend. It is worth noting that this pattern appeared when drinking these two wines, showing the reliability and repeatability of this result.
[0091] Next, paired t-tests were performed on the amplitudes of the P200 components before and after drinking under the three experimental conditions, and the FDR method was used for multiple correction. Fig. 9 As shown, the decrease in the post-drinking stage of sample 1 in the three conditions was not significant (consistent: t(18)=1.193, p corrected =0.3583; control: t(18)=0.3686, p corrected =0.3583; Inconsistency: t(18)=0.6252, p corrected =0.3583); Sample 2 under the same condition (t(18)=2.924, p corrected =0.0135) was statistically significant, while the control condition (t(18)=1.178, p corrected =0.1272) was not significantly reduced, and the reduction was not significant under the inconsistent condition (t(18)=1.831, p corrected =0.06285) was marginally significant.
[0092] The results of EEG analysis showed that the P200 component was indeed the key component representing attention in the Stroop color-word task, and that drinking alcohol reduced the amplitude of the P200 component, but the degree of influence varied between different products. In both consistent and inconsistent conditions, the decrease in sample 1 was not significant, while the decrease in sample 2 was significant or marginally significant.
[0093] In order to quantitatively evaluate the comfort quality of liquor after drinking, in this embodiment, the Stroop color word task was used to test the change in consumers' attention before and after drinking, and it was found that liquors with the same alcohol content but different qualities had significantly different effects on the behavioral scores and EEG P200 amplitude of the test task. This method shows the great application prospects of using EEG technology to objectively and finely evaluate the quality of alcoholic products.
[0094] The two liquor samples used in this embodiment have the same alcohol content, but still have different degrees of influence on the brain's attention function. Although alcohol content is a key factor affecting attention, other factors besides this should not be ignored, at least in the behavioral and EEG levels of the Stroop task in this embodiment. The reason for this phenomenon is that low-quality wine may produce more by-products that have adverse effects on the nervous system during the fermentation and distillation process, such as aldehydes, lipids, and fusel oils, which will have a greater negative impact on attention function.
[0095] In addition to the alcohol content, the amount of alcohol consumed is also an important factor to consider. In this embodiment, the appropriate amount of alcohol consumed is calculated based on the weight of each subject. However, the amount of alcohol consumed is also affected by other factors such as genes and body fat. Perhaps for some subjects with a strong tolerance to alcohol, this amount of alcohol consumed just serves to excite the nerves, and the results of the attention test did not change significantly after drinking.
[0096] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.
Claims
1. A method for evaluating attention after drinking alcoholic products based on electroencephalogram signals, characterized in that: The following steps are involved: S10, determining multiple test subjects under the same conditions and different types of liquor samples to be evaluated; S20, collecting behavioral data and EEG data of each subject when performing the Stroop color-word task before and after drinking the liquor sample; S30. Conduct statistical analysis on the behavioral data and EEG data of all subjects, compare the performance in the Stroop task and the changes in EEG signals before and after drinking, and evaluate the potential impact of alcohol products on the subjects' attention.
2. The method for evaluating attention after drinking alcoholic products based on EEG signals according to claim 1, characterized in that: The behavioral data include the subjects' reaction time and accuracy in the Stroop color-word task.
3. The method for evaluating attention after drinking alcoholic products based on EEG signals according to claim 1, characterized in that: The EEG data includes EEG signals in various frequency bands during the execution of the Stroop task.
4. The method for evaluating attention after drinking alcoholic products based on EEG signals according to claim 1, characterized in that: The EEG data were collected using a 64-channel NeuroScan system, the amplifier model was SynAmps II; the electrodes were arranged using the international 10-20 standard; the reference electrode for online collection was CZ, the sampling rate was 500 Hz, and the impedance was kept below 10 kilo-ohms.
5. The method for evaluating attention after drinking alcoholic products based on EEG signals according to claim 1, characterized in that: The step S20 also includes: recording two physiological indicators, namely, skin temperature and heart rate, of each subject when performing the Stroop color-word task before and after drinking the liquor sample.
6. The method for evaluating attention after drinking alcoholic products based on EEG signals according to claim 1, characterized in that: The step S20 further includes: preprocessing the EEG data; the preprocessing process includes: Independent component analysis algorithm is used to remove artifacts in the data; The continuous EEG data were bandpass filtered at 1-45 Hz; The segmented time periods included: 200 ms before stimulus presentation and 1000 ms after stimulus presentation, and the data segment of 200 ms before stimulus presentation was used as the baseline for signal correction.
7. The method for evaluating attention after drinking alcoholic products based on EEG signals according to claim 5, characterized in that: In step S30, the statistical analysis includes: The variance analysis method was used for the two physiological indicators of skin temperature and heart rate to determine the differences in changes in skin temperature and heart rate caused by different amounts of alcohol consumption.
8. The method for evaluating attention after drinking alcoholic products based on EEG signals according to claim 1, characterized in that: In step S30, the statistical analysis includes: A paired t-test was performed on the P200 component of the FCZ electrode site of all subjects, with the EEG data in the time window of 180–220 ms, and the FDR method was used for multiple correction; It was determined that different alcohol samples had different inhibitory effects on the amplitude of the P200 component, a key indicator of attention, in the Stroop color-word task.