A recommendation system and method for an intervention plan for patients with cognitive impairment

Abstract

The present invention relates to a system and method for recommending intervention plans for patients with cognitive impairment. The system includes at least a client and a server. The server selects an intervention plan for the user from a knowledge base based on the user's cognitive impairment and sends it to the client. The server analyzes the confidence level of the user and the user's caregiver in completing the execution process of the corresponding intervention plan based on the completion status of the corresponding intervention plan. Based on the confidence level of the execution process of the corresponding intervention plan, at least one of the effect score of the intervention plan and the effect score of the non-drug intervention item is selectively adjusted according to the intervention utility score of the corresponding intervention plan for the corresponding user. When a certain intervention plan has a poor intervention utility score for the user, the intervention plan is adjusted to find a suitable intervention plan for the user. The confidence level is obtained by multiplying a first sub-confidence level by a first coefficient and a second sub-confidence level by a second coefficient, and then adding them together.

Description

[0001] This invention is a divisional application of the invention patent with application number 201910326040.8, application date April 22, 2019, and invention name "System and method for evaluating intervention effects on patients with cognitive impairment." Technical Field

[0002] The present invention relates to the technical field of cognitive impairment, and in particular to a system and method for recommending intervention plans for patients with cognitive impairment. Background Art

[0003] The elderly have irreversibly become the majority of the global population, marking the advent of an aging era in human society. In this new era of an aging society, driven by the rapid development of science and technology and the rise of smart devices and electronic technology, the interaction between the shifting age structure of my country's aging population and changes in disease incidence and mortality has led to a qualitative shift in the health transition of the population, posing new challenges for health interventions for the elderly. At the same time, chronic diseases have become the leading cause of death among Chinese residents. With improvements in living standards and medical and health technology, the spectrum of diseases and mortality among Chinese residents has shifted from being dominated by infectious diseases to being dominated by chronic non-communicable diseases, such as cognitive impairment, cardiovascular and cerebrovascular diseases, cancer, and diabetes. Chronic diseases are often lifelong, causing pain and disability for patients, impacting their health and quality of life. Beyond medication, self-health management is crucial for their treatment and prevention. Relying solely on caregivers and medical technology for chronic disease management has its limitations, particularly for the elderly. Technological innovation offers new avenues for health interventions for chronic disease patients in this new aging era.

[0004] Furthermore, evidence-based research, which emerged in medical research in the early 1990s, has evolved to a stage where it recognizes the limitations of evidence and emphasizes the need to combine rigorous evaluation of evidence with patient values and preferences in joint treatment decisions. Evidence-based research has been introduced into domestic social work in recent years, aiming to ground social work practice on a solid scientific foundation, develop a more robust and reliable evidence base, and further guide professional practice. Applying evidence-based research methods to social work interventions for the health of older adults can provide systematic and effective evidence for the effectiveness and costs of social work interventions and enrich and support the theoretical development of evidence-based research.

[0005] Because the number and capabilities of medical staff are limited, the expenses required for long-term care by professional medical staff for patients with cognitive impairment are difficult for ordinary families to afford. Furthermore, due to the limited capabilities of medical staff, the number of patients they can see is also limited, their accumulated experience is also limited, and their judgment of intervention plans and methods is also limited. It is difficult for a single medical staff or medical staff in a single hospital to come up with a relatively universal intervention plan for a certain group of people based on their limited intervention experience with a limited number of patients with cognitive impairment. Therefore, it is necessary to improve the existing technology to be able to effectively evaluate the intervention effects of various intervention methods for patients with cognitive impairment, so that different patients with cognitive impairment can find appropriate intervention methods from a variety of intervention methods.

