A personalized alcohol craving assessment method and system based on virtual reality

Abstract

The present invention provides a personalized alcohol craving assessment method and system based on virtual reality. The present invention first constructs an alcohol cue exposure scene and uses the visual analog scale to record the subject's first baseline alcohol craving level. The subject moves freely in the virtual scene, and at the same time obtains relevant data through eye tracking and motion capture technology, including the duration and number of gazes on alcohol cues and non-alcohol cues, as well as the duration and number of pickups of alcohol cues. After a preset time, the subject's second baseline alcohol craving level is recorded. By analyzing the eye tracking and motion capture data, the gaze and pickup ratio of alcohol cues is calculated, and combined with the baseline craving level, the subject's attention bias and approach behavior are evaluated, and finally an individualized alcohol craving assessment report is generated. The present invention 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.

Description

Technical Field

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

[0002] Alcohol dependence (AD) is a serious public health problem characterized by intense cravings and uncontrollable drinking behavior. Existing medications and psychotherapy have limited effectiveness in reducing cravings, and objective and accurate assessment methods are lacking. Traditional assessment methods rely heavily on subjective patient reports, which can be subject to significant bias.

[0003] Virtual reality technology can generate a highly realistic digital environment, simulating a patient's real-life drinking experience through an immersive experience. Combined with eye tracking and motion capture technology, it can objectively record a patient's attentional bias (AB) and approach behavior. Therefore, how to utilize virtual reality technology to assess alcohol dependence has become an urgent issue. Summary of the Invention

[0004] In order to overcome the shortcomings of the existing technology, the purpose of the present invention is to provide a personalized 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 scene characteristics;

[0008] The subjects' first baseline alcohol craving was recorded using a visual analogue scale;

[0009] An alcohol cue exposure scenario is initiated, allowing the subject to move freely within the scenario, and eye tracking data and motion capture data are obtained using eye tracking technology and motion capture technology, respectively. The eye tracking data includes: the total duration and number of fixations on the alcohol cue, and the total duration and number of fixations on the non-alcohol cue; the motion capture data includes: the total duration and number of fixations on the alcohol cue, and the total duration and number of fixations on the non-alcohol cue;

[0010] After a preset time, the alcohol cue exposure scenario was turned off, and the subjects' second baseline alcohol craving was recorded using a visual analogue 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 subject's attention bias and approach behavior are analyzed in combination with the alcohol cue gaze duration ratio, the alcohol cue gaze 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 pre-set 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 were 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 eye tracking equipment and motion capture gloves to obtain the 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 pickup duration ratio = total alcohol cue pickup duration / (total alcohol cue pickup duration + total non-alcohol cue pickup duration);

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

[0026] Preferably, the subject's attention bias and approach behavior 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 second baseline alcohol craving level 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 based on the difference between the average value and the preset value, and attention bias evaluation results and approach behavior evaluation results are obtained;

[0029] calculating a difference between the first baseline alcohol craving level and the second baseline alcohol craving level, and evaluating a subjective craving change result based on 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 assessment dataset, the approach behavior assessment dataset, 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 personalized alcohol craving assessment system, including:

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

[0039] a first degree calculation unit, configured to record a first baseline alcohol craving degree of the subject using a visual analog scale;

[0040] An exposure unit is configured to initiate an alcohol cue exposure scenario, allowing the subject to move freely in the scenario, and to 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 pick-ups on alcohol cues, and the total duration and number of pick-ups on non-alcohol cues;

[0041] a second degree calculation unit, configured to close the alcohol cue exposure scene after a preset time and record the subject's second baseline alcohol craving degree through a visual analog scale;

[0042] a ratio calculation unit, configured to determine an alcohol cue fixation duration ratio and an alcohol cue fixation frequency ratio based on the eye tracking data, and to determine an alcohol cue pickup duration ratio and an alcohol cue pickup frequency ratio based on the motion capture data;

