Personalized virtual reality cognitive rehabilitation method and system based on heart rate regulation training difficulty

Abstract

The invention discloses a personalized virtual reality cognitive rehabilitation method and system based on heart rate regulation training difficulty, and the method comprises the steps: displaying virtual reality scene information to a user through a virtual reality helmet according to user instruction information, and collecting the heart rate physiological data of the user in real time; a heart rate change index is obtained by calculating the ratio of the real-time heart rate data to the user baseline heart rate, and training task difficulty adjustment is carried out. According to the method, a personalized difficulty adjustment mechanism based on heart rate regulation and control is realized, the mechanism accurately evaluates the cognitive load state of a patient by monitoring the heart rate change of the patient in real time, and the difficulty level of a training task is adjusted according to the cognitive load state; the adjustment ensures that the training content is always maintained in the most suitable challenge interval of the patient, the training value is not lost due to simplicity, and the contusion feeling caused by difficulty is avoided, so that the recovery process of cognitive competence is promoted to the maximum extent.

Description

Technical Field

[0001] The present invention relates to the field of virtual reality, and specifically to a personalized virtual reality cognitive rehabilitation method and system based on heart rate regulation of training difficulty. Background Art

[0002] Mild Cognitive Impairment (MCI) is an intermediate state between normal aging and dementia. MCI has an insidious onset and is often overlooked. If effective intervention can be carried out at the MCI stage, the cognitive function reversal rate can reach 31%, effectively slowing down cognitive decline and reducing the incidence of Alzheimer's disease.

[0003] In recent years, Virtual Reality (VR) technology, as a novel cognitive training technology, has shown potential in the field of neurorehabilitation, bringing innovation to treatment with its immersive experience, intuitive interaction and other advantages. However, there are technical defects in the virtual reality cognitive rehabilitation systems on the market, such as lack of personalized difficulty adjustment, insufficient real-time physiological response monitoring, single sensory feedback, and disconnection between task scenarios and real life, which affect the effect of patients' cognitive ability recovery and user experience.

[0004] Based on the above situation, designing a virtual reality system that can timely evaluate the training performance of patients and provide a personalized task difficulty adjustment strategy has become an urgent problem to be solved currently. Summary of the Invention

[0005] The purpose of this application is to solve the problems in the prior art, and provide a personalized virtual reality cognitive rehabilitation method and system based on heart rate regulation of training difficulty.

[0006] To achieve the above purpose, the technical solutions adopted by the present invention are as follows:

[0007] On the one hand, the present invention provides a personalized virtual reality cognitive rehabilitation method based on heart rate regulation of training difficulty, which includes:

[0008] According to the user instruction information, through the virtual reality helmet, display the virtual reality scene information to the user, and collect the user's heart rate physiological data in real time;

[0009] Calculate the ratio of the real-time heart rate data and the user's baseline heart rate to obtain the heart rate change index, and adjust the training task difficulty.

[0010] Further, the training task difficulty is adjusted as follows:

[0011] (1) If the heart rate change index < 0.8, it means that the user is in a low stress state, then increase the training task difficulty;

[0012] (2) If 0.8 < heart rate change index < 1.2, the user is in a medium stress state, and the training task difficulty is maintained;

[0013] (3) If the heart rate change index > 1.2, the user is in a high stress state, and the training task difficulty is reduced.

[0014] Furthermore, in the virtual reality scenario, use the handle to operate the UI panel, and sequentially perform cognitive rehabilitation training tasks such as "baseline heart rate test", "medium-difficulty refrigerator memory task", "adaptive-difficulty refrigerator memory task", "medium-difficulty refrigerator item classification task", "adaptive-difficulty refrigerator item classification task", "medium-difficulty poker arithmetic task", and "adaptive-difficulty poker arithmetic task", and export the training data in real time.

