Vision-based cognitive function evaluation method, device, equipment and program product

Abstract

The invention relates to the field of cognitive function evaluation, in particular to a cognitive function evaluation method and device based on vision, equipment and a program product. The method comprises the following steps: acquiring individual information of a subject; determining a subject for cognitive function evaluation according to the individual information of the subject; playing the determined question, and capturing first pupil position change information of the subject and vital sign information of the subject; correcting the first pupil position change information according to the vital sign information to obtain second pupil position change information; and comparing the second pupil position change information with a pupil reference model, and determining a cognitive function evaluation result of the subject. The corresponding question is determined through the individual information of the subject, so that the question can adapt to the difference of the individual information of different subjects, the accuracy of the evaluation result is improved, and the accuracy of the evaluation result can be further improved through vital sign information correction.

Description

Technical Field

[0001] The present application relates to the field of cognitive function assessment, and in particular to a vision-based cognitive function assessment method, device, equipment and program product. Background Art

[0002] Cognitive function is the ability of an individual to process information, understand, learn, remember, solve problems, make decisions, perceive, pay attention, and use language. Cognitive function assessment of subjects can be used to identify suspected groups and facilitate further assessment through other means.

[0003] Current cognitive function assessment methods include the use of high-precision eye trackers to capture the position and change time of the subject's pupil. However, since the focal position of the human eye's pupil changes very quickly, it usually presents a discrete and irregular single-point focus, which is not conducive to improving the accuracy of cognitive function assessment. Summary of the invention

[0004] In view of this, the embodiments of the present application provide a vision-based cognitive function assessment method, device, equipment and program product to solve the problem in the prior art that it is not conducive to improving the accuracy of cognitive function assessment when performing vision-based cognitive function assessment.

[0005] A first aspect of an embodiment of the present application provides a method for evaluating cognitive function based on vision, the method comprising:

[0006] Obtaining individual information of subjects;

[0007] Determining the questions for cognitive function assessment according to the individual information of the subject;

[0008] Playing the determined topic, and capturing the first pupil position change information of the subject, and the vital sign information of the subject;

[0009] Correcting the first pupil position change information according to the vital sign information to obtain second pupil position change information;

[0010] The second pupil position change information is compared with the pupil reference model to determine the cognitive function assessment result of the subject.

[0011] In combination with the first aspect, in a first possible implementation manner of the first aspect, the topic includes a target image for evaluation; and playing the determined topic includes:

[0012] The target image is played to move the subject's visual point in a predetermined horizontal direction.

[0013] In combination with the first possible implementation manner of the first aspect, in a second possible implementation manner of the first aspect, the target image includes a static image or a dynamic image;

[0014] Playing the target image so that the subject's visual point moves in a predetermined horizontal direction includes:

[0015] When the target image includes a plurality of static images, playing the plurality of static images according to a predetermined horizontal display direction and a predetermined static image display time;

[0016] When the target image includes a dynamic image, the dynamic image is played so that the dynamic target object included in the dynamic image moves in a predetermined horizontal direction.

[0017] In combination with the first aspect, in a third possible implementation manner of the first aspect, capturing the first pupil position change information of the subject includes at least one of the following methods:

[0018] capturing position change information of the gaze point of the subject's pupil;

[0019] capturing the movement duration between two adjacent gaze points of the subject's pupil;

[0020] Capturing the duration of the gaze point of the subject's pupil at different positions;

[0021] Capturing a line connecting positions where the dwelling time of the gaze point of the subject's pupil is greater than a predetermined first time length.

[0022] In combination with the first aspect, in a fourth possible implementation manner of the first aspect, the individual information includes the age of the subject;

[0023] The questions for cognitive function assessment are determined based on the individual information of the subject, including:

[0024] According to the age range to which the age of the subject belongs, combined with the correspondence between the preset age range and the questions, the questions for cognitive function assessment corresponding to the age of the subject are determined.

