Medical intelligent treatment system

Abstract

The invention discloses a medical intelligent treatment system, and relates to the technical field of treatment systems. The system comprises a data integration and analysis module, the output end and the input end of the data integration and analysis module are electrically connected with an emotion recognition module, and the output end and the input end of the data integration and analysis module are electrically connected with a psychological support and intervention module. Through multi-module cooperation, an emotional disorder symptom network is constructed, a core intervention node is accurately determined, the drug treatment accuracy is improved, adverse effects caused by individual differences are reduced, an exclusive emotion regulation scheme is formulated through the personalized intervention scheme generation sub-module, for example, specific courses are customized for patients associated with anxiety and wine dependence, and meanwhile, the emotion regulation effect is improved. The longitudinal dynamic analysis sub-module continuously tracks patient data, updates a symptom network model every two weeks, timely captures subtle changes of illness conditions, and comprehensively meets complex and diversified treatment requirements of wine-dependent patients.

Description

Technical Field

[0001] The present invention relates to the technical field of treatment systems, and particularly to a medical intelligent treatment system. Background Art

[0002] In recent years, the research on the emotional disorders of alcohol-dependent patients has attracted wide attention. In particular, the influence of alexithymia, a type of emotional regulation disorder, in the formation and maintenance of alcohol dependence has received a lot of empirical support. In the study of alcohol dependence, network analysis can not only reveal the interaction patterns of alexithymia, but also help identify the potential mechanisms affecting alcohol use.

[0003] Traditional treatment methods mainly include drug treatment, such as using drugs like naltrexone to inhibit alcohol addiction. However, the precise control of drug dosage depends on the doctor's experience, and there are individual differences in the drug response of some patients, which easily leads to poor treatment effects or obvious side effects. In terms of psychological counseling, the one-on-one consultation mode is mostly adopted, and the counselor formulates a treatment plan for the patient based on subjective judgment. However, the professional levels and experiences of different counselors vary greatly, making it difficult to ensure the consistency and accuracy of treatment. At the same time, limited by human and time costs, the traditional treatment mode is difficult to conduct long-term and high-frequency dynamic monitoring of patients, and it is impossible to capture the subtle changes in the patient's condition in a timely manner, which greatly limits the treatment effect and is difficult to fully meet the diverse treatment needs of alcohol-dependent patients.

[0004] Therefore, we provide a medical intelligent treatment system to solve the above problems. Summary of the Invention

[0005] The purpose of the present invention is to provide a medical intelligent treatment system. Through the cooperation of an emotion recognition module, a psychological support and intervention module, and a data integration and analysis module, it solves the problems in the prior art that traditional treatment methods rely more on the subjective judgment and experience of medical staff, and there are obvious deficiencies in accuracy, personalization, and long-term dynamic monitoring of patients, making it difficult to fully meet the diverse treatment needs of alcohol-dependent patients.

[0006] To solve the above technical problems, the present invention is realized through the following technical solutions:

[0007] The present invention is a medical intelligent treatment system, including a data integration and analysis module. The output end and the input end of the data integration and analysis module are both electrically connected to an emotion recognition module, and the output end and the input end of the data integration and analysis module are both electrically connected to a psychological support and intervention module; the data integration and analysis module includes a data collection sub-module, a network construction sub-module, a longitudinal dynamic analysis sub-module, and a randomized controlled analysis sub-module. The data collection sub-module, the network construction sub-module, the longitudinal dynamic analysis sub-module, and the randomized controlled analysis sub-module are respectively bidirectionally electrically connected to the emotion recognition module, and the data collection sub-module, the network construction sub-module, the longitudinal dynamic analysis sub-module, and the randomized controlled analysis sub-module are respectively bidirectionally electrically connected to the psychological support and intervention module; the emotion recognition module includes a facial expression recognition sub-module, a tone and intonation recognition sub-module, and a body movement recognition sub-module. The facial expression recognition sub-module, the tone and intonation recognition sub-module, and the body movement recognition sub-module are all bidirectionally electrically connected to the data integration and analysis module. The psychological support and intervention module includes a personalized intervention plan generation sub-module, an intervention implementation sub-module, and an effect evaluation sub-module. The personalized intervention plan generation sub-module, the intervention implementation sub-module, and the effect evaluation sub-module are all bidirectionally electrically connected to the data integration and analysis module. By the data integration and analysis module being bidirectionally electrically connected to the emotion recognition module and the psychological support and intervention module respectively, the emotion recognition results, the multi-source data of the patient, and the intervention effect data can be comprehensively analyzed. For example, the emotion data provided by the facial expression sub-module, the tone and intonation sub-module, and the body movement recognition sub-module are integrated by the data collection sub-module, and then the network construction sub-module analyzes the associations of various symptoms, providing an accurate basis for formulating a plan for the psychological support and intervention module, avoiding the traditional treatment relying solely on the subjective judgment of medical staff, and improving the accuracy of diagnosis and treatment. The longitudinal dynamic analysis sub-module continuously tracks the patient's data to construct a dynamic network model, which can grasp the changes of the patient's alcohol dependence and related symptoms over time in real time. The randomized controlled analysis sub-module evaluates the intervention effect by comparing the network models of the experimental group and the control group, and adjusts the intervention plan accordingly to achieve personalized treatment and long-term dynamic monitoring, making up for the deficiencies of traditional treatment.

