Health education system and method based on multi-modal data perception and adaptive intervention

Abstract

The invention discloses a health education system and method based on multi-modal data perception and self-adaptive intervention, and the system comprises a health education scheme construction module, a physiological behavior data collection module, an emotional state judgment module, a self-adaptive intervention module, and a targeted health education module. The health education scheme construction module, the physiological behavior data acquisition module, the emotional state judgment module, the self-adaptive intervention module and the targeted health education module are connected in sequence. The effectiveness of information transmission is ensured through a personalized engine, the high efficiency of nursing management is ensured through a closed-loop feedback mechanism, and finally the humanization of the medical process is ensured through immersive experience and emotion care, so that the modern nursing concept taking a patient as the center is truly realized, the efficiency and accuracy of health education are improved, and the health education experience is improved. The nursing quality, the patient safety and the medical satisfaction degree are comprehensively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of data processing, in particular to a health education system and method based on multi-modal data perception and adaptive intervention, a terminal and a computer readable storage medium. BACKGROUND

[0002] Under the traditional health education mode, the work burden of nurses not only lies in "repeated explanation", but also exists in time allocation contradiction. A nurse needs to be responsible for the health education work of multiple patients per day, and a single oral explanation takes 10-15 minutes, and if the patient asks questions or repeatedly consults, it will further squeeze the core work time such as nursing operation and disease observation. At the same time, due to the lack of unified health education examination standard, the explanation emphasis of different nurses is obviously different: experienced nurses may supplement the details of postoperative complication prevention, while new nurses are often limited to basic process notification, resulting in significant gaps in the completeness and accuracy of health education information received by patients in the same department. In addition, the judgment of nurses on the understanding degree of patients depends on "subjective observation", but this evaluation method has serious deviation, and the health education effect cannot be quantified, and it is also difficult to optimize the content.

[0003] Moreover, the mismatch between the professionalism of medical knowledge and the cognitive level of patients presents different performances in different groups. For elderly patients, there is a situation of "not understanding professional terms", while young patients have higher acceptance of basic terms, but they will ignore key information due to "too much psychological pressure", in addition, patients with lower education level have insufficient understanding rate of paper materials, and in the health education single page combined with pictures and texts, they can only recognize simple pictures and cannot interpret the logical relationship in the text explanation.

[0004] Therefore, the prior art still needs to be improved and developed. SUMMARY

[0005] The main purpose of the present application is to provide a health education system and method based on multi-modal data perception and adaptive intervention, a system and a terminal, which aims to solve the problem in the prior art that the health education of patients is not obvious due to the obvious difference between different patient groups, the deviation of subjective judgment of nurses, and the chain reaction of the influence of negative emotions of patients on the health education effect.

[0006] In order to achieve the above object, the application provides a health education system based on multi-modal data perception and adaptive intervention, which comprises a health education scheme construction module, a physiological behavior data acquisition module, an emotional state judgment module, an adaptive intervention module and a targeted health education module, and the health education scheme construction module, the physiological behavior data acquisition module, the emotional state judgment module, the adaptive intervention module and the targeted health education module are sequentially connected. The health education scheme construction module is used for acquiring static data of a patient, constructing a patient static portrait according to the static data, and constructing an individualized health education scheme from a resource library according to the static portrait. The physiological behavior data acquisition module is used for playing the individualized health education scheme to the patient through VR technology and acquiring dynamic physiological behavior data of the patient in VR immersive experience in real time. The emotional state judgment module is used for obtaining an emotional state of the patient according to the dynamic physiological behavior data and judging whether the emotional state is a negative state. The adaptive intervention module is used for performing adaptive intervention on the patient according to a type of the negative state if the emotional state is the negative state, until the negative state is eliminated, and continuing to play the individualized health education scheme. The targeted health education module is used for obtaining an instant understanding degree of the patient through an interactive questionnaire after the individualized health education scheme is played, sending the instant understanding degree to a nurse workstation for analysis and arrangement, obtaining a task list, and performing targeted health education on the patient according to the task list.

[0007] Optionally, the health education system based on multi-modal data perception and adaptive intervention, wherein the health education scheme construction module comprises a static data creation unit, a static portrait construction unit and an individualized scheme generation unit. The static data creation unit is used for creating static data containing age, educational level, diagnosis, allergy history, past operation history and language preference for the patient through a mode of docking a hospital HIS system or manual input by a nurse. The static portrait construction unit is used for labeling a plurality of labels for the patient according to the static data and constructing a patient static portrait according to the labels, wherein the labels comprise age and cognitive level, disease type and content type. The individualized scheme generation unit is used for presetting a multimedia health education resource library and constructing an individualized health education scheme adapted to the patient from the multimedia health education resource library according to the static portrait.

[0008] Optionally, the health education system based on multi-modal data perception and adaptive intervention, wherein the physiological behavior data acquisition module comprises a scene division unit, a preoperative simulation unit, an intraoperative simulation unit, a postoperative simulation unit, and a behavior data acquisition unit. The scene division unit is configured to divide the personalized health education scheme into a preoperative scene, an intraoperative scene, and a postoperative scene. The preoperative simulation unit is configured to simulate an operating room environment in the preoperative scene by using VR technology, display the operating room environment to the patient, and inform the patient of the operation in the operating room through voice explanation. The intraoperative simulation unit is configured to simulate the patient's physical sensation during the operation in the intraoperative scene by using VR technology, and transmit the physical sensation to the patient. The postoperative simulation unit is configured to simulate the patient's rehabilitation process after the operation in the postoperative scene by using VR technology, so that the patient can understand the rehabilitation steps in advance. The behavior data acquisition unit is configured to deploy a medical-grade wearable device on the patient's body or deploy a non-contact sensor in a VR head-mounted display device or a bedside tablet camera, and acquire dynamic physiological behavior data of the patient in VR immersive experience through the medical-grade wearable device or the non-contact sensor, wherein the dynamic physiological behavior data includes heart rate, heart rate variability, skin electric response, blink frequency, and head movement.

