Individualized alcohol desire evaluation method and system based on virtual reality

Abstract

The invention provides an individualized alcohol craving evaluation method and system based on virtual reality, and the method comprises the steps: firstly constructing an alcohol clue exposure scene, and recording the first baseline alcohol craving degree of a subject through a visual simulation scoring method; a subject freely moves in a virtual scene, and meanwhile, relevant data are obtained through eye movement tracking and motion capture technologies, and the relevant data comprise the watching duration and frequency of alcohol clues and non-alcohol clues and the picking duration and frequency of the alcohol clues. And after the preset time, recording the second baseline alcohol desire degree of the subject. According to the method, eye movement tracking and motion capture data are analyzed, the fixation and pickup ratio of alcohol clues is calculated, the attention deviation and approaching behavior of a subject are evaluated in combination with the baseline desire degree, and finally an individualized alcohol desire evaluation report is generated. The method has remarkable advantages in the aspects of improving the accuracy, objectivity and individualization degree of evaluation, and important support and basis are provided for diagnosis and treatment of alcohol dependence.

Description

Technical Field

[0001] The present invention relates to the technical field of mental health assessment, and in particular to an individualized alcohol craving assessment method and system based on virtual reality. Background Art

[0002] Alcohol dependence (AD) is a serious public health problem characterized by strong cravings and uncontrollable drinking behaviors. Existing drug treatments and psychotherapy have limited effects in reducing cravings and lack objective and accurate evaluation methods. Traditional evaluation methods mostly rely on subjective reports from patients and have large deviations.

[0003] Virtual reality technology can generate a highly simulated digital environment, simulate the patient's real drinking scene through immersive experience, and combine eye tracking technology and motion capture technology to objectively record the patient's attentional bias (AB) and approach behavior (AB). Based on this, how to use virtual reality technology to evaluate alcohol dependence has become an urgent problem to be solved. Summary of the invention

[0004] In order to overcome the shortcomings of the prior art, the purpose of the present invention is to provide an individualized alcohol craving assessment method and system based on virtual reality, which has significant advantages in improving the accuracy, objectivity and individualization of assessment, and provides important support and basis for the diagnosis and treatment of alcohol dependence.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] A virtual reality-based method for individualized alcohol craving assessment, including:

[0007] Based on virtual reality technology, an alcohol cue exposure scenario is constructed according to the target population’s drinking habits and scenario characteristics;

[0008] The subjects’ first baseline alcohol craving was recorded by visual analogue scale;

[0009] The alcohol cue exposure scene is started to allow the subject to move freely in the scene, and eye tracking data and motion capture data are obtained by eye tracking technology and motion capture technology respectively; the eye tracking data include: the total duration and number of alcohol cue fixations, and the total duration and number of non-alcohol cue fixations; the motion capture data include: the total duration and number of alcohol cue pick-ups, and the total duration and number of non-alcohol cue pick-ups;

[0010] The alcohol cue exposure scenario was turned off after a preset time, and the subjects’ second baseline alcohol craving was recorded using a visual analogue rating scale;

[0011] Determining an alcohol cue fixation duration ratio and an alcohol cue fixation frequency ratio based on the eye tracking data, and determining an alcohol cue pickup duration ratio and an alcohol cue pickup frequency ratio based on the motion capture data;

[0012] The attention bias and approach behavior of the subject are analyzed in combination with the alcohol cue fixation duration ratio, the alcohol cue fixation frequency ratio, the alcohol cue pickup duration ratio, the alcohol cue pickup frequency ratio, the first baseline alcohol craving level and the first baseline alcohol craving level to generate an individualized alcohol craving assessment report.

[0013] Preferably, the alcohol clue exposure scene includes: alcohol clues and non-alcohol clues; the alcohol clues include wine cabinets, wine utensils and side dishes; the non-alcohol clues include: beverages, staple foods and fruits.

[0014] Preferably, based on virtual reality technology, an alcohol cue exposure scenario is constructed according to the target population's drinking habits and scenario characteristics, including:

[0015] Through semi-structured interviews and questionnaires, the target population's drinking scene preferences were obtained;

[0016] Conduct quantitative and qualitative analysis on the drinking scene preferences and preset cues to screen out the most representative drinking scenes, alcohol cues, and non-alcohol cues;

[0017] Based on the modeling software, the most representative drinking scenes, alcohol cues and non-alcohol cues are modeled to obtain a 3D scene model;

[0018] Setting the activity range of the subject in the scene in the 3D scene model, and adding dynamic interaction functions to the alcohol clues and non-alcohol clues;

[0019] The set 3D scene model was imported into the virtual reality device, and the interactive function of the scene was tested using an eye tracking device and motion capture gloves to obtain a constructed alcohol cue exposure scene.