[0025] In combination with any one of the first aspect to the fourth implementation manner of the first aspect, in a fifth possible implementation manner of the first aspect, the vital sign information includes a pulse rate;

[0026] Correcting the first pupil position change information according to the vital sign information to obtain second pupil position change information includes:

[0027] determining a first period of time when the subject's pulse rate deviates by a predetermined ratio from a baseline value of the rate of fluctuation of the subject's pulse rate;

[0028] The third pupil position change information is searched in the first pupil position change information according to the first time period, and the third pupil position change information in the first pupil position change information is corrected to obtain the second pupil position change information.

[0029] In combination with the fifth possible implementation manner of the first aspect, in a sixth possible implementation manner of the first aspect, correcting the third pupil position change information in the first pupil position change information includes:

[0030] determining a correction parameter according to the first pupil position change information and the pupil reference model;

[0031] The third pupil position change information is corrected according to the correction parameter.

[0032] A second aspect of an embodiment of the present application provides a visual-based cognitive function assessment device, the device comprising:

[0033] An individual information acquisition unit, used to acquire individual information of a subject;

[0034] a topic determination unit, configured to determine topics for cognitive function assessment according to individual information of the subject;

[0035] an information capturing unit, used for playing the determined topic and capturing the first pupil position change information of the subject and the vital sign information of the subject;

[0036] a correction unit, configured to correct the first pupil position change information according to the vital sign information to obtain second pupil position change information;

[0037] An evaluation result determination unit is used to compare the second pupil position change information with the pupil reference model to determine the cognitive function evaluation result of the subject.

[0038] A third aspect of an embodiment of the present application provides a vision-based cognitive function assessment device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the vision-based cognitive function assessment device implements a method as described in any one of the first aspects.

[0039] A fourth aspect of the embodiments of the present application provides a computer program product, which, when executed on a computer, enables the computer to execute the method in the first aspect or its various implementations.

[0040] A fifth aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in any one of the first aspects are implemented.

[0041] The sixth aspect of the embodiment of the present application provides a chip for implementing the methods in each implementation of the first aspect. Specifically, the chip includes: a processor for calling and running a computer program from a memory, so that a device equipped with the chip executes the method in the first aspect or its implementation.

[0042] Compared with the prior art, the embodiments of the present application have the following beneficial effects: the embodiments of the present application determine corresponding questions according to the individual information of the subjects, so that the questions can adapt to the differences in individual information of different subjects, thereby improving the accuracy of the evaluation results; when playing according to the determined questions, the first pupil position change information of the subject and the vital sign information of the subject are captured, the first pupil position change information is corrected based on the vital sign information to obtain the second pupil position change information, and the cognitive function evaluation result is determined by comparing the second pupil position change information with the pupil reference model. Since the first pupil position change information can be corrected based on the vital sign information during the test, it is beneficial to further improve the accuracy of the evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0044] Figure 1 It is a schematic diagram of an implementation scenario of a vision-based cognitive function assessment method provided in an embodiment of the present application;

[0045] Figure 2 It is a schematic diagram of the implementation process of a vision-based cognitive function assessment method provided in an embodiment of the present application;

[0046] Figure 3 is a schematic diagram of an image display provided by an embodiment of the present application;

[0047] Figure 4 is a schematic diagram of determining correction parameters provided in an embodiment of the present application;

[0048] Figure 5 is a schematic diagram of correction based on correction parameters provided in an embodiment of the present application;

[0049] Figure 6 is a schematic diagram of a vision-based cognitive function assessment device provided in an embodiment of the present application;

[0050] Figure 7 It is a schematic diagram of a vision-based cognitive function assessment device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0051] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0052] In order to illustrate the technical solution described in this application, a specific embodiment is provided below for illustration.

[0053] Cognitive function refers to an individual's ability to process information, understand, learn, remember, solve problems, make decisions, perceive, concentrate, and use language. Cognitive function assessment of subjects can help identify those who may have cognitive problems, thus providing a basis for further detailed assessment.

