Brain health assessment report generation method and device, product and electronic equipment

Abstract

The invention provides a brain health assessment report generation method and device, a medium and equipment, and relates to the technical field of computers. The method may display an eye movement guide identifier and collect eye movement data including first data corresponding to a facing saccade item, second data corresponding to a reverse saccade item, third data corresponding to a smooth tracking item, and fourth data corresponding to an image observation item, and the brain health risk of the to-be-monitored object is evaluated through the eye movement data so as to determine the brain health assessment report, and the user does not need to search for conversation of a psychological counselor to obtain the brain health report issued by the psychological counselor, so that the step of learning the brain health condition by the user can be saved, and the implementation convenience of a brain health condition acquisition scheme is improved. In addition, the invention further provides a new application of the eye movement data, the eye movement data is applied to the brain health assessment process, the brain health assessment difficulty can be reduced, and the availability of a data source based on a brain health assessment report is improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method for generating a brain health assessment report, a device for generating a brain health assessment report, a computer program product, and an electronic device. Background Art

[0002] As the pace of life continues to accelerate, people's life pressure is gradually increasing, and these pressures are likely to cause poor health conditions such as brain fatigue and brain depression. In related technologies, the way to learn about brain health is usually to talk to a psychologist to obtain a brain health report issued by the psychologist, or to determine brain health through brain CT and other methods.

[0003] However, the above methods have problems such as complicated steps and insufficient implementation convenience. Summary of the invention

[0004] The purpose of this application is to provide a method for generating a brain health assessment report, a device for generating a brain health assessment report, a computer-readable storage medium, and an electronic device, which can display an eye movement guidance mark and collect eye movement data including a first data corresponding to a directional scanning item, a second data corresponding to a reverse scanning item, a third data corresponding to a smooth pursuit item, and a fourth data corresponding to an image observation item, and evaluate the brain health risk of the monitored object through the eye movement data and then determine a brain health assessment report. The user does not need to find a psychological counselor to talk to and then obtain a brain health report issued by the psychological counselor, which can save the user the steps of knowing the brain health status and improve the convenience of implementing the brain health status acquisition plan. In addition, a new use of eye movement data is provided. Applying eye movement data to the process of brain health assessment can reduce the difficulty of brain health assessment and improve the availability of the data source based on the brain health assessment report.

[0005] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0006] According to one aspect of the present application, a method for generating a brain health assessment report is provided, the method comprising:

[0007] In response to an eye movement detection instruction for an object to be monitored, an eye movement guide mark is displayed at each preset display position in the display area in turn and eye movement data is collected; the eye movement data includes at least one of the following: first data corresponding to a directional scanning item, second data corresponding to a reverse scanning item, third data corresponding to a smooth pursuit item, and fourth data corresponding to an image observation item;

[0008] generating target data for evaluating brain health risks of the subject to be monitored based on the eye movement data;

[0009] A brain health assessment report corresponding to the object to be monitored is generated based on the basic attribute information of the object to be monitored, the descriptive information used to characterize the physical health condition of the object to be monitored, and the target data.

[0010] According to one aspect of the present application, there is provided a device for generating a brain health assessment report, comprising:

[0011] An eye movement data collection unit, for responding to an eye movement detection instruction for an object to be monitored, sequentially displaying an eye movement guide mark at each preset display position in a display area and collecting eye movement data; the eye movement data includes at least one of the following: first data corresponding to a directional scanning item, second data corresponding to a reverse scanning item, third data corresponding to a smooth pursuit item, and fourth data corresponding to an image observation item;

[0012] a target data generating unit, configured to generate target data for evaluating brain health risk of a subject to be monitored based on the eye movement data;

[0013] The brain health assessment report generating unit is used to generate a brain health assessment report corresponding to the object to be monitored based on the basic attribute information of the object to be monitored, the descriptive information used to characterize the physical health condition of the object to be monitored, and the target data.

[0014] According to one aspect of the present application, a brain health assessment report generation system is provided, including a server and a virtual reality device, wherein:

[0015] A virtual reality device, configured to respond to an eye movement detection instruction for an object to be monitored sent by a server, sequentially display an eye movement guide mark at each preset display position in a display area and collect eye movement data; the eye movement data includes at least one of the following: first data corresponding to a directional scanning item, second data corresponding to a reverse scanning item, third data corresponding to a smooth pursuit item, and fourth data corresponding to an image observation item;

[0016] A server, configured to generate target data for evaluating brain health risks of a subject to be monitored based on eye movement data fed back by a virtual reality device;

[0017] The server is also used to generate a brain health assessment report corresponding to the object to be monitored based on the basic attribute information of the object to be monitored, the descriptive information used to characterize the physical health condition of the object to be monitored, and the target data.

[0018] According to one aspect of the present application, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, any one of the above methods is implemented.

[0019] According to one aspect of the present application, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform any one of the above methods by executing the executable instructions.

[0020] The exemplary embodiments of the present application may have some or all of the following beneficial effects:

[0021] In the method for generating a brain health assessment report provided in an example embodiment of the present application, an eye movement guidance mark can be displayed and eye movement data including first data corresponding to a directional scanning item, second data corresponding to a reverse scanning item, third data corresponding to a smooth pursuit item, and fourth data corresponding to an image observation item can be collected. The brain health risk of the monitored object is evaluated through the eye movement data to determine a brain health assessment report. The user does not need to find a psychological counselor to talk to and then obtain a brain health report issued by the psychological counselor, which can save the user the steps of knowing the brain health status and improve the convenience of implementing the brain health status acquisition plan. In addition, a new use of eye movement data is provided. Applying eye movement data to the brain health assessment process can reduce the difficulty of brain health assessment and improve the availability of the data source on which the brain health assessment report is based. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 A flowchart of a method for generating a brain health assessment report according to an embodiment of the present application is schematically shown;

[0024] Figure 2 A schematic diagram of a calibration mark display position according to an embodiment of the present application is schematically shown;