[0008] The present invention is further configured such that user profile management modules are electrically connected to both the output end and the input end of the data integration and analysis module. Reminder and appointment modules are electrically connected to both the output end and the input end of the data integration and analysis module. Social support modules are electrically connected to both the output end and the input end of the data integration and analysis module. Knowledge base modules are electrically connected to both the output end and the input end of the data integration and analysis module. Emergency assistance modules are electrically connected to both the output end and the input end of the data integration and analysis module. The data integration and analysis module is bidirectionally connected to the user profile management module, the reminder and appointment module, the social support module, the knowledge base module, and the emergency assistance module, enriching the treatment system. The user profile management module facilitates medical staff to comprehensively understand patients. The reminder and appointment module ensures the timely progress of treatment. The social support module promotes patient communication and mutual assistance. The knowledge base module provides knowledge popularization. The emergency assistance module responds to emergencies, comprehensively meeting the diverse treatment needs of alcohol-dependent patients.

[0009] The present invention is further configured such that sleep monitoring modules are electrically connected to both the output end and the input end of the data integration and analysis module. Exercise guidance modules are electrically connected to both the output end and the input end of the data integration and analysis module. Diet advice modules are electrically connected to both the output end and the input end of the data integration and analysis module. System setting modules are electrically connected to both the output end and the input end of the data integration and analysis module. Data backup and recovery modules are electrically connected to both the output end and the input end of the data integration and analysis module. The sleep monitoring module, the exercise guidance module, and the diet advice module are connected to the data integration and analysis module, assisting treatment from multiple aspects of life. The sleep monitoring module provides data for understanding the overall health status of patients. The exercise guidance module and the diet advice module customize plans based on the patient's situation, promoting physical recovery and collaborating with psychotherapy to achieve the comprehensive physical and mental rehabilitation of alcohol-dependent patients. The system setting module ensures the user experience, and the data backup and recovery module ensures data security and improves system stability.

[0010] The present invention is further configured such that the user profile management module includes a basic information sub-module, a medical history recording sub-module, a psychological assessment sub-module, and a profile retrieval sub-module. The basic information sub-module, the medical history recording sub-module, the psychological assessment sub-module, and the profile retrieval sub-module are all bidirectionally electrically connected to the data integration and analysis module.

[0011] The present invention is further configured such that the reminder and appointment module includes a reminder setting sub-module, a reservation management sub-module, a schedule matching sub-module, and a notification feedback sub-module. The reminder setting sub-module, the reservation management sub-module, the schedule matching sub-module, and the notification feedback sub-module are all bidirectionally electrically connected to the data integration and analysis module.

[0012] The present invention is further configured such that the social support module includes a community communication sub-module, a topic classification sub-module, a medical staff Q&A sub-module, and a reporting management sub-module, and the community communication sub-module, the topic classification sub-module, the medical staff Q&A sub-module, and the reporting management sub-module are all bidirectionally electrically connected to the data integration and analysis module.

[0013] The present invention is further configured such that the knowledge base module includes a knowledge classification sub-module, a content editing sub-module, a multimedia display sub-module, and a search query sub-module, and the knowledge classification sub-module, the content editing sub-module, the multimedia display sub-module, and the search query sub-module are all bidirectionally electrically connected to the data integration and analysis module.

[0014] The present invention is further configured such that the sleep monitoring module includes an image acquisition sub-module, a data processing sub-module, a sleep index calculation sub-module, and a report generation sub-module, and the image acquisition sub-module, the data processing sub-module, the sleep index calculation sub-module, and the report generation sub-module are all bidirectionally electrically connected to the data integration and analysis module.