[0054] Among existing assessment methods, high-precision eye trackers are widely used to capture the position and reaction time of the subject's pupil to assess cognitive function. However, due to the rapid changes in the focus position of the human pupil and the usual single-point focusing characteristics, these data often present irregular discreteness, which limits the accuracy of the assessment.

[0055] In order to improve the assessment accuracy of cognitive function, the present application embodiment proposes a method for assessing cognitive function based on vision. Figure 1Schematic diagram of the implementation scenario of the method. In the implementation scenario of the visual-based cognitive function assessment method, a visual-based cognitive function assessment device is included, which includes a screen, a vital sign information acquisition device and a pupil image acquisition device. Among them, the visual-based cognitive function assessment device can be used to obtain individual information of the subject, determine the average cognitive level of the group to which the subject belongs based on the individual information of the subject, and determine the corresponding topic based on the average cognitive level of the group to evaluate the cognitive function. The screen can be used to play the topic determined based on the individual information of the subject. The vital sign information acquisition device is used to collect the vital sign information of the subject. For example, a non-contact vital sign information acquisition device can be used, including using an infrared camera to capture the temperature change of the skin surface of the subject. Since blood flow will cause slight changes in the skin surface temperature, the blood flow of the subject can be estimated by the temperature change, thereby determining the pulse rate of the subject. The pupil image acquisition device is used to collect the pupil image of the subject, determine the change information of the center position of the pupil of the subject, and based on the change information of the center position of the pupil, the position of the subject's gaze point on the screen can be determined after pre-calibration. During the playback of the question, the changing characteristics of the subject's gaze point can be captured by the pupil image acquisition device, and the vital signs change information of the subject can be captured by the vital signs information acquisition device. The changing characteristics of the gaze point are corrected based on the vital signs change information, and then compared with the pupil reference model to obtain the evaluation results of the subject's cognitive function.

[0056] Figure 2 A schematic diagram of the implementation flow of a vision-based cognitive function assessment method provided in an embodiment of the present application is described in detail as follows:

[0057] In S201, individual information of a subject is obtained.

[0058] The individual information in the embodiments of the present application may include at least one of age, gender, education level and living habits. The individual information may be entered by the subject, or the individual information of the subject may be entered by a staff member.

[0059] In general, the human brain will show certain changes with age. As age increases, the perceptual speed basically declines linearly, and language memory, inductive reasoning and spatial orientation decline in three plateaus at 55, 65 and 75 years old. Spatial orientation declines slower than language memory and inductive reasoning. Digital calculation reaches maturity at the peak of 45 years old and then gradually declines. Language ability varies greatly from person to person, and is best maintained in the cognitive dimension.

[0060] The living habit information in the embodiment of the present application may include at least one of the following information: whether the person lives alone, exercise frequency, medical history information, and whether the person has a smoking habit.

[0061] In a possible implementation, the embodiment of the present application can obtain the age of the subject, and determine the group to which the subject belongs based on the age of the subject. For example, the subjects can be divided into groups according to age to determine a group under 55 years old, a group between 55 and 75 years old, and a group over 75 years old.

[0062] In S202, questions for cognitive function assessment are determined according to the individual information of the subject.

[0063] According to the pre-set group division plan of individual information, the group to which the subject's individual information belongs can be determined. Combined with the pre-set correspondence between groups and questions, questions that match the average cognitive level of the group to which the subject belongs can be determined, so as to obtain more accurate assessment results when cognitive function assessment is performed according to the matched questions.

[0064] In a possible implementation, the group to which the subject belongs can be determined according to the age of the subject, and the cognitive function of the subjects can be evaluated based on pre-set questions for the group.

[0065] For example, if the subject is 60 years old, he belongs to the group between 55 and 75 years old, and questions matching this age range are found to conduct cognitive function assessment.