[0025] Figure 3 A schematic diagram of a type of preset display position according to an embodiment of the present application is schematically shown;

[0026] Figure 4 A schematic diagram of two types of preset display positions according to an embodiment of the present application is schematically shown;

[0027] Figure 5 A schematic diagram of a target image according to an embodiment of the present application is schematically shown;

[0028] Figure 6A flowchart of a method for generating a brain health assessment report according to another embodiment of the present application is schematically shown;

[0029] Figure 7 The structure diagram of a brain health assessment report generation system according to an embodiment of the present application is schematically shown;

[0030] Figure 8 The structure block diagram of a device for generating a brain health assessment report according to an embodiment of the present application is schematically shown;

[0031] Fig. 9 The structure diagram of a computer system suitable for implementing an electronic device of an embodiment of the present application is schematically shown. DETAILED DESCRIPTION

[0032] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as being limited to the examples set forth herein; on the contrary, these embodiments are provided so that the present application will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art. The described features, structures, or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical solutions of the present application may be practiced while omitting one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known technical solutions are not shown or described in detail to avoid obscuring various aspects of the present application.

[0033] In addition, the accompanying drawings are only schematic illustrations of the present application and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0034] See also Figure 1 , Figure 1 The flowchart of the method for generating a brain health assessment report according to one embodiment of the present application is schematically shown. Figure 1 As shown, the method for generating a brain health assessment report may include: steps S110 to S130.

[0035] Step S110: In response to the eye movement detection instruction for the object to be monitored, the eye movement guidance mark is displayed in each preset display position in the display area in turn and the eye movement data is collected; the eye movement data includes at least one of the following: first data corresponding to the directional scanning item, second data corresponding to the reverse scanning item, third data corresponding to the smooth pursuit item, and fourth data corresponding to the image observation item.

[0036] Step S120: Generate target data for evaluating the brain health risk of the subject to be monitored based on the eye movement data.

[0037] Step S130: Generate a brain health assessment report corresponding to the object to be monitored based on the basic attribute information of the object to be monitored, the descriptive information used to characterize the physical health condition of the object to be monitored, and the target data.

[0038] In one case, steps S110 to S130 can be executed by any device such as a virtual reality device (VR device), a mobile phone, a tablet computer, etc.

[0039] Implementation Figure 1 The method shown can display eye movement guidance signs and collect eye movement data including first data corresponding to the directional scanning project, second data corresponding to the reverse scanning project, third data corresponding to the smooth pursuit project, and fourth data corresponding to the image observation project, and evaluate the brain health risk of the monitored object through the eye movement data to determine the brain health assessment report. The user does not need to find a psychological counselor to talk to and then obtain a brain health report issued by the psychological counselor, which can save the user the steps of knowing the brain health status and improve the convenience of implementing the brain health status acquisition plan. In addition, a new use of eye movement data is provided. Applying eye movement data to the brain health assessment process can reduce the difficulty of brain health assessment and improve the availability of data sources based on brain health assessment reports.

[0040] Next, the above steps of this exemplary embodiment are described in more detail.

[0041] In order to achieve brain health assessment based on eye movement data, the present application relates to a device that can be used to collect eye movement data, such as a VR device. When the device is detected to be started, it can be tested whether the device and the server can be connected normally. If so, the login information can be uploaded to the server in response to the login operation, so that the server sends the client information of the object to be monitored. Furthermore, the client can be displayed to the object to be monitored based on the client information.

[0042] In step S110, in response to the eye movement detection instruction for the object to be monitored, eye movement guidance marks are displayed in each preset display position in the display area in turn and eye movement data is collected; the eye movement data includes at least one of the following: first data corresponding to a directional scanning item, second data corresponding to a reverse scanning item, third data corresponding to a smooth pursuit item, and fourth data corresponding to an image observation item.

[0043] Specifically, the object to be monitored may be a person, an animal, or a robot. The display area may be a display screen of a VR device, a display screen of a tablet computer, an external screen, a projection, etc., which is not limited in the embodiment of the present application.

[0044] The object to be monitored can trigger the start detection function to trigger the device to generate eye movement detection instructions. After detecting the eye movement detection instructions for the object to be monitored, the eye movement guidance logo can be displayed in each preset display position in the display area in turn and the eye movement data can be collected.

[0045] Among them, each preset display position can be any number of display positions in the display position set, that is, based on the login information of the object to be monitored, a personalized number of preset display positions can be selected for it.

[0046] For example, the number of preset display positions can be made negatively correlated with the age of the subject to be monitored. The older the subject to be monitored, the smaller the number of preset display positions corresponding to the subject. Generally speaking, the younger the age, the faster the reaction speed and the better the physical fitness. Therefore, by displaying eye movement guide signs in a larger number of preset display positions, eye movement data that can more accurately represent the degree of brain health can be collected.

[0047] In addition, the eye movement guiding mark can be realized as a visual mark of any form, any size, any color, and any shape. The eye movement guiding mark is used to guide the monitored object to control the eye movement.

[0048] In the process of sequentially displaying the eye movement guiding marks at each preset display position in the display area, eye movement data may be synchronously collected, and the eye movement data may be used to record the eye movement details.

[0049] As an optional embodiment, it also includes:

[0050] In response to an eye movement calibration instruction for the subject to be monitored, controlling the calibration mark to move along a preset track in the display area and collecting eye movement calibration data;

[0051] When the eye movement calibration data meets the calibration requirements, the calibration is determined to be passed and an eye movement detection instruction is generated.

[0052] It can be seen that by implementing this optional embodiment, the accuracy of subsequently collected eye movement data can be improved through eye movement calibration.

[0053] Specifically, an eye movement calibration process can also be executed before step S110. When an eye movement calibration instruction is detected, the calibration mark can be controlled to move along a preset trajectory in the display area, and eye movement calibration data can be collected to at least verify whether the eye movement data collection module is normal and whether the display function is normal. If all functions and modules are normal, the calibration is determined to be passed.

