Depression degree evaluation method, system and equipment based on color threshold value and medium

Abstract

The invention discloses a depression degree evaluation method and system based on a color threshold value, equipment and a medium. The method comprises the following steps: acquiring illumination intensity information of an environment where a tester uses the equipment and tester information; when the illumination intensity information meets the test condition, determining a test type selected by a tester; for each color type, primary color data are determined according to the illumination intensity information; generating and displaying a test picture according to the test type and the primary color data, acquiring test data of a tester on the test picture, and determining a color recognition threshold value of the tester in a color channel corresponding to the color type according to the test data; and processing the testee information, the test data and the color recognition threshold through an evaluation model to obtain the depression degree of the testee. According to the technical scheme, the color recognition threshold value of the testee can be accurately determined, the depression degree of the testee can be automatically evaluated through the evaluation model, and then the evaluation accuracy of the depression degree is improved.

Description

Technical Field

[0001] The present invention generally relates to the technical field of computer-aided diagnosis, and in particular to a method, system, device and medium for evaluating depression degree based on color threshold. Background Art

[0002] With the continuous development of medical information technology, image recognition and processing technology, as one of the imaging technology means of computer-aided examination and diagnosis, has been increasingly applied to daily medical clinical medical treatment, especially in the detection of various mental illnesses, such as depression. In order to improve the physical and mental health of users, it is particularly important to study how to assess the degree of depression.

[0003] At present, the existing technology is based on the depression self-assessment form and the doctor's experience. However, this solution needs to rely on a lot of subjective work experience, and its detection process may be affected by actual clinical experience. The detection method is relatively single and one-sided, resulting in a low accuracy in the assessment of depression level. Another method is to use brain imaging to assess depression level, which is costly and difficult to promote. Summary of the invention

[0004] In view of the above-mentioned defects or deficiencies in the prior art, it is desirable to provide a method, system, device and medium for evaluating depression level based on color threshold.

[0005] In a first aspect, an embodiment of the present application provides a method for assessing depression level based on a color threshold, the method comprising:

[0006] Obtaining information about the light intensity of the environment in which the tester uses the device and information about the tester;

[0007] When the light intensity information meets the test conditions, determining the test type selected by the tester;

[0008] For each color type, determining primary color data according to the light intensity information;

[0009] Generate and display a test picture according to the test type and the primary color data, obtain test data of the tester on the test picture, and determine a color recognition threshold of the tester in a color channel corresponding to the color type according to the test data;

[0010] The tester information, the test data and the color recognition threshold are processed through an evaluation model to obtain the depression level of the tester.

[0011] In a second aspect, the present application provides a depression level assessment system based on color threshold, the system comprising:

[0012] An information acquisition module is used to obtain the light intensity information of the environment in which the tester uses the device and the tester information;

[0013] A type determination module, used for obtaining the test type selected by the tester when the light intensity information meets the test conditions;

[0014] A primary color determination module, configured to determine primary color data for each color type according to the illumination intensity information;

[0015] A threshold determination module, configured to generate and display a test picture according to the test type and the primary color data, obtain test data of the tester on the test picture, and determine a color recognition threshold of the tester in a color channel corresponding to the color type according to the test data;

[0016] The evaluation module is used to process the tester information, the test data and the color recognition threshold through an evaluation model to obtain the depression level of the tester.

[0017] In a third aspect, an embodiment of the present application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for assessing depression level based on color threshold as described in the first aspect above is implemented.

[0018] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program is used to implement the depression level assessment method based on color threshold as described in the first aspect above.

[0019] The color threshold-based depression level assessment method, system, device and medium provided in the embodiments of the present application obtain light intensity information of the environment in which the tester uses the device and tester information, and when the light intensity information meets the test conditions, determine the test type selected by the tester, for each color type, determine the primary color data according to the light intensity information, and generate and display a test image according to the test type and the primary color data, obtain the test data of the test image by the tester, determine the color recognition threshold of the tester in the color channel corresponding to the color type according to the test data, and finally process the tester information, test data and color recognition threshold through an assessment model to obtain the tester's depression level. Compared with the existing technology, on the one hand, this solution does not need to be affected by the doctor's subjective work experience. By automatically judging whether the light intensity of the current device meets the test conditions, the test subject can be tested when the test conditions are met, avoiding the influence of light intensity on the display of test images, and providing a good graphic display effect for the tester's test process; on the other hand, the test image is generated by integrating the information of test type, base color data and color type, so that the generated test image is more comprehensive and accurate, which is convenient for the tester to determine the accurate color recognition threshold for the test image, and by processing the tester information, test data and color recognition threshold through an evaluation model, the tester's depression level can be automatically evaluated, thereby improving the accuracy of depression level evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments 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 work.

[0021] Figure 1 A system architecture diagram of an application system for a method for assessing depression based on color thresholds provided in an embodiment of the present application;

[0022] Figure 2 A schematic diagram of a process for evaluating depression level based on color thresholds provided in an embodiment of the present application;

[0023] Figure 3 A schematic diagram of a flow chart of a method for determining a color recognition threshold value of a test subject provided in an embodiment of the present application;

[0024] Figure 4 A schematic diagram of a test image corresponding to the heterochromatic position recognition type provided in an embodiment of the present application;

[0025] Figure 5A schematic diagram of a test image corresponding to the heterochromatic shape recognition type provided in an embodiment of the present application;

[0026] Figure 6 A schematic diagram of the structure of the hardware modules and methods inside the computer device provided in the embodiments of the present application;

[0027] Figure 7 A schematic diagram of a process for evaluating depression level based on color thresholds provided in an embodiment of the present application;

[0028] Figure 8 A schematic diagram of the structure of a depression level assessment system based on color thresholds provided in an embodiment of the present application;

[0029] Fig. 9 A schematic diagram of the structure of a computer device shown in an embodiment of the present application. DETAILED DESCRIPTION

[0030] The present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the relevant invention, rather than to limit the invention. It is also necessary to explain that, for ease of description, only the parts related to the invention are shown in the accompanying drawings.

[0031] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0032] As mentioned in the background technology, with the rapid development of society, the rhythm of people's work and life is also increasing, and more and more people suffer from depression. Depression is a group of psychological disorders or affective disorders with depression as the main symptom caused by various reasons, with low mood, slow thinking, and reduced speech and movement, slowness as typical symptoms. In order to avoid further development of depression, it is very important to assess the degree of depression. In the prior art, it is determined according to the experience of the depression self-assessment test form and the doctor, but the scheme needs to rely on a large amount of subjective work experience, and its detection process may be affected by actual clinical experience. The detection method is relatively single and one-sided, resulting in a low accuracy of the assessment of the degree of depression.