[0009] Optionally, the health education system based on multi-modal data perception and adaptive intervention, wherein the emotion state judgment module comprises a tension state judgment unit, an attention dispersion state judgment unit, a stable state judgment unit, and a negative state judgment unit. The tension state judgment unit is configured to determine that the patient's emotion state is in a tension state when the heart rate is greater than a preset range, the heart rate variability is reduced, and the skin electric response is increased. The attention dispersion state judgment unit is configured to determine that the patient's emotion state is in an attention dispersion state when the heart rate is within the preset range, the blink frequency is reduced, and the head movement is in a long-time no movement state. The stable state judgment unit is configured to determine that the patient's emotion state is in a stable state when the patient's emotion state is not in a tension state or an attention dispersion state. The negative state judgment unit is configured to determine whether the emotion state is a negative state according to the judgment results of the tension state judgment unit, the attention dispersion state judgment unit, and the stable state judgment unit.

[0010] Optionally, the health education system based on multi-modal data perception and adaptive intervention, wherein the adaptive intervention module comprises: a tension intervention unit, an attention distraction intervention unit and a personalized scheme changing unit. The tension intervention unit is configured to, if the type of the negative state is the tension state, immediately pause the personalized health education scheme, play a preset soothing scene to the patient through VR technology, and continuously monitor the dynamic physiological behavior data of the patient until the dynamic physiological behavior data returns to the baseline level, then ask the patient whether to continue with a preset gentle prompt sound, and continue playing the personalized health education scheme from the pause position after obtaining the confirmation of the patient. The attention distraction intervention unit is configured to, if the type of the negative state is the attention distraction state, immediately pause the personalized health education scheme, pop up an interactive small question to reattract the attention of the patient, and continuously monitor the dynamic physiological behavior data of the patient until the dynamic physiological behavior data returns to the baseline level, then continue playing the personalized health education scheme from the pause position. The personalized scheme changing unit is configured to, if the patient is still in the attention distraction state within a preset time after the interactive small question is popped up, stop popping up the interactive small question, and change the content presentation mode of the personalized health education scheme from the pause position to continue playing the personalized health education scheme.

[0011] Optionally, the health education system based on multi-modal data perception and adaptive intervention, wherein the targeted health education module comprises: an understanding degree acquisition unit, an analysis and arrangement unit and a targeted task execution unit. The understanding degree acquisition unit is configured to match an interactive questionnaire of a corresponding level according to the static image of the patient and the personalized health education scheme, and generate an instant understanding degree of the patient in real time when the patient completes the interactive questionnaire. The analysis and arrangement unit is configured to send the instant understanding degree to a nurse workstation for analysis, obtain weak knowledge points of the patient, and arrange the weak knowledge points to obtain a task list and a priority prompt. The targeted task execution unit is configured to send the task list and the priority prompt to a corresponding nurse team to guide the nurse team to perform targeted health education on the patient according to the task list and the priority prompt.

[0012] In addition, to achieve the above-mentioned purpose, the present application further provides a health education method of a health education system based on multi-modal data perception and adaptive intervention, wherein the health education method of the health education system based on multi-modal data perception and adaptive intervention comprises: acquiring static data of a patient, constructing a static image of the patient according to the static data, constructing a personalized health education scheme from a resource library according to the static image; playing the personalized health education scheme to the patient through VR technology, and collecting dynamic physiological behavior data of the patient in VR immersive experience in real time; obtaining an emotional state of the patient according to the dynamic physiological behavior data, and determining whether the emotional state is a negative state; if the emotional state is a negative state, performing adaptive intervention on the patient according to the type of the negative state until the negative state is eliminated, and continuing to play the personalized health education scheme; after the personalized health education scheme is played, obtaining an instant understanding degree of the patient through an interactive questionnaire, sending the instant understanding degree to a nurse workstation for analysis and arrangement to obtain a task list, and performing targeted health education on the patient according to the task list.

[0013] Optionally, the health education method of the health education system based on multi-modal data perception and adaptive intervention, wherein the obtaining of the emotional state of the patient according to the dynamic physiological behavior data specifically comprises: if the heart rate is greater than a preset range, the heart rate variability is reduced, and the skin electric reaction is increased, it is determined that the emotional state of the patient is a nervous state; if the heart rate is within the preset range, the blink frequency is reduced, and the head movement condition is a long-time no-movement condition, it is determined that the emotional state of the patient is an attention dispersion state; if the emotional state of the patient is not in the nervous state or the attention dispersion state, it is determined that the emotional state of the patient is a stable state; wherein the nervous state and the attention dispersion state are negative states.

[0014] In addition, to achieve the above-mentioned purposes, the application further provides a terminal, wherein the terminal comprises a memory, a processor, and a health education program of a health education system based on multi-modal data perception and adaptive intervention stored on the memory and executable on the processor, and the health education program of the health education system based on multi-modal data perception and adaptive intervention implements the steps of the health education method of the health education system based on multi-modal data perception and adaptive intervention when executed by the processor.

[0015] In addition, in order to achieve the above-mentioned purpose, the present application also provides a computer readable storage medium, wherein the computer readable storage medium stores a health education program of a health education system based on multi-modal data perception and adaptive intervention, and the health education program of the health education system based on multi-modal data perception and adaptive intervention realizes the steps of the health education method of the health education system based on multi-modal data perception and adaptive intervention when executed by a processor.

[0016] In the present application, the health education system based on multi-modal data perception and adaptive intervention comprises a health education scheme construction module, a physiological behavior data acquisition module, an emotional state judgment module, an adaptive intervention module and a targeted health education module, which are sequentially connected. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 is a structural diagram of the health education system based on multi-modal data perception and adaptive intervention of the present application; Figure 2 is a flowchart of a preferred embodiment of the health education method of the health education system based on multi-modal data perception and adaptive intervention of the present application; Figure 3 is a principle architecture diagram of the health education method of the health education system based on multi-modal data perception and adaptive intervention of the present application; Figure 4 is a structural diagram of a preferred embodiment of the terminal of the present application. DETAILED DESCRIPTION

[0018] The present application provides a health education system, method, system and terminal based on multi-modal data perception and adaptive intervention. In order to make the purpose, technical scheme and effects of the present application clearer and more explicit, the present application will be further described in detail below with reference to the drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0019] Those skilled in the art can understand that, unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It should also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0020] In addition, if the description of "first", "second" and the like is involved in the embodiments of the present application, the description of "first", "second" and the like is only for the purpose of description, and cannot be understood as indicating or implying the relative importance of the indicated technical features or implicitly indicating the number of the indicated technical features. Therefore, the features limited by "first", "second" can be explicitly or implicitly included at least one of the features. In addition, the technical solutions of various embodiments can be combined with each other, but it must be based on the realization of ordinary skilled in the art, when the combination of technical solutions appears contradictory or unachievable, it should be considered that the combination of technical solutions does not exist, nor within the protection scope required by the present application.