[0015] The present invention is further configured such that the data backup and recovery module includes a backup policy setting sub-module, a data backup execution sub-module, a data storage sub-module, and a data recovery sub-module, and the backup policy setting sub-module, the data backup execution sub-module, the data storage sub-module, and the data recovery sub-module are all bidirectionally electrically connected to the data integration and analysis module.

[0016] The present invention is further configured such that the system setting module includes a display setting sub-module, a notification setting sub-module, a privacy setting sub-module, and a system update sub-module, and the display setting sub-module, the notification setting sub-module, the privacy setting sub-module, and the system update sub-module are all bidirectionally electrically connected to the data integration and analysis module.

[0017] The present invention has the following beneficial effects:

[0018] 1. Through the cooperation of multiple modules, the data integration and analysis module combines the multi-source data of patients collected by the emotion recognition module to construct an alexithymia symptom network, accurately determine the core intervention nodes, provide a scientific basis for personalized drug treatment, avoid relying solely on the subjective experience of doctors, improve the accuracy of drug treatment, and reduce the adverse effects caused by individual differences.

[0019] 2. The psychological support and intervention module of the present invention formulates a personalized emotion regulation plan through the personalized intervention plan generation sub-module according to the individual situation of the patient. For example, a specific course is customized for patients with the association between anxiety and alcohol dependence. At the same time, the longitudinal dynamic analysis sub-module continuously tracks the patient's data, updates the symptom network model every two weeks, and timely captures the subtle changes in the condition, fully meeting the complex and diverse treatment needs of alcohol-dependent patients. Description of the Drawings

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below.

[0021] Figure 1 It is the first system schematic diagram of the medical intelligent treatment system;

[0022] Figure 2 It is the second system schematic diagram of the medical intelligent treatment system;

[0023] Figure 3 It is the system diagram of the user profile management module in the medical intelligent treatment system;

[0024] Figure 4 It is the system diagram of the reminder and appointment module in the medical intelligent treatment system;

[0025] Figure 5 It is the system diagram of the social support module in the medical intelligent treatment system;

[0026] Figure 6 It is the system diagram of the knowledge base module in the medical intelligent treatment system;

[0027] Figure 7 It is the system diagram of the sleep monitoring module in the medical intelligent treatment system;

[0028] Figure 8 It is the system diagram of the data backup and recovery module in the medical intelligent treatment system;

[0029] Figure 9 It is the system diagram of the system settings module in the medical intelligent treatment system;

[0030] Figure 10 It is the flowchart of system startup and user login in the medical intelligent treatment system;

[0031] Figure 11 It is the flowchart of data collection and integration in the medical intelligent treatment system;

[0032] Figure 12 It is the flowchart of data integration and analysis in the medical intelligent treatment system;

[0033] Figure 13 It is the flowchart of emotion recognition and psychological support in the medical intelligent treatment system;

[0034] Figure 14 It is the flowchart of health management and intervention in the medical intelligent treatment system;

[0035] Figure 15 It is the flowchart of user feedback and system update in the medical intelligent treatment system. Specific embodiments

[0036] The technical solutions in the embodiments of the present invention will be described below with reference to the accompanying drawings in the embodiments of the present invention. The described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Specific Embodiment 1

[0038] Please refer to Figures 1 - 15 , the present invention is a medical intelligent treatment system, including a data integration and analysis module. Both the output end and the input end of the data integration and analysis module are electrically connected to an emotion recognition module, and both the output end and the input end of the data integration and analysis module are electrically connected to a psychological support and intervention module; the data integration and analysis module includes a data collection sub-module, a network construction sub-module, a longitudinal dynamic analysis sub-module, and a randomized controlled analysis sub-module. The data collection sub-module, the network construction sub-module, the longitudinal dynamic analysis sub-module, and the randomized controlled analysis sub-module are respectively bidirectionally electrically connected to the emotion recognition module, and the data collection sub-module, the network construction sub-module, the longitudinal dynamic analysis sub-module, and the randomized controlled analysis sub-module are respectively bidirectionally electrically connected to the psychological support and intervention module; the emotion recognition module includes a facial expression recognition sub-module, a tone and intonation recognition sub-module, and a body movement recognition sub-module. The facial expression recognition sub-module, the tone and intonation recognition sub-module, and the body movement recognition sub-module are all bidirectionally electrically connected to the data integration and analysis module. The psychological support and intervention module includes a personalized intervention plan generation sub-module, an intervention implementation sub-module, and an effect evaluation sub-module. The personalized intervention plan generation sub-module, the intervention implementation sub-module, and the effect evaluation sub-module are all bidirectionally electrically connected to the data integration and analysis module.