[0066] In a possible implementation, the questions used for cognitive function assessment may include questions of multiple dimensions, such as questions of visual memory, visual logic, visual perception, and visual operation. Questions of different dimensions can be further divided according to the difficulty of the questions. Therefore, after determining the group to which the individual information of the subject belongs, questions of corresponding difficulty are determined according to the average cognitive level of the group. Among the determined questions of corresponding difficulty, questions of different dimensions may be included, such as questions of visual memory, visual logic, visual perception, and visual operation.

[0067] In S203, the determined topic is played, and the first pupil position change information of the subject and the vital sign information of the subject are captured.

[0068] In the embodiment of the present application, the screen for playing the questions can be a screen of a device for interacting with the subject. For example, when the device for interacting with the subject is a robot, the screen can be a screen on the head of the robot. The device for interacting with the subject can also include an AR device, such as a virtual reality helmet.

[0069] The topic used for playing in the embodiment of the present application may include a target image. The target image may include a dynamic image or a static image. When the target image is a dynamic image, a prominent dynamic target may be included in the dynamic image, and the dynamic target may move in a predetermined direction so that the subject's visual point (the point where the attention is focused or the point where the pupil is focused) moves with the dynamic target, such as moving from left to right or from right to left with the dynamic target. When the target image is a static image, multiple static images may be included. The display time and display position of each static image may be controlled so that the subject's visual point moves in a predetermined direction, such as moving in a predetermined horizontal direction, including moving from left to right or from right to left.

[0070] for example Figure 3 In the schematic diagram of image display shown, the screen includes three areas, namely the first area, the second area and the third area, for displaying the first image, the second image and the third image respectively (the actual number of areas and the number of images may not be limited to three, for example, it may be 4, 5, 6, 7, etc.). The display time of the first image may be controlled to be the first moment t1, the display time of the second image may be the second moment t2, and the display time of the third image may be the third moment t3, and t1 may be earlier than t2, and t2 may be earlier than t3. Therefore, during playback, the subject's visual point may move with the position of the most recently displayed target image, for example, according to Figure 3 In the display mode, the visual point moves from left to right.

[0071] The questions used for cognitive function assessment in the embodiments of the present application may include questions on dimensions such as visual memory, visual logic, visual perception, and visual calculation.

[0072] For example, a series of images can be shown to the subject in a predetermined horizontal direction. After a period of time, the subject is asked to describe the details in the played images, or to identify the previously played images from a group of images, so as to evaluate the subject's visual memory.

[0073] A series of images may be shown to the subject in a predetermined horizontal direction and the subject may be asked to identify common features of the images in order to facilitate an assessment of the subject's visual logic.

[0074] A plurality of images including blurred or blocked portions may be displayed to the subject in a predetermined horizontal direction, and the subject may be asked to identify objects in the images, so as to facilitate the assessment of the subject's visual perception.

[0075] A plurality of puzzle pieces may be presented to the subject in a predetermined horizontal orientation and the subject may be asked to complete the puzzle, so as to facilitate the assessment of the subject's visual operations.

[0076] In the process of playing the topic, the embodiment of the present application can capture the pupil position change information of the subject according to the predetermined sampling period, and the first pupil position change information can be expressed as the change information of the gaze point of the subject's pupil on the screen. After calibrating the gaze point of the subject's pupil on the screen, the gaze point of the pupil on the screen at different positions can be determined according to the change of the center point of the subject's pupil. According to the first pupil position change information, the change information of the gaze point on the screen can be determined.

[0077] The first pupil position change information captured in the embodiment of the present application can be represented by the position information of the gaze point, and can be specifically represented by the following characteristic factors:

[0078] Information about the change of the gaze point: When playing the target image, the subject's gaze point will move with the change of the image, and the information about the change of the subject's gaze point can be captured. During the capture process, sampling can be performed according to a predetermined sampling period, such as a sampling period of 10 milliseconds, and noise data can be filtered out by filtering.