[0006] In addition, on the one hand, there are differences in understanding among those skilled in the art; on the other hand, the applicant studied a large number of documents and patents when making the present invention, but due to space limitations, not all details and contents are listed in detail. However, this does not mean that the present invention does not have the characteristics of these prior arts. On the contrary, the present invention already has all the characteristics of the prior art, and the applicant reserves the right to add relevant prior art to the background technology. Summary of the Invention

[0007] In response to the deficiencies of the prior art, the present invention provides a system and method for evaluating the intervention effect of patients with cognitive impairment. The present invention selects a matching intervention plan for a user based on the user's cognitive impairment condition, and then tests the intervention utility score after the intervention plan is completed. The server selectively uses this as a basis for adjusting at least one of the effectiveness score of the intervention plan and the effectiveness score of the non-drug intervention project. The server can obtain the intervention utility score of the intervention plan for different sample individuals from a large number of clients, so that the present invention can continuously accumulate data over time and adjust the effectiveness score of the intervention plan and the effectiveness score of the non-drug intervention project accordingly, so that the present invention can continuously improve and explore the effects of various intervention means, so that the present invention can effectively evaluate the effects of various non-drug intervention means that could not be effectively verified before, so as to provide better non-drug intervention plans and / or non-drug intervention projects for patients with cognitive impairment.

[0008] According to a preferred embodiment, a system for evaluating the intervention effect of patients with cognitive impairment, in particular, relates to a system for evaluating the intervention effect of cognitive impairment intervention measures, comprising: a client and a server, the server's knowledge base comprising a number of non-drug intervention items and a number of intervention plans, each intervention plan adopting at least one non-drug intervention item; the server selects an intervention plan for the user from the knowledge base based on the user's cognitive impairment and sends it to the client; the server repeatedly executes the non-drug intervention items in the intervention plan from the server on at least one of the user and the user's caregiver until the intervention plan is completed, and obtains an intervention utility score of the intervention plan on the role of delaying the user's cognitive impairment from developing in a more serious direction based at least on the user's current test feedback information and historical test feedback information; the server selectively adjusts at least one of the intervention plan's effectiveness score and the non-drug intervention project's effectiveness score based on the intervention utility score of the corresponding intervention plan for the corresponding user.

[0009] According to a preferred embodiment, the client instructs the user and at least one of the user's caregivers to repeatedly perform the non-drug intervention items in the intervention plan from the server according to the intervention plan until the intervention plan is completed; after at least one of the user and the user's caregiver completes the intervention plan according to the client's instructions, the client instructs the user to complete the cognitive test items and sends the user's feedback on the cognitive test items as cognitive test feedback information to the server; the server evaluates the user's cognitive impairment according to the cognitive test feedback information from the client in response to its operation of receiving the cognitive test feedback information from the client.

[0010] According to a preferred embodiment, the cognitive impairment condition includes optional interference factors, a cognitive impairment degree score and an intervention utility score, wherein the optional interference factors include at least one of gender, age and education level, and each optional interference factor is selectively enabled by the client according to the user's activation request. After the corresponding optional interference factor is enabled, the sample individuals that do not meet the corresponding optional interference factor will be selectively shielded by the server when the server selects an intervention plan for the client so that the shielded sample individuals are not used as the basis for the effectiveness score of the corresponding intervention plan and / or the effectiveness score of the non-drug intervention project. The cognitive impairment degree score is a score reflecting the severity of the user's cognitive impairment based on the user's test feedback information combined with the preset scoring mechanism of the cognitive test project. The higher the intervention utility score, the greater the effect of the intervention plan in delaying the development of the user's cognitive impairment in a more serious direction.

[0011] According to a preferred embodiment, the system includes: at least one of a first client and a second client, the first client is a client of a first type of user, and the second client is a client of a second type of user, wherein when a user selects on his client that the intervention plan he needs is an intervention plan that includes at least two non-drug intervention items, the user is marked as a first type of user by the server; when a user selects on his client that the intervention plan he needs is an intervention plan that only includes one non-drug intervention item, the user is marked as a second type of user by the server; the server adjusts only the effect score of the corresponding intervention plan based on the intervention utility score of the corresponding intervention plan for the first type of user; the server adjusts the effect score of the corresponding intervention plan and the effect score of the corresponding non-drug intervention item at the same time based on the intervention utility score of the corresponding intervention plan for the second type of user; when the effect scores of different intervention plans are the same, the server performs secondary sorting of the different intervention plans based on the sum of the effect scores of the non-drug intervention items in the intervention plan, so that among the different intervention plans with the same effect score, the one with a larger sum of the effect scores of all non-drug intervention items in the intervention plan has a higher effect score ranking.