[0015] Even further, the steps of the rehabilitation training task are as follows:

[0016] S1. After the scene is loaded, automatically enter the "baseline heart rate level test". Before starting the training, measure the average heart rate data of the subject in the resting state as the baseline heart rate, and at the same time, the system displays the real-time heart rate status of the subject through the visualization interface;

[0017] S2. Click the UI interface button through the handle interaction, and the scene jumps to the medium-difficulty refrigerator item memory task;

[0018] S3. After the training is over, calculate the heart rate change index of the subject according to the average real-time heart rate data in the subject's just-completed training task, and at the same time evaluate the cognitive load level of the subject. Adjust the training difficulty according to the different results, and perform the refrigerator item memory task with adaptive difficulty;

[0019] S4. After the adaptive-difficulty refrigerator item memory task is over, click the UI interface button through the handle interaction, and the scene jumps to the medium-difficulty refrigerator item classification task;

[0020] S5. After the training is over, calculate the heart rate change index of the subject according to the average real-time heart rate data in the subject's just-completed training task, and at the same time evaluate the cognitive load level of the subject. Adjust the training difficulty according to the different results, and perform the refrigerator item classification task with adaptive difficulty;

[0021] S6. After the adaptive-difficulty refrigerator item classification task is over, click the UI interface button through the handle interaction, and the scene jumps to the medium-difficulty poker arithmetic task;

[0022] S7. After the training is completed, calculate the heart rate change index of the subject based on the average real-time heart rate data in the subject's just-completed training task, and at the same time evaluate the cognitive load level of the subject. Adjust the training difficulty according to the different results, and perform an adaptive-difficulty poker arithmetic task.

[0023] Furthermore, the step S2 includes:

[0024] S21. Before starting to find the location of the item, the refrigerator door automatically opens, and the subject uses a period of time to memorize the placement location of the food in the refrigerator.

[0025] S22. After the memorization is completed, enter the searching stage; the subject recalls the location of the food specified by the system within a specific time, opens the corresponding refrigerator door of the food, takes out the food and puts it into the basket, and there will be different sound feedbacks on whether the placed item is correct or not when the subject puts in the food.

[0026] S23. If the subject finds the locations of five foods successively in the searching stage, record the subject's real-time heart rate data, the time used for each search, whether the wrong door is opened, and whether the correct food is put into the basket for subsequent analysis.

[0027] Furthermore, the step S4 includes:

[0028] S41. In the memorization stage, the refrigerator door automatically opens, and according to the different difficulties, the subject memorizes the placement locations of different partitions in the refrigerator within 10 - 15 seconds.

[0029] S42. After the memorization is completed, enter the classification stage; in the classification stage, the foods randomly appear at various positions in the refrigerator, and the specific positions of the partitions are no longer displayed. The subject recalls the specific positions of different partitions within the specified time limit and takes out the foods and puts them into the correct partitions.

[0030] S43. When the time limit ends or the subject presses the stop button, count the number of correct classifications of the subject, and write the time used by the subject in this training, the number of times of using hints, and the real-time heart rate into the text for subsequent analysis.

[0031] Furthermore, the step S6 includes:

[0032] S61. During the training process, two different groups of playing cards randomly appear on the table, with 2 - 3 cards in each group. At the same time, the system requires the subject to perform four arithmetic operations on the two groups of playing cards according to the card face sizes, and the operation type will randomly be one of addition, subtraction, and multiplication.

[0033] S62. After the subject completes the operation, let the subject point out which group of playing cards has a larger operation result and judge whether the answer is correct or not.

[0034] S63. After the training is completed, record the real-time heart rate data, calculation time, and score data of the subject during this training for subsequent analysis and research.

[0035] On the other hand, the present invention also provides a personalized virtual reality cognitive rehabilitation system based on heart rate regulation of training difficulty. The system includes:

[0036] A virtual reality helmet that, according to the user's instructions, displays virtual scene information and a real-time heart rate visualization interface to the user, collects the user's real-time heart rate, calculates a heart rate change index, and adjusts the training difficulty according to this index;

[0037] A heart rate feedback visualization interface module that displays the real-time heart rate status of the subject through a visualization interface.

[0038] Furthermore, it includes three training task scenarios, namely: a refrigerator item memory scenario, a refrigerator item classification scenario, and a poker arithmetic scenario.

[0039] Even further, different task scenarios are set with different training difficulties.