[0033] Based on the above-mentioned defects, the present application provides a method, system, device and medium for assessing the degree of depression based on color threshold. Compared with the prior art, on the one hand, the scheme does not need to be affected by the subjective work experience of the doctor. By automatically judging whether the light intensity of the current device meets the test conditions, the test subject is tested when the test conditions are met, avoiding the influence of light intensity on the display of test images, and providing a good graphic display effect for the test process of the test subject; on the other hand, by comprehensively generating test images by information of test type, base color data and color type, the generated test images are more comprehensive and accurate, which makes it easier for the test subject to determine an accurate color recognition threshold for the test image, and by processing the test subject information, test data and color recognition threshold through an evaluation model, the test subject's depression degree can be automatically assessed, thereby improving the accuracy of depression degree assessment.

[0034] Figure 1 : is a diagram of the implementation environment of a method for assessing depression based on color thresholds provided in an embodiment of the present application. Figure 1 As shown, the implementation environment architecture includes: a computer device, which may include a terminal 100 and a server 200.

[0035] The terminal 100 may be a terminal device in various AI application scenarios. For example, the terminal 100 may be a smart home device such as a smart TV or a smart TV set-top box, or the terminal 100 may be a mobile portable terminal such as a smart phone, a tablet computer, and an e-book reader, or the terminal 100 may be a smart wearable device such as smart glasses or a smart watch, or may be a vehicle-mounted terminal, etc., which is not specifically limited in this embodiment.

[0036] Among them, some AI applications may be installed in the terminal 100. For example, the AI ​​application may be an application such as image processing or data processing.

[0037] The server 200 may be a single server, or a server cluster consisting of a plurality of servers, or the server 200 may include one or more virtualization platforms, or the server 200 may be a cloud computing service center.

[0038] The server 200 may be a server device that provides background services for the AI ​​application installed in the terminal 100 .

[0039] The terminal 100 and the server 200 establish a communication connection via a wired or wireless network. Optionally, the wireless network or wired network uses standard communication technology and / or protocols. The network is usually the Internet, but can also be any network, including but not limited to a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a mobile, wired or wireless network, a private network or any combination of a virtual private network.

[0040] In the process of providing AI application services, the terminal 100 can obtain the light intensity information of the environment in which the tester uses the device, receive the tester's operation instructions to obtain the tester's information, and when the light intensity information meets the test conditions, generate and display the test picture based on the color type and test type, and then determine the tester's depression level through the evaluation model, so as to provide AI application services based on the feature extraction results. The above-mentioned evaluation model can be set in the server 200, trained and applied by the server; or, the above-mentioned evaluation model can also be set in the terminal 100, and trained and updated by the server 200.

[0041] The method for evaluating depression based on color threshold provided in this embodiment can be used to evaluate people with cognitive function loss caused by nervous system diseases, for example, it can include but is not limited to neurodegenerative diseases (Alzheimer's disease, Parkinson's disease, Lewy body dementia, progressive supranuclear palsy, multiple system atrophy, frontotemporal dementia, cortical basal ganglia deformation, motor neuron disease), cerebrovascular disease (ischemic stroke, hemorrhagic stroke, cerebral small vessel disease, aneurysm, cerebral vascular malformation), brain tumor (primary tumor, metastatic tumor), intracranial infection, central immune disease (autoimmune brain The system can be used to evaluate the following diseases: encephalitis, paraneoplastic encephalitis), genetic diseases (mitochondrial encephalopathy, brain iron deposition disease, etc.), metabolic diseases (vitamin B deficiency, glucose metabolism disorder, lipid metabolism disorder), poisoning (lead poisoning, mercury poisoning), endocrine-related encephalopathy (thyroid dysfunction, parathyroid dysfunction, adrenal cortex dysfunction), structural abnormalities (subdural hematoma, normal intracranial pressure hydrocephalus, etc.), cognitive impairment related to mental and psychological diseases: evaluation of people with schizophrenia, depression, anxiety, mania, bipolar disorder, attention deficit hyperactivity disorder, autism, etc. It can also evaluate the binocular information integration ability of healthy people.

[0042] For ease of understanding and explanation, the following Figures 2 to 9 The method, system, device and medium for evaluating depression level based on color threshold provided in the embodiments of the present application are described in detail.

[0043] Figure 2The flowchart of the depression level assessment method based on color threshold according to an embodiment of the present application is shown. The method can be executed by a computer device, which can be the above-mentioned Figure 1 The server 200 or the terminal 100 in the system shown, or the computer device can also be a combination of the terminal 100 and the server 200. Figure 2 As shown, the method includes:

[0044] S101. Obtaining light intensity information of the environment in which the tester uses the device and tester information.

[0045] It should be noted that the above-mentioned tester's device refers to the test device used when the tester needs to evaluate the degree of depression. The test device may include a display screen, which has a display function and a touch function, such as a computer device, wherein the display function is used to display the test picture, and the touch function is used to receive the tester's touch command to obtain the corresponding information. The above-mentioned light intensity information refers to the luminous flux of visible light received by the tester's device per unit area, which is used to indicate the intensity of light and the degree of illumination of the device surface.

[0046] Optionally, the above-mentioned device may be provided with a light sensor to obtain the light intensity information of the environment in which the tester uses the device, or the light intensity information may be obtained through transmission from an external device. This embodiment does not impose any limitation on the method of obtaining the light intensity information of the environment in which the computer device is located.

[0047] As an optional implementation, the above device may be provided with a touch component to implement the touch function, and the device may be pre-set with a tester's personal information option, so that the user clicks or touches the touch component on the device to select the corresponding option, so that the device acquires the tester's information. The tester's information may include the tester's age, height, gender, job, education level, whether he or she is ill, and other information.

[0048] As another possible implementation method, the above-mentioned device can send an information acquisition instruction to an external device with user authorization, so that the external device receives and responds to the information acquisition instruction, obtains the tester information and sends it to the device, thereby allowing the computer device to obtain the tester information.

[0049] S102: When the light intensity information meets the test conditions, determine the test type selected by the tester.

[0050] Specifically, after obtaining the light intensity information, it can be determined whether the light intensity information meets the test conditions, for example, it can be determined whether the light intensity information is greater than or equal to a preset threshold. When the light intensity is greater than or equal to the preset threshold, it is determined that the light intensity information meets the test conditions; when the light intensity is less than the preset threshold, it is determined that the light intensity information does not meet the test conditions. The preset threshold can be a custom setting based on the actual test requirements of the computer device.