[0039] Specifically: by bidirectionally electrically connecting the data integration and analysis module with the emotion recognition module and the psychological support and intervention module respectively, the emotion recognition results, the multi-source data of the patient, and the intervention effect data can be comprehensively analyzed. For example, the emotion data provided by the facial expression sub-module, the tone and intonation sub-module, and the body movement recognition sub-module are integrated by the data collection sub-module, and then the network construction sub-module analyzes the association of each symptom, providing an accurate basis for formulating a plan for the psychological support and intervention module, avoiding the traditional treatment relying solely on the subjective judgment of medical staff, improving the accuracy of diagnosis and treatment. The longitudinal dynamic analysis sub-module continuously tracks the patient data to construct a dynamic network model, which can grasp the changes of the patient's alcohol dependence and related symptoms over time in real time. The randomized controlled analysis sub-module evaluates the intervention effect by comparing the network models of the experimental group and the control group, and adjusts the intervention plan accordingly to achieve personalized treatment and long-term dynamic monitoring, making up for the deficiencies of traditional treatment. Specific Embodiment 2

[0041] Please refer to Figures 1 - 15, on the basis of the first specific embodiment, the output end and the input end of the data integration and analysis module are electrically connected to a user profile management module, the output end and the input end of the data integration and analysis module are electrically connected to a reminder and appointment module, the output end and the input end of the data integration and analysis module are electrically connected to a social support module, the output end and the input end of the data integration and analysis module are electrically connected to a knowledge base module, the output end and the input end of the data integration and analysis module are electrically connected to an emergency assistance module, the output end and the input end of the data integration and analysis module are electrically connected to a sleep monitoring module, the output end and the input end of the data integration and analysis module are electrically connected to an exercise guidance module, the output end and the input end of the data integration and analysis module are electrically connected to a diet advice module, the output end and the input end of the data integration and analysis module are electrically connected to a system settings module, the output end and the input end of the data integration and analysis module are electrically connected to a data backup and recovery module. The user profile management module includes a basic information sub-module, a medical history record sub-module, a psychological assessment sub-module, and a profile retrieval sub-module. The basic information sub-module, the medical history record sub-module, the psychological assessment sub-module, and the profile retrieval sub-module are all bidirectionally electrically connected to the data integration and analysis module. The reminder and appointment module includes a reminder setting sub-module, an appointment management sub-module, a schedule matching sub-module, and a notification feedback sub-module. The reminder setting sub-module, the appointment management sub-module, the schedule matching sub-module, and the notification feedback sub-module are all bidirectionally electrically connected to the data integration and analysis module. The social support module includes a community communication sub-module, a topic classification sub-module, a medical staff Q&A sub-module, and a reporting management sub-module. The community communication sub-module, the topic classification sub-module, the medical staff Q&A sub-module, and the reporting management sub-module are all bidirectionally electrically connected to the data integration and analysis module. The knowledge base module includes a knowledge classification sub-module, a content editing sub-module, a multimedia display sub-module, and a search query sub-module. The knowledge classification sub-module, the content editing sub-module, the multimedia display sub-module, and the search query sub-module are all bidirectionally electrically connected to the data integration and analysis module. The sleep monitoring module includes an image acquisition sub-module, a data processing sub-module, a sleep index calculation sub-module, and a report generation sub-module. The image acquisition sub-module, the data processing sub-module, the sleep index calculation sub-module, and the report generation sub-module are all bidirectionally electrically connected to the data integration and analysis module. The data backup and recovery module includes a backup strategy setting sub-module, a data backup execution sub-module, a data storage sub-module, and a data recovery sub-module. The backup strategy setting sub-module, the data backup execution sub-module, the data storage sub-module, and the data recovery sub-module are all bidirectionally electrically connected to the data integration and analysis module. The system settings module includes a display settings sub-module, a notification settings sub-module, a privacy settings sub-module, and a system update sub-module. The display settings sub-module, the notification settings sub-module, the privacy settings sub-module, and the system update sub-module are all bidirectionally electrically connected to the data integration and analysis module.