[0043] An evaluation unit is configured to analyze the subject's attention bias and approach behavior based on 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 assessing individualized alcohol craving based on virtual reality, comprising: constructing an alcohol cue exposure scenario 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 level through a visual analog scale; starting the alcohol cue exposure scenario so that the subject can move freely in the scenario, and acquiring 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 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 fixations on alcohol cues, and the total duration and number of fixations on non-alcohol cues times; after a preset time, the alcohol cue exposure scene is closed, and the subject's second baseline alcohol craving level is recorded by visual analog scale; the alcohol cue fixation duration ratio and the alcohol cue fixation frequency ratio are determined based on the eye tracking data, and the alcohol cue pickup duration ratio and the alcohol cue pickup frequency ratio are determined based on the motion capture data; the subject's attention bias and approach behavior are analyzed based on 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. The present invention has significant advantages in improving assessment accuracy, objectivity, and individualization, 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 following briefly introduces the drawings required for use in the embodiments. 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 any creative work.

[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 clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0050] The purpose of the present invention is to provide a personalized 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.

[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 the method provided in the embodiment of the present invention is shown in FIG. Figure 1 As shown, the present invention provides a personalized 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 the subject's first baseline alcohol craving level using a visual analog scale;

[0055] Step 300: Activate an alcohol cue exposure scenario, allowing the subject to move freely within the scenario, and acquire 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 the alcohol cue, and the total duration and number of fixations on the non-alcohol cue; the motion capture data includes: the total duration and number of fixations on the alcohol cue, and the total duration and number of fixations on the non-alcohol cue.

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

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

[0058] Step 600: Analyze the subject's attention bias and approach behavior based on the alcohol cue fixation duration ratio, alcohol cue fixation frequency ratio, alcohol cue pickup duration ratio, alcohol cue pickup frequency ratio, first baseline alcohol craving level, and 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 pre-set 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 were 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 eye tracking equipment and motion capture gloves to obtain the constructed alcohol cue exposure scene.

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

[0067] 1. Data collection and analysis. First, through semi-structured interviews and questionnaires, the drinking habits and scene preferences of the target population are collected. This process involves in-depth communication with the respondents to understand their common drinking places, drinking methods, and specific expectations of the drinking environment. At the same time, a questionnaire is 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 cues (such as wine cabinets, wine utensils and side dishes) and non-alcohol cues (such as beverages, staple foods and fruits).

[0068] 2. 3D scene modeling: After determining the target population's drinking scenarios and related cues, professional modeling software (such as Unity or Unreal Engine) is used to create 3D scene models. Based on the collected drinking scene preferences, a highly simulated virtual environment is constructed to ensure the realism and interactivity of alcohol and non-alcohol cues. During the modeling process, designers need to consider the scene's spatial layout, object proportions, and materials to ensure that the final model truly reflects the subject's drinking environment.

[0069] 3. Dynamic Interaction Setup: After completing the 3D scene model, the subject's range of movement within the scene was set, and dynamic interaction features were added for both alcohol and non-alcohol cues. This included allowing the subject to interact with objects in the scene using motion capture gloves, such as picking up wine glasses or viewing the wine in the wine cabinet. The dynamic interaction features were designed to enhance the subject's sense of immersion, allowing them to freely explore the virtual environment and interact realistically.

[0070] 4. Scenario Testing and Optimization. Finally, the constructed 3D scenario model was imported into a VR device and tested using eye-tracking equipment and motion capture gloves to verify the scenario's interactive functionality and user experience. During testing, the subjects' behaviors and reactions were observed, and data was collected to evaluate the scenario's effectiveness and immersiveness. Based on the test results, necessary adjustments and optimizations were made to ensure that the constructed alcohol cue exposure scenario accurately reflected the target population's drinking habits and provided a 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 and ensure that they understand how to use the visual analog scale (VAS). The researcher will explain the meaning of the score, explaining 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 own true feelings when scoring to ensure the accuracy of the score.