[0079] The moving time between two adjacent gaze points: When the subject's gaze point moves from a first position to a second position (the second position is temporally adjacent to the first position), the moving time of the gaze point from the first position to the second position can be recorded. Among them, two adjacent gaze points are gaze points whose stay time is greater than the predetermined second time.

[0080] The duration of gaze at different positions: During the evaluation of viewers, the duration of gaze at different positions varies. The duration of gaze at different screen positions can be collected, or the type of the hotspot area can be determined based on the duration. For example, multiple hotspot areas can be divided according to values ​​such as 300 milliseconds, 500 milliseconds, 1 second, 2 seconds, and 3 seconds to determine the hotspot area where the gaze position is located.

[0081] Connecting the positions where the duration of fixation is longer than the predetermined first duration: Filter the duration of fixation of each fixation point by the first duration, connect the fixation points whose duration is longer than the first duration, and obtain the trajectory of the subject's main fixation points.

[0082] In the embodiment of the present application, while acquiring the first pupil position change information of the subject, the subject's vital sign information is also collected. The vital sign information may include the subject's pulse rate. Not limited to this, the subject's body temperature, respiratory rate and other vital sign information may also be collected.

[0083] For example, an infrared camera can emit infrared light of a specific wavelength, which can penetrate the surface of the skin. The blood under the skin has specific absorption characteristics for these infrared lights. After the infrared light hits the skin, part of it is reflected back to the camera, and part of it is absorbed by the blood. The amount of infrared light reflected back is related to the blood flow. Information related to blood flow can be extracted to calculate the pulse rate (PR value).

[0084] In S204, the first pupil position change information is corrected according to the vital sign information to obtain second pupil position change information.

[0085] When the first pupil position change information is corrected by using the vital sign information, it can be determined whether the vital sign information is within a predetermined normal range. When the vital sign information is not within the normal range (is within an abnormal range), the third pupil position change information that needs to be corrected is determined based on the period of time that is not within the normal range.

[0086] The vital sign information may include pulse rate. When determining whether the current pulse rate is within the normal range, a predetermined time period may be collected, such as the pulse rate of 3 cycles / 90 seconds before the current time (which may be the most recent 3 cycles / 90 seconds before the current time, or may be a fixed time range) to determine the pulse rate fluctuation baseline value. If the deviation of the current pulse rate from the fluctuation baseline value is greater than a predetermined deviation threshold, such as greater than 35%, it indicates that the pulse rate is within the abnormal range.

[0087] for example, Figure 4 The figure shows a schematic diagram of correcting the first pupil position change information based on the pulse rate provided by an embodiment of the present application. According to the deviation of the pulse rate relative to the baseline value of the fluctuation rate, the first time range is determined to be a period of abnormal pulse rate. During this period, the subject may be in a state of tension or abnormal emotion. The third pupil position change information (the dotted line part in the figure) can be determined accordingly according to the first time range, which is the pupil position change information that needs to be corrected. In the second time range outside the first time range, the pulse rate is in a normal state. Reliable and effective fourth pupil position change information is determined according to the second time range. After completing the correction of the third pupil position change information, the second pupil position change information can be obtained based on the corrected third pupil position change information combined with the reliable and effective fourth pupil position change information.

[0088] When correcting the third pupil position change information, the correction parameter may be determined based on the deviation between the first pupil position change information and the pupil reference model (the pupil reference model has standard pupil position change information, which may be determined by the mean of pupil position change information when the same group completes the same question). Figure 5In the correction schematic diagram shown, the reliable and effective fourth pupil position change information can be compared with the pupil reference model to determine the deviation between the two. The average deviation can be calculated based on multiple deviation values, and the average deviation can be used as a correction parameter. The correction parameter can be superimposed on the third pupil position change information in the first time range, combined with the fourth pupil position change information, to obtain the corrected second pupil position change information.