[0012] According to a preferred embodiment, the client collects body movements of at least one of the user and the user's caregiver to identify the completion status of the corresponding intervention plan by at least one of the user and the user's caregiver. The server analyzes the confidence level of the user and the user's caregiver in completing the execution process of the corresponding intervention plan based on the completion status of the corresponding intervention plan. The server selectively adjusts at least one of the effect score of the intervention plan and the effect score of the non-drug intervention item based on the confidence level of the execution process of the corresponding intervention plan according to the intervention utility score of the corresponding intervention plan for the corresponding user. When the confidence level of the completion of the execution process of the corresponding intervention plan is lower than a preset confidence threshold, The server does not use the corresponding user's information, the adopted intervention plan and the intervention utility score after adopting the intervention plan as the server's sample individual, so that the server does not adjust at least one of the intervention plan's effect score and the non-drug intervention project's effect score based on the intervention plan's intervention utility score for the corresponding user. When the confidence level of the completion of the execution process of the corresponding intervention plan is greater than or equal to a preset confidence threshold, the server uses the corresponding user's information, the adopted intervention plan and the intervention utility score after adopting the intervention plan as the server's sample individual, so that the server adjusts at least one of the intervention plan's effect score and the non-drug intervention project's effect score based on the intervention plan's intervention utility score for the corresponding user.

[0013] According to a preferred embodiment, in the process in which the client instructs at least one of the user and the user's caregiver to repeatedly perform non-drug intervention items in the intervention plan from the server according to the intervention plan, the client collects body movements of at least one of the user and the user's caregiver based on the image acquisition element and the wearable sensor to identify the completion status of at least one of the user and the user's caregiver in completing the corresponding intervention plan.

[0014] According to a preferred embodiment, the client downloads an instruction video and sensor verification data corresponding to a corresponding non-drug intervention item from a server. The client plays the instruction video to instruct the user and at least one of the user's caregivers to repeatedly perform the non-drug intervention item in the intervention plan from the server. The sensor verification data is motion data including body movements of the demonstrator measured by a wearable sensor worn by the demonstrator in the instruction video during the performance of the non-drug intervention item. The client collects image information including body movements of at least one of the user and the user's caregiver according to an image acquisition element and compares it with an image of the instruction video including body movements of the demonstrator to identify a first completion status of at least one of the user and the user's caregiver completing the corresponding intervention plan so as to analyze a first sub-confidence of the process of at least one of the user and the user's caregiver completing the execution of the corresponding intervention plan. The client collects image information including body movements of at least one of the user and the user's caregiver according to the wearable sensor. The motion data containing body movements are compared with the sensor verification data to identify the second completion status of the corresponding intervention plan completed by at least one of the user and the user's caregiver to analyze the second sub-confidence of the execution process of the corresponding intervention plan completed by at least one of the user and the user's caregiver, and then the first sub-confidence is multiplied by the first coefficient and the second sub-confidence is multiplied by the second coefficient and then added to obtain the confidence of the corresponding intervention plan, wherein the sum of the first coefficient and the second coefficient is equal to 1. Preferably, the client dynamically adjusts the first coefficient and the second coefficient by comparing the angle deviation, distance deviation and clarity of the shooting angle of the image information captured by the image acquisition element with the standard angle, wherein the greater the angle deviation, distance deviation and / or the lower the clarity of the image information when the client compares the shooting angle of the image information captured by the image acquisition element with the standard angle, the greater the distance deviation and / or the lower the clarity of the image information, the greater the amplitude of the downward adjustment of the first coefficient, and the size of the second coefficient is adjusted accordingly after the first coefficient is adjusted.

