Cognitive impairment risk assessment apparatus, device, and storage medium

Abstract

The application relates to a cognitive disorder risk assessment device, equipment and storage medium, and belongs to the technical field of intelligent medical treatment. The device comprises a display module, which is used for randomly displaying a first type of picture, a second type of picture and a third type of picture from a preset picture set; the first type of picture is a picture displayed for the second time to a target object, the second type of picture is related to the first type of picture, and the third type of picture is unrelated to the first type of picture; an acquisition module is used for acquiring the situational memory ability, the pattern separation ability, the anti-interference ability and the reaction time of the target object; and an evaluation module is used for determining the risk degree of cognitive disorder of the target object according to the situational memory ability, the pattern separation ability, the anti-interference ability and the reaction time of the target object and outputting. The technical scheme of the embodiment of the application can solve the technical problem of high cost.

Description

Technical Field

[0001] This application relates to the field of smart healthcare technology, and in particular to a cognitive impairment risk assessment device, equipment, and storage medium. Background Technology

[0002] Neurodegenerative diseases, such as Alzheimer's and Parkinson's, are a group of age-related illnesses characterized by the gradual loss of neuronal function and structure, leading to cognitive and motor impairments and ultimately causing patients to lose their ability to live independently. These diseases pose a significant threat to both individuals and society. For patients, the decline in cognitive abilities severely impacts their quality of life, and their gradual loss of self-care ability requires substantial care from family members, placing a heavy economic and psychological burden on families. For society, the increasing prevalence of neurodegenerative diseases against the backdrop of a rapidly aging global population further exacerbates the burden on society as a whole.

[0003] The key to treating neurodegenerative diseases lies in early and accurate screening so that intervention can be initiated as early as possible to slow disease progression. However, current early screening methods typically rely on professionals to observe and subjectively rate subjects' performance in tasks such as image recognition, memory retrieval, or attention. This assessment process is cumbersome, inefficient, and results in high human and time costs. Summary of the Invention

[0004] In view of this, this application provides a cognitive impairment risk assessment device, equipment, and storage medium to solve at least one problem existing in the prior art.

[0005] To achieve the above objectives, the technical solution of this application is implemented as follows:

[0006] In a first aspect, embodiments of this application provide a cognitive impairment risk assessment device, the device comprising:

[0007] The display module is used to randomly display a first type of image, a second type of image, and a third type of image from a preset image set; the first type of image is an image that is displayed to the target object for the second time, the second type of image is related to the first type of image, and the third type of image is not related to the first type of image;

[0008] The acquisition module is used to acquire the contextual memory ability, pattern separation ability, anti-interference ability, and reaction time of the target object; the contextual memory ability, the pattern separation ability, and the anti-interference ability are respectively the ability of the target object to recognize the first type of image, the second type of image, and the third type of image, and the reaction time is the time taken for the recognition process;

[0009] The assessment module is used to determine and output the risk level of cognitive impairment of the target object based on the target object's contextual memory ability, pattern separation ability, anti-interference ability and reaction time.

[0010] In an optional implementation, the display module is further configured to:

[0011] In response to a user-triggered start evaluation operation, multiple images are randomly displayed from a preset image set to enable the target object to form a short-term memory; the multiple images are recorded as first-class images for a second display.

[0012] In an optional implementation, the display module is further configured to:

[0013] Within a preset time period after the first display of the first type of image, the first type of image, the second type of image, and the third type of image are displayed a second time. Between the first display and the second display, interfering content different from the first type of image is displayed.

[0014] In one alternative implementation, the interference content includes at least one of the following:

[0015] A math problem that requires a response from the target object;

[0016] A color recognition question that requires a response from the target object.

[0017] In an optional implementation, the display module is further configured to:

[0018] Obtain images of the second category that are at least partially identical to the images of the first category from a preset image set;

[0019] Alternatively, some features of the images in the first category can be modified to create the second category of images.

[0020] In an alternative embodiment, the apparatus further includes:

[0021] The image update module is used to update the feature descriptions of images in a preset image set based on the target object's contextual memory ability, pattern separation ability, anti-interference ability, and reaction time.

[0022] In one optional implementation, the number of the first type of image, the second type of image, and the third type of image are all 4.

[0023] In an optional implementation, the contextual memory capability, the pattern separation capability, and the anti-interference capability are respectively the accuracy of the target object in recognizing the first type of image, the second type of image, and the third type of image;

[0024] The evaluation module is also used for:

[0025] The scenario memory ability, the pattern separation ability, and the anti-interference ability are accumulated according to preset weights, and then the timeout penalty is subtracted to obtain the total risk score; the timeout penalty is determined based on the reaction time.

