Computer implementation methods, devices, and systems

Abstract

A computer implementation method for determining the neurological state of a subject by calculating a score indicating the subject's neurological state. The method includes the steps of (a) performing an encoding stage in which the subject is presented with a number of items to be recalled in a recall stage; (b) performing an intermediate task stage in which a metacognitive judgment score is obtained from the subject and / or a task to be performed is presented to the subject, resulting in an intermediate task score; (c) performing a recall stage in which the subject is asked to recall the number of items presented in the encoding stage, resulting in a recall stage score; and (d) calculating a score indicating the subject's neurological state based on the recall stage score and one or both of the metacognitive judgment score and the intermediate task score.

Description

Technical Field

[0001] Technical Field The present disclosure relates to computer-implemented methods, devices, and systems.

Background Art

[0002] Background The diagnosis of dementia types, particularly Alzheimer's disease (AD), and the monitoring of the mental abilities of subjects before and after diagnosis are an active and multifaceted research field. Alzheimer's disease is a progressive neurological disease in which excessive proteins accumulate in the brain, impairing nerve function and ultimately leading to cell death. This disease is characterized by continuous progression, although the rate of progression varies among individuals. It is important to be able to identify the early stages of Alzheimer's disease, but there are many obstacles that make early diagnosis of Alzheimer's disease difficult. The first is that significant damage to the brain may already have occurred before the disease can be detected by conventional methods (e.g., imaging, regular health checkups, etc.). The second is that typically, neurological evaluations (such as the Mini-Mental State Examination - MMSE, or the Alzheimer's Disease Assessment Scale - Cognitive Subscale - ADAS-Cog, etc.) require a significant amount of time on the part of the subject and may require clinical resources such as nurses or doctors to perform the examination.

[0003] The present disclosure has been achieved in view of the above considerations.

Summary of the Invention

Means for Solving the Problems

[0004] Summary Thus, in a first aspect, embodiments of the present invention provide a computer-implemented method for determining a subject's neurological state by calculating a score indicative of the subject's neurological state, the method comprising: (a) performing an encoding step in which a plurality of items to be remembered at a later stage are presented to the subject; (b) A step of performing an intermediate task stage in which a metacognitive judgment score is obtained from the subject and / or the subject is presented with a task to be performed, and as a result an intermediate task score is obtained, (c) A step in which the subject is asked to recall several items presented in the encoding stage, and a recall stage score is obtained as a result, (d) The step of calculating a score indicating the subject's neurological state based on the recall stage score and either or both of the metacognitive judgment score and the intermediate task score.

[0005] This method allows for accurate and rapid assessment of a subject's neurological condition through a self-monitoring system.

[0006] In some examples, the method involves both obtaining a metacognitive judgment score from the subject and performing an intermediate task stage in which the subject is presented with a task to be performed, resulting in an intermediate task score. In such examples, the calculation of a score indicating the subject's neurological state is based on the recall stage score, the metacognitive judgment score, and the intermediate task score. Obtaining the metacognitive judgment score may be indexed as step (b), performing the intermediate task stage may be indexed as step (c), and subsequent steps may be re-indexed.

[0007] Metacognitive judgment scores can be obtained before, during, or after the coding phase. Metacognitive judgment scores can be obtained before, during, or after the intermediate task phase. Metacognitive judgment scores can be obtained before, during, or after the recall phase.

[0008] The metacognitive judgment score, intermediate task score, and recall stage score may be weighted individually when used to calculate the score. The recall stage score may be weighted more heavily than the intermediate task score and the metacognitive judgment score. The intermediate task score may be weighted less heavily than the metacognitive judgment score. The metacognitive judgment score may have a weight intermediate between the weight of the intermediate task judgment score and the weight of the recall stage score.

[0009] A score indicating a subject's neurological condition is sometimes called a composite score.

[0010] Scores may be compared to a baseline score or score range, and subjects may be classified according to this comparison. For example, a score between a first and second value may indicate that the subject is healthy. A score below the first value may indicate that the subject has or is at risk of developing Alzheimer's disease. For example, a score between 55 and 80 may indicate that the subject is healthy, and a score below that range may indicate that the subject has or is at risk of developing Alzheimer's disease. A score above this range may indicate a problem with the testing process (e.g., the subject needed assistance).

[0011] The score may be calculated based on a formula selected based on the subject's gender.

[0012] The components of the recall stage score may be weighted based on the position and / or location indicating the order of each item to be recalled. For example, the coding stage may be implemented as a grid of items revealed to the user one by one for coding, and the weights assigned to any given correct answer may be weighted based on (i) the position indicating the order of the items in the order of the items revealed; and / or (ii) the position of the items within the grid of items.

[0013] Neurological state can be the cognitive state of the subject.

[0014] The metacognitive judgment score may be an indicator of how well a subject believes they perform during the retrieval phase. The metacognitive judgment score may also be an indicator of how well or poorly a subject believes they perform during the retrieval phase.

[0015] The score can also be calculated based on the subject's age.

[0016] The intermediate task could be a reaction rate test. The coding stage could be implemented as a grid of items revealed sequentially to the user for coding. "Sequentially" could mean that the items are revealed one by one in any order (i.e., not spatial order).