[0054] In addition, optionally, the eye position may be calibrated to guide the subject to be monitored to move the device so that the eyes are at a specified position.

[0055] For example, you can follow Figure 2 The preset trajectory movement calibration mark is shown, and the monitored object can control the eyeball to move along the preset trajectory. When the overlap rate of the monitored eye movement calibration data and the preset trajectory is greater than a preset value, it is determined that the calibration is passed.

[0056] As an optional embodiment, the eye movement data includes at least one of the following: first data corresponding to a directional scan item, second data corresponding to a reverse scan item, third data corresponding to a smooth pursuit item, and fourth data corresponding to an image observation item.

[0057] It can be seen that implementing this optional embodiment can improve the richness of eye movement data, which is beneficial to improving the accuracy of brain health reports generated based on eye movement data.

[0058] Specifically, the toward-saccade project refers to a project that guides the user to control the eyeball to move along the movement of the eye movement guide marker; the reverse-saccade project refers to a project that guides the user to control the eyeball to move in the opposite direction of the movement of the eye movement guide marker; the smooth-tracking project refers to a project that guides the user to control the eyeball to move along the movement trajectory of the eye movement guide marker; the image observation project refers to a project that guides the user to control the eyeball to look at the eye movement guide marker in the image.

[0059] That is to say, in the process of sequentially displaying the eye movement guiding mark at each preset display position in the display area, at least one of the directional scanning item, the reverse scanning item, the smooth pursuit item, and the image observation item can be executed.

[0060] In addition, optionally, the eye movement data may also include data of other items. For example, the eye movement data may also include fifth data of a video observation item; a video observation item refers to a item that guides the user to control the eyeballs to continuously focus on the position of the eye movement guide mark in the video without being disturbed by other elements in the video.

[0061] As an optional embodiment of step S110, when the eye movement data includes the first data, sequentially displaying an eye movement guide mark at each preset display position in the display area and collecting the eye movement data includes:

[0062] Step S1101a: sequentially displaying eye movement guidance marks at each type of preset display position in the display area;

[0063] Step S1102a: collecting first data corresponding to each type of preset display position as eye movement data;

[0064] Among them, the first data includes at least one of the following: forward scanning accuracy, the time from the time when the eye movement guidance mark is displayed at each preset display position until the eye movement is detected, the average forward scanning time, the average forward scanning speed, and the maximum forward scanning speed.

[0065] It can be seen that the implementation of this optional embodiment can realize the acquisition of eye movement data based on the directional scanning items, which is conducive to improving the precision of the eye movement data.

[0066] Specifically, the eye movement guiding mark can be displayed in each type of preset display position in the display area in sequence. For example, Figure 3 , first display the eye movement guide mark at the first type of preset display position 320, and then display the eye movement guide mark at the first type of preset display position 310. After the eye movement guide mark is displayed at the first type of preset display position 310 for a preset time, the eye movement guide mark displayed at the first type of preset display position 320 may be hidden to guide the monitored object to look from the first type of preset display position 320 to the first type of preset display position 310. In this process, the first data corresponding to each of the first type of preset display positions may be collected as eye movement data.

[0067] Assuming that the number of a type of preset display positions is n1, the collected first data can be expressed as the following table, where the target refers to the eye movement guiding mark.

[0068]

[0069]

[0070] As an optional embodiment of step S110, when the eye movement data includes the second data, the eye movement guiding mark is displayed at each preset display position in the display area in sequence and the eye movement data is collected, and the method further includes:

[0071] Step S1101b: sequentially displaying eye movement guidance marks at the second-category preset display positions in the display area;

[0072] Step S1102b: collecting second data corresponding to each of the two types of preset display positions as eye movement data;

[0073] Among them, the second data includes at least one of the following: the accuracy rate of reverse scanning in the direction opposite to the moving direction of the eye movement guidance mark, the time from the eye movement guidance mark being displayed at each of the two preset display positions until the eye movement is detected, the average completion time of reverse scanning, the average error correction rate of reverse scanning, the error correction time, the average reverse scanning speed, and the maximum reverse scanning speed.

[0074] It can be seen that the implementation of this optional embodiment can realize the acquisition of eye movement data based on the reverse scanning project, which is conducive to improving the precision of the eye movement data.

[0075] Specifically, the eye movement guiding mark can be displayed in turn at each of the two types of preset display positions in the display area. For example, Figure 4 , first display the eye movement guide mark at the second type preset display position 410, and then display the eye movement guide mark at the second type preset display position 320. After the eye movement guide mark is displayed at the second type preset display position 320 for a preset time, the eye movement guide mark displayed at the second type preset display position 310 can be hidden to guide the monitored object to control the eyeball in the opposite direction of the moving direction of the eye movement guide mark. In this process, the first data corresponding to each of the second type preset display positions can be collected as eye movement data.

[0076] Assuming that the number of the second type of preset display positions is n2, the collected second data can be expressed as the following table, where the target refers to the eye movement guiding mark.

[0077]

[0078]

[0079] As an optional embodiment of step S110, when the eye movement data includes the third data, displaying the eye movement guide mark at each preset display position in the display area in sequence and collecting the eye movement data includes:

[0080] Step S1101c: controlling the eye movement guiding mark to move to three types of preset display positions in sequence in the display area;

[0081] Step S1102c: collecting third data corresponding to the three types of preset display positions as eye movement data;

[0082] The third data includes at least one of the following: the number of times the eyeball correctly follows the eye movement guiding mark, and the number of times the eyeball deviates from the moving track of the eye movement guiding mark.

[0083] It can be seen that the implementation of this optional embodiment can realize the acquisition of eye movement data based on the smooth tracking project, which is conducive to improving the precision of the eye movement data.

[0084] Specifically, the eye movement guide mark can be controlled to move to each of the three preset display positions in the display area in sequence. For example, the eye movement guide mark can be displayed at the three preset display positions A, and then at the three preset display positions B, so as to guide the monitored object to control the eye movement according to the movement trajectory of the eye movement guide mark. In this process, the third data corresponding to each of the three preset display positions can be collected as the eye movement data.