[0026] Based on the total risk score, the degree of cognitive impairment risk of the target individual is determined;

[0027] The weight range of the contextual memory ability is 8%-54%, the weight range of the pattern separation ability is 10%-90%, the weight range of the anti-interference ability is 4%-36%, and the sum of the weights of the contextual memory ability, the pattern separation ability, and the anti-interference ability is 1.

[0028] In an optional implementation, the evaluation module is further configured to:

[0029] Obtain and output the trend of the risk level of the target object at different times.

[0030] In an alternative embodiment, the apparatus further includes:

[0031] The encoding module is used to process and encode the input images based on the graph neural network (GNN) to form a preset image set.

[0032] In one alternative implementation, the encoded content includes: name, shape, color, and rotation angle.

[0033] In one alternative implementation, the input image is a typical, straightforward, everyday image.

[0034] Secondly, embodiments of this application provide a computing device, the computing device comprising: a storage component, a communication bus, and a processing component, wherein:

[0035] The storage component is used to store the operating program of the cognitive impairment risk assessment device;

[0036] The communication bus is used to enable communication between the storage component and the processing component;

[0037] The processing component is used to execute the operating program of the cognitive impairment risk assessment device to realize the operation of each module in any of the cognitive impairment risk assessment devices described above.

[0038] Thirdly, embodiments of this application provide a computer-readable storage medium storing an executable program, which, when executed by a processor, enables the operation of various modules in any of the cognitive impairment risk assessment devices described above.

[0039] The cognitive impairment risk assessment device, equipment, and storage medium provided in this application include: a display module for randomly displaying a first type of image, a second type of image, and a third type of image from a preset image set; the first type of image is an image shown to the target object a second time, the second type of image is related to the first type of image, and the third type of image is unrelated to the first type of image; an acquisition module for acquiring the target object's episodic memory ability, pattern separation ability, anti-interference ability, and reaction time; and an assessment module for determining and outputting the risk level of the target object's cognitive impairment based on the target object's episodic memory ability, pattern separation ability, anti-interference ability, and reaction time. As can be seen, the cognitive impairment risk assessment device, equipment, and storage medium provided in this application, by intuitively displaying multiple types of images, obtains the target object's episodic memory ability, pattern separation ability, anti-interference ability, and reaction time based on the target object's ability to recognize images, and determines and outputs the risk level of the target object's cognitive impairment accordingly. This is achieved through images, without the need for professional personnel, and at a low cost. Therefore, the cognitive impairment risk assessment device, equipment, and storage medium provided in this application can solve the technical problem of high cost.

[0040] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0041] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0042] Figure 1 Schematic diagram of the structure of the cognitive impairment risk assessment device provided in the embodiments of this application Figure 1 ;

[0043] Figure 2 Schematic diagram of the structure of the cognitive impairment risk assessment device provided in the embodiments of this application Figure 2 ;

[0044] Figure 3 A schematic diagram illustrating the principle of image encoding in the cognitive impairment risk assessment device provided in this application embodiment;

[0045] Figure 4 A schematic diagram showing the features of the original image in the cognitive impairment risk assessment device provided in the embodiments of this application;

[0046] Figure 5 This is a schematic diagram of the generation of the second type of image in the cognitive impairment risk assessment device provided in the embodiments of this application. Figure 1 ;

[0047] Figure 6 This is a schematic diagram of the generation of the second type of image in the cognitive impairment risk assessment device provided in the embodiments of this application. Figure 2 ;

[0048] Figure 7 This is a schematic diagram of the generation of the second type of image in the cognitive impairment risk assessment device provided in the embodiments of this application. Figure 3 ;

[0049] Figure 8 A flowchart illustrating the execution process of the cognitive impairment risk assessment device provided in this application embodiment;

[0050] Figure 9 A detailed flowchart illustrating the execution process of the cognitive impairment risk assessment device provided in this application embodiment;

[0051] Figure 10 A schematic diagram of the structure of a computing device provided in an embodiment of this application.

[0052] Explanation of reference numerals in the attached figures:

[0053] 10. Cognitive Impairment Risk Assessment Device; 11. Display Module; 12. Acquisition Module; 13. Assessment Module; 14. Image Update Module; 15. Encoding Module; 50. Computing Device; 51. Storage Component; 52. Communication Bus; 53. Processing Component; 54. Input Device; 55. Output Device; 56. External Communication Interface. Detailed Implementation

[0054] Exemplary embodiments of the present application will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be implemented in various forms and should not be limited to the specific embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present application and to fully convey the scope of the disclosure of the present application to those skilled in the art.

[0055] The following description provides numerous specific details to offer a more thorough understanding of this application. However, it will be apparent to those skilled in the art that this application can be practiced without one or more of these details. In other instances, to avoid confusion with this application, some technical features well-known in the art have not been described; that is, not all features of actual embodiments are described herein, nor are well-known functions and structures described in detail.