[0020] Preferably, the formulas for the alcohol cue fixation duration ratio and the alcohol cue fixation frequency ratio are:

[0021] Alcohol cue fixation duration ratio = total alcohol cue fixation duration / (total alcohol cue fixation duration + total non-alcohol cue fixation duration);

[0022] Alcohol cue fixation ratio = total alcohol cue fixation / (total alcohol cue fixation + total non-alcohol cue fixation).

[0023] Preferably, the formulas for the total time and number of alcohol clue picking and the total time and number of non-alcohol clue picking are:

[0024] Alcohol cue picking time ratio = total alcohol cue picking time / (total alcohol cue picking time + total non-alcohol cue picking time);

[0025] Alcohol cue pickup frequency ratio = total alcohol cue pickup frequency / (total alcohol cue pickup frequency + total non-alcohol cue pickup frequency).

[0026] Preferably, the attention bias and approach behavior of the subject are analyzed in combination with the alcohol cue fixation duration ratio, the alcohol cue fixation frequency ratio, the alcohol cue pickup duration ratio, the alcohol cue pickup frequency ratio, the first baseline alcohol craving degree, and the second baseline alcohol craving degree to generate an individualized alcohol craving assessment report, including:

[0027] Calculate the average of the alcohol cue fixation duration ratio and the alcohol cue fixation frequency ratio, and the average of the alcohol cue pickup duration ratio and the alcohol cue pickup frequency ratio;

[0028] Attention bias and approach behavior are evaluated according to the difference between the average value and the preset value, and attention bias evaluation results and approach behavior evaluation results are obtained;

[0029] Calculating the difference between the first baseline alcohol craving level and the second baseline alcohol craving level, and evaluating the subjective craving change result according to whether the difference between the first baseline alcohol craving level and the second baseline alcohol craving level is positive or negative;

[0030] The attention bias assessment result, the approach behavior assessment result and the subjective craving change result are input into a trained individualized alcohol craving assessment model to obtain an alcohol craving result.

[0031] Preferably, the method for constructing the individualized alcohol craving assessment model comprises:

[0032] Obtain the preset attention bias assessment dataset, approach behavior assessment dataset, and subjective craving change dataset;

[0033] Build deep learning models;

[0034] The deep learning model is trained according to the attention bias evaluation data set, the approach behavior evaluation data set and the subjective craving change data to obtain a trained first classifier, a second classifier and a third classifier;

[0035] The trained classifiers are cascaded to obtain the individualized alcohol craving assessment model.

[0036] Preferably, the alcohol craving assessment report includes: attention bias assessment results, approach behavior assessment results, subjective craving change results and alcohol craving results.

[0037] A virtual reality-based individualized alcohol craving assessment system, including:

[0038] A scenario construction unit, which is used to construct alcohol cue exposure scenarios based on the target population’s drinking habits and scenario characteristics based on virtual reality technology;

[0039] a first degree calculation unit, used for recording a first baseline alcohol craving degree of the subject by a visual analog scale method;

[0040] An exposure unit is used to start an alcohol cue exposure scene, so that the subject can move freely in the scene, and obtain eye tracking data and motion capture data through eye tracking technology and motion capture technology respectively; the eye tracking data includes: the total duration and number of alcohol cue fixations, and the total duration and number of non-alcohol cue fixations; the motion capture data includes: the total duration and number of alcohol cue pick-ups, and the total duration and number of non-alcohol cue pick-ups;

[0041] a second degree calculation unit, used for closing the alcohol cue exposure scene after a preset time and recording the subject's second baseline alcohol craving degree through a visual analog scale;

[0042] a ratio calculation unit, for determining an alcohol cue fixation duration ratio and an alcohol cue fixation frequency ratio according to the eye tracking data, and determining an alcohol cue pickup duration ratio and an alcohol cue pickup frequency ratio according to the motion capture data;

[0043] An evaluation unit is used to analyze the subject's attention bias and approach behavior in combination with the alcohol cue fixation duration ratio, the alcohol cue fixation frequency ratio, the alcohol cue pickup duration ratio, the alcohol cue pickup frequency ratio, the first baseline alcohol craving level and the first baseline alcohol craving level to generate an individualized alcohol craving evaluation report.