[0040] The beneficial effects of the present invention are as follows: Through a series of innovative designs, the present invention significantly improves the personalization and user experience of the virtual reality cognitive rehabilitation system, thereby more effectively promoting the recovery of the patient's cognitive ability. Specifically, the system first realizes a personalized difficulty adjustment mechanism based on heart rate regulation. This mechanism accurately evaluates the cognitive load status of the patient by real-time monitoring of the heart rate change, and adjusts the difficulty level of the training task accordingly. This adjustment ensures that the training content always remains within the most suitable challenge range for the patient, neither too simple to lose the training value nor too difficult to cause frustration, thus maximizing the promotion of the cognitive ability recovery process.

[0041] In the design of the training scenario, it closely adheres to the daily life needs of the patient, sets the training environment as a home scenario, such as familiar environments like the kitchen and living room. By simulating tasks close to life such as refrigerator memory and poker arithmetic, the system not only improves the practicality of the training but also enhances the patient's ability to apply the training results to real life.

[0042] In addition, the present invention designs a visualization interface and an operation UI in the virtual scene, which allows the patient to independently select the next training task and the difficulty of the current training task.

[0043] Additional aspects and advantages of the present invention will be given in part in the following description, will become apparent in part from the following description, or will be understood through the practice of the present invention. Description of the Drawings

[0044] Figure 1Flow chart for adjusting the difficulty of cognitive load training according to the present invention;

[0045] Figure 2 VR scene diagram for measuring the baseline heart rate according to the present invention;

[0046] Figure 3 Heart rate feedback visualization interface diagram according to the present invention;

[0047] Figure 4 Scene diagram of the memory stage of the refrigerator item memory task according to the present invention;

[0048] Figure 5 Scene diagram of the searching stage of the refrigerator item memory task according to the present invention;

[0049] Figure 6 Three difficulty design diagrams of the refrigerator item memory task according to the present invention;

[0050] Figure 7 Scene diagram of the memory stage of the refrigerator item classification task according to the present invention;

[0051] Figure 8 Scene diagram of the classification stage of the refrigerator item classification task according to the present invention;

[0052] Figure 9 Three difficulty design diagrams of the refrigerator item classification task according to the present invention;

[0053] Figure 10 Specific scene diagram of the playing card arithmetic training according to the present invention;

[0054] Figure 11 UI design diagram in the refrigerator memory task according to the present invention;

[0055] Figure 12 Three difficulty design diagrams of the playing card arithmetic task according to the present invention. Detailed implementation manners

[0056] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific implementation methods, but the protection scope of the present invention is not limited thereto.

[0057] Embodiment 1

[0058] As Figure 1 shown, a personalized virtual reality cognitive rehabilitation method based on adjusting the training difficulty according to heart rate includes:

[0059] S101, using the real-time heart rate data of the subject to determine whether the training difficulty is suitable for the subject. At the same time, in order to eliminate as much as possible the individual differences in heart rate and its changes among different people during the execution of the training task, a heart rate change index I is introduced:

[0060]

[0061] where I represents the relative heart rate change index, and H train is the average heart rate data of the medium training tasks during the subject's training, and H base is the baseline average heart rate, which is the average heart rate of the subject at rest. By calculating the degree of change in the average heart rate of the subject during the task execution relative to the baseline average heart rate of the subject at rest, the psychological stress state of the current subject is judged, and the training task difficulty is adjusted accordingly.

[0062] S102. Before starting the training, the system automatically measures the heart rate of the subject. The subject needs to remain in a relaxed state for 1 - 2 minutes. After the measurement, the system calculates the average heart rate during this period and uses it as the baseline heart rate. For the VR scenario of measuring the baseline heart rate, such as Figure 2 shown.

[0063] S103. According to the collected heart rate information, calculate the heart rate change index of the subject and adjust the training difficulty. The adjustment of the training task difficulty is as follows:

[0064] (1) If the heart rate change index < 0.8, it means the user is in a low - stress state, then increase the training task difficulty;

[0065] (2) If 0.8 < heart rate change index < 1.2, it means the user is in a medium - stress state, then maintain the training task difficulty;

[0066] (3) If the heart rate change index > 1.2, it means the user is in a high - stress state, then reduce the training task difficulty.