[0056] To fully understand this application, detailed steps and structures will be presented in the following description to illustrate the technical solution of this application. Preferred embodiments of this application are described in detail below; however, in addition to these detailed descriptions, this application may have other implementation methods.

[0057] According to the medical consensus on mild cognitive impairment (MCI), commonly used screening scales for cognitive function assessment include: Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Addenbrooke's Cognitive Examination (ACE), Clock Drawing Test (CDT) and Mini-Cog, Alzheimer's Disease Assessment Scale-Cognitive (ADAS-cog), 8-item Informant Interview to Differentiate Aging and Dementia (AD8), Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE), and Quick Dementia Rating System (QDRS). The above screening scale has the following problems: 1) The above screening scale is usually assessed separately according to different cognitive domains. Paper materials need to be prepared in advance, and nurses or family members need to accompany and guide the assessment. Professional assessors are required. The assessment process is time-consuming, inefficient and costly; 2) It has requirements on the education level and cultural level of the subjects. Subjects are easily influenced by the assessors. The assessors' scores are subjective and can easily lead to inaccurate final assessment results. 3) Existing rapid screening systems for cognitive impairment based on graphic memory mostly adopt a multi-module testing system based on memory pictures. For example, the "System and Method for Rapid Screening of Cognitive Impairment" by Xiamen Hejia Brain Intelligence Technology Co., Ltd., patent number CN116473519 A, includes multiple cognitive ability testing modules such as memory function testing module, processing speed testing module, working memory testing module, planning ability testing module, geometric space testing module, and comprehensive assessment module. The functional system is complex and has many implicit requirements for the subjects, such as cultural and educational level, complete logical ability, language expression ability, and complex behavioral control ability. In community screening scenarios with complex subjects, subjects may be misjudged as having cognitive impairment due to loss of behavioral ability due to old age.4) Cognitive scales are widely used in the early detection and early intervention of AD, but they are limited to fixed items. Subjects need to be asked to test their cognitive impairment function multiple times. In cognitive impairment screening systems based on traditional fixed picture question banks, the accuracy of continuous application to the same subject may also be affected.

[0058] In response, the inventors of this application have conducted extensive research and practice, and have proposed the following technical solution. Example 1

[0059] This application provides a cognitive impairment risk assessment device 10, with reference to... Figure 1 The device includes:

[0060] The display module 11 is used to randomly display a first type of image, a second type of image, and a third type of image from a preset image set; the first type of image is an image that is displayed for the second time for the target object, the second type of image is related to the first type of image, and the third type of image is not related to the first type of image;

[0061] The acquisition module 12 is used to acquire the contextual memory ability, pattern separation ability, anti-interference ability, and reaction time of the target object; the contextual memory ability, the pattern separation ability, and the anti-interference ability are respectively the ability of the target object to recognize the first type of image, the second type of image, and the third type of image, and the reaction time is the time taken for the recognition process;

[0062] The assessment module 13 is used to determine and output the risk level of the target object's cognitive impairment based on the target object's contextual memory ability, pattern separation ability, anti-interference ability and reaction time.

[0063] It should be noted that the target audience is the person being tested, such as a patient who may have cognitive impairment. However, it is important to note that the concept of "user" mentioned below is not entirely the same as the target audience. In some examples, the user can be the target audience, while in other examples, the user can be the target audience's relatives, doctors, or related personnel. It needs to be understood in the context of the specific circumstances.

[0064] Understandably, the first type of images are images shown to the target object a second time, and therefore can be used to assess the target object's ability to remember image contexts. The second type of images are related to the first type of images and can be used to assess the target object's ability to distinguish image patterns; the third type of images are unrelated to the first type of images and can be used to assess the target object's ability to resist image interference.

[0065] Specifically, the second type of image is related to the first type of image, and the two types of images can be similar images (i.e. images that are easily confused), so they can be used to evaluate the pattern separation capability of the target object.

[0066] Specifically, the third type of image is unrelated to the first type of image, and the content of the two types of images can be completely different, so it can be used to evaluate the anti-interference ability of the target object.

[0067] For example, reaction time, measured in seconds, can be used to assess a target's ability to respond to a displayed image, such as the speed of information extraction, information processing efficiency, and level of attention.

[0068] Therefore, based on the target subject's contextual memory ability, pattern separation ability, anti-interference ability, and reaction time, it can comprehensively reflect from multiple dimensions and more accurately determine the risk level of the target subject's cognitive impairment, so as to achieve the purpose of rapid screening.