[0021] The health education system and method based on multi-modal data perception and adaptive intervention according to the preferred embodiments of the present application, as shown in Figure 1 The health education system based on multi-modal data perception and adaptive intervention comprises a health education scheme construction module, a physiological behavior data acquisition module, an emotional state judgment module, an adaptive intervention module and a targeted health education module, and the health education scheme construction module, the physiological behavior data acquisition module, the emotional state judgment module, the adaptive intervention module and the targeted health education module are connected in sequence.

[0022] The health education scheme construction module is used to acquire static data of a patient, construct a static portrait of the patient according to the static data, and construct a personalized health education scheme from a resource library according to the static portrait.

[0023] Specifically, the health education scheme construction module comprises a static data creation unit, a static portrait construction unit and a personalized scheme generation unit. The static data creation unit is used to create static data including age, education level, diagnosis, allergy history, past operation history and language preference for the patient by means of interfacing with a hospital HIS system or manual entry by a nurse. The static portrait construction unit is used to label a plurality of labels for the patient according to the static data, and construct a static portrait of the patient according to the labels, wherein the labels include age and cognitive level, disease type and content type. The personalized scheme generation unit is used for presetting a multimedia health education resource library, and constructing a personalized health education scheme suitable for the patient from the multimedia health education resource library according to the static portrait.

[0024] It can be understood that, in the system initialization, an electronic file containing fields of age, education level, diagnosis, allergy history, past operation history, language preference and the like is created for each patient by connecting a hospital HIS (Hospital Information System) or manually inputting by a nurse. A multimedia health education resource library labeled by medical experts and health education experts is preset. Each resource is labeled with multiple tags (such as age and cognitive level, disease type, content type). The patient is labeled with multiple tags according to the static data, a static portrait of the patient is constructed according to the tags, and a personalized health education scheme is dynamically constructed from the resource library according to the static portrait.

[0025] Further, the physiological behavior data acquisition module is used for playing the personalized health education scheme to the patient through VR technology, and acquiring dynamic physiological behavior data of the patient in VR immersive experience in real time.

[0026] The physiological behavior data acquisition module comprises a scene division unit, a preoperative simulation unit, an intraoperative simulation unit, a postoperative simulation unit and a behavior data acquisition unit. The scene division unit is used for dividing the personalized health education scheme into a preoperative scene, an intraoperative scene and a postoperative scene. The preoperative simulation unit is used for simulating an operating room environment in the preoperative scene through VR technology, displaying the operating room environment to the patient, and informing the patient of the operation after entering the operating room in cooperation with voice explanation. The intraoperative simulation unit is used for simulating the physical feeling of the patient in the operation process in the intraoperative scene through VR technology, and transmitting the physical feeling to the patient. The postoperative simulation unit is used for simulating the rehabilitation process of the patient after the operation in the postoperative scene through VR technology, so that the patient can know the rehabilitation steps in advance. The behavior data acquisition unit is used for deploying a medical wearable device on the patient, or deploying a non-contact sensor in a VR head-mounted display device or a bedside tablet camera, and acquiring dynamic physiological behavior data of the patient in VR immersive experience through the medical wearable device or the non-contact sensor, wherein the dynamic physiological behavior data comprises heart rate, heart rate variability, skin electric response, blink frequency and head movement.

[0027] It can be understood that the VR (Virtual Reality) scene in the embodiment is divided into three types of preoperative scene, intraoperative scene and postoperative scene. The preoperative scene simulates the operating room environment (such as the placement of the operating bed, instrument equipment, and the operation process of medical staff), and cooperates with voice explanation of each step of operation after the patient enters the operating room (such as anesthesia, disinfection), to eliminate the patient's fear of the unknown environment; the intraoperative scene simulates the first perspective (such as showing the patient's body feeling during the operation process from the patient's perspective, such as slight vibration and no pain feeling), to correct the patient's wrong cognition of the operation (such as "the operation will be very painful" and "the operation time is very long"); the postoperative scene simulates the rehabilitation process (such as the action essentials of turning over in bed on the first day after operation, and the specific action of rehabilitation training one week after operation), to enable the patient to intuitively understand the rehabilitation steps and reduce operation concerns.

[0028] For patients who have never entered the operating room, the unfamiliar environment and cold instruments are a huge source of pressure. Through VR technology, the patient can walk into a highly simulated virtual operating room in advance, understand the appearance of the operating bed, shadowless lamp and monitor, and even experience the whole process from entering the operating room to anesthesia induction in the first perspective. This "controllable exposure therapy" can greatly reduce the fear caused by the unknown, visualize abstract concepts, overcome cognitive barriers, and achieve the effect of pre-experience.

[0029] Further, the emotional state judgment module is configured to obtain the emotional state of the patient according to the dynamic physiological behavior data, and determine whether the emotional state is a negative state.

[0030] The emotional state judgment module includes a tension state judgment unit, an attention distraction state judgment unit, a stable state judgment unit and a negative state judgment unit. The tension state judgment unit is configured to determine that the emotional state of the patient is a tension state when the heart rate is greater than a preset range, the heart rate variability is reduced, and the skin conductance response is increased. The attention distraction state judgment unit is configured to determine that the emotional state of the patient is an attention distraction state when the heart rate is within the preset range, the blink frequency is reduced, and the head movement condition is a long time no movement condition. The stable state judgment unit is configured to determine that the emotional state of the patient is a stable state when the emotional state of the patient is not in a tension state or an attention distraction state. The negative state judgment unit is configured to determine whether the emotional state is a negative state according to the judgment results of the tension state judgment unit, the attention distraction state judgment unit and the stable state judgment unit.