[0017] The computer implementation method may further include converting the calculated score into a different score indicating the subject's neurological state. The computer implementation method may further include a step of calculating a predicted MMSE or ADAS-Cog value from the score. The computer implementation method may further include calculating a predicted score selected from a list including (1) Addenbrooke's ACE-III cognitive function test, (2) Montreal Cognitive Assessment (MOCA), (3) Repetitive Battery for Neuropsychological State Assessment (RBANS), (4) Pre-symptomatic Alzheimer's Disease Cognitive Complex (PACC5), (5) Pre-symptomatic Alzheimer's Disease Prevention Initiative Pre-symptomatic Cognitive Complex (APCC), (6) Cambridge Assessment of Memory and Cognitive Ability (CAMDEX), (7) Alzheimer's Disease (AD) Composite Score (ADCOMS), (8) Neuropsychological Assessment Battery (NTB), and (9) General Practitioner Cognitive Assessment (GPCOG). Therefore, the method may include a step of classifying the subject's neurological condition according to the corresponding cutoff in either the MMSE, ADAS-Cog, or other predictive score.

[0018] The computer implementation method may further include repeating steps (a), (b), and (c) for multiple test cycles. Step (a) in each test cycle may be modified to show the subject only items that were overlooked in step (c) of the preceding cycle. Step (b) in each test cycle may be modified so that only an intermediate task stage is performed for each test cycle after the first test cycle, the first test cycle including both an intermediate task stage and a step to obtain a metacognitive judgment score. If there are no items overlooked from the preceding step (c), step (a) is skipped because there are no items to show. After repeating steps (a), (b), and (c) for multiple test cycles, the method may further include obtaining an additional metacognitive judgment score indicating how the subject believes they performed during the delayed recall stage. The method may then include performing the delayed recall stage after obtaining the additional metacognitive judgment score. The method may further include performing one or more bridging tasks after obtaining the additional metacognitive judgment score and before the delayed recall stage.

[0019] The score is given by formula (1):

number

number

[0020] The method may further include transmitting the calculated score to a remote device, such as a clinician's terminal or a web portal to which the clinician can access the score. The method may include outputting the calculated score on a device, for example, via display means.

[0021] The method may include an initial step of requiring the subject to provide one or more authentication information for registering or identifying themselves.

[0022] The calculated score may sometimes be referred to as the HiPAL score.

[0023] In a second aspect, an embodiment of the present invention provides a device for determining a subject's neurological state by calculating a score indicating the subject's neurological state. The device includes a display, a processor, and a user input component. The device further includes a memory containing machine-executable instructions. When the machine-executable instructions are executed on the processor, the device is caused to (a) execute an encoding stage in which a plurality of items that the subject should recall in the recall stage are displayed via the display, (b) use the display and the user input component to execute an intermediate task stage in which a metacognitive judgment score is obtained from the subject via the user input component and / or a task to be executed is presented to the user, resulting in an intermediate task score, (c) use the display and the user input component to execute a recall stage in which the subject is required to recall the plurality of items presented in the encoding stage, resulting in a recall stage score, (d) calculate a score indicating the subject's neurological state based on the recall stage score and one or both of the metacognitive judgment score and the intermediate task score.

[0024] Such a device method can accurately and quickly determine the subject's neurological state in a self-administered manner.

[0025] In some examples, the method involves both obtaining a metacognitive judgment score from the subject and performing an intermediate task stage in which the subject is presented with a task to perform, resulting in an intermediate task score. In such examples, the calculation of a score indicating the subject's neurological state is based on the recall stage score, the metacognitive judgment score, and the intermediate task score. Obtaining the metacognitive judgment score may be indexed as step (b), performing the intermediate task stage may be indexed as step (c), and subsequent steps may be re-indexed.

[0026] Metacognitive judgment scores can be obtained before, during, or after the coding phase. Metacognitive judgment scores can be obtained before, during, or after the intermediate task phase. Metacognitive judgment scores can be obtained before, during, or after the recall phase.

[0027] When calculating scores indicating a subject's neurological state, the metacognitive judgment score, intermediate task score, and recall stage score may be weighted individually. The recall stage score may be weighted more heavily than the intermediate task score and the metacognitive judgment score. The intermediate task score may be weighted less heavily than the metacognitive judgment score. The metacognitive judgment score may be weighted less heavily than the recall stage score. The metacognitive judgment score may have a weight intermediate between the weight of the intermediate task score and the weight of the recall stage score.

[0028] When calculating the score, the formula may be used by the processor, and the formula may be selected based on the subject's gender.

[0029] The score may be compared by the processor to a baseline score or score range, and the subject may be classified according to this comparison. For example, a score between a first and second value may indicate that the subject is healthy. A score below the first value may indicate that the subject has or is at risk of developing Alzheimer's disease. For example, a score between 55 and 80 may indicate that the subject is healthy, and a score below that range may indicate that the subject has or is at risk of developing Alzheimer's disease. A score above this range may indicate a problem with the testing process (e.g., the subject needed assistance).

[0030] The components of the recall stage score may be weighted based on the position and / or location indicating the order of each item to be recalled. For example, the coding stage may be implemented as a grid of items revealed to the user one by one for coding, and the weights assigned to any given correct answer may be weighted based on (i) the position indicating the order of the items in the order of the items revealed; and / or (ii) the position of the items within the grid of items.