[0085] For example, the collected third data can be represented as the following table, where the target refers to the eye movement guiding mark.

[0086]

[0087] As an optional embodiment of step S110, when the eye movement data includes the fourth data, the eye movement guiding mark is displayed at each preset display position in the display area in sequence and the eye movement data is collected, and the method further includes:

[0088] Step S1101d: displaying a target image in the display area; wherein the target image includes a plurality of eye movement guiding marks, and the plurality of eye movement guiding marks correspond to different preset display positions;

[0089] Step S1102d: outputting prompt information to guide the user to gaze at each preset display position in turn and collect eye movement data;

[0090] The fourth data includes at least one of the following: the number of preset display positions that the eyeball gazes at, the number of glances that the line of sight moves between the preset display positions, the average gaze duration, and the binocular convergence duration.

[0091] It can be seen that the implementation of this optional embodiment can realize the acquisition of eye movement data based on image observation items, which is conducive to improving the precision of eye movement data.

[0092] Specifically, the following may be displayed in the display area: Figure 5 The target image shown in the figure is then output with prompt information to guide the user to sequentially gaze at each preset display position and collect eye movement data; wherein the prompt information may be any information such as text information, voice information, highlight prompt information, etc. For example, the prompt information may sequentially include the following voice information: "Please gaze at the eyes", "Please gaze at the upper left corner of the picture", "Please gaze at the nose".

[0093] For example, the collected fourth data may be represented as the following table, where the target refers to the eye movement guiding mark.

[0094]

[0095] In step S120, target data for evaluating the brain health risk of the subject to be monitored is generated based on the eye movement data.

[0096] Specifically, the target data used to evaluate the brain health risk of the subject to be monitored can be implemented in any form such as numerical values, characters, symbols, etc., and the embodiments of the present application are not limited thereto.

[0097] As an optional embodiment of step S120, generating target data for evaluating the brain health risk of the subject to be monitored based on the eye movement data includes:

[0098] Step S1201: generating health data for evaluating brain health of the subject to be monitored based on at least one of the first data, the second data, the third data, and the fourth data;

[0099] Step S1202: Generate target data for evaluating the brain health risk of the subject to be monitored based on the health data and risk rules.

[0100] It can be seen that by implementing this optional embodiment, target data for evaluating the brain health risk of the monitored object can be generated based on the diverse eye movement data, thereby improving the accuracy of the target data.

[0101] Specifically, based on at least one of the first data, the second data, the third data, and the fourth data, health data generation can be achieved, wherein, although there are differences in accuracy between the health data generated based on different amounts of data, they can all be used to evaluate the brain health of the subject to be monitored. The specific implementation method is to compare the first data / second data / third data / fourth data with the corresponding rules to determine the score corresponding to the first data / second data / third data / fourth data, and based on the score, health data for evaluating the brain health of the subject to be monitored can be generated, and the score can also be called a specific evaluation grade.

[0102] The relationship between the first data, the second data, the third data, the fourth data and the rule can be expressed as the following table:

[0103]

[0104]

[0105]

[0106]

[0107] Among them, a', a", b', b", c', c", d', d", e', e",

[0109] f', f", g', g", h, h, j', j", k', k", l', l",

[0111] m', m', o', o', p', p', q', q', r', r', s', s', u', u' are all preset thresholds and can be customized according to actual needs.

[0112] In one case, health data for evaluating the brain health of the subject to be monitored can be generated based on the first data, the second data, the third data, and the fourth data. Based on the above table, the score of at least one of the first data, the second data, the third data, and the fourth data can be determined, and the score can be substituted into the expression brainscore=log(ascore+bscore+cscore+dscore+escore+fscore+gscore+hscore+jscore+kscore+lscore+mscore+oscore+pscore+qscore+rscore+sscore+uscore) / log(v) to calculate the health data for evaluating the brain health of the subject to be monitored.

[0113] Optionally, if health data for evaluating the brain health of the subject to be monitored is generated based on the first data, the second data, and the third data, the corresponding health data expression may be: brainscore=log(ascore+bscore+cscore+dscore+escore+fscore+gscore+hscore+jscore+kscore+lscore+mscore+oscore+pscore) / log(v). Similarly, health data for evaluating the brain health of the subject to be monitored generated based on one or more of the first data, the second data, the third data, and the fourth data may be substituted into the corresponding health data expression.

[0114] Furthermore, target data for evaluating the brain health risk of the subject to be monitored can be generated based on the health data and the risk rules. The target data can be expressed as low risk, medium risk or high risk. For example, the risk rules can be expressed as the following table:

[0115]

[0116] Among them, brainscore' and brainscore" are two preset risk rule thresholds, and brainscore' is less than brainscore".

[0117] In step S130, a brain health assessment report corresponding to the object to be monitored is generated based on the basic attribute information of the object to be monitored, the descriptive information used to characterize the physical health condition of the object to be monitored, and the target data.

[0118] Specifically, since the target data can characterize the brain health of the subject to be monitored, a brain health assessment report corresponding to the subject to be monitored can be generated based on the target data; wherein, the brain health assessment report is used as detailed analysis information of the brain health of the subject to be monitored for reference by the subject to be monitored, and the brain health assessment report may include at least one of the following information: name, gender, age, test time, examination number, brain health risk index, risk index development trend chart, health risk reminder information, and health advice.

[0119] Among them, the basic attribute information includes at least one of the following: age and gender; the descriptive information includes at least one of the following: BMI, body fat percentage, and underlying disease information; the brain health assessment report includes at least one of the following: assessment of fatigue index, anxiety index, attention index, executive function index, impaired reaction ability index, and depression index.