[0031] It can be understood that the emotional state of the patient is obtained according to the dynamic physiological behavior data, and in this embodiment, the condition for determining as “tension / anxiety” is that the heart rate > 100 times / min + heart rate variability decreases + skin electricity reaction increases. The condition for determining as “distraction / fatigue” is that the heart rate is stable + the blink frequency is reduced + the head is long time without movement. When it is determined that the patient enters the “tension” or “distraction” state, it is judged that the emotional state is a negative state, at this time the control center is triggered to start the adaptive intervention. If the emotional state of the patient is not in the tension state or the distraction state, it is determined that the emotional state of the patient is a stable state.

[0032] Further, the adaptive intervention module is used to perform adaptive intervention on the patient according to the type of the negative state if the emotional state is a negative state, until the negative state is eliminated, and the personalized health education scheme is continuously played.

[0033] The adaptive intervention module comprises a tension intervention unit, a distraction intervention unit and a personalized scheme changing unit. The tension intervention unit is used to immediately pause the personalized health education scheme if the type of the negative state is the tension state, play a preset soothing scene to the patient through VR technology, and continuously monitor the dynamic physiological behavior data of the patient until the dynamic physiological behavior data returns to the baseline level, then ask the patient whether to continue with a preset gentle prompt sound, and continue to play the personalized health education scheme from the pause position after the patient confirms. The distraction intervention unit is used to immediately pause the personalized health education scheme if the type of the negative state is the distraction state, pop up an interactive small question to reattract the attention of the patient, and continuously monitor the dynamic physiological behavior data of the patient until the dynamic physiological behavior data returns to the baseline level, then continue to play the personalized health education scheme from the pause position. The personalized scheme changing unit is used to stop popping up interactive small questions if the patient is still in the distraction state within a preset time after the interactive small question is popped up, change the content presentation mode of the personalized health education scheme from the pause position to continue to complete the playing of the personalized health education scheme.

[0034] It can be understood that the intervention process of the tension state is: immediately pause the current health education content → switch to the preset "relaxing scene" (such as a quiet forest, beach VR scene, and play alpha wave music or guided meditation voice) → continuously monitor physiological indicators until the baseline level is restored → ask "whether to continue?" with a gentle prompt sound, and continue from the pause or the previous content after confirmation (voice or nod recognition).

[0035] The intervention process of the distraction state is: an interactive small question can be popped up, if the patient is still in the distraction state within the preset time after the interactive small question is popped up, the interactive small question is stopped, and the content presentation mode is changed (such as switching from text to short video) to reattract the patient's attention.

[0036] Further, the personalized health education module is used after the personalized health education scheme is played, the real-time understanding degree of the patient is obtained through an interactive questionnaire, the real-time understanding degree is sent to a nurse workstation for analysis and arrangement, a task list is obtained, and the patient is given personalized health education according to the task list.

[0037] The personalized health education module comprises an understanding degree acquisition unit, an analysis and arrangement unit, and a personalized task execution unit. The understanding degree acquisition unit is configured to match an interactive questionnaire of a corresponding level according to the static image of the patient and the personalized health education scheme, and generate the real-time understanding degree of the patient in real time when the patient completes the interactive questionnaire. The analysis and arrangement unit is configured to send the real-time understanding degree to the nurse workstation for analysis, obtain the weak knowledge points of the patient, and arrange the weak knowledge points to obtain a task list and a priority prompt. The personalized task execution unit is configured to send the task list and the priority prompt to a corresponding nurse team to guide the nurse team to give the patient personalized health education according to the task list and the priority prompt.

[0038] It can be understood that after traditional health education, nurses can only rely on their feelings or simply ask "do you understand?" to evaluate the effect, and the result is very vague. The present application quantifies the abstract concept of "understanding degree" into specific data (such as the correct rate of answering questions, the time of staying on key knowledge points, and the number of tension times). The difficulty of the questions corresponds to the matching level of the patient information (such as the elderly patient, the difference between the options is more obvious, and the understanding interference is reduced). After the patient completes the questions, the system generates a personal understanding report in real time, which shows the real-time understanding degree of the patient.

[0039] The instant understanding degree is sent to a nurse workstation for analysis, and the knowledge points mastered and the weak knowledge points of the patient are marked (such as "postoperative dietary taboos are well mastered, and there are doubts about postoperative activity requirements"). By integrating the instant understanding degrees of multiple patients, the nurse obtains the overall health education effect of the department (such as 80% of the patients do not master the postoperative complication identification method), and of course, individual problems (such as the patient Zhang understands the drug taking time incorrectly) can also be located. Importantly, the nurse will and collate the weak knowledge points to obtain a task list and a priority prompt to guide the nurse team to carry out targeted health education on the patients according to the task list and the priority prompt.

[0040] Based on the multi-modal data perception and adaptive intervention-based health education system described in the above embodiments, the present application also provides a multi-modal data perception and adaptive intervention-based health education system health education method, specifically as shown in Figure 2 and Figure 3 The multi-modal data perception and adaptive intervention-based health education system health education method includes the following steps: Step S10, acquiring static data of a patient, constructing a patient static portrait according to the static data, and constructing a personalized health education scheme from a resource library according to the static portrait.

[0041] Specifically, by means of interfacing a medical system or manual entry by a nurse, static data including age, education level, diagnosis, allergy history, past surgery history, and language preference is created for the patient.

[0042] It can be understood that, when the system is initialized, by interfacing a hospital HIS (Hospital Information System) or manual entry by a nurse, an electronic file including fields such as age, education level, diagnosis, allergy history, past surgery history, and language preference is created for each patient.

[0043] Further, a plurality of labels are marked for the patient according to the static data, and a patient static portrait is constructed according to the labels, wherein the labels include age and cognitive level, disease type, and content type. A preset multimedia health education resource library is constructed, and a personalized health education scheme adapted to the patient is constructed from the multimedia health education resource library according to the static portrait.

[0044] In the embodiment, a multimedia health education resource library labeled by medical experts and health education experts is preset. Each resource is labeled with multiple tags (such as age and cognitive level, disease type, and content type). Multiple tags are labeled for the patient according to the static data, a patient static portrait is constructed according to the tags, and a personalized health education scheme is dynamically constructed from the resource library according to the static portrait.

[0045] Further, the personalized health education scheme includes a first health education scheme and a second health education scheme.