[0051] When the light intensity information does not meet the test conditions, the test experiment will not be carried out. The light shield and other components can be adjusted so that the light intensity information of the environment in which the tester uses the device meets the test conditions. When the light intensity information meets the test conditions, the test type selection can be displayed on the device display screen, and the tester can touch the display screen to select the corresponding test type, so that the device receives and responds to the touch command and determines the test type selected by the tester.

[0052] It should be noted that the above test types may include a heterochromatic position recognition type and a heterochromatic shape recognition type. The heterochromatic position recognition type refers to the tester recognizing the position of a graphic block with a color different from that of other graphic blocks; the heterochromatic shape recognition type refers to the tester recognizing the shape of an inner ring graphic block with a color different from that of an outer ring graphic block. The tester may select the corresponding test type according to their own situation.

[0053] In this embodiment, by automatically determining whether the light intensity of the environment in which the device is used meets the test conditions, the tester is tested when the test conditions are met, avoiding the influence of light intensity on the display of test images, providing a good graphic display effect for the tester's test process, and accurately determining the test type of the tester, so that the corresponding test image can be generated and displayed later according to the test type.

[0054] S103: For each color type, determine base color data according to light intensity information.

[0055] It is understandable that under the influence of negative emotions, the visual perception area of ​​the brain of a depressed person will be affected, resulting in a decrease in the ability to distinguish colors. Therefore, the color perception ability of the brain of a depressed person is different from that of a normal person, and the corresponding color recognition threshold is also different.

[0056] Specifically, the computer device may pre-store multiple color wheels, each color wheel corresponding to a color type. For example, eight color wheels may be stored, including eight color types of red, orange, yellow, yellow-green, green, cyan, blue, and blue-purple; ten color wheels may also be stored, including ten color types of red, orange, yellow, yellow-green, green, cyan, blue, blue-purple, purple, and purple-red.

[0057] It should be noted that, in this embodiment, different illumination intensity information corresponds to the same primary color data. When the illumination intensity varies within the allowable range, a visor or other fine-tuning device can be used to fine-tune the color data, thereby presenting the corresponding primary color data. For example, taking the color type as blue as an example, the color data can be fine-tuned according to the illumination intensity information to determine that the primary color data is blue.

[0058] S104 , generating and displaying a test picture according to the test type and the base color data, obtaining the test data of the tester on the test picture, and determining the color recognition threshold of the tester in the color channel corresponding to the color type according to the test data.

[0059] After determining the test type and primary color data, the heterochromatic data can be calculated based on the primary color data, and the primary color data and the heterochromatic data can be combined to obtain a test picture, which can be displayed on a computer device so that the tester can identify the test picture. The recognition results for different test types are also different.

[0060] It is understandable that the above test picture is a picture that the tester needs to test, which may include multiple graphic blocks, and the color of one graphic block among the multiple graphic blocks is different from the colors of other graphic blocks. The test picture may also include graphic blocks of inner and outer rings, and the status of the graphic blocks of the inner and outer rings may be the same or different, and the colors of the graphic blocks of the inner and outer rings are different.

[0061] After the computer device displays the test picture, the tester can identify the position or shape of the test picture and generate test data, which may include test duration and test results. The test duration may include multiple test durations, each of which refers to the duration from the time the test picture is displayed to the time the tester determines the test result, and may include the test duration corresponding to each time the tester identifies the test picture. The test result refers to the result of the tester's correct or incorrect recognition of the test picture.

[0062] Optionally, the computer device can set a preset time for the test result, and the tester can identify the correct result within the preset time as a correct test result; the tester can identify the correct or incorrect result beyond the preset time, or the incorrect result within the preset time as an incorrect test result. The preset time can be customized in advance according to actual needs, for example, it can be 5s.

[0063] In this embodiment, after obtaining the test data of the test image, it is possible to judge whether the tester has identified the correct comprehensive test result based on the test duration and the test result. The preset duration and the test duration are compared. When the test duration is greater than the preset duration, it is determined that the comprehensive test result is an identification error; when the test duration is not greater than the preset duration and the test result is a correct identification, it is determined that the comprehensive test result is a correct identification.

[0064] After the test data is obtained, it can be determined whether the comprehensive test result meets the preset conditions. When the preset conditions are met, the color recognition threshold of the tester in the color channel corresponding to the color type is determined.

[0065] S105 , processing the tester information, test data and color recognition threshold through an evaluation model to obtain the tester's depression level.

[0066] It should be noted that the above evaluation model is used to evaluate the depression level of the tester, which may include mild, moderate and severe levels, and may include the color recognition thresholds of normal people for different color types. Among them, the mild depression level is lower than the moderate depression level, and the moderate depression level is lower than the severe depression level.

[0067] Specifically, after obtaining the tester information, test data and color recognition threshold, the tester's visual perception ability characteristics are extracted according to the tester information, test data and color recognition threshold, and the visual perception ability characteristics are processed through the evaluation model to obtain the tester's depression level. The visual perception ability characteristics integrate the information of the tester information, test data and color recognition threshold.

[0068] Optionally, the evaluation model may be a classification network, which may include common neural networks such as ConvNeXt, SwinNet_v2, Googlenet, Inception_v3, Resnet18, DenseNet, Vgg11, Efficientnet and MobileNet.

[0069] The above classification network may include a binary classification function and a multi-classification function. Inputting the visual perception ability characteristics of the tester into the binary classification function can obtain the predicted depression type of the tester, and inputting the visual perception ability characteristics of the tester into the multi-classification function can obtain the predicted depression attribute of the tester. The binary classification function may be a sigmoid function, and the multi-classification function may be a softmax function. The predicted depression type may include depression and normal type, and the predicted depression attribute may include mild, moderate and severe; it may also include a scoring value, which may include multiple scores, each score corresponding to a different degree of depression, the higher the score, the higher the corresponding depression degree, and the lower the score, the lower the corresponding depression degree.

[0070] The method for assessing depression level based on color threshold provided in the embodiment of the present application obtains the light intensity information of the environment in which the tester uses the device and the tester information, and when the light intensity information meets the test conditions, determines the test type selected by the tester, for each color type, determines the primary color data according to the light intensity information, and generates and displays a test picture according to the test type and the primary color data, obtains the test data of the test picture by the tester, determines the color recognition threshold of the tester in the color channel corresponding to the color type according to the test data, and finally processes the tester information, test data and color recognition threshold through an evaluation model to obtain the depression level of the tester. Compared with the existing technology, on the one hand, this solution does not need to be affected by the doctor's subjective work experience. By automatically judging whether the light intensity of the current device meets the test conditions, the test subject can be tested when the test conditions are met, avoiding the influence of light intensity on the display of test images, and providing a good graphic display effect for the tester's test process; on the other hand, the test image is generated by integrating the information of test type, base color data and color type, so that the generated test image is more comprehensive and accurate, which is convenient for the tester to determine the accurate color recognition threshold for the test image, and by processing the tester information, test data and color recognition threshold through an evaluation model, the tester's depression level can be automatically evaluated, thereby improving the accuracy of depression level evaluation.