[0031] Neurological state can be the cognitive state of the subject.

[0032] The metacognitive judgment score may be an indicator of how well a subject perceives their abilities during the retrieval phase. The metacognitive judgment score may also be an indicator of how well or poorly a subject performs during the retrieval phase.

[0033] The score can also be calculated based on the age of the subject.

[0034] The intermediate task could be a reaction rate test. The coding stage can be implemented as a grid of items revealed one by one to the user for coding.

[0035] The memory may further include machine-executable instructions, which allow a device (e.g., a processor) to convert the calculated score into a different score indicating the subject's neurological state. For example, the device may be instructed to calculate a predicted MMSE or ADAS-Cog value from the score. The device may be instructed to calculate a predicted score selected from a list including (1) Addenbrooke's Scale of Cognitive Function (ACE-III), (2) Montreal Cognitive Assessment (MOCA), (3) Repetitive Battery for Neuropsychological State Assessment (RBANS), (4) Pre-symptomatic Alzheimer's Disease Cognitive Complex (PACC5), (5) Pre-symptomatic Alzheimer's Disease Prevention Initiative Pre-symptomatic Cognitive Complex (APCC), (6) Cambridge Assessment of Memory and Cognitive Ability (CAMDEX), (7) Alzheimer's Disease (AD) Composite Score (ADCOMS), (8) Neuropsychological Scale Battery (NTB), and (9) General Practitioner's Cognitive Assessment (GPCOG).

[0036] Memory may include further machine-executable instructions that cause the device to repeat steps (a), (b), and (c) for multiple test cycles. Step (a) in each test cycle may be modified to show the subject only items that were overlooked in step (c) of the preceding cycle. Step (b) in each test cycle may be modified so that only the intermediate task stage is performed for each test cycle after the first, the first test cycle including both the intermediate task stage and the step of obtaining a metacognitive judgment score. If there are no items overlooked from the preceding step (c), step (a) is skipped because there are no items to show. Memory may include further machine-executable instructions that, after repeating steps (a), (b), and (c) for multiple test cycles, cause the device to obtain a further metacognitive judgment score indicating how the subject believes they are performing during the delayed recall stage. Memory may include further machine-executable instructions that cause the device to perform the delayed recall stage after obtaining the further metacognitive judgment score. The memory may include further machine-executable instructions that cause the device to perform one or more bridging tasks after obtaining further metacognitive judgment scores but before the delayed recall stage.

[0037] The score is given by formula (1):

number

number

[0038] In a third aspect, an embodiment of the present invention provides a system for determining the neurological state of a subject by calculating a score indicating the subject's neurological state, the system comprising one or more processors, a display, and a user input component, the system further comprising a memory containing machine-executable instructions, the machine-executable instructions, when executed on one or more processors, the system, (a) The subject is instructed to perform an encoding stage in which several items that the subject needs to recall are displayed on a screen at a later stage, (b) Using a display and user input components, an intermediate stage is performed in which the subject is allowed to obtain a metacognitive judgment score via a user input component, and / or a task to be performed is presented to the user, resulting in an intermediate task score being obtained. (c) The recall stage is performed using a display and user input component, in which the subject is asked to recall several items presented in the coding stage, and a recall stage score is obtained as a result. (d) The subject's neurological state is assessed by calculating a score based on the recall stage score and either or both of the metacognitive judgment score and the intermediate task score.

[0039] The processor performing steps (a) through (c) may be a different processor from the processor performing step (d). The two processors may be connected via a local area network or a wide area network.

[0040] The system may include further processors connected to the processor performing steps (a) to (d), and the calculated scores may be transmitted to these further processors.

[0041] The memory may include machine-readable instructions, which, when executed on one or more processors, cause the system to execute a computer implementation method according to the first embodiment, including any one of the optional features described with reference to the first embodiment, or any combination thereof, as long as these features are compatible.

[0042] The present invention includes combinations of the described embodiments and optional features, except that such combinations are explicitly unacceptable or explicitly avoided.

[0043] Further aspects of the present invention provide a computer program comprising code that, when executed on a computer, causes the computer to perform the method of the first aspect; a computer-readable medium for storing the computer program comprising code that, when executed on a computer, causes the computer to perform the method of the first aspect; and a computer system programmed to perform the method of the first aspect. [Brief explanation of the drawing]