[0089] Not limited to this, corrections can also be made through statistical data of multiple evaluations, or the third pupil position change information within an abnormal range can be corrected through machine learning.

[0090] In S205, the second pupil position change information is compared with a pupil reference model to determine a cognitive function assessment result of the subject.

[0091] The characteristic factors used to represent the second pupil position change information include characteristic factors such as the position change information of the gaze point, the moving time between two adjacent gaze points, the stay time of the gaze point at different positions, and the connecting line of the position where the stay time of the gaze point is greater than the predetermined first time. The standard pupil position change information can be obtained in the pupil reference model according to the individual information and the topic of the subject. Based on the deviation between the second pupil position change information and the standard pupil position change information, the cognitive function evaluation result of the subject is determined in combination with the predetermined correspondence between the deviation and the cognitive function evaluation result. Alternatively, in a possible implementation, the standard pupil position change information and the subject's second pupil position change information can be input into a pre-trained cognitive function evaluation model to output the subject's cognitive function evaluation result.

[0092] The embodiment of the present application evaluates and screens the subjects through the deviation of pupil position change information from big data statistics, which can obviously effectively improve the evaluation efficiency and the accuracy of the evaluation compared with text evaluation or inquiry-based evaluation. In addition, through the detection of non-contact vital signs information, the influence of process data distortion caused by the emotions of the subjects can be effectively reduced, and the evaluation accuracy can be improved. In addition, the embodiment of the present application can effectively improve the sensitivity of the detection data by moving the gaze point in the horizontal direction, thereby improving the accuracy of the evaluation results.

[0093] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0094] Figure 6 A schematic diagram of a visual-based cognitive function assessment device provided in an embodiment of the present application, the device comprising:

[0095] Individual information acquisition unit 601, used to acquire individual information of the subject;

[0096] A topic determination unit 602, configured to determine a topic for cognitive function assessment according to the individual information of the subject;

[0097] An information capturing unit 603, used to play the determined topic and capture the first pupil position change information of the subject and the vital sign information of the subject;

[0098] A correction unit 604, configured to correct the first pupil position change information according to the vital sign information to obtain second pupil position change information;

[0099] The evaluation result determination unit 605 is used to compare the second pupil position change information with the pupil reference model to determine the cognitive function evaluation result of the subject.

[0100] Figure 6 The visual-based cognitive function assessment device shown is Figure 2 The visual-based cognitive function assessment method shown corresponds to .

[0101] Figure 7 Schematic diagram of a visual-based cognitive function assessment device provided in an embodiment of the present application. Figure 7 As shown, the vision-based cognitive function assessment device 7 of this embodiment includes: a processor 70, a memory 71, and a computer program 72 stored in the memory 71 and executable on the processor 70, such as a vision-based cognitive function assessment program. When the processor 70 executes the computer program 72, the steps in the above-mentioned vision-based cognitive function assessment method embodiments are implemented. Alternatively, when the processor 70 executes the computer program 72, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0102] Exemplarily, the computer program 72 may be divided into one or more modules / units, which are stored in the memory 71 and executed by the processor 70 to complete the present application. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program 72 in the vision-based cognitive function assessment device 7.

[0103] The vision-based cognitive function assessment device 7 can be a computing device such as a robot, an AR device, a desktop computer, a notebook, a PDA, and a cloud server. The vision-based cognitive function assessment device can include, but is not limited to, a processor 70 and a memory 71. Those skilled in the art can understand that Figure 7 It is merely an example of a vision-based cognitive function assessment device 7 and does not constitute a limitation of the vision-based cognitive function assessment device 7. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the vision-based cognitive function assessment device may also include input and output devices, network access devices, buses, etc.

[0104] The processor 70 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0105] The memory 71 may be an internal storage unit of the vision-based cognitive function assessment device 7, such as a hard disk or memory of the vision-based cognitive function assessment device 7. The memory 71 may also be an external storage device of the vision-based cognitive function assessment device 7, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the vision-based cognitive function assessment device 7. Further, the memory 71 may also include both an internal storage unit and an external storage device of the vision-based cognitive function assessment device 7. The memory 71 is used to store the computer program and other programs and data required by the vision-based cognitive function assessment device. The memory 71 may also be used to temporarily store data that has been output or is to be output.