[0042] Specifically: The data integration and analysis module is bi-directionally connected to the user profile management module, reminder and appointment module, social support module, knowledge base module, and emergency assistance module, enriching the treatment system. The user profile management module enables medical staff to comprehensively understand patients. The reminder and appointment module ensures the timely progress of treatment. The social support module promotes patient communication and mutual assistance. The knowledge base module provides knowledge popularization. The emergency assistance module responds to emergencies, fully meeting the diverse treatment needs of alcohol-dependent patients. The sleep monitoring module, exercise guidance module, and diet advice module are connected to the data integration and analysis module, assisting treatment from multiple aspects of life. The sleep monitoring module provides data for understanding the overall health status of patients. The exercise guidance module and diet advice module customize plans based on the patient's situation to promote physical recovery and cooperate with psychotherapy to achieve the comprehensive physical and mental rehabilitation of alcohol-dependent patients. The system settings module guarantees the user experience. The data backup and recovery module ensures data security and enhances system stability. Each sub-module of the user profile management module is bi-directionally connected to the data integration and analysis module. The basic information sub-module, medical history record sub-module, and psychological assessment sub-module provide comprehensive patient information for medical staff. The file retrieval sub-module facilitates quick query, enabling medical staff to formulate more accurate personalized treatment plans based on accurate information and improve the treatment effect. Each sub-module of the reminder and appointment module is connected to the data integration and analysis module. The reminder settings sub-module meets the personalized reminder needs of patients. The appointment management sub-module and schedule matching sub-module ensure reasonable treatment arrangements. The notification feedback sub-module promotes doctor-patient communication, improves patients' compliance with treatment, and ensures the smooth progress of treatment. Each sub-module of the social support module is connected to the data integration and analysis module. The community communication sub-module provides a communication platform for patients. The topic classification sub-module facilitates patients to find resonance. The medical staff Q&A sub-module provides professional guidance. The reporting management sub-module maintains community order, creates a good social environment, and enhances patients' confidence and motivation for rehabilitation. Each sub-module of the knowledge base module is connected to the data integration and analysis module. The knowledge classification sub-module and content editing sub-module ensure the accurate classification and update of knowledge. The multimedia display sub-module and search query sub-module facilitate patients to obtain knowledge. Medical staff can also optimize treatment plans based on the knowledge base to assist in treatment decision-making. Each sub-module of the sleep monitoring module is connected to the data integration and analysis module. The image acquisition sub-module, data processing sub-module, and sleep index calculation sub-module deeply analyze patients' sleep data. The report generation sub-module intuitively presents the results, providing more dimensional data for alcohol dependence treatment, helping medical staff comprehensively understand patients' physical and mental states, and improving treatment plans. Each sub-module of the data backup and recovery module is connected to the data integration and analysis module. The backup strategy setting sub-module and data backup execution sub-module regularly back up data. The data storage sub-module stores data securely. The data recovery sub-module quickly recovers data in case of data loss, ensuring the security of patients' treatment data and ensuring that the treatment process is not affected by data problems. Each sub-module of the system settings module is connected to the data integration and analysis module. The display settings sub-module and notification settings sub-module meet the personalized usage needs of patients.The privacy settings sub-module ensures the security of patient information. The system update sub-module keeps the system up-to-date, enhances the system's adaptability and user experience, and promotes better use of the treatment system by patients. Specific Embodiment Three

[0044] Embodiment of Randomized Controlled Experiment for Alcohol-Dependent Patients

[0045] Experiment Preparation

[0046] Patient Recruitment and Grouping: 150 alcohol-dependent patients were recruited through channels such as hospitals and alcohol abstinence support organizations. The patients were randomly divided into an experimental group and a control group using a random number table method, with 75 patients in each group. Ensure that there are no significant differences between the two groups of patients in terms of age, gender, drinking history, severity of alcohol dependence, etc., to ensure the comparability of the experiment.

[0047] System Setup and Training: Laptop computers installed with the medical intelligent treatment system were equipped for the patients participating in the experiment, and the patients were trained on the system's use to ensure that they could operate the emotion recognition module proficiently and understand the functions of each module. At the same time, the medical staff participating in the experiment were trained on the system to familiarize them with the operation of the data integration and analysis module and the experimental process.