[0044] Brief explanation of the drawing [Figure 1] I will show you the method. [Figure 2] This is a schematic diagram of the device. [Figure 3] This is a schematic diagram of the system. [Figure 4] This is a scatter plot of the number of items accurately recalled (y-axis) against age (x-axis). [Figure 5] This is a smoothed histogram of the items that were recalled accurately. [Figure 6] This is a scatter plot of the number of items accurately recalled after a 10-minute delay (y-axis) against age (x-axis). [Figure 7]This is a smoothed histogram of items that were accurately recalled after a 10-minute delay. [Figure 8] This is a scatter plot of composite scores (y-axis) against age (x-axis). [Figure 9] This is a smoothed histogram of the composite score. [Figure 10] This is a smoothed histogram plot of the absolute accuracy of the metacognitive judgment score (also known as the learning task judgment or JOL). [Figure 11] This is a smoothed histogram plot of reaction time. [Figure 12] This is a scatter plot of the composite score (x-axis) and the measured MMSE score (y-axis), with the predicted MMSE score shown by the curve. [Figure 13] The curve shows the predicted ADAS-Cog score, and the scatter plot shows the composite score (x-axis) and the measured ADAS-Cog score. [Figure 14] This is a scatter plot of measured MMSE scores (x axis) and predicted MMSE scores (y axis). [Figure 15] This is an exemplary interface for the display when performing the encoding stage. [Figure 16] This is an exemplary interface for a display used when acquiring metacognitive judgment scores. [Figure 17] This is an exemplary interface for the display when performing an intermediate task. [Figure 18] This is an exemplary display interface for when performing the recall stage. [Figure 19] This is an exemplary interface for a display during various bridging tasks. [Figure 20] This is an exemplary interface for a display during various bridging tasks. [Figure 21] This is an exemplary interface for a display during various bridging tasks. [Figure 22] This is an exemplary interface for a display during various bridging tasks. [Modes for carrying out the invention]

[0045] Detailed explanation Hereinafter, aspects and embodiments of the present invention will be described with reference to the accompanying drawings. Further aspects and embodiments will be apparent to those skilled in the art.

[0046] Figure 1 shows Method 400. In the first step of the Method, namely step S402, the coding stage is performed. Articles are presented or displayed to the subject, and the subject is asked to memorize the articles. In some examples, as will be described in more detail below, articles are presented in a grid, and the subject is asked to memorize the locations of the articles. Articles may be presented one by one in sequence. The coding stage may form part of a paired associative learning test, which involves displaying 12 cards in a 3x4 grid. The cards are “opened” in a random order, revealing articles (e.g., basketballs). After an article is displayed for a short time, it is hidden, and the next object is revealed. Articles are revealed one by one until all 12 articles have been revealed. The subject is instructed to endeavor to memorize each article and its location in the grid. In this specification, article and object may be considered synonymous.

[0047] Next, in step S404, the subject is asked to provide a metacognitive judgment score. For example, the subject may be asked to indicate the number of items whose exact location they remember. This is followed by step S406, in which the user is presented with a task to perform, and an intermediate task stage is performed, resulting in an intermediate task score. Steps S404 and S406 can be considered together as a distraction task to ensure that the subject does not proceed directly from the encoding stage to the retrieval stage. In one example, the intermediate task stage is a reaction task in which the subject is asked to tap an element (e.g., a dot) that appears in a random location on the screen as quickly as possible. As a result of the intermediate task, an intermediate task score is obtained.

[0048] Next, the method proceeds to step S408, in which the recall stage is performed. The subject is asked to recall the items shown to them in S402, and the result is the recall stage score. For example, if the items are shown in a grid, the subject is asked to indicate where the given items are located in the grid. In some examples, the recall stage result is an indicator of how many items were recalled correctly. Next, the method proceeds to step S410, in which a score is calculated based on the metacognitive judgment score, the intermediate task score, and the recall stage score.

[0049] When calculating scores, it is important to consider the order and location of the presented items. The scoring of items may need to be weighted to take into account one or both of these factors. Firstly, the order in which stimuli are presented can have a significant effect on which items subjects can recall. The serial position effect shows that information presented at the beginning (initial) and end (recency) of a task may be easier to recall than information presented in the middle (Troyer, 2011). Therefore, weighting objects according to their presentation order ensures that the method explains this phenomenon. Secondly, the location of items within a grid (when a grid is used) can affect the user's ability to recall. For example, a stimulus presented adjacent to a corner requires more cognitive resources than a stimulus appearing along a straight edge (Cole, Skarratt, & Gellatly, 2007). Therefore, it is useful to weight object stimuli not only according to their presentation order (location indicating order) but also according to their location at the time of presentation (place of presentation).

[0050] In one example, the weights of the presentation order were as follows:

[0051] [Table 1]

[0052] The weights for the presentation order were based on the odds ratio between the healthy control group and the group of subjects diagnosed with Alzheimer's disease. These were normalized so that the sum equaled 12 (the number of items).

[0053] Regarding the location of the items, a weight of 0.6 was used for items at corners and a weight of 1.2 for items not at corners. In this way, corners, which are easy to remember, are given a lighter weight than non-corner areas. In this case as well, the total weight was set to be equal to 12 (the number of items).

[0054] In addition to weighted recall scores, metacognitive judgment scores (also known as learning task scores or value judgments) were taken into consideration. As will be described in more detail below, subjects diagnosed with AD were more accurate in predicting the number of items they would remember the exact location of. Healthy subjects were found to underestimate their ability to remember by an average of three items. The metacognitive judgment score can then be used together with the number of items recalled as an additional part of the overall output score. Furthermore, since subjects diagnosed with AD were found to have slower reaction times compared to healthy subjects, this intermediate task score is also taken into consideration when calculating the overall output score.

[0055] All three subscores (metacognitive judgment score, intermediate task score, and recall stage score) are determined by the subject's age and sex. Therefore, age and sex adjustments were introduced for each subject by normalizing each subscore to a baseline age and sex. Next, weights were assigned to each component of the overall score, considering that the recall task is the most accurate of the three and therefore should contribute more to the overall output score when dividing the subjects into two groups.