[0044] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0045] The present invention provides a method and system for evaluating individualized alcohol craving based on virtual reality, comprising: constructing an alcohol cue exposure scene based on the drinking habits and scene characteristics of a target population based on virtual reality technology; recording a subject's first baseline alcohol craving degree by visual analog scale; starting the alcohol cue exposure scene to allow the subject to move freely in the scene, and acquiring eye tracking data and motion capture data by eye tracking technology and motion capture technology, respectively; the eye tracking data includes: total alcohol cue fixation duration and number of times, and total non-alcohol cue fixation duration and number of times; the motion capture data includes: total alcohol cue pickup duration and number of times, and total non-alcohol cue pickup duration and number of times; times; after a preset time, the alcohol cue exposure scene is closed, and the subject's second baseline alcohol craving degree is recorded by visual analog scale; the alcohol cue fixation duration ratio and the alcohol cue fixation frequency ratio are determined according to the eye tracking data, and the alcohol cue pickup duration ratio and the alcohol cue pickup frequency ratio are determined according to the motion capture data; the attention bias and approach behavior of the subject are analyzed by combining the alcohol cue fixation duration ratio, the alcohol cue fixation frequency ratio, the alcohol cue pickup duration ratio, the alcohol cue pickup frequency ratio, the first baseline alcohol craving degree and the first baseline alcohol craving degree to generate an individualized alcohol craving assessment report. The present invention has significant advantages in improving the accuracy, objectivity and individualization of assessment, and provides important support and basis for the diagnosis and treatment of alcohol dependence. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0047] Figure 1 A flow chart of a method provided by an embodiment of the present invention;

[0048] Figure 2 A schematic diagram of the system structure provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] The purpose of the present invention is to provide an individualized alcohol craving assessment method and system based on virtual reality, which has significant advantages in improving the accuracy, objectivity and individualization of the assessment, and provides important support and basis for the diagnosis and treatment of alcohol dependence.

[0051] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0052] Figure 1 A flow chart of a method provided by an embodiment of the present invention, such as Figure 1 As shown, the present invention provides an individualized alcohol craving assessment method based on virtual reality, comprising:

[0053] Step 100: Based on virtual reality technology, construct an alcohol cue exposure scenario according to the target population's drinking habits and scenario characteristics;

[0054] Step 200: Recording a first baseline alcohol craving level of the subject by visual analog scale;

[0055] Step 300: Start an alcohol cue exposure scene to allow the subject to move freely in the scene, and obtain eye tracking data and motion capture data through eye tracking technology and motion capture technology respectively; the eye tracking data includes: the total duration and number of alcohol cue fixations, and the total duration and number of non-alcohol cue fixations; the motion capture data includes: the total duration and number of alcohol cue pick-ups, and the total duration and number of non-alcohol cue pick-ups;

[0056] Step 400: closing the alcohol cue exposure scene after a preset time, and recording the subject's second baseline alcohol craving level by visual analog scale;

[0057] Step 500: determining the alcohol cue fixation duration ratio and the alcohol cue fixation frequency ratio according to the eye tracking data, and determining the alcohol cue pickup duration ratio and the alcohol cue pickup frequency ratio according to the motion capture data;

[0058] Step 600: Analyze the subject's attention bias and approach behavior by combining the alcohol cue fixation duration ratio, the alcohol cue fixation frequency ratio, the alcohol cue pickup duration ratio, the alcohol cue pickup frequency ratio, the first baseline alcohol craving level, and the first baseline alcohol craving level to generate an individualized alcohol craving assessment report.

[0059] Preferably, the alcohol clue exposure scene includes: alcohol clues and non-alcohol clues; the alcohol clues include wine cabinets, wine utensils and side dishes; the non-alcohol clues include: beverages, staple foods and fruits.