[0046] The personalized health education scheme constructed from the multimedia health education resource library according to the static portrait specifically includes: The first health education scheme adapted to the patient is constructed from the multimedia health education resource library according to the age and cognitive level of the static portrait. The second health education scheme adapted to the patient is constructed from the multimedia health education resource library according to the disease type of the static portrait. The personalized health education scheme adapted to the patient is obtained by combining the first health education scheme and the second health education scheme.

[0047] The first health education scheme adapted to the patient is constructed from the multimedia health education resource library according to the age and cognitive level of the static portrait, including: if the age and cognitive level are low, using pictures, videos, and icons instead of text, and using simple and understandable language to obtain the first health education scheme (such as comparing “coronary artery” to “oil pipeline of heart”); if the age and cognitive level are high, providing deeper pathological mechanism, data support, and professional term options to obtain the first health education scheme.

[0048] For example, for elderly patients or patients with low education, “oral language + dynamic animation demonstration” is automatically selected (such as using animation to demonstrate “postoperative wound dressing steps”, and combining with the popular explanation “just like putting clothes on a wound, first apply ointment and then apply gauze”); for patients with high education, “professional terms + 3D model disassembly” is provided.

[0049] The second health education scheme adapted to the patient is constructed from the multimedia health education resource library according to the disease type of the static portrait, including: selecting surgical knowledge, rehabilitation knowledge, and precautions corresponding to the disease type from the multimedia health education resource library, and constructing the second health education scheme adapted to the patient according to the surgical knowledge, the rehabilitation knowledge, and the precautions.

[0050] It can be understood that the multimedia health education resource library of the present application has a large knowledge graph built in, which can automatically focus on diet control and blood glucose monitoring for diabetic patients, highlight rehabilitation training actions for orthopedic surgery patients, and focus on explaining chemotherapy procedures and side effect management for cancer patients. For example, for orthopedic postoperative patients, the relevant health education of "joint range of motion training" and "weight bearing time node" is pushed; for postoperative patients in the cardiology department, the "heart rate monitoring method" and "anticoagulant drug taking precautions" are highlighted.

[0051] Further, for the personal preferences of the patient, the patient or family member can also make preference adjustments to the generated personalized health education plan when first performing health education, such as selecting preferred language style (such as "strict type" or "encouraging type") and display mode (such as "text and image dominant" or "video dominant").

[0052] Step S20, playing the personalized health education plan to the patient through VR technology and collecting dynamic physiological behavior data of the patient in VR immersive experience in real time.

[0053] Said playing the personalized health education plan to the patient through VR technology, specifically comprising: Said personalized health education plan is divided into preoperative scene, intraoperative scene and postoperative scene; In the preoperative scene, the operating room environment is simulated through VR technology, the operating room environment is displayed to the patient, and the patient is informed of the operation after entering the operating room through voice explanation; In the intraoperative scene, the patient's physical sensation during the operation is simulated through VR technology, and the physical sensation is transmitted to the patient; In the postoperative scene, the patient's rehabilitation process after the operation is simulated through VR technology, so that the patient can understand the rehabilitation steps in advance.

[0054] It can be understood that in the present embodiment, the VR (Virtual Reality) scene is divided into three types of preoperative scene, intraoperative scene and postoperative scene. The preoperative scene simulates the operating room environment (such as the placement of operating beds and instrument equipment, and the operation process of medical staff), and cooperates with voice explanation to inform the patient of each step of operation after entering the operating room (such as anesthesia and disinfection), so as to eliminate the patient's fear of unknown environment; the intraoperative scene simulates the first visual angle (such as showing the patient's physical sensation during the operation from the patient's visual angle, such as slight vibration and no pain), and corrects the patient's wrong cognition of the operation (such as "the operation will be very painful" and "the operation time is very long"); the postoperative scene simulates the rehabilitation process (such as the action essentials of turning over in bed on the first day after the operation, and the specific actions of rehabilitation training one week after the operation), so that the patient can intuitively understand the rehabilitation steps and reduce the operation concerns.

[0055] For patients who have never been to the operating room, the unfamiliar environment and cold instruments are a huge source of stress. Through VR technology, patients can walk into a highly simulated virtual operating room in advance, understand the appearance of the operating bed, shadow lamp, and monitor, and even experience the whole process from entering the operating room to anesthesia induction in the first person perspective. This "controllable exposure therapy" can greatly reduce the fear caused by the unknown, visualize abstract concepts, overcome cognitive barriers, and achieve the effect of pre-experience.

[0056] For example: It is difficult to explain to patients "how stents are put into the heart through blood vessels." However, in VR, patients can "transform" into a red blood cell and shuttle in the blood vessels, and see with their own eyes how arterial plaques block blood vessels and how stents prop open and restore blood flow. The depth of understanding brought by this experience is unmatched by any verbal or textual description.

[0057] At the same time, VR content is not only watchable, but also interactive. Patients can use a handle to virtually pick up an instrument to understand its purpose, or follow a virtual coach to complete rehabilitation movements, with the system providing real-time feedback on the standard degree of movement through the handle or built-in sensors.

[0058] Further, the real-time collection of dynamic physiological behavior data of the patient in the VR immersive experience includes: Deploying a medical-grade wearable device on the patient's body or a non-contact sensor in the VR headset or bedside tablet camera; Collecting dynamic physiological behavior data of the patient in the VR immersive experience through the medical-grade wearable device or the non-contact sensor, wherein the dynamic physiological behavior data includes heart rate, heart rate variability, skin conductance response, blink rate, and head movement.

[0059] In this embodiment, the patient wears a medical-grade wearable device (such as a smart bracelet or a chest patch heart rate monitor) or uses a non-contact sensor (such as a micro-expression recognition integrated in the VR headset or a bedside tablet camera, or a blood oxygen pulse wave monitor). The collected data includes heart rate, heart rate variability, skin conductance response, blink rate, and head movement.

[0060] Step S30, obtaining the emotional state of the patient according to the dynamic physiological behavior data, and determining whether the emotional state is a negative state.

[0061] Specifically, if the heart rate is greater than the preset range, the heart rate variability is reduced, and the skin conductance response is increased, it is determined that the emotional state of the patient is a nervous state; If the heart rate is within the preset range, the blink rate is reduced, and the head movement is long-term non-movement, it is determined that the emotional state of the patient is a state of distraction. If the emotional state of the patient is not in the state of tension or distraction, it is determined that the emotional state of the patient is stable.