[0120] Specifically, the basic attribute information of the monitored object, the descriptive information used to characterize the physical health of the monitored object, and the target data can be compared with the comparison table to determine the corresponding groups, and then a brain health assessment report corresponding to the monitored object can be generated according to each group. The comparison table can be expressed as the following table:

[0121]

[0122] As an optional embodiment, it also includes:

[0123] A health improvement plan is generated based on the brain health assessment report; wherein the health improvement plan includes at least one of a psychological assistance plan, a sleep assistance plan, an exercise assistance plan, and a conditioning plan.

[0124] It can be seen that the implementation of this optional embodiment can provide users with health improvement plans based on brain health assessment reports, thereby improving interactivity with users.

[0125] Specifically, the health improvement plan can be used to provide information on improving brain health, which is specifically implemented as at least one of a psychological assistance plan, a sleep assistance plan, an exercise assistance plan, and a conditioning plan. In addition, the health improvement plan may also include a drug assistance plan, a doctor assistance plan, etc., which are not limited in the embodiments of the present application. Among them, the health improvement plan can be implemented in the user interface, and the health improvement plan can be implemented in any form such as text, image, video, etc.

[0126] As an optional embodiment, it also includes:

[0127] Sending a brain health assessment report and / or a health improvement plan to a client corresponding to the subject to be monitored;

[0128] The client is used to display a brain health assessment report and / or a health improvement plan in response to a report query instruction.

[0129] It can be seen that by implementing this optional embodiment, brain health assessment reports and / or health improvement plans can be sent to users in a timely manner, reducing the difficulty of knowing brain health conditions.

[0130] Specifically, the clients corresponding to different monitored objects are used to display corresponding brain health assessment reports, health improvement plans, historical brain health assessment reports, and historical health improvement plans.

[0131] In one application scenario, the technical solution of the present application can be oriented to company employees. Each employee can control eye movements based on the eye movement guidance signs displayed by the virtual reality device at each preset display position in the display area, and collect eye movement data through the virtual reality device. Furthermore, the server can generate target data for evaluating the brain health risks of employees based on the eye movement data fed back by the virtual reality device, and generate a brain health assessment report corresponding to the employee based on the target data. Furthermore, the server can send each brain health assessment report to each employee's client, so that each employee can understand the brain health status in a quick way.

[0132] In another application scenario, the technical solution of the present application can be used for animals with high IQ (such as silverback gorillas). Animals with high IQ are prone to brain health problems in the confined environment of the zoo. Through the solution of the present application, the brain health of animals with high IQ can be monitored and response strategies can be made in a timely manner, which can be conducive to the implementation of animal protection strategies. Animals with high IQ can control their eye movements based on the eye movement guidance signs displayed by the virtual reality device at each preset display position in the display area, and collect eye movement data through the virtual reality device. Furthermore, the server can generate target data for evaluating the brain health risks of animals with high IQ based on the eye movement data fed back by the virtual reality device, and generate a brain health assessment report corresponding to the animals with high IQ based on the target data. Furthermore, the server can send each brain health assessment report to the client of the corresponding breeder, so that each breeder can understand the brain health of the high IQ animals they raise in a quick way, so as to intervene in treatment in time.

[0133] See also Figure 6 , Figure 6 The flowchart of the method for generating a brain health assessment report according to another embodiment of the present application is schematically shown. Figure 6 As shown, the method for generating a brain health assessment report includes: steps S610 to S690.

[0134] Step S610: In response to the eye movement calibration instruction for the object to be monitored, the calibration mark is controlled to move along a preset trajectory in the display area and collect eye movement calibration data. When the eye movement calibration data meets the calibration requirements, it is determined that the calibration is passed and an eye movement detection instruction is generated.

[0135] Step S620: displaying eye movement guidance marks at each of the first-class preset display positions in the display area in turn, and collecting first data corresponding to each of the first-class preset display positions as eye movement data; wherein the first data includes at least one of the following: forward scanning accuracy, the duration from the time when the eye movement guidance marks are displayed at each of the first-class preset display positions until the eye movement is detected, the average forward scanning duration, the average forward scanning speed, and the maximum forward scanning speed.

[0136] Step S630: displaying eye movement guidance marks at each of the two preset display positions in the display area in turn, and collecting second data corresponding to each of the two preset display positions as eye movement data; wherein the second data includes at least one of the following: the accuracy rate of reverse scanning in the direction opposite to the moving direction of the eye movement guidance mark, the time from the time when the eye movement is detected after the eye movement guidance mark is displayed at each of the two preset display positions, the average completion time of reverse scanning, the average error correction rate of reverse scanning, the error correction time, the average reverse scanning speed, and the maximum reverse scanning speed.

[0137] Step S640: Control the eye movement guide mark to move to the three types of preset display positions in the display area in turn, and collect third data corresponding to the three types of preset display positions as eye movement data; wherein the third data includes at least one of the following: the number of correct times the eyeball follows the eye movement guide mark, the number of times the eyeball deviates from the movement trajectory of the eye movement guide mark.

[0138] Step S650: displaying a target image in the display area; wherein the target image includes multiple eye movement guiding marks, and the multiple eye movement guiding marks correspond to different preset display positions; outputting prompt information to guide the user to gaze at each preset display position in turn and collect eye movement data; wherein the fourth data includes at least one of the following: the number of preset display positions gazed at, the number of glances when the line of sight moves between preset display positions, the average gaze duration, and the duration of binocular convergence.

[0139] Step S660: Based on the first data, the second data, the third data, and the fourth data, generate health data for evaluating the brain health of the subject to be monitored, and based on the health data and the risk rules, generate target data for evaluating the brain health risk of the subject to be monitored.

[0140] Step S670: Generate a brain health assessment report corresponding to the object to be monitored based on the basic attribute information of the object to be monitored, the descriptive information used to characterize the physical health status of the object to be monitored, and the target data; wherein the basic attribute information includes at least one of the following: age, gender; the descriptive information includes at least one of the following: BMI, body fat percentage, and underlying disease information; the brain health assessment report includes at least one of the following: an assessment of fatigue index, anxiety index, attention index, executive function index, impaired reaction ability index, and depression index.