[0056] In some examples, the scores are normalized so that the overall output score is a number between 0 and 100. This conveniently provides a scale with clearly defined start and end points.

[0057] The resulting score is calculated based on one of the following formulas:

number

[0058] In some examples, the result of the expression is rounded. The result is set to 0 if it is less than zero, and to 100 if the selected expression yields a value greater than 100.

[0059] As will be described in more detail below, there is a strong correlation between the score calculated using the above formula and the Mini-Mental State Examination (MMSE) and the Alzheimer's Disease Assessment Scale - Cognitive Subscales (ADAS-Cog). As a result, the overall score calculated using the above formula can be used to predict a subject's MMSE and ADAS-Cog scores. Advantageously, this allows the calculated score to be converted to other known scales, thus facilitating the interpretation of the calculated score. In both cases, the relationship was found to be better explained by using nonlinear functions. A logarithmic function was used to predict the MMSE score, and an exponential function was used to predict the ADAS-Cog score. Predicted MMSE and ADAS-Cog scores can be calculated using the following formulas: Predicted MMSE score = 30 + 4.632(ln[score] - ln

[0100] ) Predicted ADAScog score = 24.3·e -0.016·[スコア] Here, the score is the score calculated using either formula (1) or (2) above.

[0060] In some examples, steps S402, S406, and 408 are repeated for multiple test cycles (e.g., a total of six cycles), and only the scores from the first test cycle are used to calculate the scores described above. The steps can be modified so that only items that were not accurately recalled are shown in the subsequent coding stage (this can be called a selective recall test). After these further test cycles, subjects are given different distraction tasks over a period of time (e.g., 10 minutes) before the final delayed recall of items. In investigating how classification changes for the total number recalled after five selective recall stages and a 10-minute delay, 190 datasets (95 individuals diagnosed with AD and 95 healthy control subjects) were randomly selected to train a linear classifier, and the remaining 96 datasets (43 individuals diagnosed with AD and 53 healthy control subjects) were used to validate classification performance. This procedure was repeated 100 times to obtain the median classification performance. The median accuracy based on the delayed recall task was 74%, and the median area under the ROC curve for AD subjects was 0.76. This is equivalent to the results of a single test cycle and indicates that long-term assessment is not necessary to gain insights into the cognitive state of subjects.

[0061] Figure 2 is a schematic diagram of device 200. The device includes a processor 202, memory 204, long-term storage 206, a display 208, a user input component 210, and (optionally) a network interface 212. Memory 204 contains machine-readable instructions, which, when executed on the processor 202, cause the processor 202 to execute in the manner described above. In some examples, device 200 is a tablet or smartphone, and therefore the display 208 and user input component 210 may be combined as a touchscreen display. The network interface 212 may be a wired or wireless connection and may enable connection to a local area network or a wide area network. Long-term storage may also contain machine-executable instructions or copies thereof, but may also contain scores calculated using the formula described above.

[0062] Figure 3 is a schematic diagram of the system. The system includes a device 200 of the type referenced in Figure 2, which is connected to a further device 302 via a network 300. In some examples, device 200 is used to perform steps S402 to S408. After device 200 has collected the subscores, it transmits the subscores to the further device 302 via the network (which may be a local area network or a wide area network). This further device can then calculate the score, optionally return the score to device 200 via the network, and / or store the result.

[0063] Figure 4 is a scatter plot of the number of items accurately recalled (y-axis) against age (x-axis). Data was collected from 286 subjects. Figure 5 is a smoothed histogram of the items accurately recalled.

[0064] The recall stage score data was randomly split into a training subset and a validation subset. 190 datasets were used to train a linear classification algorithm (95 individuals corresponding to those diagnosed with AD and 95 healthy control subjects), while the remaining 96 datasets (43 individuals diagnosed with AD and 53 healthy control subjects) were used to test classification ability with untrained data. This process was repeated 100 times to investigate how well the classification functioned on average. Based on this procedure, the median accuracy achieved for the number of items accurately recalled was 74%. The median area under the ROC curve for AD subjects was 0.77.

[0065] Figure 6 is a scatter plot of the number of items accurately recalled after a 10-minute delay (y-axis) against age (x-axis). Figure 7 is a smoothed histogram of the items accurately recalled after a 10-minute delay.

[0066] Figure 8 is a scatter plot of composite scores (y-axis) against age (x-axis). Figure 9 is a smoothed histogram of composite scores. Figure 10 is a smoothed histogram plot of absolute precision for metacognitive judgment scores (also known as learning task judgments, i.e., JOL). Figure 11 is a smoothed histogram plot of reaction time.

[0067] For the composite score, the same procedure described above was repeated for Figures 4 and 5. That is, subjects were randomly selected to be included in the training dataset, and the precision and area under the ROC curve were calculated for the remaining subjects. This was repeated 100 times, and the median precision was 75.5%, while the median area under the ROC curve for AD subjects was 0.82.

[0068] Figure 12 is a scatter plot of the composite score (x-axis) and measured MMSE score (y-axis), with the predicted MMSE score shown by a curve. Figure 13 is a scatter plot of the composite score (x-axis) and measured ADAS-Cog score, with the predicted ADAS-Cog score shown by a curve. Figure 14 is a scatter plot of the measured MMSE score (x-axis) and predicted MMSE score (y-axis).