[0060] Preferably, based on virtual reality technology, an alcohol cue exposure scenario is constructed according to the target population's drinking habits and scenario characteristics, including:

[0061] Through semi-structured interviews and questionnaires, the target population's drinking scene preferences were obtained;

[0062] Conduct quantitative and qualitative analysis on the drinking scene preferences and preset cues to screen out the most representative drinking scenes, alcohol cues, and non-alcohol cues;

[0063] Based on the modeling software, the most representative drinking scenes, alcohol cues and non-alcohol cues are modeled to obtain a 3D scene model;

[0064] Setting the activity range of the subject in the scene in the 3D scene model, and adding dynamic interaction functions to the alcohol clues and non-alcohol clues;

[0065] The set 3D scene model was imported into the virtual reality device, and the interactive function of the scene was tested using an eye tracking device and motion capture gloves to obtain a constructed alcohol cue exposure scene.

[0066] Specifically, step 100 of this embodiment includes:

[0067] 1. Data collection and analysis. First, the drinking habits and scene preferences of the target population are collected through semi-structured interviews and questionnaires. This process involves in-depth communication with the respondents to understand their common drinking places, drinking methods, and specific expectations for the drinking environment. At the same time, questionnaires are designed to quantify the preferences of the respondents to ensure the comprehensiveness and representativeness of the data. The collected data will be quantitatively and qualitatively analyzed to screen out the most representative drinking scenes, alcohol clues (such as wine cabinets, wine utensils, and side dishes), and non-alcohol clues (such as beverages, staple foods, and fruits).

[0068] 2. 3D scene modeling: After determining the drinking scenes and related cues of the target population, use professional modeling software (such as Unity or UnrealEngine) to perform 3D scene modeling. Based on the collected drinking scene preferences, build a highly simulated virtual environment to ensure the realism and interactivity of alcohol cues and non-alcohol cues. During the modeling process, designers need to consider the spatial layout of the scene, the proportions and materials of the objects to ensure that the final model can truly reflect the drinking environment of the subjects.

[0069] 3. Dynamic interaction function setting: After completing the 3D scene model, set the subject's activity range in the scene and add dynamic interaction functions for alcohol cues and non-alcohol cues. This includes allowing the subject to interact with objects in the scene through motion capture gloves, such as picking up wine utensils, checking the wine in the wine cabinet, etc. The dynamic interaction function is designed to enhance the subject's sense of immersion, allowing them to freely explore the virtual environment and interact with the environment in a real way.

[0070] 4. Scene testing and optimization. Finally, the set 3D scene model is imported into the virtual reality device and tested using eye tracking equipment and motion capture gloves to verify the interactive function and user experience of the scene. During the test, the behavior and reaction of the subjects are observed, and data is collected to evaluate the effectiveness and immersion of the scene. Necessary adjustments and optimizations are made according to the test results to ensure that the constructed alcohol cue exposure scene can accurately reflect the drinking habits of the target population and provide reliable environmental support for subsequent craving assessments.

[0071] Specifically, step 200 of this embodiment includes:

[0072] 1. Subject preparation and training. Before recording the first baseline alcohol craving level, the researcher first needs to provide brief training and guidance to the subjects. The subjects will be informed of the purpose and process of the experiment to ensure that they understand how to use the visual analog scale (VAS). The researcher will explain the meaning of the score, stating that 0 points means "no alcohol craving at all" and 10 points means "extremely strong alcohol craving." In addition, the researcher will emphasize that the subjects should evaluate based on their true feelings when scoring to ensure the accuracy of the scoring.

[0073] 2. Preparation and use of scoring tools. During the preparation stage, researchers will provide scoring tools, usually a straight-line scoring table marked with 0 to 10 points, or a sliding bar displayed by an electronic device. Subjects select a score on the scoring tool to indicate their current level of craving for alcohol. To ensure the effectiveness of the scoring, researchers will ensure that the environment is quiet and free of distractions, and score before the subjects enter the virtual reality scene to obtain baseline data.

[0074] 3. Data recording and confirmation. After the subject completes the scoring, the researcher will record the score and ask the subject whether he is satisfied with the scoring result to confirm its accuracy. If the subject has questions about the score or needs to adjust it, the researcher will allow him to re-score. Finally, the first baseline alcohol craving level recorded will serve as the baseline data for subsequent analysis to help researchers evaluate the changes in the subject's psychological craving in the virtual reality alcohol cue exposure scenario.