[0062] It can be understood that the emotional state of the patient is obtained according to the dynamic physiological behavior data, and in this embodiment, the condition for determining “tension / anxiety” is that the heart rate is greater than 100 beats per minute, the heart rate variability is reduced, and the skin electricity response is increased. The condition for determining “distraction / fatigue” is that the heart rate is stable, the blink frequency is reduced, and the head is motionless for a long time. When it is determined that the patient enters the state of “tension” or “distraction”, it is determined that the emotional state is a negative state, and the adaptive intervention is triggered at this time. If the emotional state of the patient is not in the state of tension or distraction, it is determined that the emotional state of the patient is stable.

[0063] Step S40, if the emotional state is a negative state, adaptive intervention is performed on the patient according to the type of the negative state until the negative state is eliminated, and the personalized health education scheme is continued to be played.

[0064] When it is determined that the patient enters the state of tension or distraction, the emotional state of the patient is a negative state, and adaptive intervention is performed on the patient according to the type of the negative state. Specifically, if the type of the negative state is the state of tension, the personalized health education scheme is immediately paused, a preset soothing scene is played to the patient through VR technology, and the dynamic physiological behavior data of the patient is continuously monitored until the dynamic physiological behavior data returns to the baseline level. After that, a preset gentle prompt sound is used to ask the patient whether to continue, and after the confirmation of the patient, the personalized health education scheme is continued to be played from the paused place.

[0065] In this embodiment, the intervention process of the state of tension is: immediately pause the current health education content → switch to a preset “soothing scene” (such as a quiet forest, beach VR scene, and play alpha wave music or guided meditation voice) → continuously monitor physiological indicators until they return to the baseline level → ask “do you want to continue?” with a gentle prompt sound, and after confirmation (voice or nod recognition), continue from the paused place or the content before.

[0066] Further, if the type of the negative state is the attention distraction state, the personalized health education program is immediately paused, an interactive mini-question is popped up to re-attract the attention of the patient, and the dynamic physiological behavior data of the patient is continuously monitored until the dynamic physiological behavior data returns to the baseline level, and then the personalized health education program is continued to play from the pause; if the patient is still in the attention distraction state within a preset time after the interactive mini-question is popped up, the interactive mini-question is stopped from being popped up, and the content presentation mode of the personalized health education program is changed from the pause to continue to complete the playing of the personalized health education program.

[0067] In the embodiment, the intervention process of the attention distraction state is that an interactive mini-question can be popped up, if the patient is still in the attention distraction state within a preset time after the interactive mini-question is popped up, the interactive mini-question is stopped from being popped up, and the content presentation mode is changed (such as switching from text to short video) to re-attract the attention of the patient.

[0068] Further, the application is provided with an intervention resource library, which internally embeds a relaxation resource library verified by psychology, and contains various types of soothing music, natural white noise, mindfulness meditation guiding language, and 360-degree panoramic beautiful scenery videos. At the same time, personalized intervention strategies can also be implemented, and the most effective intervention method can be selected according to the patient profile. For example, classic light music familiar to the elderly patients when they were young can be played for the elderly patients, and more modern environmental music can be selected for young patients.

[0069] Step S50, after the personalized health education program is played, the real-time understanding degree of the patient is obtained through an interactive questionnaire, the real-time understanding degree is sent to a nurse workstation for analysis and arrangement, a task list is obtained, and the patient is given targeted health education according to the task list.

[0070] Specifically, according to the static profile of the patient and the personalized health education program, an interactive questionnaire of a corresponding level is matched, and when the patient completes the interactive questionnaire, the real-time understanding degree of the patient is generated in real time.

[0071] It can be understood that after traditional health education, nurses can only evaluate the effect by feeling or simply asking “do you understand?”, and the result is very vague. The application quantifies the abstract concept of “understanding degree” into specific data (such as the correct rate of answering questions, the time of staying on key knowledge points, and the number of nervous times). The difficulty of the questions corresponds to the matching level of the patient information (such as the elderly patients, the difference between the options is more obvious, and the understanding interference is reduced). After the patient completes the answering, the system generates a personal understanding report in real time, and the personal understanding report shows the real-time understanding degree of the patient.

[0072] Further, the instant comprehension degree is sent to the nurse workstation for analysis, weak knowledge points of the patient are obtained, the weak knowledge points are sorted, a task list and a priority prompt are obtained.

[0073] It can be understood that the instant comprehension degree is sent to the nurse workstation for analysis, The mastered knowledge points and the weak knowledge points of the patient are marked (for example, “postoperative dietary taboos are well mastered, and postoperative activity requirements are questioned”). By integrating the instant comprehension degrees of multiple patients, the nurse obtains the overall health education effect of the department (for example, 80% of the patients do not master the postoperative complication identification method), and of course, individual problems can also be located (for example, patient Zhang Mou misunderstands the drug taking time). Importantly, the nurse will sort the weak knowledge points, obtain a task list and a priority prompt.

[0074] Further, the task list and the priority prompt are sent to the corresponding nurse team, and the nurse team is guided to carry out targeted health education on the patient according to the task list and the priority prompt.

[0075] It can be understood that the present application automatically completes repetitive basic knowledge explanation and preliminary testing, and the nurse workstation system generates a clear task list and a priority prompt, thereby liberating the nurse from the role of a “repeat machine”. For example: “Bed 3, Zhang Mou, has an understanding degree of only 40% for ‘postoperative activity precautions’, and it is suggested to focus on coaching”; “The error rate of patients in the department for ‘analgesic pump use’ is as high as 70%, and it is suggested to emphasize it in the afternoon group health lecture”. This enables the nurse to have a clear target for subsequent intervention, and to use valuable time to solve difficult and individualized problems.