[0069] Specifically, the method of identifying the target object as a first type of image, a second type of image, and a third type of image can be achieved by selecting the "seen" and "never seen" options.

[0070] Understandably, the random display is an alternating display without a prescribed order. The first type of image, the second type of image, and the third type of image all have the opportunity to be displayed first, and the number of images displayed is also different.

[0071] More specifically, the display module 11 can display the first type of image, the second type of image, and the third type of image on the touch screen. The target object can be selected as "seen" or "not seen" by clicking directly on the screen.

[0072] Specifically, the cognitive impairment risk assessment device 10 can be installed on a mobile phone, tablet computer, or personal computer (PC). The display module 11 can display the first type of image, the second type of image, and the third type of image on a screen or monitor.

[0073] The cognitive impairment risk assessment device 10 provided in this application embodiment intuitively displays various types of pictures. Based on the target object's ability to recognize pictures, it obtains the target object's contextual memory ability, pattern separation ability, anti-interference ability, and reaction time, and determines and outputs the risk level of the target object's cognitive impairment. That is, by recognizing pictures by the target object, no professional personnel are required, and the cost is low.

[0074] Furthermore, the cognitive impairment risk assessment device 10 provided in this application embodiment can be installed in a smart terminal such as a mobile phone, eliminating the need to go to a professional location. Through assessment by professional personnel, the impact of professional locations and personnel on the target object can be reduced.

[0075] Furthermore, the cognitive impairment risk assessment device 10 provided in this application embodiment can automatically determine the assessment results by a program, thereby reducing the subjectivity of professionals.

[0076] In some embodiments of this application, the display module 11 is further configured to:

[0077] In response to a user-triggered start evaluation operation, multiple images are randomly displayed from a preset image set to enable the target object to form a short-term memory; the multiple images are recorded as first-class images for a second display.

[0078] Specifically, the user-triggered action to start the assessment can be clicking the "Start" button, which can be a physical button or a virtual button. Alternatively, the user-triggered action to start the assessment can also be uttering the voice command "Start," which is suitable for older users, those with lower levels of education, or those who are unfamiliar with operating smart devices.

[0079] Understandably, short-term memory is a professional term in psychology, especially in cognitive psychology, where it occupies a central position to describe a key memory stage in the human information processing process. It involves working memory mechanisms, responsible for temporarily storing and processing information, and serves as an intermediary link between sensory memory and long-term memory. The retention time of short-term memory is typically between 5 seconds and 1 minute; that is, the short duration of short-term memory is definite and clear to those skilled in the art.

[0080] Images that have already been displayed need to be recorded as Category 1 images for a second display.

[0081] Furthermore, it is also necessary to record the features of the first type of images. These features can be labeled, or encoded as described below, to facilitate the mixing of the second or third type of images when displaying the first type of images.

[0082] In some embodiments of this application, the display module 11 is further configured to:

[0083] Within a preset time period after the first display of the first type of image, the first type of image, the second type of image, and the third type of image are displayed a second time. Between the first display and the second display, interfering content different from the first type of image is displayed.

[0084] The purpose of the above-described application of the display module 11 is to reduce the probability that the target object will develop short-term memory into long-term memory.

[0085] Understandably, the second presentation, occurring within a predetermined timeframe after the first presentation, is intended to assess the target subject's short-term memory. Understandably, presenting distracting content different from the first type of image between the first and second presentations is primarily intended to reduce the target subject's repetition and decrease the accuracy of the short-term memory test. In the psychological context of memory research, repetition refers to the process by which an individual, during the memory process, repeats received information, either aloud or silently, to help retain information in short-term memory or transfer information from short-term memory to long-term memory. Furthermore, it is understandable that a predetermined time interval is required after the first presentation to assess the target subject's short-term memory. Otherwise, if the second presentation immediately follows the first, it would assess not short-term memory, but rather instantaneous memory or instantaneous observation skills.

[0086] Understandably, long-term memory is also a core professional term in psychology (especially in the field of cognitive psychology). The starting point for "long-term" in long-term memory is that the information is retained for more than one minute, which is clear to those skilled in the art.

[0087] Understandably, the second presentation is the random presentation mentioned above.

[0088] In some embodiments of this application, the interference content includes at least one of the following:

[0089] A math problem that requires a response from the target object;

[0090] A color recognition question that requires a response from the target object.

[0091] In this way, the target audience can only answer the question and has no time to consider the reproduction of the first type of image.

[0092] For example, a math problem could be in the form of "3+5=?", and a color recognition problem could be "What color is the object in the picture?" (the object in the picture does not belong to the first, second, or third category of pictures).

[0093] In some embodiments of this application, the display module 11 is further configured to:

[0094] Obtain images of the second category that are at least partially identical to the images of the first category from a preset image set;

[0095] Alternatively, some features of the images in the first category can be modified to create the second category of images.