[0075] Preferably, the formulas for the alcohol cue fixation duration ratio and the alcohol cue fixation frequency ratio are:

[0076] Alcohol cue fixation duration ratio = total alcohol cue fixation duration / (total alcohol cue fixation duration + total non-alcohol cue fixation duration);

[0077] Alcohol cue fixation ratio = total alcohol cue fixation / (total alcohol cue fixation + total non-alcohol cue fixation).

[0078] Preferably, the formulas for the total time and number of alcohol clue picking and the total time and number of non-alcohol clue picking are:

[0079] Alcohol cue picking time ratio = total alcohol cue picking time / (total alcohol cue picking time + total non-alcohol cue picking time);

[0080] Alcohol cue pickup frequency ratio = total alcohol cue pickup frequency / (total alcohol cue pickup frequency + total non-alcohol cue pickup frequency).

[0081] Specifically, in this embodiment, a virtual reality alcohol cue exposure scene is started, and the subject moves freely in the scene. During the exposure process, the olfactory stimulation of liquor is provided to enhance the cue exposure effect. The exposure process lasts for 10 minutes.

[0082] Preferably, the attention bias and approach behavior of the subject are analyzed in combination with the alcohol cue fixation duration ratio, the alcohol cue fixation frequency ratio, the alcohol cue pickup duration ratio, the alcohol cue pickup frequency ratio, the first baseline alcohol craving degree, and the second baseline alcohol craving degree to generate an individualized alcohol craving assessment report, including:

[0083] Calculate the average of the alcohol cue fixation duration ratio and the alcohol cue fixation frequency ratio, and the average of the alcohol cue pickup duration ratio and the alcohol cue pickup frequency ratio;

[0084] Attention bias and approach behavior are evaluated according to the difference between the average value and the preset value, and attention bias evaluation results and approach behavior evaluation results are obtained;

[0085] Calculating the difference between the first baseline alcohol craving level and the second baseline alcohol craving level, and evaluating the subjective craving change result according to whether the difference between the first baseline alcohol craving level and the second baseline alcohol craving level is positive or negative;

[0086] The attention bias assessment result, the approach behavior assessment result and the subjective craving change result are input into a trained individualized alcohol craving assessment model to obtain an alcohol craving result.

[0087] Preferably, the method for constructing the individualized alcohol craving assessment model comprises:

[0088] Obtain the preset attention bias assessment dataset, approach behavior assessment dataset, and subjective craving change dataset;

[0089] Build deep learning models;

[0090] The deep learning model is trained according to the attention bias evaluation data set, the approach behavior evaluation data set and the subjective craving change data to obtain a trained first classifier, a second classifier and a third classifier;

[0091] The trained classifiers are cascaded to obtain the individualized alcohol craving assessment model.

[0092] Preferably, the alcohol craving assessment report includes: attention bias assessment results, approach behavior assessment results, subjective craving change results and alcohol craving results.

[0093] Specifically, this embodiment first calculates the average values ​​of the alcohol cue fixation duration ratio, fixation frequency ratio, pickup duration ratio, and pickup frequency ratio based on the eye tracking data and motion capture data. These average values ​​can comprehensively reflect the subject's attention allocation and approach behavior intensity to the alcohol cue, providing a basis for subsequent deviation and behavior evaluation.

[0094] Compare the calculated average values ​​of fixation ratio and picking ratio with the preset values ​​and calculate the difference. The preset values ​​are usually derived from the baseline data of the normal population or the reference values ​​in the experimental design. The specific analysis is as follows:

[0095] If the average value of the fixation ratio is significantly higher than the preset value, it indicates that the subject has a strong attention bias towards alcohol cues. If the average value of the picking ratio is significantly higher than the preset value, it indicates that the subject has a strong approach behavior towards alcohol cues. Through this comparative analysis, the degree of the subject's attention bias and approach behavior can be quantified, and the attention bias evaluation results and approach behavior evaluation results can be generated. Exemplarily, the preset value can be set to 0.5.

[0096] The change in the subjective craving of the subjects was evaluated based on the difference between the first baseline alcohol craving and the second baseline alcohol craving. If the change in subjective craving is positive, it means that the subject's alcohol craving increased after exposure to alcohol cues, indicating that alcohol cues have a strong stimulating effect on their psychological craving. If the change in subjective craving is negative, it means that the subject's alcohol craving decreased after exposure to alcohol cues, which may indicate that their craving for alcohol is weak or there is an inhibitory mechanism.