[0071] In one embodiment, the embodiment of the present application further provides a specific implementation method for generating and displaying a test picture according to the test type and the primary color data, obtaining the test data of the tester on the test picture, and determining the color recognition threshold of the tester in the color channel corresponding to the primary color wheel according to the test data, see Figure 3 As shown, the method includes:

[0072] S201, determining an initial color level and calculating initial heterochromatic data according to the initial color level, initial color values ​​of color channels corresponding to the initial color level, and primary color data.

[0073] It should be noted that each color type may include multiple color levels, and the color difference between the heterochromatic data and the primary color data is different in each color level. For example, five color levels may be included, namely color level 1, color level 2, color level 3, color level 4 and color level 5. The higher the color level, the greater the color difference between the corresponding heterochromatic data and the primary color data.

[0074] Optionally, before executing the test task, the test task operation steps may be displayed to the tester on the computer device. The operation steps may be in the form of text or language to explain the test process and the tasks to be completed to the tester.

[0075] After obtaining the test type and the primary color data, the initial color level can be determined, and then the initial heterochromatic data can be calculated according to the initial color level, the initial color value of the color channel corresponding to the initial color level, and the primary color data. The initial heterochromatic data can be obtained by determining the current format of the primary color data, converting the current format of the primary color data into a preset color coding format, the color coding format including multiple color channels, and selecting a color channel in the primary color data in the color coding format for modification according to the initial color level and the initial color value of the color channel corresponding to the initial color level.

[0076] For example, if the current format of the base color data is RGB, the color brightness can be changed in the custom module to adapt to the change of ambient light intensity during use. And the current RGB format can be converted to YCbCr color encoding format by the following formula:

[0077] ColorR=0.98ColorY+1.1*1.402*(ColorCr-128);

[0078] ColorG=0.98ColorY–1.1*0.34414*(ColorCb-128)–1.1*0.71414*(

[0079] ColorCr-128);

[0080] ColorB=0.98ColorY+1.1*1.772*(ColorCb-128);

[0081] Among them, ColorY is the color value of the Y channel, ColorCb is the color value of the Cb channel, ColorCr is the color value of the Cr channel, ColorR is the color value of the R channel, ColorG is the color value of the G channel, and ColorB is the color value of the B channel.

[0082] After determining the initial color level and the initial color value, one of the color channels can be selected for modification according to the initial color level and the initial color value of the color channel corresponding to the initial color level to obtain initial heterochromatic data. For example, the color value of the Y channel can be kept unchanged, and the color value of the Cb channel or the Cr channel can be changed to obtain initial heterochromatic data.

[0083] It can be understood that the initial heterochromatic data refers to data that is different from the primary color data at the initial color level. The above-mentioned YCbCr is a color encoding format commonly used in digital video and image processing. It consists of a brightness component Y and two chrominance components Cb and Cr, where Y represents brightness, and Cb and Cr represent the chrominance information of blue and red respectively. The YCbCr format supports a variety of sampling formats, such as 4:4:4, 4:2:2, 4:1:1 and 4:2:0, which determine the sampling rate of the chrominance component in the image, thereby affecting the data compression efficiency and image quality of the image. Among them, in the 4:4:4 format, each pixel has complete Y, Cb and Cr information, which is suitable for high-quality image transmission and processing. For the 4:2:2, 4:1:1 and 4:2:0 formats, these formats achieve data compression by reducing the sampling rate of the chrominance component, which is suitable for different application scenarios. For example, the 4:2:0 format is often used in high-definition video encoding because it achieves high compression efficiency while maintaining image quality.

[0084] In this embodiment, by converting the RGB format into the YCbCr format, the image data can be effectively compressed while maintaining good image quality, and the color level, color value and other information are comprehensively considered, so that the determined initial heterochromatic data can be more accurate.

[0085] S202 , generating and displaying an initial test picture based on the test type, the primary color data and the initial heterochromatic data; the initial test picture is generated by changing the positions of the initial heterochromatic data and the primary color data.

[0086] Specifically, after determining the test type, primary color data, and initial heterochromatic data, a preset graphic corresponding to the test type may be first obtained, and the primary color data and initial heterochromatic data may be filled into the preset graphic to obtain an initial test image and display it for identification by the tester. The preset graphic may be custom-set according to the test type, and different preset graphics may correspond to different test types.

[0087] As an implementable method, when the test type is heterochromatic position recognition type, the preset graphic includes multiple graphic blocks, and the initial heterochromatic data is filled into one graphic block of the preset graphic, and the primary color data is filled into the remaining graphic blocks of the preset graphic to obtain the initial test image. For example, see Figure 4 The initial test picture shown includes four squares, and the square in the right corner is a square of a different color from the other three squares.

[0088] As another possible implementation, when the test type is heterochromatic shape recognition type, the initial heterochromatic data is filled into the inner ring of the preset graphic, and the base color data is filled into the outer ring of the preset graphic to obtain the initial test image. For example, see Figure 5The initial test picture shown includes inner and outer ring figures, the inner ring figure is a triangle, the outer ring figure is a circle, and the inner ring figure is a heterochromatic figure and has a different color from the outer ring figure.

[0089] The computer device generates heterochromatic data once each time, combines it with the primary color data into a test picture, and uses a preset algorithm to process it into a 10-bit test picture and output it to the display screen. 10-bit means that the color depth of the picture is 10 bits. Color depth is an important indicator to measure the richness of colors. It is expressed by the power of 2. The higher the number of bits, the higher the color depth value, and the more colors the image can show. Specifically, the number of colors that a 10-bit image can display is 2 to the power of 10, that is, 1024 color level changes, which provides more color depth and fineness than 8-bit pictures (256 color levels), making the picture more rich and natural in transition and detail expression.

[0090] Taking the data processing method of a 10-bit test image as an example, it can be converted into the YCbCr format in the following ways: One way is to use the cvCvtColor function in the OpenCV library to implement it. By first creating an RGB image and converting it to the YCbCr color space, and calling the cvCvtColor function to implement it, you can specify the conversion type as CV_BGR2YCrCb. For example, the instruction generated by this function can be expressed in the following form: cvCvtColor(img_rgb,ycbcr_img,CV_BGR2YCrCb); this instruction is used to represent the conversion of an RGB image to a YCbCr color space, where img_rgb is the input RGB image and ycbcr_img is the output YCbCr image.