[0076] In a specific solution, if a large number of patients repeatedly have understanding difficulties or nervousness on a certain knowledge point, it is prompted that the health education content or form of this part needs to be redesigned and optimized by education experts. For department common weak knowledge points, nurses can initiate centralized health education through the system (such as playing a VR short film of "postoperative complication identification" in the ward). And for individual problems, the system automatically recommends "personalized supplementary health education content" (such as pushing a "drug taking time table" picture + voice explanation to Zhang). After the nurse confirms, it can be pushed to the patient. After the supplementary health education is completed, the system generates a simple test (3-5 questions) again to verify whether the patient has mastered it. The whole "health education-evaluation-feedback-strengthening" process forms a data closed loop, and the nurse does not need to manually record, and the system automatically counts "the number of health education of each patient, test pass rate, weak link", not only reduces the nurse's paperwork time (daily saving 30-40 minutes), but also continuously optimizes the health education content through data tracking (such as replacing professional terms that patients generally do not understand with popular expressions), and improves the accuracy of nursing.

[0077] It can be seen that the present application ensures the effectiveness of information transmission through the personalized engine, ensures the efficiency of nursing management through the closed-loop feedback mechanism, and finally ensures the humanization of the medical process through immersive experience and emotional care. The method can provide an intelligent nursing partner integrating educators, guardians and pacifiers, truly realizing the modern nursing concept of patient-centeredness, and finally bringing comprehensive improvement of nursing quality, patient safety and medical satisfaction.

[0078] Further, as shown in Figure 4 Based on the health education method of the health education system based on multi-modal data perception and adaptive intervention, the present application also correspondingly provides a terminal, which comprises a processor 10, a memory 20 and a display 30. Figure 4 Only part of the components of the terminal are shown, but it should be understood that all the shown components are not required, and more or less components can be alternatively implemented.

[0079] The memory 20 can be an internal storage unit of the terminal in some embodiments, such as a hard disk or a memory of the terminal. The memory 20 can also be an external storage device of the terminal in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped on the terminal. Further, the memory 20 can include both the internal storage unit and the external storage device of the terminal. The memory 20 is used to store application software and various data installed on the terminal, such as program codes of the terminal, etc. The memory 20 can also be used to temporarily store data that has been output or will be output. In an embodiment, the memory 20 stores a health education program 40 of a health education system based on multi-modal data perception and adaptive intervention, which can be executed by the processor 10 to implement the health education method of the health education system based on multi-modal data perception and adaptive intervention.

[0080] The processor 10 can be a Central Processing Unit (CPU), a microprocessor or other data processing chip in some embodiments, which is used to run program codes or process data stored in the memory 20, such as to execute the health education system and method based on multi-modal data perception and adaptive intervention, etc.

[0081] The display 30 can be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, etc. in some embodiments. The display 30 is used to display information of the terminal and to display a visualized patient interface. The components of the terminal communicate with each other through a system bus.

[0082] In an embodiment, the health education method described above is implemented when the processor 10 executes the health education program 40 of the health education system based on multi-modal data perception and adaptive intervention in the memory 20.

[0083] The present application also provides a computer readable storage medium, wherein the computer readable storage medium stores a health education program of a health education system based on multi-modal data perception and adaptive intervention, which, when executed by a processor, implements the steps of the health education method of the health education system based on multi-modal data perception and adaptive intervention as described above.

[0084] In summary, the present application provides a health education system, method, system and terminal based on multi-modal data perception and adaptive intervention, the system comprising: a health education scheme construction module, a physiological behavior data acquisition module, an emotional state judgment module, an adaptive intervention module and a targeted health education module, the health education scheme construction module, the physiological behavior data acquisition module, the emotional state judgment module, the adaptive intervention module and the targeted health education module are connected in sequence. The present application ensures the effectiveness of information transmission through the personalized engine, ensures the efficiency of nursing management through the closed-loop feedback mechanism, and finally ensures the humanization of the medical process through immersive experience and emotional care, truly realizes the modern nursing concept of patient-centered, improves the efficiency and accuracy of health education, and brings comprehensive improvement of nursing quality, patient safety and medical satisfaction.

[0085] It should be noted that in this paper, the term "includes", "comprises" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or terminal including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or terminal. Without more limitations, the element defined by the statement "includes one" does not exclude the presence of other identical elements in the process, method, article or terminal including the element.

[0086] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the computer program can include the processes of the above-mentioned embodiments of the method. Any reference to memory, storage, database or other medium used in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0087] It should be understood that the application is not limited to the above examples, and those skilled in the art can make improvements or changes according to the above description, and all these improvements and changes shall fall within the protection scope of the appended claims of the present application.

Claims

1. A health education system based on multimodal data perception and adaptive intervention, characterized in that, The health education system based on multimodal data perception and adaptive intervention includes: a health education program construction module, a physiological behavior data acquisition module, an emotional state judgment module, an adaptive intervention module, and a targeted health education module, wherein the health education program construction module, the physiological behavior data acquisition module, the emotional state judgment module, the adaptive intervention module, and the targeted health education module are connected sequentially. The health education program construction module is used to acquire the patient's static data, construct a static profile of the patient based on the static data, and construct a personalized health education program from the resource library based on the static profile. The physiological behavior data acquisition module is used to play the personalized health education program to the patient through VR technology and to collect the patient's dynamic physiological behavior data in the VR immersive experience in real time. The emotional state judgment module is used to obtain the patient's emotional state based on the dynamic physiological behavior data, and to determine whether the emotional state is negative. The adaptive intervention module is used to perform adaptive intervention on the patient according to the type of the negative emotional state if the emotional state is negative, until the negative state is eliminated, and then continue playing the personalized health education program. The targeted health education module is used to obtain the patient's immediate comprehension level through an interactive questionnaire after the personalized health education program has finished playing. The immediate comprehension level is then sent to the nurse workstation for analysis and organization to obtain a task list, and targeted health education is conducted on the patient based on the task list.

2. The health education system based on multimodal data perception and adaptive intervention according to claim 1, characterized in that, The health education program construction module includes: a static data creation unit, a static profile construction unit, and a personalized program generation unit; The static data creation unit is used to create static data for the patient, including age, education level, diagnosis, allergy history, past surgical history, and language preference, by connecting to the hospital's HIS system or by manual input by nurses. The static profile building unit is used to label the patient with multiple tags based on the static data and to build a static profile of the patient based on the tags, wherein the tags include age and cognitive level, disease type and content type; The personalized solution generation unit is used to preset a multimedia health education resource library, and based on the static profile, construct a personalized health education solution adapted to the patient from the multimedia health education resource library.