[0096] They must be at least partially the same, which can include the same item, such as apples; the same shape, such as round; the same color, such as red, etc., without limitation.

[0097] In some embodiments of this application, reference is made to Figure 2 The device further includes:

[0098] Image update module 14 is used to update the feature descriptions of images in a preset image set based on the target object's contextual memory ability, pattern separation ability, anti-interference ability, and reaction time.

[0099] Understandably, the images in the image set have feature descriptions, such as labels or codes. Labels may include names and shapes. Then, based on the target object's contextual memory ability, pattern separation ability, anti-interference ability, and reaction time, the feature descriptions of the images can be added or changed. For example, cases of target object misidentification can be recorded as features, or, if the reason for the target object misidentification can be determined, the reason for the error can also be recorded. In this way, the update of the image feature descriptions is completed.

[0100] Furthermore, if certain images or types of images consistently produce errors during multiple tests of the target object, such as failing to accurately identify it, these errors can be recorded to remove the image from the image set or reduce its display probability. This process can be analyzed based on GNN (Graph Neural Network).

[0101] In some embodiments of this application, the number of the first type of image, the second type of image, and the third type of image is 4.

[0102] There are a total of 12 images, which is a sufficient number of images, with four in each category, increasing the reliability of the risk assessment. However, the number of images is not too large, and the time required is relatively short.

[0103] In some embodiments of this application, the contextual memory capability, the pattern separation capability, and the anti-interference capability are respectively the accuracy of the target object in recognizing the first type of image, the second type of image, and the third type of image;

[0104] The evaluation module 13 is also used for:

[0105] The scenario memory ability, the pattern separation ability, and the anti-interference ability are accumulated according to preset weights, and then the timeout penalty is subtracted to obtain the total risk score; the timeout penalty is determined based on the reaction time.

[0106] Based on the total risk score, the degree of cognitive impairment risk of the target individual is determined;

[0107] The weight range of the contextual memory ability is 8%-54%, the weight range of the pattern separation ability is 10%-90%, the weight range of the anti-interference ability is 4%-36%, and the sum of the weights of the contextual memory ability, the pattern separation ability, and the anti-interference ability is 1.

[0108] In this way, each ability and reaction time is converted into a score to obtain a total risk score. The risk level of the cognitive impairment of the target object is determined by the total risk score, which is relatively more objective and more operable.

[0109] Specifically, the values ​​of the contextual memory ability, the pattern separation ability, and the anti-interference ability are all between 0 and 1. For example, an accuracy rate of 50% is 0.5.

[0110] Specifically, the preset weights can be contextual memory ability (A), pattern separation ability (B), and anti-interference ability (C). For ease of calculation, the percentage sign of the weights is removed, and the sum of A, B, and C is 100, meaning the cumulative weights are 100, making the calculation more convenient.

[0111] The total score can be calculated using expression (1):

[0112] Total score = (Episode memory ability × A) + (Pattern separation ability × B) + (Interference resistance ability × C) - Deduction for reaction time (1)

[0113] Deductions for reaction time can be made by deducting M points for every second exceeding the standard time, up to a maximum deduction of N% of the total score. The standard time can be obtained based on the average test result of normal individuals.

[0114] Specifically, the value range of A can be 8-54, the value range of B can be 10-90, the value range of C can be 4-36, and the sum of A, B, and C is 100. The value range of M can be 0-10, and the value range of N can be 0-10.

[0115] More specifically, the value of A can be 15-45, the value of B can be 25-75, the value of C can be 10-30, and the sum of A, B, and C is 100.

[0116] More specifically, the value of A can be 24-36, the value of B can be 40-60, the value of C can be 16-24, and the sum of A, B, and C is 100.

[0117] In certain specific embodiments, A, B, and C can take values ​​of 30, 50, and 20, respectively. This allows for a more scientific evaluation of the target object.

[0118] The risk level of a target object can be generated based on the total score, as detailed below:

[0119] Total score range: 80-100 points, risk level is low, target subject has normal cognitive function, regular follow-up examination is recommended.

[0120] Total score range: 60-79 points, risk level is medium risk, the target subject may have early cognitive decline, and it is recommended to conduct detailed examinations at the hospital (such as MMSE, MRI).

[0121] Total score range: less than 60 points indicates high risk, and the target individual is highly at risk of Alzheimer's disease, requiring immediate medical attention and intervention.

[0122] In some embodiments of this application, the evaluation module 13 is further configured to:

[0123] Obtain and output the trend of the risk level of the target object at different times.

[0124] This allows for observation of changes in cognitive impairment in the target individuals, facilitating more scientific assessments. The time intervals can be days, weeks, or months; there are no restrictions.