[0091] Another way is to directly calculate the values ​​of Y, Cb, and Cr through a formula. This involves weighted summation of the RGB values ​​and adding an appropriate offset. The specific conversion formula can be shown as follows:

[0092] Y=0.257×R+0.504×G+0.098×B+16;

[0093] Cb=-0.148×R-0.291×G+0.439×B+128;

[0094] Cr=0.439×R-0.368×G-0.071×B+128.

[0095] In this embodiment, by selecting the YCbCr color output format and adding weights to the conversion matrix of the basic color RGB, the brightness of different colors can be controlled to be constant in the eyes of the tester. At the same time, by selecting the color depth of the test image to be 10 bits, the test results of the tester are more accurate.

[0096] S203: Obtain the tester's initial test data for the initial test picture.

[0097] After the initial test picture is displayed on the display screen, the tester can identify it according to the displayed initial test picture to obtain initial test data, which may include initial test duration and initial test results. The initial test duration refers to the duration from the time the initial test picture is displayed to the time when the tester's test result is determined, and may include the test duration corresponding to each time the tester identifies the test picture. The initial test result refers to the result of the tester's correct or incorrect identification of the initial test picture. In this embodiment, the computer device can obtain the initial test duration by detecting the duration from the time the initial test picture is displayed to the time when the tester's test result is determined, and determine the initial test result by receiving the tester's touch command.

[0098] S204: When the initial test data indicates that the tester has correctly identified the initial test image for a preset number of consecutive times, the initial color value of the color channel corresponding to the initial color level of the tester is used as a color recognition threshold.

[0099] Specifically, after obtaining the user's initial test data, the computer device can adjust the position of the initial heterochromatic data and the primary color data, obtain the next initial test picture and display it, continue to receive the tester's touch command to obtain the initial test data, and determine whether the tester has correctly identified the initial test picture for a preset number of consecutive times. If the tester has correctly identified the initial test picture for a preset number of consecutive times, the initial color value of the color channel corresponding to the initial color level of the tester is used as the color recognition threshold. Among them, the preset number of times can be customized according to actual needs.

[0100] S205 . When the initial test data indicates that the tester has not correctly identified the initial test image for a preset number of consecutive times, the initial color value on the color channel is adjusted to a next color value.

[0101] S206, calculating next different color data according to the initial color level, the next color value of the color channel corresponding to the initial color level and the primary color data; the color difference between the next different color data and the primary color data in the initial color level is greater than the color difference between the initial different color data and the primary color data in the initial color level.

[0102] S207 , generating and displaying a next test picture based on the test type, the primary color data and the next different color data; the next test picture is generated by changing the positions of the next different color data and the primary color data.

[0103] S208, obtaining the next test data of the tester for the next test picture;

[0104] S209, when the next test data indicates that the tester correctly recognizes the next heterochromatic data for a preset number of consecutive times, the next color value of the tester corresponding to the color channel at the initial color level is used as the color recognition threshold.

[0105] Exemplarily, taking the test type as the heterochromatic position recognition type and the preset number of times as three times as an example, the computer device generates and displays the first four-color block picture according to the initial test level and the test type, and the heterochromatic block of the first four-color block picture is at the lower right corner, so that the tester can identify the position of the heterochromatic block in the first four-color block picture, and obtain the corresponding first initial test result, and the position of the heterochromatic block is changed to generate and display the second four-color block picture, for example, it can be set at the lower left corner, so that the tester can identify the position of the heterochromatic block in the second four-color block picture, and obtain the corresponding second initial test result. When the first initial test result and the second initial test result both indicate that the recognition is correct, the position of the heterochromatic block can be changed to generate and display the third four-color block picture, for example, it can be set at the upper left corner, so that the tester can identify the position of the heterochromatic block in the third four-color block picture, and obtain the corresponding third initial test result. When the third initial test result indicates that the recognition is correct, it indicates that the tester has recognized correctly three times in a row, and the initial color value of the color channel corresponding to the initial color level can be used as the color recognition threshold.

[0106] When the first initial test result indicates that the recognition is correct, and the second initial test result indicates that the recognition is incorrect, indicating that the tester has not recognized correctly three times in a row, then the initial color level is added to the color value of the Cb or Cr color channel by 0.2 to obtain the next color value of the Cb or Cr channel corresponding to the initial color level, and the next heterochromatic data is calculated based on the primary color data. Similarly, in accordance with the generation method of the initial test image, the next test image is generated and displayed based on the test type, primary color data and the next heterochromatic data. The next test data corresponding to the initial color level of the tester is received, and the next test data includes the next test duration and the next test result. The next test duration refers to the time between the display time of the next test image and the time when the tester's test result is determined, and the next test result refers to the result of the tester's correct or incorrect recognition of the next test image. And determine whether the next heterochromatic data is recognized correctly for three consecutive times. When the next heterochromatic data is recognized correctly for three consecutive times, the next color value of the color channel corresponding to the initial color level of the tester is used as the color recognition threshold; when the recognition is not correct for three consecutive times, it is necessary to continue to determine the next color value and the next heterochromatic data, and further perform the picture generation and recognition process similar to the above steps until the color recognition threshold is determined.

[0107] It should be noted that when the test type is a heterochromatic position recognition type, when the multiple graphic blocks are four squares, each of the four squares can be a square or a circle; when the test type is a heterochromatic shape recognition type, the inner ring graphic in the corresponding inner and outer ring images can be a triangle or a star, and the outer ring graphic can be a circle or a square.

[0108] In this embodiment, for the same color level, by modifying the color values ​​of different color channels, including modifying the Cb color channel and modifying the Cr channel, the test image can be adjusted more diversely, thereby improving the efficiency of central visual processing detection for people with cognitive impairment.

[0109] In one of the embodiments, the present embodiment also provides a specific implementation method for determining the color recognition threshold. The method also includes: when the tester fails to correctly recognize the next test image for a preset number of times in the initial color level, adjusting the initial color level to the next color level; calculating another heterochromatic data according to the next color level, the initial color value corresponding to the color channel of the next color level and the primary color data; the color difference between the another heterochromatic data and the primary color data in the next color level is greater than the color difference between the initial heterochromatic data and the primary color data in the initial color level; generating and displaying another test image based on the primary color data and the another heterochromatic data; the another test image is generated by changing the positions of the another heterochromatic data and the primary color data; obtaining another test data of the tester for the another test image; when the another test data indicates that the tester has correctly recognized the another test image for a preset number of times in a row, taking the initial color value of the color channel corresponding to the next color level of the tester as the color recognition threshold.