[0069] In the 286-element dataset, only 25.8% of subjects showed a difference of 3 points or more between their predicted MMSE score and their actual MMSE score. For 35.2% of subjects, the difference was less than 1 point on the MMSE scale. Regarding predicted ADAS-Cog scores among the 286 subjects, 30.1% showed a difference of 5 points or more, while 31.6% showed a difference of less than 2 points on the ADAS-Cog scale. Table 2 shows the results of this comparison for MMSE, and Table 3 shows the results of this comparison for ADAS-Cog:

[0070] [Table 2]

[0071] [Table 3]

[0072] For further comparison, a separate dataset was used. This separate dataset consisted of 187 subjects recruited in Kuala Lumpur, Malaysia. Since these were volunteers recruited without any inclusion or exclusion criteria, diagnostic status was not available for these subjects. It was possible to compare the predicted MMSE scores, obtained by calculating predicted MMSE scores using a composite score and then evaluating subjects using the MMSE, with the measured MMSE scores. For 33.7% of subjects, the predicted MMSE score differed from the measured MMSE score by 3 points or more. For 19.8% of subjects, the difference on the MMSE scale was less than 1 point. Table 4 shows the results of this comparison in more detail:

[0073] [Table 4]

[0074] Figure 15 shows an exemplary interface of the display when performing the coding phase. The aforementioned type of device 150 displays a 4x3 grid of cards 154 on its display 152. The items 156 are revealed to the subject one by one during the coding phase. For example, the basketball 156 is presented in the third row of the third column. The order in which the items are revealed and the position of one item relative to the next item to be revealed are randomly selected.

[0075] Figure 16 shows an exemplary interface of the display 152 when device 150 is acquiring a metacognitive judgment score. In this example, the display prompts the user to enter the number of items the user has memorized. In this example, the user input component is a touchscreen, so the subject can slide their finger across the screen to select the number of items they believe they have memorized. The subject presses the submit button when they have selected the correct number.

[0076] Figure 17 shows an exemplary interface of display 152 when performing an intermediate task stage. A green dot 158 ​​appears on display 152 along with a prompt to tap the dot as quickly as possible. This process is repeated until an average response time is calculated, which is recorded as the intermediate task stage score. This process can be repeated for a set duration (e.g., 30 seconds) or until a set number of response times are measured.

[0077] Figure 18 shows an exemplary interface of display 152 when performing the recall phase. Item 182 is presented on a 3x4 grid of cards, and the subject is prompted to indicate the location in the grid where they believe the item appeared during the encoding phase. In this example, the subject points to card 184 by tapping the relevant location on the touchscreen display.

[0078] Figures 19–22 show exemplary display interfaces during various connecting tasks. Figure 19 shows a display during a questionnaire regarding the subject's subjective cognitive abilities. Figure 20 shows a symbol matching exercise where a key or index is presented when showing symbols with corresponding numerical values. A prompt value (e.g., 4) is shown on the display, and the subject is asked to indicate which symbol corresponds to the prompt value according to the key or index. In subsequent or modified versions of this exercise, the exercise is rearranged, and the subject must match the prompted symbol with a numerical value. Figure 21 shows a complex response connecting task, which has three versions with increasing difficulty. Each version is introduced with a short tutorial. The screen layout is the same for all three versions, with a large button in the center of the display labeled "Ready". Eight circles are arranged semicircularly and at equal intervals around the top of this large button. The subject is asked to place their finger on the Ready button and respond to a stimulus using the same finger. As a stimulus, one of the eight circles is highlighted. In the first version, the same location is highlighted, and the participant is asked to tap that location as quickly as possible. The task is repeated until the participant has responded exactly 16 times. In the second version, four different locations are highlighted one at a time. Each time, one of the four locations is randomly selected. Again, the participant is asked to tap the highlighted location as quickly as possible. The task is repeated until the participant has responded exactly 16 times. In the third and most complex version of the task, any of eight locations can be highlighted. However, the participant is asked to tap only if the highlighted location is not one of the so-called "forbidden locations" (see locations highlighted in red in Figure 22). This task continues until a 10-minute timer expires (starting at the beginning of the bridging task and / or after the completion of the encoding phase corresponding to the delayed recall phase).

[0079] The systems and methods of the above embodiments can be implemented in a computer system (particularly in computer hardware or computer software), in addition to the structural components and user interactions described.

[0080] The term "computer system" includes hardware, software, and data storage devices for implementing the system or performing the methods in accordance with the embodiments described above. For example, a computer system may include a central processing unit (CPU), input means, output means, and data storage devices. A computer system may have a monitor for providing a visible output display. Data storage devices may include RAM, disk drives, or other computer-readable media. A computer system may include a plurality of computing devices connected by a network and capable of communicating with each other through that network.

[0081] The method of the above embodiment may be provided as a computer program, or as a computer program product or computer-readable medium carrying a computer program configured to perform the above method when executed on a computer.

[0082] The term “computer-readable media” includes, but is not limited to, any one or more non-temporary media that can be directly read and accessed by a computer or computer system. These media may include, but are not limited to, magnetic storage media such as floppy disks, hard disks, and magnetic tapes; optical storage media such as optical disks or CD-OMs; electrical storage media such as memory, including RAM, ROM, and flash memory; and hybrids and combinations of the above, such as magnetic / optical storage media.