[0067] Embodiment 2

[0068] Based on the above - mentioned method for adjusting training difficulty based on heart rate, this embodiment proposes a system for adjusting training difficulty based on heart rate regulation, which may include:

[0069] A virtual reality helmet, according to the user's instruction, displays virtual scene information and a real - time heart rate visualization interface to the user. Collects the user's real - time heart rate, calculates the heart rate change index, and adjusts the training difficulty according to this index.

[0070] A heart rate feedback visualization interface module. The system displays the real - time heart rate state of the subject through the visualization interface. Figure 3The HP Omnicept G2 headset is used to collect the current heart rate data of the subject and display it through this interface, which can enable the subject, caregiver, and physician to better understand the subject's training situation, and also enable the subject to better understand the task plan and self-status, thereby improving the training effect and operation experience. In this embodiment, the HeartrateDisplay.cs script can be written to complete this function. This script aims to obtain heart rate data from the sensor object and display this data on the UI. Specifically, text (Text component) is used to display the heart rate value, and different pictures are displayed according to different ranges of the heart rate value.

[0071] The implementation process of this system is as follows:

[0072] S1. Open the mixed reality portal software, connect the HP Omnicept G2 virtual reality headset to the computer in series, start the exe project developed by unity, and wait for the scene to load.

[0073] S2. In the VR environment, use the handle to operate the UI panel, and sequentially perform three cognitive rehabilitation training tasks: "Baseline heart rate test", "Refrigerator memory task (medium difficulty)", "Refrigerator memory task (adaptive difficulty)", "Refrigerator item classification task (medium difficulty)", "Refrigerator item classification task (adaptive difficulty)", "Playing card arithmetic task (medium difficulty)", "Playing card arithmetic task (adaptive difficulty)", and export the training data in real time.

[0074] As an application example, the present invention can be applied to the rehabilitation training of diseases such as patients with mild cognitive impairment. In practical applications, the present invention can be applied to any scenario where training on memory, attention, executive function, visual-spatial ability, and logical reasoning ability is required.

[0075] As an example, the personalized virtual reality cognitive rehabilitation system based on heart rate regulation of training difficulty mainly includes three training task scenarios.

[0076] (1) Refrigerator item memory scenario. During the process of the user using the virtual reality headset to perform the virtual refrigerator item memory task, it can include:

[0077] 1.1 Scene construction

[0078] In order to better simulate the daily life scenario of the subject, the VR scene of the present invention is set as a home scene, and the three-door refrigerator for placing food is placed in the prescription of this scene. The foods to be searched for are composed of foods that the elderly often see in daily life, mainly including some fruits, vegetables, and meats. At the same time, a basket is set on the left side of the refrigerator, and the subject needs to take out the food from the refrigerator and put it into the basket to complete the task.

[0079] 1.2 Training Process

[0080] 1.2.1 Memory Stage: Before starting to search for the location of the items specified by the system, the refrigerator door will automatically open, and the subject needs to spend some time memorizing the placement of the food inside the refrigerator. As Figure 4 shown, during this stage, the food will randomly appear at the specified positions inside the refrigerator.

[0081] 1.2.2 The OpenDoor method can achieve the function of automatically opening the refrigerator door. First, set the initial state of the door to the closed state and define the target rotation angle as 90 degrees. Then, by traversing each frame, according to the set rotation speed rotationSpeed and the time difference (Time.deltaTime) between the current frame and the previous frame, calculate the angle that should be rotated in the current frame and accumulate it to the rotated angle. For each door, it rotates around its respective rotation axis (axis) through the RotateAround method, where the left door handle rotates upward, while the right door and the upper right door handle rotate downward (achieved through negative angles). When the accumulated rotation angle reaches or exceeds the target angle, stop the rotation process and end the coroutine. This process achieves a smooth rotation animation effect through frame-by-frame updates and checks. During the training search stage of the refrigerator memory task.