[0073] 2. Preparation and Use of the Scoring Tool. During the preparation phase, researchers will provide a scoring tool, typically a linear scale marked from 0 to 10, or a sliding bar displayed on an electronic device. Subjects will select a score on the scoring tool to represent their current level of alcohol craving. To ensure the validity of the scoring, researchers will ensure a quiet and distraction-free environment and conduct the scoring before the subject enters 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 if they are satisfied with the result to confirm its accuracy. If the subject has questions about the score or needs to make adjustments, the researcher will allow them to re-score. Ultimately, the recorded first baseline alcohol craving level will serve as the baseline data for subsequent analysis, helping researchers assess the changes in the subject's psychological craving during 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 pickup duration ratio = total alcohol cue pickup duration / (total alcohol cue pickup duration + total non-alcohol cue pickup duration);

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

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

[0082] Preferably, the subject's attention bias and approach behavior 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 second baseline alcohol craving level 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 based on the difference between the average value and the preset value, and attention bias evaluation results and approach behavior evaluation results are obtained;

[0085] calculating a difference between the first baseline alcohol craving level and the second baseline alcohol craving level, and evaluating a subjective craving change result based on 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 assessment dataset, the approach behavior assessment dataset, 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 example first calculates the average of the alcohol cue fixation duration ratio, fixation count ratio, pickup duration ratio, and pickup count ratio based on eye tracking and motion capture data. These averages comprehensively reflect the subject's attention allocation and approach behavior to the alcohol cue, providing a basis for subsequent deviation and behavioral assessment.

[0094] Compare the calculated average fixation ratio and average pickup 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 fixation ratio is significantly higher than a preset value, it indicates that the subject has a strong attentional bias towards alcohol cues. If the average pickup ratio is significantly higher than a 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 attentional bias and approach behavior can be quantified, and an attentional bias assessment result and an approach behavior assessment result can be generated. For example, the preset value can be set to 0.5.

[0096] The difference between the first and second baseline alcohol craving levels was used to assess changes in the subject's subjective craving. A positive change in subjective craving indicates an increase in the subject's alcohol craving after alcohol cue exposure, suggesting that alcohol cues have a strong stimulating effect on their psychological craving. A negative change in subjective craving indicates a decrease in the subject's alcohol craving after alcohol cue exposure, possibly indicating a weaker craving or the presence of an inhibitory mechanism.

[0097] The results of attention bias assessment, approach behavior assessment, and subjective craving change are input into a trained individualized alcohol craving assessment model. This model, constructed using a deep learning algorithm, comprehensively analyzes 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 intensity of the subject's approach behavior.

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

[0101] By cascading three classifiers, the model is able to comprehensively analyze multidimensional data and generate personalized 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] Attentional 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 clinicians and researchers with comprehensive, personalized analysis results. Through a comprehensive assessment of attentional biases, approach behavior, and subjective craving changes in the report, a more accurate assessment of the subject's alcohol craving intensity and psychological characteristics can be made. This not only facilitates the development of targeted interventions but also provides a scientific basis for the diagnosis and treatment of alcohol dependence, while also 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 is shown in FIG. Figure 2 As shown, this embodiment provides a personalized alcohol craving assessment system based on virtual reality, including:

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

[0115] a first degree calculation unit, configured to record a first baseline alcohol craving degree of the subject using a visual analog scale;

[0116] An exposure unit is configured to initiate an alcohol cue exposure scenario, allowing the subject to move freely in the scenario, and to 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 pick-ups on alcohol cues, and the total duration and number of pick-ups on non-alcohol cues;

[0117] a second degree calculation unit, configured to close the alcohol cue exposure scene after a preset time and record the subject's second baseline alcohol craving degree through a visual analog scale;

[0118] a ratio calculation unit, configured to determine an alcohol cue fixation duration ratio and an alcohol cue fixation frequency ratio based on the eye tracking data, and to determine an alcohol cue pickup duration ratio and an alcohol cue pickup frequency ratio based on the motion capture data;

[0119] An evaluation unit is configured to analyze the subject's attention bias and approach behavior based on 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) This invention uses eye tracking and motion capture technology to provide objective data, reducing the bias 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 subjects to conduct evaluations 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 a personalized assessment report. This personalized analysis helps to formulate more targeted intervention measures and improve treatment effects.