[0097] The attention bias assessment results, approach behavior assessment results, and subjective craving change results are input into the trained individualized alcohol craving assessment model. The model is constructed by a deep learning algorithm and can comprehensively analyze multi-dimensional data to generate the final alcohol craving results. The specific structure of the model includes:

[0098] The first classifier is trained based on the attention bias assessment dataset and is used to assess the degree of attention bias of the subject.

[0099] The second classifier is trained based on the approach behavior evaluation dataset and is used to evaluate the approach behavior intensity of the subject.

[0100] The third classifier is trained based on the subjective craving change dataset and is used to evaluate the psychological craving changes of the subjects.

[0101] By cascading three classifiers, the model is able to comprehensively analyze multidimensional data and generate individualized alcohol craving assessment results.

[0102] Based on the alcohol craving results output by the model, combined with the attention bias assessment results, approach behavior assessment results and subjective craving change results, an individualized alcohol craving assessment report is generated. The report includes:

[0103] Attention bias assessment results: Quantifying subjects' attention allocation to alcohol cues.

[0104] Approach behavior assessment results: Quantify the intensity of the subjects' behavioral approach to alcohol cues.

[0105] Subjective craving change results: reflects the changes in the subjects' psychological craving before and after exposure to alcohol cues.

[0106] Alcohol craving results: The final evaluation results of the comprehensive analysis are used to determine the degree of alcohol craving of the subjects.

[0107] Furthermore, the construction of the individualized alcohol craving assessment model of this embodiment is based on deep learning technology, and specifically includes the following steps:

[0108] Obtain the preset attention bias assessment dataset, approach behavior assessment dataset, and subjective craving change dataset to ensure data diversity and representativeness.

[0109] A deep learning model framework was constructed, and three classifiers were designed to correspond to the evaluation tasks of attention bias, approach behavior, and subjective craving changes, respectively.

[0110] Use the corresponding data set to train the classifier and optimize the model parameters to ensure the accuracy and robustness of the classifier.

[0111] The trained classifiers are cascaded to form the final individualized alcohol craving assessment model.

[0112] Optionally, the alcohol craving assessment report generated in this embodiment can provide comprehensive and personalized analysis results for clinicians and researchers. Through the comprehensive evaluation of attention bias, approach behavior and subjective craving changes in the report, the degree of alcohol craving and its psychological characteristics of the subject can be more accurately judged. This not only helps to formulate targeted intervention measures, but also provides a scientific basis for the diagnosis and treatment of alcohol dependence, while promoting the application and development of virtual reality technology in the field of mental health.

[0113] Figure 2 A schematic diagram of the system structure provided by an embodiment of the present invention, such as Figure 2 As shown, this embodiment provides an individualized alcohol craving assessment system based on virtual reality, including:

[0114] A scenario construction unit, which is used to construct alcohol cue exposure scenarios based on the target population’s drinking habits and scenario characteristics based on virtual reality technology;

[0115] a first degree calculation unit, used for recording a first baseline alcohol craving degree of the subject by a visual analog scale method;

[0116] An exposure unit is used to start an alcohol cue exposure scene, so that the subject can move freely in the scene, and obtain eye tracking data and motion capture data through eye tracking technology and motion capture technology respectively; the eye tracking data includes: the total duration and number of alcohol cue fixations, and the total duration and number of non-alcohol cue fixations; the motion capture data includes: the total duration and number of alcohol cue pick-ups, and the total duration and number of non-alcohol cue pick-ups;

[0117] a second degree calculation unit, used for closing the alcohol cue exposure scene after a preset time and recording the subject's second baseline alcohol craving degree through a visual analog scale;

[0118] a ratio calculation unit, for determining an alcohol cue fixation duration ratio and an alcohol cue fixation frequency ratio according to the eye tracking data, and determining an alcohol cue pickup duration ratio and an alcohol cue pickup frequency ratio according to the motion capture data;

[0119] An evaluation unit is used to analyze the subject's attention bias and approach behavior in combination with the alcohol cue fixation duration ratio, the alcohol cue fixation frequency ratio, the alcohol cue pickup duration ratio, the alcohol cue pickup frequency ratio, the first baseline alcohol craving level and the first baseline alcohol craving level to generate an individualized alcohol craving evaluation report.