[0141] Step S680: Generate a health improvement plan based on the brain health assessment report; wherein the health improvement plan includes at least one of a psychological assistance plan, a sleep assistance plan, an exercise assistance plan, and a conditioning plan.

[0142] Step S690: Send the brain health assessment report and / or health improvement plan to the client corresponding to the subject to be monitored; wherein the client is used to display the brain health assessment report and / or health improvement plan in response to the report query instruction.

[0143] It should be noted that steps S610 to S690 are Figure 1 The steps and embodiments shown correspond to Figure 6 For the specific implementation of the steps, please refer to Figure 1 The steps and embodiments shown are not described in detail here.

[0144] It can be seen that implementation Figure 6 The method shown can display eye movement guidance signs and collect eye movement data including first data corresponding to the directional scanning project, second data corresponding to the reverse scanning project, third data corresponding to the smooth pursuit project, and fourth data corresponding to the image observation project, and evaluate the brain health risk of the monitored object through the eye movement data to determine the brain health assessment report. The user does not need to find a psychological counselor to talk to and then obtain a brain health report issued by the psychological counselor, which can save the user the steps of knowing the brain health status and improve the convenience of implementing the brain health status acquisition plan. In addition, a new use of eye movement data is provided. Applying eye movement data to the brain health assessment process can reduce the difficulty of brain health assessment and improve the availability of data sources based on brain health assessment reports.

[0145] See also Figure 7 , Figure 7 The structure block diagram of the brain health assessment report generation system according to one embodiment of the present application is schematically shown. Figure 1 The method shown corresponds to Figure 7 As shown, the brain health assessment report generation system 700 includes:

[0146] The virtual reality device 701 is used to respond to the eye movement detection instruction for the monitored object sent by the server 702, display the eye movement guide mark at each preset display position in the display area in turn and collect eye movement data; the eye movement data includes at least one of the following: first data corresponding to the directional scanning item, second data corresponding to the reverse scanning item, third data corresponding to the smooth pursuit item, and fourth data corresponding to the image observation item;

[0147] The server 702 is used to generate target data for evaluating the brain health risk of the subject to be monitored based on the eye movement data fed back by the virtual reality device 701;

[0148] Server 702 is also used to generate a brain health assessment report corresponding to the object to be monitored based on the basic attribute information of the object to be monitored, the descriptive information used to characterize the physical health condition of the object to be monitored, and the target data.

[0149] Optionally, the brain health assessment report generation system 700 may also include a client. After the server 702 generates the brain health assessment report, the brain health assessment report may be sent to the client corresponding to the subject to be monitored, so that the subject to be monitored can view the brain health assessment report from the client. In addition, the server 702 may also generate a health improvement plan based on the brain health assessment report, and send the health improvement plan to the client corresponding to the subject to be monitored.

[0150] It can be seen that implementation Figure 7 The system shown can display eye movement guidance signs and collect eye movement data including first data corresponding to the directional scanning project, second data corresponding to the reverse scanning project, third data corresponding to the smooth pursuit project, and fourth data corresponding to the image observation project, and evaluate the brain health risk of the monitored object through the eye movement data and then determine the brain health assessment report. The user does not need to find a psychological counselor to talk to and then obtain a brain health report issued by the psychological counselor, which can save the user the steps of knowing the brain health status and improve the convenience of implementing the brain health status acquisition plan. In addition, a new use of eye movement data is provided. Applying eye movement data to the brain health assessment process can reduce the difficulty of brain health assessment and improve the availability of the data source based on the brain health assessment report.

[0151] See also Figure 8 , Figure 8 The structure block diagram of the brain health assessment report generation device according to one embodiment of the present application is schematically shown. Figure 1 The method shown corresponds to Figure 8 As shown, the brain health assessment report generating device 800 includes:

[0152] The eye movement data collection unit 801 is used to respond to the eye movement detection instruction for the monitored object, sequentially display the eye movement guide mark at each preset display position in the display area and collect eye movement data; the eye movement data includes at least one of the following: first data corresponding to the directional scanning item, second data corresponding to the reverse scanning item, third data corresponding to the smooth pursuit item, and fourth data corresponding to the image observation item;

[0153] A target data generating unit 802 is used to generate target data for evaluating the brain health risk of the subject to be monitored based on the eye movement data;

[0154] The brain health assessment report generating unit 803 is used to generate a brain health assessment report corresponding to the object to be monitored based on the basic attribute information of the object to be monitored, the descriptive information used to characterize the physical health condition of the object to be monitored, and the target data.

[0155] In an exemplary embodiment of the present application, the eye movement data includes at least one of the following: first data corresponding to a directional scan item, second data corresponding to a reverse scan item, third data corresponding to a smooth pursuit item, and fourth data corresponding to an image observation item.

[0156] It can be seen that implementing this optional embodiment can improve the richness of eye movement data, which is beneficial to improving the accuracy of brain health reports generated based on eye movement data.

[0157] In an exemplary embodiment of the present application, when the eye movement data includes the first data, the eye movement data collection unit 801 sequentially displays an eye movement guide mark at each preset display position in the display area and collects the eye movement data, including:

[0158] Displaying eye movement guidance marks at each type of preset display position in the display area in turn;

[0159] collecting first data corresponding to each type of preset display position as eye movement data;

[0160] Among them, the first data includes at least one of the following: forward scanning accuracy, the time from the time when the eye movement guidance mark is displayed at each preset display position until the eye movement is detected, the average forward scanning time, the average forward scanning speed, and the maximum forward scanning speed.

[0161] It can be seen that the implementation of this optional embodiment can realize the acquisition of eye movement data based on the directional scanning items, which is conducive to improving the precision of the eye movement data.