[0125] In some embodiments of this application, reference is made to Figures 3-7 The device further includes:

[0126] The encoding module 15 is used to process and encode the input images based on the graph neural network (GNN) to form a preset image set.

[0127] This involves collecting various images, encoding them using a graph neural network (GNN), and forming a pre-defined image set.

[0128] Specifically, the collected images serve as original or reference images. Based on the original images, various features or elements are modified, such as changing the shape or color, to form new images related to the original images, namely, second-type images or interference images. This allows the display module 11 to quickly display the second-type images and serves to test the pattern separation capability.

[0129] It should be noted that, Figure 3 The image encoding logic in the cognitive level judgment includes three parts: visuospatial, episodic memory, and executive function. It is related to the geometry, color, text, and rotation in the interference image, and does not mean that a certain image represents visuospatial or executive function. Figure 3 It presents the general process of image encoding, rather than the encoding of a specific image.

[0130] In some embodiments of this application, the encoded content includes: name, shape, color, and rotation angle.

[0131] These are some commonly used and easy-to-implement coding elements that serve both as tests for pattern separation capabilities and as a way to simplify the computational load on the processing chip. These can be understood, or they can be other elements such as lighting (brightness, contrast, color temperature, highlights and shadows), color (saturation, hue), and composition (cropping, rotation), etc.

[0132] In this way, by modifying various features or elements based on the original images, more images can be obtained, enriching the content of the image set. This results in the following beneficial effects: First, it reduces the fatigue and boredom experienced by target subjects during testing, which is common in existing technologies and affects their emotions, thus impacting the accuracy of test results; Second, it reduces the tendency for target subjects to easily remember some images after multiple tests, which also affects the accuracy of test results.

[0133] In some embodiments of this application, the input image is a common, straightforward image.

[0134] Everyday, straightforward, and universally applicable images can be understood as images whose content is easily recognizable to the average person, regardless of factors such as low education level or advanced age. Examples include fruits like apples and bananas. This concept is used in psychological testing, and its meaning is understandable to those skilled in the art.

[0135] In this way, the evaluation results can reduce the influence of factors that are not closely related to the evaluation content, such as the target's education level, logical ability, and language expression ability, making the evaluation results more scientific and accurate.

[0136] To better understand the cognitive impairment risk assessment device 10 provided in this application embodiment, the execution process of the cognitive impairment risk assessment device 10 provided in this application embodiment will be described below. Figure 8 A flowchart illustrating the execution process of the cognitive impairment risk assessment device 10 provided in this application embodiment is shown below. Figure 8 As shown, the execution process may include:

[0137] Step 201: Randomly display images of the first, second, and third categories from a preset image set;

[0138] Step 202: Acquire the target object's contextual memory ability, pattern discrimination ability, anti-interference ability, and reaction time;

[0139] Step 203: Determine and output the risk level of cognitive impairment of the target subject based on the subject's episodic memory ability, pattern separation ability, anti-interference ability and reaction time.

[0140] Figure 9 A detailed flowchart illustrating the execution process of the cognitive impairment risk assessment device 10 provided in this application embodiment is shown below. Figure 9 As shown, the execution process may include:

[0141] Step 301: Obtain the original image.

[0142] Step 302: Image encoding.

[0143] Step 303: Create and update the image library.

[0144] Step 304: Display the first type of image. This means displaying the first type of image for the first time.

[0145] Step 305: Present the interference test questions.

[0146] Step 306: Display test images. This involves displaying a mix of images from the first, second, and third categories.

[0147] Step 307: Obtain feedback from the target object. This requires the target object to provide feedback on the image recognition, i.e., to confirm whether they have "seen" or "have not seen" the image.

[0148] Step 308: Obtain cognitive impairment indicator data. This includes data on episodic memory ability, pattern discrimination ability, resistance to interference, and reaction time.

[0149] Step 309: GNN model analysis. After execution, return to step 303.

[0150] Step 310: Obtain the total score for the cognitive impairment assessment. That is, calculate the total score according to expression (1). This is performed after step 308.

[0151] Step 311: Output the risk assessment of cognitive impairment.

[0152] Step 312: Obtain historical changes in assessment values. That is, obtain the trend of changes in the cognitive impairment risk assessment values ​​of the same target subject at different times.

[0153] The modules included in this embodiment can be implemented using a processor in a computer; alternatively, they can be implemented using logic circuits in a computer. The processor can be a general-purpose processor, a digital signal processor (DSP), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a central processing unit (CPU), a microprocessor (MPU), or any other conventional processor. Example 2

[0154] This application provides a computing device 50, with reference to... Figure 10 The computing device 50 includes: a storage unit 51, a communication bus 52, and a processing unit 53, wherein:

[0155] The storage component 51 is used to store the operating program of the cognitive impairment risk assessment device 10;

[0156] The communication bus 52 is used to realize the connection and communication between the storage component 51 and the processing component 53.