[0120] The beneficial effects of the present invention are as follows:

[0121] (1) The present invention uses eye tracking and motion capture technology to provide objective data and reduce the deviation caused by subjective factors in traditional evaluation methods. The subject's attention and behavior can be accurately recorded through quantitative indicators.

[0122] (2) The environment constructed by the present invention using virtual reality technology can simulate a real drinking situation, allowing the subjects to make assessments in a more immersive scene, thereby more realistically reflecting their craving for alcohol.

[0123] (3) The present invention combines individual drinking habits and psychological characteristics to generate individualized assessment reports. This personalized analysis helps to formulate more targeted intervention measures and improve treatment effects.

[0124] (4) The present invention can comprehensively analyze the psychological state of the subject, including attention bias and approach behavior, by combining the visual analog scale and behavioral data. This comprehensive analysis helps to better understand the craving mechanism of the subject.

[0125] (5) The attention bias and approach behavior analysis results included in the evaluation report of the present invention can provide a scientific basis for subsequent treatment and intervention measures, and help clinicians develop more effective treatment plans.

[0126] (6) The innovation and scientific nature of this invention provide a new perspective for the study of alcohol dependence, promote further research and application in related fields, and promote the application of virtual reality technology in the field of mental health.

[0127] (7) The present invention uses virtual reality technology for assessment, which can provide a more interesting and interactive experience, reduce the tension and discomfort that may be caused by traditional assessment methods, and enhance the subject's sense of participation and enthusiasm.

[0128] (8) The present invention can obtain data in real time during the evaluation process, facilitate timely adjustment of evaluation strategies and methods, and improve the flexibility and adaptability of the evaluation.

[0129] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0130] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for assessing individualized alcohol craving based on virtual reality, characterized in that: include: Based on virtual reality technology, an alcohol cue exposure scenario is constructed according to the target population’s drinking habits and scenario characteristics; The subjects’ first baseline alcohol craving was recorded by visual analogue scale; Start the alcohol cue exposure scene to allow the subject to move freely in the scene, and obtain eye tracking data and motion capture data using eye tracking technology and motion capture technology, respectively; The eye tracking data includes: the total duration and number of fixations on alcohol cues, and the total duration and number of fixations on non-alcohol cues; the motion capture data includes: the total duration and number of alcohol cues picked up, and the total duration and number of non-alcohol cues picked up; The alcohol cue exposure scenario was turned off after a preset time, and the subjects’ second baseline alcohol craving was recorded using a visual analogue rating scale; Determining an alcohol cue fixation duration ratio and an alcohol cue fixation frequency ratio based on the eye tracking data, and determining an alcohol cue pickup duration ratio and an alcohol cue pickup frequency ratio based on the motion capture data; The attention bias and approach behavior of the subject are analyzed in combination with the alcohol cue fixation duration ratio, the alcohol cue fixation frequency ratio, the alcohol cue pickup duration ratio, the alcohol cue pickup frequency ratio, the first baseline alcohol craving level and the first baseline alcohol craving level to generate an individualized alcohol craving assessment report.

2. The method for individualized alcohol craving assessment based on virtual reality according to claim 1, characterized in that: The alcohol clue exposure scenes include: alcohol clues and non-alcohol clues; the alcohol clues include wine cabinets, wine utensils and side dishes; the non-alcohol clues include: beverages, staple foods and fruits.

3. The method for individualized alcohol craving assessment based on virtual reality according to claim 1, characterized in that: Based on virtual reality technology, an alcohol cue exposure scenario is constructed according to the target population’s drinking habits and scenario characteristics, including: Through semi-structured interviews and questionnaires, the target population's drinking scene preferences were obtained; Conduct quantitative and qualitative analysis on the drinking scene preferences and preset cues to screen out the most representative drinking scenes, alcohol cues, and non-alcohol cues; Based on the modeling software, the most representative drinking scenes, alcohol cues and non-alcohol cues are modeled to obtain a 3D scene model; Setting the activity range of the subject in the scene in the 3D scene model, and adding dynamic interaction functions to the alcohol clues and non-alcohol clues; The set 3D scene model was imported into the virtual reality device, and the interactive function of the scene was tested using an eye tracking device and motion capture gloves to obtain a constructed alcohol cue exposure scene.