3. The health education system based on multimodal data perception and adaptive intervention according to claim 1, characterized in that, The physiological behavior data acquisition module includes: a scene division unit, a preoperative simulation unit, an intraoperative simulation unit, a postoperative simulation unit, and a behavior data acquisition unit; The scenario segmentation unit is used to divide the personalized health education program into preoperative scenarios, intraoperative scenarios, and postoperative scenarios. The preoperative simulation unit is used to simulate the operating room environment in the preoperative scenario using VR technology, display the operating room environment to the patient, and provide the patient with voice explanations to guide them on the procedures after entering the operating room. The intraoperative simulation unit is used to simulate the patient's physical sensations during the operation using VR technology in the intraoperative scenario, and to transmit the physical sensations to the patient. The postoperative simulation unit is used to simulate the patient's postoperative recovery process in the postoperative scenario using VR technology, so that the patient can understand the recovery steps in advance. The behavioral data acquisition unit is used to deploy a medical-grade wearable device on the patient, or to deploy a non-contact sensor in a VR head-mounted display device or a bedside tablet camera, to collect dynamic physiological behavioral data of the patient during the VR immersive experience through the medical-grade wearable device or the non-contact sensor. The dynamic physiological behavioral data includes heart rate, heart rate variability, skin conductance response, blink frequency, and head movement.

4. The health education system based on multimodal data perception and adaptive intervention according to claim 3, characterized in that, The emotional state judgment module includes: a tension state judgment unit, an attention distraction state judgment unit, a stable state judgment unit, and a negative state judgment unit; The tension state judgment unit is used to determine that the patient's emotional state is tense when the heart rate is greater than a preset range, the heart rate variability is reduced, and the skin conductance response is increased. The attention distraction state judgment unit is used to determine that the patient's emotional state is an attention distraction state when the heart rate is within the preset range, the blinking frequency is reduced, and the head movement is a prolonged period of no movement. The stable state determination unit is used to determine that the patient's emotional state is stable when the patient's emotional state is not in a state of tension or distraction. The negative state judgment unit is used to determine whether the emotional state is negative based on the judgment results of the tension state judgment unit, the distraction state judgment unit, and the stable state judgment unit.

5. The health education system based on multimodal data perception and adaptive intervention according to claim 4, characterized in that, The adaptive intervention module includes: a tension intervention unit, an attention distraction intervention unit, and a personalized treatment plan modification unit; The tension intervention unit is used to immediately pause the personalized health education program if the type of negative state is tension, play a preset soothing scene to the patient through VR technology, and continuously monitor the patient's dynamic physiological behavior data until the dynamic physiological behavior data returns to the baseline level. Then, it asks the patient with a preset gentle prompt tone whether to continue. After receiving confirmation from the patient, it resumes playing the personalized health education program from the pause point. The attention distraction intervention unit is used to immediately pause the personalized health education program if the type of the negative state is the attention distraction state, pop up interactive questions to re-attract the patient's attention, and continuously monitor the patient's dynamic physiological behavior data until the dynamic physiological behavior data returns to the baseline level, and then resume playing the personalized health education program from the pause point. The personalized program modification unit is used to stop popping up the interactive mini-questions if the patient remains in a distracted state within a preset time after the interactive mini-questions pop up, and to change the content presentation mode of the personalized health education program from the pause point to continue playing the personalized health education program.

6. The health education system based on multimodal data perception and adaptive intervention according to claim 1, characterized in that, The targeted health education module includes: a comprehension acquisition unit, an analysis and organization unit, and a targeted task execution unit; The comprehension acquisition unit is used to match the corresponding level of interactive questionnaires based on the patient's static profile and the personalized health education program. When the patient completes the interactive questionnaire, the unit generates the patient's instant comprehension level in real time. The analysis and organization unit is used to send the real-time comprehension level to the nurse workstation for analysis, to obtain the patient's weak knowledge points, and to organize the weak knowledge points to obtain a task list and priority prompts; The targeted task execution unit is used to send the task list and the priority prompts to the corresponding nursing team, and guide the nursing team to conduct targeted health education for the patient according to the task list and the priority prompts.

7. A health education method based on the health education system based on multimodal data perception and adaptive intervention as described in any one of claims 1-6, characterized in that, The health education methods include: Acquire static data of patients, construct static profiles of patients based on the static data, and construct personalized health education programs from resource databases based on the static profiles; The personalized health education program is played to the patient using VR technology, and the patient's dynamic physiological and behavioral data during the VR immersive experience are collected in real time. The patient's emotional state is obtained based on the dynamic physiological behavior data, and it is determined whether the emotional state is negative. If the emotional state is negative, then adaptive intervention is performed on the patient according to the type of negative state until the negative state is eliminated, and then the personalized health education program continues to be played. After the personalized health education program is played, the patient's immediate comprehension level is obtained through an interactive questionnaire. The immediate comprehension level is then sent to the nurse workstation for analysis and organization to obtain a task list. Based on the task list, targeted health education is then provided to the patient.

8. The health education method based on a multimodal data perception and adaptive intervention health education system according to claim 7, characterized in that, The process of obtaining the patient's emotional state based on the dynamic physiological behavior data specifically includes: If the heart rate is greater than the preset range, the heart rate variability is reduced, and the skin conductance response is increased, then the patient's emotional state is determined to be a state of tension. If the heart rate is within the preset range, the blinking frequency decreases, and the head movement is inactive for a long time, then the patient's emotional state is determined to be a state of distraction. If the patient's emotional state is not tense or distracted, then the patient's emotional state is determined to be stable. Among them, the state of tension and the state of distraction are negative states.

9. A terminal, characterized in that, The terminal includes: a memory, a processor, and a health education program based on a health education system of multimodal data perception and adaptive intervention, stored in the memory and executable on the processor. When the health education program based on a health education system of multimodal data perception and adaptive intervention is executed by the processor, it implements the steps of the health education method based on a health education system of multimodal data perception and adaptive intervention as described in any one of claims 7-8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a health education program based on a health education system with multimodal data perception and adaptive intervention. When the health education program based on the health education system with multimodal data perception and adaptive intervention is executed by a processor, it implements the steps of the health education method based on the health education system with multimodal data perception and adaptive intervention as described in any one of claims 7-8.

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