[0110] In this embodiment, taking the preset number of times as three as an example, for the initial color level, when it is determined according to the next test data that the tester has not correctly identified the next test picture three times in a row in the initial color level, it is necessary to adjust the color level, that is, adjust the color difference between the heterochromatic data and the primary color data, obtain another heterochromatic data corresponding to the next color level, generate another test picture and display it on the display screen, so that the tester can recognize the test picture, and can receive the tester's touch command to obtain the corresponding another test data, the another test data includes another test duration and another test result, the another test duration refers to the time between the display moment of the another test picture and the moment when the tester's test result is determined, and the another test result refers to the result of the tester's correct or incorrect recognition of the another test picture. When it is determined whether the another test picture is correctly recognized three times in a row, the initial color value of the color channel corresponding to the next color level is used as the color recognition threshold of the tester. Optionally, when the tester has not correctly identified the another test picture for the preset number of times in the next color level, the next color level is adjusted to another color level, and the picture generation and recognition process is further performed until the color recognition threshold is determined.

[0111] Optionally, when the test type is a heterochromatic shape recognition type, the generated test image includes inner and outer ring graphics of different colors, and the tester can identify the inner ring shape to obtain corresponding test data.

[0112] In this embodiment, the different color position recognition types are set to include multiple graphic blocks, and the graphics are relatively simple, which can avoid fatigue of the tester during the test and reduce the involvement of the tester's experience or cognitive factors in the test, thereby improving the test accuracy; and by determining the color recognition threshold, the tester's visual central nervous system can be measured, and the tester can identify and judge the position or shape of color blocks of fixed levels, reflecting the accuracy of the visual center's color information processing neural activity, which is beneficial to improving detection efficiency and can evaluate the degree of cognitive impairment.

[0113] For example, see Figure 6 As shown, the computer device may include multiple hardware modules, which are a data acquisition module, an ambient light intensity sensing module, a computer management module, a processing module and a display module, wherein the processing module may include a color data calculation unit and a depression level assessment unit. The data acquisition module is used to collect the test data of the tester; the ambient light intensity sensing module is used to obtain the light intensity information of the environment in which the tester uses the device; the computer management module is used to process the data of each module and to determine the color recognition threshold; the color data calculation unit block is used to generate heterochromatic data according to the light intensity information and the basic color data, and generate a test picture according to the heterochromatic data and send it to the display module; the display module is used to display the test picture, and the depression level assessment unit is used to process the test data, the color recognition threshold and the tester information through the assessment model to obtain the depression level of the tester.

[0114] The experimental paradigm in this embodiment consists of a color difference level adjustment part and an image presentation part, and there are 16 groups of experiments in total, such as Figure 7As shown, the base color data is selected from a preset 8-color wheel designed for depression. The computer device can determine the base color data according to the environmental intensity information, and modify the color value of the color channel to obtain the heterochromatic data, so as to combine the base color data and the heterochromatic data to form a test picture and display it, so that the tester can select the test type. When the test type is a heterochromatic position recognition type, the generated test picture includes multiple graphic blocks. For example, when it is a four-color block, in each group of four-color block test tasks, the heterochromatic block appears randomly at any position, so that the tester can recognize the position of the heterochromatic block; when the test type is a heterochromatic shape recognition type, the generated test picture includes inner and outer ring graphics, so that the tester can recognize the shape of the heterochromatic block, and then determine whether it is recognized correctly three times in a row. When it is recognized correctly three times in a row, the color recognition threshold of the tester in the color channel corresponding to the color type can be determined according to the test data. By analogy, the color recognition threshold of two color channels can be determined for each color type, and the color recognition threshold of sixteen color channels can be determined for eight color types. The tester information, test data and color recognition threshold are processed through the evaluation model to obtain the depression level of the tester, and a test report is generated. The test report can be saved in a specified path of the computer device.

[0115] Furthermore, the above-mentioned evaluation model may include color thresholds of normal people for different color types. After obtaining the color recognition threshold of the tester, the color recognition threshold can be compared with the color threshold. For example, taking two color types as an example, the color threshold of normal people for yellow is 5, and the color threshold for red is 6. The determined tester's color recognition threshold for yellow is 8, and the color recognition threshold for red is 15. The evaluation model can then comprehensively consider the tester information and the color recognition threshold, thereby determining that the tester's depression level is bidirectional depression, and the tester's depression level for identifying yellow is intermediate, and the depression level for identifying red is severe.

[0116] The depression degree assessment method based on color threshold provided in the present embodiment can not only be applied to the presence of neurological diseases such as cognitive impairment, mental and psychological diseases and healthy people, but also display the test picture on the computer device, and can accurately determine the color recognition threshold of the tester. For people with cognitive impairment, this paradigm is not affected by the decline of advanced cognitive function, and can accurately measure the degree of damage of the visual perception of patients with cognitive impairment (or patients with mental and psychological diseases), thereby improving the accuracy of central visual processing measurement. And by setting different test types, it is suitable for people with different test needs, and the efficiency of central visual processing detection of people with cognitive impairment is improved, which meets the actual needs of clinical practice for rapid measurement and effective measurement. At the same time, this method does not need to be limited by the application scenario, and can be adapted to more application places, such as families, communities or other places, to meet the actual needs of people's visual perception and indirect cognitive function screening such as cognitive impairment, mental and psychological diseases. And without complex equipment or high-standard measurement environment, it can be free from the limitation of the test environment, and can quickly and conveniently realize the test operation, thereby reducing time cost and economic cost.

[0117] on the other hand, Figure 8 This is a schematic diagram of the structure of a depression level assessment system based on color thresholds provided in an embodiment of the present application. The system may be a system in a terminal or a server, such as Figure 8 As shown, the system 700 includes:

[0118] The information acquisition module 710 is used to obtain the light intensity information of the environment in which the tester uses the device and the tester information;

[0119] A type determination module 720, for obtaining a test type selected by a tester when the light intensity information meets the test conditions;

[0120] A primary color determination module 730, for determining primary color data for each color type according to the illumination intensity information;

[0121] The threshold determination module 740 is used to generate and display a test picture according to the test type and the base color data, obtain the test data of the tester on the test picture, and determine the color recognition threshold of the tester in the color channel corresponding to the color type according to the test data;

[0122] The evaluation module 750 is used to process the tester information, test data and color recognition threshold through the evaluation model to obtain the depression level of the tester.