4. The method for individualized alcohol craving assessment based on virtual reality according to claim 1, characterized in that: The formulas for the alcohol cue fixation duration ratio and the alcohol cue fixation frequency ratio are: Alcohol cue fixation duration ratio = total alcohol cue fixation duration / (total alcohol cue fixation duration + total non-alcohol cue fixation duration); Alcohol cue fixation ratio = total alcohol cue fixation / (total alcohol cue fixation + total non-alcohol cue fixation).

5. The method for individualized alcohol craving assessment based on virtual reality according to claim 1, characterized in that: The formulas for the total time and number of alcohol clue picking and the total time and number of non-alcohol clue picking are: Alcohol cue picking time ratio = total alcohol cue picking time / (total alcohol cue picking time + total non-alcohol cue picking time); Alcohol cue pickup frequency ratio = total alcohol cue pickup frequency / (total alcohol cue pickup frequency + total non-alcohol cue pickup frequency).

6. The method for individualized alcohol craving assessment based on virtual reality according to claim 1, characterized in that: The attention bias and approach behavior of the subject are analyzed in combination with the alcohol cue fixation duration ratio, the alcohol cue fixation frequency ratio, the alcohol cue pickup duration ratio, the alcohol cue pickup frequency ratio, the first baseline alcohol craving degree, and the second baseline alcohol craving degree to generate an individualized alcohol craving assessment report, including: Calculate the average of the alcohol cue fixation duration ratio and the alcohol cue fixation frequency ratio, and the average of the alcohol cue pickup duration ratio and the alcohol cue pickup frequency ratio; Attention bias and approach behavior are evaluated according to the difference between the average value and the preset value, and attention bias evaluation results and approach behavior evaluation results are obtained; Calculating the difference between the first baseline alcohol craving level and the second baseline alcohol craving level, and evaluating the subjective craving change result according to whether the difference between the first baseline alcohol craving level and the second baseline alcohol craving level is positive or negative; The attention bias assessment result, the approach behavior assessment result and the subjective craving change result are input into a trained individualized alcohol craving assessment model to obtain an alcohol craving result.

7. The method for individualized alcohol craving assessment based on virtual reality according to claim 1, characterized in that: The method for constructing the individualized alcohol craving assessment model includes: Obtain the preset attention bias assessment dataset, approach behavior assessment dataset, and subjective craving change dataset; Build deep learning models; The deep learning model is trained according to the attention bias evaluation data set, the approach behavior evaluation data set and the subjective craving change data to obtain a trained first classifier, a second classifier and a third classifier; The trained classifiers are cascaded to obtain the individualized alcohol craving assessment model.

8. The method for individualized alcohol craving assessment based on virtual reality according to claim 7, characterized in that: The alcohol craving assessment report includes: attention bias assessment results, approach behavior assessment results, subjective craving change results and alcohol craving results.

9. A virtual reality-based individualized alcohol craving assessment system, characterized in that: include: A scenario construction unit, which is used to construct alcohol cue exposure scenarios based on the target population’s drinking habits and scenario characteristics based on virtual reality technology; a first degree calculation unit, used for recording a first baseline alcohol craving degree of the subject by a visual analog scale method; An exposure unit, used to initiate an alcohol cue exposure scenario so that the subject can move freely in the scenario, and to obtain eye tracking data and motion capture data through eye tracking technology and motion capture technology, respectively; The eye tracking data includes: the total duration and number of fixations on alcohol cues, and the total duration and number of fixations on non-alcohol cues; the motion capture data includes: the total duration and number of alcohol cues picked up, and the total duration and number of non-alcohol cues picked up; a second degree calculation unit, used for closing the alcohol cue exposure scene after a preset time and recording the subject's second baseline alcohol craving degree through a visual analog scale; a ratio calculation unit, for determining an alcohol cue fixation duration ratio and an alcohol cue fixation frequency ratio according to the eye tracking data, and determining an alcohol cue pickup duration ratio and an alcohol cue pickup frequency ratio according to the motion capture data; An evaluation unit is used to analyze the subject's attention bias and approach behavior in combination with the alcohol cue fixation duration ratio, the alcohol cue fixation frequency ratio, the alcohol cue pickup duration ratio, the alcohol cue pickup frequency ratio, the first baseline alcohol craving level and the first baseline alcohol craving level to generate an individualized alcohol craving evaluation report.

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