[0048] Experimental Implementation Phase

[0049] Intervention for the Experimental Group

[0050] Carrying out Emotional Regulation Intervention: During the 12-week experiment, the psychological support and intervention module of the medical intelligent treatment system was used to conduct emotional regulation intervention for the patients in the experimental group. The personalized intervention plan generation sub-module developed a personalized emotional regulation intervention plan for each patient based on the patient's individual situation, such as information such as the patient's psychological assessment results and medical history obtained through the user profile management module. For example, for some patients whose anxiety is closely related to alcohol dependence, the plan includes online cognitive behavioral therapy courses four times a week to help patients identify and change negative thinking patterns caused by alcohol dependence; relaxation training three times a week, with exercises such as deep breathing and progressive muscle relaxation guided by audio to relieve anxiety.

[0051] Intervention Implementation and Feedback Collection: The intervention implementation sub-module pushed intervention content to the patients in the experimental group through the system. The patients studied and practiced according to the course schedule and provided feedback information such as learning feelings and problems encountered in the system. This feedback information was transmitted in real-time to the data collection sub-module in the data integration and analysis module.

[0052] Control group treatment: Patients in the control group only received conventional alcohol dependence treatment, including regular doctor follow-ups and drug treatment (such as naltrexone, etc.), but did not receive emotional regulation intervention based on the medical intelligent treatment system. During the experiment, patients in the control group also used the system's emotion recognition module and user profile management module, etc. for data collection, which was used for subsequent comparative analysis with the experimental group.

[0053] Data collection and monitoring

[0054] Multi-module data collection: During the experiment, the emotion recognition module was continuously working. The facial expression recognition sub-module, tone and intonation recognition sub-module, and body movement recognition sub-module captured the emotion-related information of patients in real time and transmitted it to the data collection sub-module of the data integration and analysis module. The sleep monitoring module started the image acquisition sub-module through the computer camera every night at the patient's home to monitor the patient's sleep situation. The data processing sub-module extracted information such as respiratory rate and micro-expression changes, and the sleep index calculation sub-module calculated indicators such as sleep onset time, awakening times, and sleep depth. The report generation sub-module generated a sleep monitoring report and transmitted it to the data collection sub-module. At the same time, the user profile management module updated data such as the patient's basic information and changes in physical condition during the treatment process.

[0055] Construction of the alexithymia symptom network: The network construction sub-module in the data integration and analysis module constructed a symptom network for each patient based on the multi-source data collected, with various symptoms of alcohol-dependent patients (including alexithymia-related symptoms, such as difficulty in recognizing one's own emotions and difficulty in expressing emotions) as nodes and the mutual relationships between symptoms as edges. The longitudinal dynamic analysis sub-module continuously tracked the patient data and updated the symptom network model every two weeks, recording the changes in the network structure and node indicators (such as the degree of the node, betweenness centrality, etc.).

[0056] Experimental result analysis stage

[0057] Data comparative analysis

[0058] Changes in the alexithymia symptom network: After the experiment, the effect evaluation sub-module, with the help of the data integration and analysis module, compared the dynamic changes in the alexithymia symptom network of patients in the experimental group and the control group before and after the intervention. By analyzing the key indicators of the network model, such as the degree of the node, betweenness centrality, etc., the core intervention nodes of alexithymia were determined. For example, it was found that in some patients in the experimental group, the betweenness centrality of the node related to anxiety emotion in the alexithymia symptom network decreased significantly after the intervention, indicating that the influence of this node in the symptom network weakened, and the associative and conductive effects of anxiety emotion on other symptoms decreased.

[0059] Emotional management ability assessment: Using the data from the emotion recognition module in the system and the feedback of patients during the intervention process, combined with a professional emotional management ability assessment scale (such as the Emotional Intelligence Scale), the emotional management abilities of the experimental group and the control group of patients were evaluated. The results showed that after 12 weeks of emotional regulation intervention, the scores of the emotional management ability of the experimental group patients were significantly higher than those of the control group, indicating that the intervention effectively improved the emotional management ability of the experimental group patients.

[0060] Relapse rate statistics: By conducting regular follow-up visits (such as follow-up visits 3 months and 6 months after the end of the experiment), the relapse situations of the experimental group and the control group of patients were statistically analyzed. The results found that the relapse rate of the experimental group patients was significantly lower than that of the control group, proving that the emotional regulation intervention based on the medical intelligent treatment system can significantly reduce the relapse rate of patients.