[0162] In an exemplary embodiment of the present application, when the eye movement data includes the second data, the eye movement data collection unit 801 sequentially displays an eye movement guide mark at each preset display position in the display area and collects the eye movement data, and further includes:

[0163] sequentially displaying eye movement guidance marks at each of the second types of preset display positions in the display area;

[0164] collecting second data corresponding to each of the second types of preset display positions as eye movement data;

[0165] Among them, the second data includes at least one of the following: the accuracy rate of reverse scanning in the direction opposite to the moving direction of the eye movement guidance mark, the time from the eye movement guidance mark being displayed at each of the two preset display positions until the eye movement is detected, the average completion time of reverse scanning, the average error correction rate of reverse scanning, the error correction time, the average reverse scanning speed, and the maximum reverse scanning speed.

[0166] It can be seen that the implementation of this optional embodiment can realize the acquisition of eye movement data based on the reverse scanning project, which is conducive to improving the precision of the eye movement data.

[0167] In an exemplary embodiment of the present application, when the eye movement data includes the third data, the eye movement data collection unit 801 sequentially displays the eye movement guide mark at each preset display position in the display area and collects the eye movement data, including:

[0168] Controlling the eye movement guide mark to move to three types of preset display positions in the display area in sequence;

[0169] collecting third data corresponding to each of the three types of preset display positions as eye movement data;

[0170] The third data includes at least one of the following: the number of times the eyeball correctly follows the eye movement guiding mark, and the number of times the eyeball deviates from the moving track of the eye movement guiding mark.

[0171] It can be seen that the implementation of this optional embodiment can realize the acquisition of eye movement data based on the smooth tracking project, which is conducive to improving the precision of the eye movement data.

[0172] In an exemplary embodiment of the present application, when the eye movement data includes the fourth data, the eye movement data collection unit 801 sequentially displays the eye movement guide mark at each preset display position in the display area and collects the eye movement data, and further includes:

[0173] Displaying a target image in the display area; wherein the target image includes a plurality of eye movement guiding marks, and the plurality of eye movement guiding marks correspond to different preset display positions;

[0174] Output prompt information to guide the user to look at each preset display position in turn and collect eye movement data;

[0175] The fourth data includes at least one of the following: the number of preset display positions that the eyeball gazes at, the number of glances that the line of sight moves between the preset display positions, the average gaze duration, and the binocular convergence duration.

[0176] It can be seen that the implementation of this optional embodiment can realize the acquisition of eye movement data based on image observation items, which is conducive to improving the precision of eye movement data.

[0177] In an exemplary embodiment of the present application, the target data generating unit 802 generates target data for evaluating the brain health risk of the subject to be monitored based on the eye movement data, including:

[0178] generating health data for evaluating brain health of the subject to be monitored based on at least one of the first data, the second data, the third data, and the fourth data;

[0179] Target data for evaluating the brain health risk of the subject to be monitored is generated based on health data and risk rules.

[0180] It can be seen that by implementing this optional embodiment, target data for evaluating the brain health risk of the monitored object can be generated based on the diverse eye movement data, thereby improving the accuracy of the target data.

[0181] In an exemplary embodiment of the present application, the basic attribute information includes at least one of the following: age, gender; the descriptive information includes at least one of the following: BMI, body fat percentage, underlying disease information; the brain health assessment report includes at least one of the following: assessment of fatigue index, anxiety index, attention index, executive function index, impaired reaction ability index, and depression index.

[0182] It can be seen that by implementing this optional embodiment, a personalized brain health assessment report can be generated.

[0183] In an exemplary embodiment of the present application, it further includes:

[0184] A health improvement plan generating unit is used to generate a health improvement plan based on a brain health assessment report; wherein the health improvement plan includes at least one of a psychological assistance plan, a sleep assistance plan, an exercise assistance plan, and a conditioning plan.

[0185] It can be seen that the implementation of this optional embodiment can provide users with health improvement plans based on brain health assessment reports, thereby improving interactivity with users.

[0186] In an exemplary embodiment of the present application, it further includes:

[0187] A transmission unit, used to send a brain health assessment report and / or a health improvement plan to a client corresponding to the subject to be monitored;

[0188] The client is used to display a brain health assessment report and / or a health improvement plan in response to a report query instruction.

[0189] It can be seen that by implementing this optional embodiment, brain health assessment reports and / or health improvement plans can be sent to users in a timely manner, reducing the difficulty of knowing brain health conditions.

[0190] In an exemplary embodiment of the present application, it further includes:

[0191] The calibration unit is used to respond to the eye movement calibration instruction for the object to be monitored, control the calibration mark to move along a preset trajectory in the display area and collect eye movement calibration data; when the eye movement calibration data meets the calibration requirements, it is determined that the calibration is passed and an eye movement detection instruction is generated.

[0192] It can be seen that by implementing this optional embodiment, the accuracy of subsequently collected eye movement data can be improved through eye movement calibration.

[0193] See also Fig. 9 , Fig. 9 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown.

[0194] It should be noted that Fig. 9 The computer system 900 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0195] like Fig. 9 As shown, the computer system 900 includes a central processing unit (CPU) 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage part 908 into a random access memory (RAM) 903. In the RAM 903, various programs and data required for system operation are also stored. The CPU 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0196] The following components are connected to the I / O interface 905: an input section 906 including a keyboard, a mouse, etc.; an output section 907 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, a modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the I / O interface 905 as needed. A removable medium 911, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 910 as needed, so that a computer program read therefrom is installed into the storage section 908 as needed.

[0197] In particular, according to an embodiment of the present application, the process described with reference to the flowchart above can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 909, and / or installed from a removable medium 911. When the computer program is executed by a central processing unit (CPU) 901, various functions defined in the method and apparatus of the present application are executed.

[0198] The exemplary embodiments of the present disclosure also provide a computer program product, which includes a computer program, and when the computer program is executed by a processor, the method for generating a brain health assessment report is implemented.

[0199] In one embodiment, the computer program product may be a tangible product containing a computer program, such as a computer-readable storage medium storing a computer program. The readable storage medium may be a storage medium based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, including but not limited to: random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory (Flash), mechanical hard disk (HDD), solid-state drive (SSD), and the like. Exemplarily, the computer program product may be implemented as a non-volatile storage medium storing a computer program, such as a read-only memory, a NAND flash memory, and the like.