[0123] Optionally, the threshold determination module 740 is specifically configured to:

[0124] Determine an initial color grade and calculate initial heterochromatic data according to the initial color grade, initial color values ​​of color channels corresponding to the initial color grade, and primary color data;

[0125] Generate and display an initial test picture based on the test type, the primary color data and the initial heterochromatic data; the initial test picture is generated by changing the positions of the initial heterochromatic data and the primary color data;

[0126] Obtaining the tester's initial test data for the initial test image;

[0127] When the initial test data indicates that the tester correctly recognizes the initial test picture for a preset number of consecutive times, the initial color value of the tester's color channel corresponding to the initial color level is used as the color recognition threshold.

[0128] Optionally, the threshold determination module 740 is further configured to:

[0129] When the initial test data indicates that the tester has not correctly identified the initial test image for a preset number of consecutive times, the initial color value on the color channel is adjusted to a next color value;

[0130] Calculating next different color data according to the initial color level, the next color value of the color channel corresponding to the initial color level and the primary color data; the color difference between the next different color data and the primary color data in the initial color level is greater than the color difference between the initial different color data and the primary color data in the initial color level;

[0131] Generate and display the next test picture based on the test type, the primary color data and the next different color data; the next test picture is generated by changing the positions of the next different color data and the primary color data;

[0132] Obtain the next test data of the tester for the next test picture;

[0133] When the next test data indicates that the tester correctly recognizes the next heterochromatic picture for a preset number of consecutive times, the next color value of the tester's color channel corresponding to the initial color level is used as the color recognition threshold.

[0134] Optionally, the threshold determination module 740 is further configured to:

[0135] When the tester fails to correctly identify the next test image at the initial color level for a preset number of consecutive times, the initial color level is adjusted to the next color level;

[0136] Calculate further different color data according to the next color level, the initial color value corresponding to the color channel of the next color level and the primary color data; the color difference between the further different color data and the primary color data in the next color level is greater than the color difference between the initial different color data and the primary color data in the initial color level;

[0137] Generate and display a further test picture based on the primary color data and the further different color data; the further test picture is generated by changing the positions of the further different color data and the primary color data;

[0138] Obtaining the test data of the tester for another test picture;

[0139] When another test data indicates that the tester correctly recognizes another test picture for a preset number of consecutive times, the initial color value of the tester's color channel corresponding to the next color level is used as the color recognition threshold.

[0140] Optionally, the threshold determination module 740 is further configured to:

[0141] Determine the current format of the base color data;

[0142] Converting a current format of the base color data into a preset color encoding format; the color encoding format includes a plurality of color channels;

[0143] According to the initial color level and the initial color value of the color channel corresponding to the initial color level, a color channel in the primary color data in the color coding format is selected for modification to obtain initial heterochromatic data.

[0144] Optionally, the threshold determination module 740 is further configured to:

[0145] Get the preset graph corresponding to the test type;

[0146] Fill the primary color data and the initial heterochromatic color data into the preset graph to obtain the initial test image.

[0147] Optionally, the threshold determination module 740 is further configured to:

[0148] When the test type is a heterochromatic position recognition type, the initial heterochromatic data is filled into a graphic block of a preset graphic, and the primary color data is filled into the remaining graphic blocks of the preset graphic to obtain an initial test image; and / or

[0149] When the test type is a heterochromatic shape recognition type, the initial heterochromatic data is filled into the inner ring of the preset graphic, and the base color data is filled into the outer ring of the preset graphic to obtain an initial test image.

[0150] Optionally, the evaluation module 750 is specifically configured to:

[0151] Extracting the visual perception ability characteristics of the tester according to the tester information, test data and color recognition threshold;

[0152] The visual perception ability characteristics are processed through the evaluation model to obtain the depression level of the test subject.

[0153] It can be understood that the functions of each functional module of the depression level assessment system based on color threshold in this embodiment can be specifically implemented according to the method in the above method embodiment, and its specific implementation process can refer to the relevant description of the above method embodiment, which will not be repeated here.

[0154] On the other hand, a computer device provided in an embodiment of the present application includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the above-mentioned method for assessing depression level based on color threshold is implemented.

[0155] Reference below Fig. 9 , Fig. 9 A schematic diagram of the structure of a computer system of a terminal device according to an embodiment of the present application.

[0156] like Fig. 9 As shown, the computer system 300 includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage part 303 to a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the system 300 are also stored. The CPU 301, the ROM 302, and the RAM 303 are connected to each other through a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0157] The following components are connected to the I / O interface 305: an input section 306 including a keyboard, a mouse, etc.; an output section 307 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed, so that a computer program read therefrom is installed into the storage section 308 as needed.

[0158] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart 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 machine-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 303, and / or installed from the removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, the above-mentioned functions defined in the system of the present application are executed.

[0159] It should be noted that the computer-readable medium shown in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0160] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of the code, and the aforementioned module, program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0161] The units or modules involved in the embodiments described in the present application may be implemented by software or by hardware. The units or modules described may also be arranged in a processor, for example, may be described as: a processor comprising: an information acquisition module, a type determination module, a base color determination module, a threshold determination module and an evaluation module. The names of these units or modules do not, in certain cases, constitute limitations on the units or modules themselves, for example, the information acquisition module may also be described as "used to obtain light intensity information and tester information of the environment in which the tester uses the device".

[0162] As another aspect, the present application further provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiment; or may exist independently and not be assembled into the electronic device. The above computer-readable storage medium stores one or more programs, and when the above programs are used by one or more processors to execute the depression level assessment method based on color threshold described in the present application:

[0163] Obtaining information about the light intensity of the environment in which the tester uses the device and information about the tester;

[0164] When the light intensity information meets the test conditions, determining the test type selected by the tester;

[0165] For each color type, determining primary color data according to the light intensity information;

[0166] Generate and display a test picture according to the test type and the primary color data, obtain test data of the tester on the test picture, and determine a color recognition threshold of the tester in a color channel corresponding to the color type according to the test data;

[0167] The tester information, the test data and the color recognition threshold are processed through an evaluation model to obtain the depression level of the tester.