[0061] Analysis of economic and social benefits

[0062] Economic benefits: From the perspective of the utilization of medical resources, due to the reduction in the relapse rate of the experimental group patients, the medical treatment costs, hospitalization costs, etc. caused by repeated alcoholism were reduced. At the same time, after the physical condition of the patients improved, they could return to work faster and create economic value. Through the calculation of the cost-benefit analysis model, it was concluded that implementing this emotional regulation intervention measure has significant economic benefits in the long term.

[0063] Social benefits: The reduction in the relapse rate of patients has reduced family conflicts and social security problems caused by alcoholism, which helps to improve family relationships and maintain social stability. In addition, this experiment provides new ideas and methods for the treatment of alcohol addiction, which can be popularized and applied to a wider group of alcohol-dependent patients, having good social benefits.

[0064] Experiment summary and promotion

[0065] Based on the experimental results, clarify the core intervention nodes of alexithymia, such as the key roles of anxiety emotions, sleep disorders, etc. in the symptom network of alcohol-dependent patients. Based on this, further optimize the personalized intervention plan generation sub-module of the medical intelligent treatment system, so that it can more accurately formulate intervention measures for these core nodes.

[0066] Write the experimental results into an academic paper for publication, participate in relevant medical conferences for communication, and promote this innovative alcohol addiction treatment method to the medical industry, bringing hope for rehabilitation to more alcohol-dependent patients and promoting the development of the alcohol addiction treatment field.

[0067] The working principle of the present invention is as follows: the emotion recognition module serves as the front end of information collection, and the facial expression recognition submodule, the tone and intonation recognition submodule and the body movement recognition submodule capture the patient's emotion-related information in real time through devices such as computer cameras and microphones. This information is then transmitted to the data collection submodule in the data integration and analysis module. The data collection submodule integrates the emotion recognition data and other multi-source data of the patient, such as basic information, medical history, etc. The network construction submodule constructs a complex network with alcohol dependence and related symptoms as nodes based on the integrated data, and analyzes the correlation between the symptoms. The longitudinal dynamic analysis submodule continuously tracks patient data, constructs a dynamic network model, and monitors alcohol dependence and related symptoms. As time goes by, the randomized controlled analysis submodule evaluates the intervention effect by comparing the network models of the experimental group and the control group. The psychological support and intervention module works based on the results of the data integration and analysis module. The personalized intervention program generation submodule refers to the key nodes and core symptoms determined by network analysis, and formulates personalized intervention plans based on the individual conditions of patients. The intervention implementation submodule presents the intervention content to patients in various forms and collects patient feedback. The effect evaluation submodule again uses the data integration and analysis module to compare the emotion recognition results and network model changes before and after the intervention, evaluate the intervention effect, and provide a basis for program adjustment. The user profile management module provides basic information support for patients for the entire system. The sub-modules such as medical information, medical history records, and psychological assessment interact with the data integration and analysis module in a two-way manner, which facilitates medical staff to fully understand the patient and assist in treatment decision-making. The reminder and appointment module is connected with the data integration and analysis module to provide patients with personalized reminder and appointment services based on the treatment plan and patient needs to ensure the smooth progress of the treatment process. The social support module creates an environment for communication and mutual assistance for patients, promotes communication between patients and between doctors and patients, and enhances the patient's motivation for rehabilitation. The knowledge base module provides the system with knowledge resources related to alcohol dependence, and is connected with the data integration and analysis module to facilitate inquiries by patients and medical staff, and assist in treatment decision-making. When patients face emergencies, the emergency help module uses the data integration and analysis module to help them According to the connection of the integration and analysis module, a message for help is quickly sent to the emergency contact to ensure the safety of the patient. The sleep monitoring module obtains the patient's sleep data and transmits it to the data integration and analysis module to provide data support for understanding the patient's overall health status. The exercise guidance module and the diet suggestion module customize personalized plans based on the patient's physical condition and other data in the data integration and analysis module to promote the patient's physical recovery. The system setting module ensures the user experience, and the data backup and recovery module ensures data security. The two work together with the data integration and analysis module to improve the stability and adaptability of the system. Through the circulation and interaction of data, each module cooperates with each other to provide comprehensive, accurate and personalized treatment services for alcohol-dependent patients.

[0068] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. These embodiments are selected and specifically described in this specification in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can well understand and utilize the present invention.