[0200] In one embodiment, the computer program product may be an intangible product including a computer program. Exemplarily, the computer program product may be implemented as a virtual digital product, such as a digital file storing an executable file, an installation package, etc. of the computer program.

[0201] The code of the computer program can be written in one or more programming languages. Programming languages ​​such as C language, Java, C++, etc. The program code can be executed entirely on the user computing device, or partially on the user computing device, or as a separate software package, or partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, such as a local area network (LAN), a wide area network (WAN), etc., or can be connected to an external computing device (e.g., an Internet connection provided by an operator).

[0202] The computer program may be carried or transmitted via electrical, magnetic, optical, electromagnetic, infrared, or other signals. The electronic device may convert the signal carrying the computer program into a digital signal, thereby running the computer program. When the computer program is run on an electronic device, its code is used to enable the electronic device to execute (more specifically, the processor of the electronic device may execute) the method steps of various exemplary embodiments of the present disclosure.

Claims

1. A method for generating a brain health assessment report, characterized in that: include: In response to an eye movement detection instruction for an object to be monitored, an eye movement guide mark is displayed at each preset display position in the display area in turn and eye movement data is collected; the eye movement data includes at least one of the following: first data corresponding to a directional scanning item, second data corresponding to a reverse scanning item, third data corresponding to a smooth pursuit item, and fourth data corresponding to an image observation item; generating target data for evaluating the brain health risk of the subject to be monitored based on the eye movement data; A brain health assessment report corresponding to the object to be monitored is generated based on the basic attribute information of the object to be monitored, the descriptive information used to characterize the physical health condition of the object to be monitored, and the target data.

2. The method according to claim 1, characterized in that When the eye movement data includes the first data, sequentially displaying eye movement guide marks at respective preset display positions in the display area and collecting eye movement data includes: Displaying eye movement guidance marks at each type of preset display position in the display area in turn; collecting first data corresponding to each type of preset display position as eye movement data; Among them, the first data includes at least one of the following: the accuracy of forward scanning, the time from the display of the eye movement guidance mark at each preset display position until the eye movement is detected, the average forward scanning time, the average forward scanning speed, and the maximum forward scanning speed.

3. The method according to claim 1, characterized in that When the eye movement data includes the second data, sequentially displaying eye movement guide marks at each preset display position in the display area and collecting eye movement data further includes: sequentially displaying eye movement guidance marks at each of the second types of preset display positions in the display area; collecting second data corresponding to the two types of preset display positions as eye movement data; Among them, the second data includes at least one of the following: the accuracy rate of reverse scanning in the direction opposite to the moving direction of the eye movement guiding mark, the time from the eye movement guiding mark being displayed at each of the two types of preset display positions until the eye movement is detected, the average completion time of reverse scanning, the average error correction rate of reverse scanning, the error correction time, the average reverse scanning speed, and the maximum reverse scanning speed.

4. The method according to claim 1, characterized in that: When the eye movement data includes the third data, sequentially displaying eye movement guide marks at each preset display position in the display area and collecting eye movement data includes: Controlling the eye movement guide mark to move to three types of preset display positions in the display area in sequence; collecting third data corresponding to the three types of preset display positions as eye movement data; The third data includes at least one of the following: the number of times the eyeball correctly follows the eye movement guiding mark, and the number of times the eyeball deviates from the moving track of the eye movement guiding mark.

5. The method according to claim 1, characterized in that When the eye movement data includes the fourth data, the eye movement guiding mark is displayed at each preset display position in the display area in sequence and the eye movement data is collected, further comprising: Displaying a target image in the display area; wherein the target image includes a plurality of eye movement guiding marks, and the plurality of eye movement guiding marks correspond to different preset display positions; Output prompt information to guide the user to look at each preset display position in turn and collect eye movement data; The fourth data includes at least one of the following: the number of preset display positions that the eyeball gazes at, the number of glances that the line of sight moves between preset display positions, the average gaze duration, and the binocular convergence duration.

6. The method according to claim 1, characterized in that Generating target data for evaluating the brain health risk of the subject to be monitored based on the eye movement data includes: generating health data for evaluating the brain health of the subject to be monitored based on at least one of the first data, the second data, the third data, and the fourth data; Target data for evaluating the brain health risk of the subject to be monitored is generated based on the health data and risk rules.

7. A device for generating a brain health assessment report, characterized in that: include: An eye movement data collection unit, for responding to an eye movement detection instruction for an object to be monitored, sequentially displaying an eye movement guide mark at each preset display position in a display area and collecting eye movement data; the eye movement data includes at least one of the following: first data corresponding to a directional scanning item, second data corresponding to a reverse scanning item, third data corresponding to a smooth pursuit item, and fourth data corresponding to an image observation item; a target data generating unit, configured to generate target data for evaluating the brain health risk of the subject to be monitored based on the eye movement data; A brain health assessment report generating unit is used to generate a brain health assessment report corresponding to the object to be monitored based on the basic attribute information of the object to be monitored, the descriptive information used to characterize the physical health condition of the object to be monitored, and the target data.

8. A brain health assessment report generation system, characterized in that: Including servers and virtual reality equipment, including: The virtual reality device is used to respond to the eye movement detection instruction for the monitored object sent by the server, display eye movement guidance marks at each preset display position in the display area in turn and collect eye movement data; the eye movement data includes at least one of the following: first data corresponding to a directional scanning item, second data corresponding to a reverse scanning item, third data corresponding to a smooth pursuit item, and fourth data corresponding to an image observation item; The server is used to generate target data for evaluating the brain health risk of the subject to be monitored based on the eye movement data fed back by the virtual reality device; The server is also used to generate a brain health assessment report corresponding to the object to be monitored based on the basic attribute information of the object to be monitored, the descriptive information used to characterize the physical health condition of the object to be monitored, and the target data.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

10. An electronic device, characterized in that: include: processor; as well as A memory, configured to store executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 6 by executing the executable instructions.

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