[0082] 1.2.3 Search Stage: As Figure 5 shown, the subject needs to recall the location of the food specified by the system within a specific time, open the corresponding correct refrigerator door, take out the food and put it into the basket. When the subject puts in the food, there will be different sound feedbacks on whether the item put in is correct or not. The subject needs to find the locations of five foods successively during the search stage. After the answer is completed, the system will record the subject's real-time heart rate data, the time taken for each search, whether the wrong door is opened, and whether the correct food is put into the basket and other data for subsequent analysis.

[0083] 1.3 Difficulty Design

[0084] This task is designed with three levels of difficulty, as shown in the appendix Figure 6 shown. Figure 6 (a) is the low difficulty level, where seven foods whose locations need to be memorized will appear inside the refrigerator, and the subject has 30s of memory time; Figure 6 (b) is the medium difficulty level, where nine foods whose locations need to be memorized will appear inside the refrigerator, and the subject has 30s of memory time; Figure 6 (c) is the high difficulty level, where nine foods whose locations need to be memorized will appear inside the refrigerator, and the subject has 20s of memory time.

[0085] (2) Refrigerator item classification scenario. During the process of the user using a virtual reality headset to perform a virtual refrigerator item classification task, it may include:

[0086] 2.1 Scene construction

[0087] Similar to the refrigerator memory task, the VR scene is set as a home scene. The refrigerator is placed in the kitchen, and the foods to be classified will be placed inside the refrigerator. These foods are composed of foods that the elderly often see in daily life, mainly including vegetables, fruits, meats, and some beverages.

[0088] 2.2 Training process

[0089] 2.2.1 Memory stage: As Figure 7 shown, in this stage, the refrigerator door will automatically open. Depending on the difficulty level, the subject needs to memorize the placement positions of different compartments inside the refrigerator, such as the vegetable compartment, the freezer compartment, etc., including behind which refrigerator door and on which shelf within the compartment, within 10 - 15 seconds. At this time, the foods to be classified will appear in the correct compartments for the subject to memorize.

[0090] 2.2.2 Classification stage: As Figure 8 shown, during the classification stage, the foods will randomly appear in various positions inside the refrigerator, and the specific positions of the compartments will no longer be displayed. The subject needs to recall the specific positions of different compartments within the specified time limit (30 - 60 seconds) and take out the foods and place them in the correct compartments. When the time limit ends or the subject presses the stop button, the system will count the number of correctly classified items by the subject and write the time used by the subject in this training, the number of times of using prompts, and the real-time heart rate into the text for subsequent analysis.

[0091] 2.3 Difficulty design

[0092] This task is designed with three difficulty levels, as shown in the appendix Figure 9 shown. Appendix Figure 9 (a) is the low difficulty level. The foods inside the refrigerator need to be classified into two compartments, namely the freezer compartment and the refrigerating compartment, and the subject has 15 seconds of memory time; Figure 9 (b) is the medium difficulty level. The foods inside the refrigerator need to be classified into three compartments, namely the freezer compartment, the vegetable compartment, and the fruit compartment, and the subject has 15 seconds of memory time; Figure 9 (c) is the high difficulty level. The foods inside the refrigerator need to be classified into four compartments, namely the freezer compartment, the vegetable compartment, the fruit compartment, and the beverage compartment, and the subject has 10 seconds of memory time.

[0093] (3) Playing card arithmetic scenario. During the process of the user using a virtual reality headset to perform a virtual playing card arithmetic task, it may include:

[0094] 3.1 Scene construction

[0095] To better simulate the scenario of subjects playing poker at home usually, the VR scenario is set in a home environment. The task scenario is set on the table in the living room at home. The poker cards that need to be calculated are placed on the table and divided into two groups on the left and right sides respectively. The subjects need to calculate the size and then select which side has a larger value through a button.

[0096] 3.2 Training process

[0097] 3.2.1 Training process: Two different groups of poker cards will randomly appear on the table, with 2 - 3 cards in each group. At the same time, the system will require the subjects to perform four arithmetic operations on the two groups of poker cards respectively according to the size of the poker card faces, and the operation type will randomly be one of addition, subtraction, and multiplication. After the subjects complete the operations, they need to indicate which group of poker cards has a larger operation result. Whether the answer is correct or not, after the subjects give the answer, they can proceed to the next question to continue training, as Figure 10 shown. After the training is over, the system will record the real - time heart rate data, calculation time, and score data of the subjects during this training for subsequent analysis and research.