[0083] While this disclosure is described in relation to the exemplary embodiments described above, many equivalent modifications and variations will become apparent to those skilled in the art once this disclosure is given. Therefore, the exemplary embodiments of this disclosure above are intended to aid understanding and are not limiting. Various modifications may be made to the embodiments described without departing from the spirit and scope of this disclosure.

[0084] In particular, although the methods of the embodiments described above have been described as being implemented on the systems of the embodiments described, the methods and systems of this disclosure do not need to be implemented in combination with each other, and can each be implemented on an alternative system or using an alternative method.

[0085] Features disclosed in this Specified Specification, or in the following claims, or in the accompanying drawings, and expressed in a particular form or relating to means for performing the function of the disclosure or methods or processes for obtaining the results of the disclosure, may be used, as necessary, separately or in any combination of such features, to implement the Disclosure in a variety of forms.

[0086] While this disclosure is described in relation to the exemplary embodiments described above, many equivalent modifications and variations will become apparent to those skilled in the art once this disclosure is given. Therefore, the exemplary embodiments of this disclosure above are intended to aid understanding and are not limiting. Various modifications may be made to the embodiments described without departing from the spirit and scope of this disclosure.

[0087] To avoid any doubt, all theoretical explanations provided herein are for the purpose of improving the reader's understanding. The inventors do not wish to be bound by any of these theoretical explanations.

[0088] Any section headings used in this specification are for structural purposes only and should not be interpreted as limiting the subject matter described.

[0089] Throughout this Spec., including the subsequent claims, unless the context requires otherwise, the terms “comprise” and “include,” as well as variations such as “comprises,” “comprising,” and “including,” will be understood to mean that they include the integers or steps or groups of integers or steps described, but not any other integers or steps or groups of integers or steps.

[0090] It should be noted that, as used herein and in the appended claims, the singular forms “a,” “an,” and “the” refer to multiple objects unless the context clearly indicates otherwise. Ranges may be expressed herein as “about” one particular value and / or “about” another particular value. Where such ranges are expressed, another embodiment includes one particular value and / or another particular value. Similarly, the use of the antecedent “about” will be understood to mean that a particular value forms another embodiment when the value is expressed as an approximation. The term “about” with respect to numbers is optional and means, for example, ±10%.

[0091] References Cole, GG, Skarratt, PA, & Gellatly, AR (2007). Object and spatial representations in the corner enhancement effect. Perception & psychophysics, 69(3), 400-412. Troyer, AK (2011). Serial Position E ect. In JS Kreutzer, J. DeLuca, & B. Caplan (Eds.), Encyclopaedia of Clinical Neuropsychology (pp. 2263-2264). New York, NY: Springer New York.

Claims

1. A computer implementation method for determining the neurological state of a subject by calculating a score indicating the subject's neurological state, wherein the method is: (a) A step of performing an encoding stage in which the subject is presented with several items to be recalled during the recall stage, (b) A step of performing an intermediate task stage in which a metacognitive judgment score is obtained from the subject and / or a task to be performed is presented to the subject, and as a result an intermediate task score is obtained, (c) A step of performing a recall stage, in which the subject is asked to recall the multiple items presented in the coding stage, and as a result a recall stage score is obtained, (d) A step of calculating a score indicating the neurological state of the subject based on the recall stage score and one or both of the metacognitive judgment score and the intermediate task score. Computer implementation methods, including those mentioned above.

2. The computer implementation method according to claim 1, wherein the metacognitive judgment score, the intermediate task score, and the recall stage score are individually weighted when used to calculate the scores.

3. The computer implementation method according to claim 1 or claim 2, wherein the score is calculated based on a formula selected based on the gender of the subject.

4. The computer implementation method according to any one of claims 1 to 3, wherein the components of the recall stage score are weighted based on the position and / or location indicating the order of each item to be recalled.

5. The computer implementation method according to any one of claims 1 to 4, wherein the neurological state is the cognitive state of the subject.

6. The computer implementation method according to any one of claims 1 to 5, wherein the metacognitive judgment score is an indicator of how the subject believes they are performing their abilities during the recall stage.

7. The computer implementation method according to any one of claims 1 to 6, wherein the score is further calculated based on the age of the subject.

8. The computer implementation method according to any one of claims 1 to 7, wherein the intermediate task is a reaction rate test.

9. The computer implementation method according to any one of claims 1 to 8, further comprising the step of calculating a predicted MMSE or ADAS-Cog value from the score.

10. The computer implementation method according to any one of claims 1 to 9, further comprising repeating steps (a), (c), and (d) for a plurality of inspection cycles.

11. The computer implementation method according to claim 10, wherein step (a) in each inspection cycle is modified to show only the items that were overlooked in step (d) of the preceding cycle to the subject.

12. The computer implementation method according to claim 10 or 11, further comprising, after repeating steps (a), (c), and (d) for the plurality of test cycles, obtaining a further metacognitive judgment score indicating how the subject believes they are performing their abilities during the delayed recall phase.

13. The computer implementation method according to claim 12, further comprising performing the delayed recall stage after obtaining a further metacognitive judgment score.