[0168] In summary, the method, system, device and medium for assessing the degree of depression based on color threshold provided in the embodiments of the present application obtain the light intensity information of the environment in which the tester uses the device and the tester information, and when the light intensity information meets the test conditions, determine the test type selected by the tester, for each color type, determine the primary color data according to the light intensity information, and generate and display a test image according to the test type and the primary color data, obtain the test data of the test image by the tester, determine the color recognition threshold of the tester in the color channel corresponding to the color type according to the test data, and finally process the tester information, test data and color recognition threshold through an evaluation model to obtain the tester's depression level. Compared with the existing technology, on the one hand, this solution does not need to be affected by the doctor's subjective work experience. By automatically judging whether the light intensity of the current device meets the test conditions, the test subject can be tested when the test conditions are met, avoiding the influence of light intensity on the display of test images, and providing a good graphic display effect for the tester's test process; on the other hand, the test image is generated by integrating the information of test type, base color data and color type, so that the generated test image is more comprehensive and accurate, which is convenient for the tester to determine the accurate color recognition threshold for the test image, and by processing the tester information, test data and color recognition threshold through an evaluation model, the tester's depression level can be automatically evaluated, thereby improving the accuracy of depression level evaluation.

[0169] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other.

Claims

1. A method for evaluating depression level based on color threshold, characterized in that: The depression level assessment method based on color threshold comprises: Obtaining information about the light intensity of the environment in which the tester uses the device and information about the tester; When the light intensity information meets the test conditions, determining the test type selected by the tester; For each color type, determining primary color data according to the light intensity information; Generate and display a test picture according to the test type and the primary color data, obtain test data of the tester on the test picture, and determine a color recognition threshold of the tester in a color channel corresponding to the color type according to the test data; The tester information, the test data and the color recognition threshold are processed through an evaluation model to obtain the depression level of the tester.

2. The method for evaluating depression level based on color threshold according to claim 1, characterized in that: Generating and displaying a test picture according to the test type and the primary color data, obtaining test data of the tester on the test picture, and determining a color recognition threshold of the tester in a color channel corresponding to the primary color wheel according to the test data, including: Determine an initial color grade and calculate initial heterochromatic data according to the initial color grade, an initial color value of a color channel corresponding to the initial color grade, and the primary color data; Generate and display an initial test picture based on the test type, the primary color data and the initial heterochromatic data; the initial test picture is generated by changing the positions of the initial heterochromatic data and the primary color data; Acquiring initial test data of the tester on the initial test picture; When the initial test data indicates that the tester correctly identifies the initial test picture for a preset number of consecutive times, the initial color value of the tester in the color channel corresponding to the initial color level is used as the color recognition threshold.

3. The method for evaluating depression level based on color threshold according to claim 2, characterized in that: The method further comprises: When the initial test data indicates that the tester has not correctly identified the initial test picture for a preset number of consecutive times, adjusting the initial color value on the color channel to a next color value; Calculating next different color data according to the initial color level, the next color value of the color channel corresponding to the initial color level and the primary color data; the color difference between the next different color data and the primary color data in the initial color level is greater than the color difference between the initial different color data and the primary color data in the initial color level; Generate and display a next test picture based on the test type, the primary color data and the next different color data; the next test picture is generated by changing the positions of the next different color data and the primary color data; Obtaining next test data of the tester for the next test picture; When the next test data indicates that the tester correctly identifies the next heterochromatic picture for a preset number of consecutive times, the next color value of the tester in the color channel corresponding to the initial color level is used as the color recognition threshold.

4. The method for evaluating depression level based on color threshold according to claim 3, characterized in that: The method further comprises: When the tester fails to correctly identify the next test image at the initial color level for a preset number of times in a row, the initial color level is adjusted to the next color level; Calculate further different color data according to the next color level, the initial color value corresponding to the color channel of the next color level and the primary color data; the color difference between the further different color data and the primary color data in the next color level is greater than the color difference between the initial different color data and the primary color data in the initial color level; Generate and display another test picture based on the primary color data and the further different color data; the further test picture is generated by changing the positions of the further different color data and the primary color data; Obtaining further test data of the tester on the further test picture; When the further test data indicates that the tester correctly identifies the further test picture for a preset number of consecutive times, the initial color value of the tester in the color channel corresponding to the next color level is used as the color recognition threshold.

5. The method for evaluating depression level based on color threshold according to claim 2, characterized in that: Calculating initial heterochromatic data according to the initial color level, the initial color value of the color channel corresponding to the initial color level and the primary color data, including: determining a current format of the primary color data; Converting the current format of the base color data into a preset color encoding format; the color encoding format includes a plurality of color channels; According to the initial color level and the initial color value of the color channel corresponding to the initial color level, a color channel in the primary color data in the color coding format is selected for modification to obtain the initial heterochromatic data.

6. The method for evaluating depression level based on color threshold according to claim 2, characterized in that: Generating an initial test picture based on the test type, the primary color data and the initial heterochromatic data, comprising: Obtaining a preset graphic corresponding to the test type; The primary color data and the initial heterochromatic data are filled into the preset graph to obtain the initial test image.

7. The method for evaluating depression level based on color threshold according to claim 6, characterized in that: The test types include: heterochromatic position recognition type and heterochromatic shape recognition type; filling the base color data and the initial heterochromatic data into the preset graph to obtain the initial test picture, including: When the test type is a heterochromatic position recognition type, the initial heterochromatic data is filled into a graphic block of the preset graphic, and the primary color data is filled into the remaining graphic blocks of the preset graphic to obtain the initial test picture; and / or, When the test type is a heterochromatic shape recognition type, the initial heterochromatic data is filled into the inner ring graphic of the preset graphic, and the primary color data is filled into the outer ring graphic of the preset graphic to obtain the initial test picture.

8. The method for evaluating depression level based on color threshold according to claim 1, characterized in that: Processing the tester information, the test data and the color recognition threshold through an evaluation model to obtain the depression level of the tester includes: Extracting visual perception ability characteristics of the tester according to the tester information, the test data and the color recognition threshold; The visual perception ability characteristics are processed by the evaluation model to obtain the depression level of the test subject.

9. A depression level assessment system based on color threshold, characterized in that: The depression level assessment system based on color threshold comprises: An information acquisition module is used to obtain the light intensity information of the environment in which the tester uses the device and the tester information; A type determination module, used for obtaining the test type selected by the tester when the light intensity information meets the test conditions; A primary color determination module, configured to determine primary color data for each color type according to the illumination intensity information; A threshold determination module, configured to generate and display a test picture according to the test type and the primary color data, obtain test data of the tester on the test picture, and determine a color recognition threshold of the tester in a color channel corresponding to the color type according to the test data; The evaluation module is used to process the tester information, the test data and the color recognition threshold through an evaluation model to obtain the depression level of the tester.

10. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method for assessing depression level based on color thresholds described in any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for assessing depression level based on color thresholds described in any one of claims 1 to 8 are implemented.

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