[0098] 3.2.2 Training scenario jump: After completing this task, click the UI to perform a scenario jump, as Figure 11 shown. In this system, to avoid the occurrence of VR motion sickness, all operations in the system do not involve movement. The switching between different tasks also imitates the teleportation behavior time of the first - person virtual controller in the VRIF framework, that is, when jumping tasks, the subject's field of vision will briefly darken for a period of time, and then become bright again after the jump is completed. For example, switching the scene back to the refrigerator memory task is implemented by the BackToMemoryTest() function: First, prepare the visual effect before teleportation through the BeforeTeleportFade() method of the PlayerTeleport component; then, set the player's position to the preset position in front of the refrigerator in the VR scene of the refrigerator memory task and retain the player's rotation information; next, use the TeleportPlayer method to teleport the player to the new position in combination with the new position and the retained rotation information; after that, start a coroutine RotationToMemory to handle the animation related to rotation; finally, update the status flag to indicate the end of the calculation phase and close the relevant UI interface.

[0099] 3.3 Difficulty design

[0100] This task is designed with three levels of difficulty, as shown in the appendix Figure 12 shown. The low difficulty is as shown in Figure 12 (a), and all operations are addition and subtraction operations between two cards; the medium difficulty is as shown in Figure 12(As shown in (b), multiplication operations between two cards will occur. And to reflect the increasing difficulty, the frequency of multiplication operations will be greater than that of addition and subtraction operations. For high difficulty levels, as shown in Figure 12 (c), the number of cards for addition and subtraction operations increases to three per group. The subjects can choose different task difficulties for training according to their own psychological stress levels.

[0101] The above has shown and described the basic principles, main features and advantages of the present invention. Those of ordinary skill in the art should understand that the above embodiments do not limit the protection scope of the present invention in any form. Any technical solutions obtained by means of equivalent replacement and the like all fall within the protection scope of the present invention. The parts not involved in the present invention are the same as or can be implemented by the prior art.

Claims

1. A personalized virtual reality cognitive rehabilitation method based on the difficulty of heart rate regulation training, characterized in that: include: According to the user's instruction information, the virtual reality scene information is displayed to the user through the virtual reality helmet, and the user's heart rate physiological data is collected in real time; By calculating the ratio of real-time heart rate data and the user's baseline heart rate, the heart rate change index is obtained to adjust the difficulty of the training task.

2. The personalized virtual reality cognitive rehabilitation method based on heart rate regulation training difficulty according to claim 1, characterized in that: The difficulty of training missions has been adjusted as follows: (1) If the heart rate variability index is <0.8, the user is in a low-stress state, and the difficulty of the training task is increased; (2) If 0.8 < HRV < 1.2, the user is in a moderate stress state, and the training task difficulty is maintained; (3) If the heart rate variability index is >1.2, the user is under high stress, so the difficulty of the training task is reduced.

3. The personalized virtual reality cognitive rehabilitation method based on heart rate regulation training difficulty according to claim 1, characterized in that: In the virtual reality scene, use the handle to operate the UI panel to perform the cognitive rehabilitation training tasks of "baseline heart rate test", "medium difficulty refrigerator memory task", "adaptive difficulty refrigerator memory task", "medium difficulty refrigerator item classification task", "adaptive difficulty refrigerator item classification task", "medium difficulty playing card arithmetic task", and "adaptive difficulty playing card arithmetic task" in turn, and export the training data in real time.