[0106] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0107] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0108] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0109] In the embodiments provided in the present application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0110] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0111] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0112] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the process in the above-mentioned embodiment method, and can also be completed by hardware related to computer program instructions. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0113] In addition, an embodiment of the present application also provides a computer program product, which, when executed on a computer, enables the computer to execute the methods in the above-mentioned implementation modes.

[0114] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for evaluating cognitive function based on vision, characterized in that: The method comprises: Obtaining individual information of subjects; Determining the questions for cognitive function assessment according to the individual information of the subject; Playing the determined topic, and capturing the first pupil position change information of the subject, and the vital sign information of the subject; Correcting the first pupil position change information according to the vital sign information to obtain second pupil position change information; The second pupil position change information is compared with the pupil reference model to determine the cognitive function assessment result of the subject.

2. The method according to claim 1, characterized in that The topic includes a target image for evaluation; playing the determined topic includes: The target image is played to move the subject's visual point in a predetermined horizontal direction.

3. The method according to claim 2, characterized in that The target image includes a static image or a dynamic image; Playing the target image so that the subject's visual point moves in a predetermined horizontal direction includes: When the target image includes a plurality of static images, playing the plurality of static images according to a predetermined horizontal display direction and a predetermined static image display time; When the target image includes a dynamic image, the dynamic image is played so that the dynamic target object included in the dynamic image moves in a predetermined horizontal direction.

4. The method according to claim 1, characterized in that Capturing the first pupil position change information of the subject includes at least one of the following methods: capturing position change information of the gaze point of the subject's pupil; capturing the movement duration between two adjacent gaze points of the subject's pupil; Capturing the duration of the gaze point of the subject's pupil at different positions; Capturing a line connecting positions where the dwelling time of the gaze point of the subject's pupil is greater than a predetermined first time length.

5. The method according to claim 1, characterized in that The individual information includes the age of the subject; The questions for cognitive function assessment are determined based on the individual information of the subject, including: According to the age range to which the age of the subject belongs, combined with the correspondence between the preset age range and the questions, the questions for cognitive function assessment corresponding to the age of the subject are determined.

6. The method according to any one of claims 1 to 5, characterized in that: The vital sign information includes pulse rate; Correcting the first pupil position change information according to the vital sign information to obtain second pupil position change information includes: determining a first period of time when the subject's pulse rate deviates by a predetermined ratio from a baseline value of the rate of fluctuation of the subject's pulse rate; The third pupil position change information is searched in the first pupil position change information according to the first time period, and the third pupil position change information in the first pupil position change information is corrected to obtain the second pupil position change information.

7. The method according to claim 6, characterized in that Correcting the third pupil position change information in the first pupil position change information includes: determining a correction parameter according to the first pupil position change information and the pupil reference model; The third pupil position change information is corrected according to the correction parameter.

8. A vision-based cognitive function assessment device, characterized in that: The device comprises: An individual information acquisition unit, used to acquire individual information of a subject; a topic determination unit, configured to determine topics for cognitive function assessment according to individual information of the subject; an information capturing unit, used for playing the determined topic and capturing the first pupil position change information of the subject and the vital sign information of the subject; a correction unit, configured to correct the first pupil position change information according to the vital sign information to obtain second pupil position change information; An evaluation result determination unit is used to compare the second pupil position change information with the pupil reference model to determine the cognitive function evaluation result of the subject.

9. A vision-based cognitive function assessment device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the vision-based cognitive function assessment device implements the method according to any one of claims 1 to 7.

10. A computer program product comprising computer program instructions, characterized in that When the computer program is executed, the method according to any one of claims 1 to 7 is performed.

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