[0157] The processing unit 53 is used to execute the operating program of the cognitive impairment risk assessment device 10 to realize the operation of each module in the cognitive impairment risk assessment device 10 described in Embodiment 1. That is, to realize steps 201-203 in Embodiment 1.

[0158] The type or structure of the storage component 51 can be found in the storage medium section below, and will not be repeated here.

[0159] The processing unit 53 can be a general-purpose processor, a digital signal processor (DSP), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor can be a central processing unit (CPU), a microprocessor (MPU), or any other conventional processor.

[0160] In some embodiments, the computing device 50 may further include an input device 54, an output device 55, and an external communication interface 56, which are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0161] In some embodiments, the input device 54 may include, for example, a keyboard, mouse, microphone, etc. The output device 55 may output various information to the outside, including a display, speaker, printer, projector, and communication network and its connected remote output devices, etc. The external communication interface 56 may be wired, such as a standard serial port (RS232), a General-Purpose Interface Bus (GPIB) interface, an Ethernet interface, or a Universal Serial Bus (USB) interface, or it may be wireless, such as wireless network communication technology (WiFi), Bluetooth, etc.

[0162] The descriptions of the above device embodiments are similar to those of the above apparatus embodiments, and have similar beneficial effects. For technical details not disclosed in the embodiments of this application, please refer to the descriptions of the apparatus embodiments in this application for understanding. Example 3

[0163] This application provides a computer-readable storage medium on which an executable program is stored.

[0164] When the executable program is executed by the processor, it implements the operation of each module in the cognitive impairment risk assessment device 10 described in Embodiment 1. That is, it implements steps 201-203 in Embodiment 1.

[0165] Exemplary examples show that a computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A computer-readable storage medium is a tangible device capable of holding and storing instructions for use by an instruction execution device. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), flash memory, compact disc read-only memory (CD-ROM), digital versatile discs (DVDs), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combinations thereof.

[0166] The RAM includes: Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), SyncLink Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).

[0167] The ROM includes: Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), and Electrically Erasable Programmable Read-Only Memory (EEPROM).

[0168] The description of the computer-readable storage medium embodiments above is similar to the description of the device embodiments above, and has similar beneficial effects. For technical details not disclosed in the embodiments of this application, please refer to the description of the device embodiments in this application for understanding.

[0169] It should be noted that the various embodiments provided in this application belong to the same concept; the technical features in the technical solutions described in each embodiment can be arbitrarily combined to form new embodiments without conflict.

[0170] The embodiments of this application may be systems, methods, and / or computer program products. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this application. The computer program product may be written in any combination of one or more programming languages ​​to perform operations of the embodiments of this application. Programming languages ​​include object-oriented programming languages ​​such as Java, C++, etc., and also conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code may be executed entirely on a user's computer, partially on a user's device, as a standalone software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuits, such as programmable logic circuits, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), are personalized by utilizing state information of computer-readable program instructions. These electronic circuits can execute computer-readable program instructions to implement various aspects of this application.

[0171] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0172] Various aspects of this application are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0173] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0174] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0175] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple modules or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or modules can be electrical, mechanical, or other forms.

[0176] The modules described above as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules. They may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected to achieve the purpose of this embodiment according to actual needs.

[0177] In addition, each functional module in the various embodiments of this application can be integrated into one processing module, or each functional module can be a separate module, or two or more functional modules can be integrated into one module; the integrated module can be implemented in hardware or in the form of hardware plus software functional modules.

[0178] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments.

[0179] Alternatively, if the integrated modules described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an electronic device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. Thus, the embodiments of this application are not limited to any specific hardware and software combination.

[0180] In the above description, the terms "first, second, ..." are used only to distinguish similar objects and do not represent a specific order of objects. Understandably, "first, second, third" can be interchanged in a specific order or sequence where permitted.

[0181] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0182] In the embodiments described in this application, unless otherwise stated and limited, the term "connection" should be interpreted broadly. For example, it can be an electrical connection or a connection between two internal components. It can be a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above term according to the specific circumstances.

[0183] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. When used herein, the singular forms “a,” “an,” and “the” are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising” and / or “including,” when used in this specification, identify the presence of said features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups. When used herein, the term “and / or” includes any and all combinations of the associated listed items. It should be understood that “an embodiment” or “some embodiments” as used throughout the specification means that a particular feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, “in an embodiment” or “in some embodiments” appearing throughout the specification do not necessarily refer to the same embodiment. Furthermore, these particular features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the embodiment numbers are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0184] It should be understood that the sequence number of each process does not imply 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 this application.