14. The computer implementation method according to claim 13, further comprising performing one or more bridging tasks after obtaining the further metacognitive judgment score and before the delayed recall stage.

15. The score is calculated using formula (1): [Math 1] Or formula (2): [Math 2] It is calculated according to one of the following methods: The computer implementation method according to any one of claims 1 to 14, wherein formula (1) is used when the subject is male, and formula (2) is used when the subject is not male, wherein age is the age of the subject, L is the weight of the location where a given item was presented during the coding stage, P is the weight of the order in which a given item was presented during the coding stage, jol is the metacognitive judgment score, and RT is the mean reaction time which is the intermediate task score.

16. A device for determining the neurological state of a subject by calculating a score indicating the subject's neurological state, wherein the device includes a display, a processor, and a user input component, and the device further includes a memory containing machine-executable instructions, the machine-executable instructions, when executed on the processor, are transmitted to the device. (a) Perform an encoding step in which a number of items that the subject should recall in a later stage are displayed via the display, (b) Using the display and the user input component, an intermediate task stage is performed in which a metacognitive judgment score is obtained from the subject via the user input component, and / or a task to be performed is presented to the user, resulting in an intermediate task score being obtained. (c) The subject is asked to recall the items presented in the coding stage, and a recall stage score is obtained as a result of performing the recall stage using the display and the user input component, (d) A device that causes the device to calculate a score indicating the neurological state of the subject based on the recall stage score and one or both of the metacognitive judgment score and the intermediate task score.

17. The device according to claim 16, wherein, in calculating the score indicating the neurological state of the subject, the metacognitive judgment score, the intermediate task score, and the recall stage score are individually weighted.

18. The device according to claim 16 or 17, wherein, in calculating the score, the formula is used by the processor and the formula is selected based on the gender of the subject.

19. The device according to any one of claims 16 to 18, wherein the components of the recall stage score are weighted based on the position and / or location indicating the order of each item to be recalled.

20. The device according to any one of claims 16 to 19, wherein the neurological state is the cognitive state of the subject.

21. The device according to any one of claims 16 to 20, wherein the metacognitive judgment score is an indicator of how the subject believes they are performing their abilities during the recall stage.

22. The device according to any one of claims 16 to 21, further comprising calculating the score based on the age of the subject.

23. The device according to any one of claims 16 to 22, wherein the intermediate task is a reaction rate test.

24. The device according to any one of claims 16 to 23, wherein the memory includes further machine-executable instructions, the further machine-executable instructions causing the device to calculate a predicted MMSE or ADAS-Cog value from the score.

25. The device according to any one of claims 16 to 24, wherein the memory includes further executable instructions, the further executable instructions causing the device to repeat steps (a), (c), and (d) for a plurality of check cycles.

26. The device according to claim 25, wherein step (a) in each inspection cycle is modified to show only the articles that were overlooked in step (d) of the preceding cycle to the subject.

27. The device according to claim 25 or 26, wherein the memory includes further machine-executable instructions, the further machine-executable instructions cause the device to obtain further metacognitive judgment scores about how the subject believes he or she is performing during the delayed recall phase, after repeating steps (a), (c), and (d) for the plurality of cycles.

28. The device according to claim 27, wherein the memory includes further machine-executable instructions, the further execution instructions causing the device to perform the delayed recall stage after obtaining the further metacognitive judgment score.

29. The device according to claim 28, wherein the memory includes further machine-executable instructions, the further execution instructions causing the device to perform a transitional phase in which the subject is required to perform one or more transitional tasks after obtaining the further metacognitive judgment score and before the delayed recall phase.

30. The score is calculated using formula (1): [Math 3] Or formula (2): [Math 4] It is calculated according to one of the following methods: The device according to any one of claims 16 to 29, wherein formula (1) is used when the subject is male, and formula (2) is used when the subject is not male, wherein age is the age of the subject, L is the weight of the location where a given item was presented during the coding stage, P is the weight of the order in which a given item was presented during the coding stage, jol is the metacognitive judgment score, and RT is the mean reaction time which is the intermediate task score.

31. A system for determining the neurological state of a subject by calculating a score indicating the subject's neurological state, wherein the system comprises one or more processors, a display, and a user input component, and further comprises a memory containing machine-executable instructions, wherein when the machine-executable instructions are executed on the one or more processors, the system... (a) The subject is instructed to perform an encoding stage in which several items that the subject needs to recall in a later stage are displayed on the screen, (b) Using the display and the user input component, an intermediate step is performed in which a metacognitive judgment score is obtained from the subject via the user input component, and / or a task to be performed is presented to the user, resulting in an intermediate task score being obtained. (c) The subject is asked to recall the items presented in the coding stage, and a recall stage score is obtained as a result of performing the recall stage using the display and the user input component, (d) Calculate the score indicating the neurological state of the subject based on the recall stage score and one or both of the metacognitive judgment score and the intermediate task score. system.

32. The system according to claim 31, wherein the processor that performs steps (a) to (c) is a different processor from the processor that performs step (d).

33. The system according to claim 31 or 32, wherein the memory includes machine-readable instructions, and when the machine-readable instructions are executed on one or more processors, the system causes the system to execute the computer implementation method according to any one of claims 1 to 16.

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