4. The personalized virtual reality cognitive rehabilitation method based on heart rate regulation training difficulty according to claim 3, characterized in that: The steps of the rehabilitation training task are as follows: S1. After the scene is loaded, it will automatically enter the "Baseline Heart Rate Level Test". Before starting training, the average heart rate data of the subject in the resting state is measured as the baseline heart rate. At the same time, the system displays the subject's real-time heart rate status through a visual interface; S2. Click the UI button through the controller interaction to jump into the medium-difficulty refrigerator item memory task; S3. After the training, the heart rate change index of the subject is calculated based on the average real-time heart rate data of the subject in the training task just now, and the cognitive load level of the subject is evaluated at the same time. The training difficulty is adjusted according to the different results, and the refrigerator item memory task with adaptive difficulty is carried out; S4. After the adaptive difficulty refrigerator item memory task is completed, click the UI interface button through the controller interaction, and the scene jumps to the medium difficulty refrigerator item classification task; S5. After the training, the heart rate change index of the subject is calculated based on the average real-time heart rate data of the subject in the training task just now, and the cognitive load level of the subject is evaluated at the same time. The training difficulty is adjusted according to the different results, and the refrigerator item classification task with adaptive difficulty is carried out; S6. After the adaptive difficulty refrigerator item classification task is completed, click the UI interface button through the controller interaction, and the scene jumps to the medium difficulty poker card arithmetic task; S7. After the training, the heart rate change index of the subject is calculated according to the average real-time heart rate data of the subject in the training task just now, and the cognitive load level of the subject is evaluated at the same time. The training difficulty is adjusted according to the different results, and a poker arithmetic task of adaptive difficulty is carried out.

5. The personalized virtual reality cognitive rehabilitation method based on heart rate regulation training difficulty according to claim 3, characterized in that: The step S2 comprises: S21. Before starting to look for the location of the items, the refrigerator door automatically opens, and the subjects spend some time memorizing the location of the food in the refrigerator; S22. After the memory is completed, the search phase begins; the subject recalls the food location specified by the system at a specific time, opens the refrigerator door corresponding to the food, takes out the food and puts it into the basket. When the subject puts the food in, different sounds will give feedback to indicate whether the item is put in correctly or not; S23. If the subject finds the locations of five foods in succession during the searching phase, record the subject's real-time heart rate data, the time taken to complete each search, whether the wrong door was opened, and whether the correct food was placed in the basket for subsequent analysis.

6. The personalized virtual reality cognitive rehabilitation method based on heart rate regulation training difficulty according to claim 3, characterized in that: The step S4 comprises: S41. In the memorizing phase, the refrigerator door opens automatically. Depending on the difficulty, the subject memorizes the locations of different partitions in the refrigerator within 10-15 seconds. S42, after the memory is completed, the classification stage begins; in the classification stage, the food appears randomly in various locations of the refrigerator, and the specific locations of the partitions are no longer displayed. The subject recalls the specific locations of different partitions within a specified time limit, and takes out the food and puts it in the correct partition; S43. When the time limit ends or the subject presses the stop button, the number of correct classifications of the subject is counted and written into a text together with the time the subject spent in this training, the number of times the prompt is used, and the real-time heart rate for subsequent analysis.

7. The personalized virtual reality cognitive rehabilitation method based on heart rate regulation training difficulty according to claim 3, characterized in that: The step S6 comprises: S61. During the training, two different sets of playing cards appeared randomly on the table, with 2-3 cards in each set. At the same time, the system required the subjects to perform four arithmetic operations on the two sets of playing cards according to the size of the cards. The operation type was randomly selected from one of the three types of addition, subtraction, and multiplication. S62. After the subject has completed the calculation, ask him / her to indicate which set of playing cards has the larger result, and judge whether his / her answer is right or wrong; S63. After the training is finished, the real-time heart rate data, calculation time and score data of the subject in this training are recorded for subsequent analysis and research.

8. A personalized virtual reality cognitive rehabilitation system based on the difficulty of heart rate regulation training, characterized in that: The system includes: The virtual reality helmet displays virtual scene information and a real-time heart rate visualization interface to the user according to the user's instructions, collects the user's real-time heart rate, calculates the heart rate change index, and adjusts the training difficulty according to the index; The heart rate feedback visualization interface module displays the subject's real-time heart rate status through a visualization interface.

9. The personalized virtual reality cognitive rehabilitation system based on heart rate regulation training difficulty according to claim 8, characterized in that: The method includes three training task scenarios, namely: refrigerator item memory scenario, refrigerator item classification scenario and playing card arithmetic scenario.

10. The personalized virtual reality cognitive rehabilitation system based on heart rate regulation training difficulty according to claim 9, characterized in that: Different training difficulties are set for different task scenarios.

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