[0185] It should be understood that the above embodiments are exemplary and are not intended to encompass all possible implementations of the technical solutions contained in this application. Various modifications and changes can be made to the above embodiments without departing from the scope of this application. Similarly, the various technical features of the above embodiments can be arbitrarily combined to form other embodiments of this application that may not be explicitly described. Therefore, the above embodiments merely illustrate several implementations of this application and do not limit the scope of protection of this patent application.

Claims

1. A cognitive impairment risk assessment device, characterized in that, The device includes: The display module is used to randomly display three types of images from a preset image set: a first type of image, a second type of image, and a third type of image. The first type of image is an image that is displayed for the second time to the target object. The second type of image is related to the first type of image, and the third type of image is not related to the first type of image. The random display is an alternating display without a prescribed order to reduce guesswork. The acquisition module is used to acquire the contextual memory ability, pattern separation ability, anti-interference ability, and reaction time of the target object; the contextual memory ability, the pattern separation ability, and the anti-interference ability are respectively the ability of the target object to recognize the first type of image, the second type of image, and the third type of image, and the reaction time is the time taken for the recognition process; the display adopts the serialization principle, and the recognition adopts the no-comparison, binary judgment principle; The assessment module is used to determine and output the risk level of cognitive impairment of the target object based on the target object's episodic memory ability, pattern separation ability, anti-interference ability and reaction time; The display module is also used for: In response to a user-triggered start evaluation operation, multiple images are randomly displayed from a preset image set to enable the target object to form a short-term memory; the multiple images are recorded as first-class images for a second display. Within a preset time after the first display of the first type of image, the first type of image, the second type of image, and the third type of image are displayed a second time. Between the first display and the second display, interfering content different from the first type of image is displayed to reduce short-term memory reinforcement. The device further includes: The encoding module is used to process and encode input images based on graph neural networks (GNNs) to form a preset image set; it can quickly generate a second type of image instead of just selecting from the preset image set; and it can support personalized question banks. The image update module is used to update the feature descriptions of images in a preset image set based on the target object's contextual memory ability, pattern separation ability, anti-interference ability, and reaction time; record situations where the target object is misidentified or the reasons for the error, so as to remove the image from the image set or reduce the probability of displaying the image; or perform error cause attribution analysis and dynamically intervene in the content of the image set.

2. The cognitive impairment risk assessment device according to claim 1, characterized in that, The interference content includes at least one of the following: A math problem that requires a response from the target object; A color recognition question that requires a response from the target object.

3. The cognitive impairment risk assessment device according to claim 1, characterized in that, The display module is also used for: Obtain images of the second category that are at least partially identical to the images of the first category from a preset image set; Alternatively, some features of the images in the first category can be modified to create the second category of images.

4. The cognitive impairment risk assessment device according to claim 1, characterized in that, The number of images in the first category, the second category, and the third category is 4 each.

5. The cognitive impairment risk assessment device according to claim 1, characterized in that, The contextual memory capability, the pattern separation capability, and the anti-interference capability are respectively the accuracy rates of the target object in recognizing the first type of image, the second type of image, and the third type of image; The evaluation module is also used for: The scenario memory ability, the pattern separation ability, and the anti-interference ability are accumulated according to preset weights, and then the timeout penalty is subtracted to obtain the total risk score; the timeout penalty is determined based on the reaction time. Based on the total risk score, the degree of cognitive impairment risk of the target individual is determined; The weight range of the contextual memory ability is 8%-54%, the weight range of the pattern separation ability is 10%-90%, the weight range of the anti-interference ability is 4%-36%, and the sum of the weights of the contextual memory ability, the pattern separation ability, and the anti-interference ability is 1.

6. The cognitive impairment risk assessment device according to claim 5, characterized in that, The evaluation module is also used for: Obtain and output the trend of the risk level of the target object at different times.

7. The cognitive impairment risk assessment device according to claim 1, characterized in that, The encoded content includes: name, shape, color, and rotation angle.

8. The cognitive impairment risk assessment device according to claim 1, characterized in that, The input image is a typical, straightforward, everyday image.

9. A computing device, characterized in that, The computing device includes: a storage component, a communication bus, and a processing component, wherein: The storage component is used to store the operating program of the cognitive impairment risk assessment device; The communication bus is used to enable communication between the storage component and the processing component; The processing unit is used to execute the operating program of the cognitive impairment risk assessment device to realize the operation of each module in the cognitive impairment risk assessment device according to any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores an executable program, which, when executed by a processor, enables the operation of each module in the cognitive impairment risk assessment device according to any one of claims 1-8.

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