Claims

1. Medical intelligent treatment system, including data integration and analysis module, characterized by: The output end and the input end of the data integration and analysis module are both electrically connected to the emotion recognition module, and the output end and the input end of the data integration and analysis module are both electrically connected to the psychological support and intervention module; The data integration and analysis module includes a data collection submodule, a network construction submodule, a longitudinal dynamic analysis submodule and a random control analysis submodule, wherein the data collection submodule, the network construction submodule, the longitudinal dynamic analysis submodule and the random control analysis submodule are respectively bidirectionally electrically connected to the emotion recognition module, and the data collection submodule, the network construction submodule, the longitudinal dynamic analysis submodule and the random control analysis submodule are respectively bidirectionally electrically connected to the psychological support and intervention module; The emotion recognition module includes a facial expression recognition submodule, a tone and intonation recognition submodule and a body movement recognition submodule, and the facial expression recognition submodule, the tone and intonation recognition submodule and the body movement recognition submodule are all bidirectionally electrically connected to the data integration and analysis module. The psychological support and intervention module includes a personalized intervention program generation submodule, an intervention implementation submodule and an effect evaluation submodule, and the personalized intervention program generation submodule, the intervention implementation submodule and the effect evaluation submodule are all bidirectionally electrically connected to the data integration and analysis module.

2. The medical intelligent treatment system according to claim 1, characterized in that: The output end and input end of the data integration and analysis module are electrically connected to the user profile management module, the output end and input end of the data integration and analysis module are electrically connected to the reminder and appointment module, the output end and input end of the data integration and analysis module are electrically connected to the social support module, the output end and input end of the data integration and analysis module are electrically connected to the knowledge base module, and the output end and input end of the data integration and analysis module are electrically connected to the emergency assistance module.

3. The medical intelligent treatment system according to claim 1, characterized in that: The output end and input end of the data integration and analysis module are electrically connected to the sleep monitoring module, the output end and input end of the data integration and analysis module are electrically connected to the exercise guidance module, the output end and input end of the data integration and analysis module are electrically connected to the diet advice module, the output end and input end of the data integration and analysis module are electrically connected to the system setting module, and the output end and input end of the data integration and analysis module are electrically connected to the data backup and recovery module.

4. The medical intelligent treatment system according to claim 2, characterized in that: The user file management module includes a basic information submodule, a medical history recording submodule, a psychological assessment submodule and a file retrieval submodule, and the basic information submodule, the medical history recording submodule, the psychological assessment submodule and the file retrieval submodule are all bidirectionally electrically connected to the data integration and analysis module.

5. The medical intelligent treatment system according to claim 2, characterized in that: The reminder and appointment module includes a reminder setting submodule, an appointment management submodule, a schedule matching submodule and a notification feedback submodule, and the reminder setting submodule, the appointment management submodule, the schedule matching submodule and the notification feedback submodule are all bidirectionally electrically connected to the data integration and analysis module.

6. The medical intelligent treatment system according to claim 2, characterized in that: The social support module includes a community communication submodule, a topic classification submodule, a medical question and answer submodule and a reporting management submodule. The community communication submodule, the topic classification submodule, the medical question and answer submodule and the reporting management submodule are all bidirectionally electrically connected to the data integration and analysis module.

7. The medical intelligent treatment system according to claim 2, characterized in that: The knowledge base module includes a knowledge classification submodule, a content editing submodule, a multimedia display submodule and a search query submodule, and the knowledge classification submodule, content editing submodule, multimedia display submodule and search query submodule are all bidirectionally electrically connected to the data integration and analysis module.

8. The medical intelligent treatment system according to claim 3, characterized in that: The sleep monitoring module includes an image acquisition submodule, a data processing submodule, a sleep index calculation submodule and a report generation submodule, and the image acquisition submodule, the data processing submodule, the sleep index calculation submodule and the report generation submodule are all bidirectionally electrically connected to the data integration and analysis module.

9. The medical intelligent treatment system according to claim 3, characterized in that: The data backup and recovery module includes a backup strategy setting submodule, a data backup execution submodule, a data storage submodule and a data recovery submodule. The backup strategy setting submodule, the data backup execution submodule, the data storage submodule and the data recovery submodule are all bidirectionally electrically connected to the data integration and analysis module.

10. The medical intelligent treatment system according to claim 3, characterized in that: The system setting module includes a display setting submodule, a notification setting submodule, a privacy setting submodule and a system update submodule, and the display setting submodule, the notification setting submodule, the privacy setting submodule and the system update submodule are all bidirectionally electrically connected to the data integration and analysis module.

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