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

[0125] (5) The attention bias and approach behavior analysis results contained 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] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0130] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A method for individualized alcohol craving assessment 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 scene characteristics; The subjects' first baseline alcohol craving was recorded using a visual analogue scale; An alcohol cue exposure scenario is initiated to allow the subject to move freely in the scenario, and eye tracking data and motion capture data are acquired 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 pick-ups on alcohol cues, and the total duration and number of pick-ups on non-alcohol cues; After a preset time, the alcohol cue exposure scenario was turned off, and the subjects' second baseline alcohol craving was recorded using a visual analogue 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; analyzing the subject's attention bias and approach behavior based on 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 second baseline alcohol craving level to generate a personalized alcohol craving assessment report; The subject's attention bias and approach behavior 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 second baseline alcohol craving level to generate a personalized alcohol craving assessment report, including: Calculate the average of the alcohol cue fixation duration ratio and the alcohol cue fixation frequency ratio, as well as the average of the alcohol cue pickup duration ratio and the alcohol cue pickup frequency ratio; Attention bias and approach behavior are evaluated based on the difference between the average value of the alcohol cue fixation duration ratio and the alcohol cue fixation frequency ratio and a preset value, and the difference between the average value of the alcohol cue pickup duration ratio and the alcohol cue pickup frequency ratio and a preset value, to obtain an attention bias evaluation result and an approach behavior evaluation result; calculating a difference between the first baseline alcohol craving level and the second baseline alcohol craving level, and evaluating a subjective craving change result based on 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.

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 scene 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 pre-set 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 were 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 eye tracking equipment and motion capture gloves to obtain the 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 alcohol clue picking duration ratio and the alcohol clue picking times ratio are: Alcohol cue pickup duration ratio = total alcohol cue pickup duration / (total alcohol cue pickup duration + total non-alcohol cue pickup duration); Alcohol cue pickup ratio = total alcohol cue pickup times / (total alcohol cue pickup times + total non-alcohol cue pickup times).

6. 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 assessment dataset, the approach behavior assessment dataset, and the subjective craving change dataset 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.

7. The method for individualized alcohol craving assessment based on virtual reality according to claim 6, 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.

8. A virtual reality-based individualized alcohol craving assessment system, characterized in that: include: A scenario construction unit is used to construct alcohol cue exposure scenarios based on the target population's drinking habits and scenario characteristics using virtual reality technology; a first degree calculation unit, configured to record a first baseline alcohol craving degree of the subject using a visual analog scale; An exposure unit, configured to initiate an alcohol cue exposure scenario, allowing the subject to move freely in the scenario, and to acquire 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 pick-ups on alcohol cues, and the total duration and number of pick-ups on non-alcohol cues; a second degree calculation unit, configured to close the alcohol cue exposure scene after a preset time and record the subject's second baseline alcohol craving degree through a visual analog scale; a ratio calculation unit, configured to determine an alcohol cue fixation duration ratio and an alcohol cue fixation frequency ratio based on the eye tracking data, and to determine an alcohol cue pickup duration ratio and an alcohol cue pickup frequency ratio based on the motion capture data; an assessment unit, configured to analyze the subject's attention bias and approach behavior based on 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 second baseline alcohol craving level to generate an individualized alcohol craving assessment report; The subject's attention bias and approach behavior 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 second baseline alcohol craving level to generate a personalized 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 based on the difference between the average value of the alcohol cue fixation duration ratio and the alcohol cue fixation frequency ratio and a preset value, and the difference between the average value of the alcohol cue pickup duration ratio and the alcohol cue pickup frequency ratio and a preset value, to obtain an attention bias evaluation result and an approach behavior evaluation result; calculating a difference between the first baseline alcohol craving level and the second baseline alcohol craving level, and evaluating a subjective craving change result based on 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.

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