[0015] According to a preferred embodiment, the server regularly generates a recommendation report containing at least two preferred intervention plans and at least two preferred non-drug intervention projects suitable for different populations based on the real-time effectiveness scores of the intervention plans and the effectiveness scores of the non-drug intervention projects. Different populations are distinguished by population characteristics, and the population characteristics may include at least one of gender, age and education level. In the process of the server selecting the preferred intervention plans and preferred non-drug intervention projects suitable for the same population, the server selectively blocks sample individuals that do not meet the population characteristics of the population so that the blocked sample individuals are not used as the basis for scoring the effectiveness scores of the intervention plans and / or the effectiveness scores of the non-drug intervention projects.

[0016] According to a preferred embodiment, the server requests manual review in response to the action of generating the corresponding recommendation report, and after the server receives a notification that the corresponding recommendation report has passed the manual review, the server publishes the corresponding recommendation report to at least one social network.

[0017] According to a preferred embodiment, a method for evaluating the intervention effect of patients with cognitive impairment, in particular, relates to a method for evaluating the intervention effect of cognitive impairment intervention means, wherein the method uses a client and a server to assist in completing the evaluation process of the intervention effect of the cognitive impairment intervention means, wherein the knowledge base of the server includes a plurality of non-drug intervention items and a plurality of intervention plans, and each intervention plan adopts at least one non-drug intervention item; the server selects an intervention plan for the user from the knowledge base according to the user's cognitive impairment and sends it to the client; the server repeatedly executes the non-drug intervention items in the intervention plan from the server on at least one of the user and the user's caregiver until the intervention plan is completed, and obtains an intervention utility score of the intervention plan on the role of delaying the development of the user's cognitive impairment in a more serious direction based on at least the user's current test feedback information and historical test feedback information; the server selectively adjusts at least one of the effect score of the intervention plan and the effect score of the non-drug intervention item according to the intervention utility score of the corresponding intervention plan for the corresponding user.

[0018] The present invention also provides a recommendation system for intervention plans for patients with cognitive impairment, which includes at least a client and a server. The system uses the client and the server to assist in completing the evaluation process of the intervention effect of cognitive impairment intervention means, wherein the knowledge base of the server includes a number of non-drug intervention items and a number of intervention plans, and each intervention plan adopts at least one non-drug intervention item; the server selects an intervention plan for the user from the knowledge base according to the user's cognitive impairment and sends it to the client; the server repeatedly executes the non-drug intervention items in the intervention plan from the server on at least one of the user and the user's caregiver until after the intervention plan is completed, at least based on the user's current test feedback information and historical test feedback information, it is concluded that the intervention plan has an effect on delaying the user's cognitive impairment. the server analyzes the confidence of at least one of the user and the user's caregiver in completing the execution process of the corresponding intervention plan based on the completion status of the corresponding intervention plan, and the server selectively adjusts at least one of the effect score of the intervention plan and the effect score of the non-drug intervention item according to the confidence of the execution process of the corresponding intervention plan based on the intervention utility score of the corresponding intervention plan for the corresponding user, and adjusts the intervention plan when the intervention utility score of a certain intervention plan for the user is not good, so as to find a suitable intervention plan for the user, wherein the confidence is obtained by adding the first sub-confidence multiplied by the first coefficient and the second sub-confidence multiplied by the second coefficient, and the sum of the first coefficient and the second coefficient is equal to 1.

[0019] Preferably, the server regularly generates a recommendation report containing at least two intervention plans and at least two non-drug intervention projects that are preferably recommended for different populations based on the real-time effect scores of the intervention plans and the effect scores of the non-drug intervention projects.

[0020] In the process of the server selecting the preferred recommended intervention plan and the preferred recommended non-drug intervention project suitable for the same population, the server will selectively block sample individuals that do not meet the population characteristics of the population, so that the blocked sample individuals are not used as the basis for scoring the effectiveness of the intervention plan and / or the effectiveness of the non-drug intervention project.

[0021] Preferably, the first sub-confidence is obtained in the following manner: the client collects image information containing body movements of at least one of the user and the user's caregiver according to the image acquisition element, and compares it with the image of the instruction video containing the demonstrator's body movements to identify the first completion status of at least one of the user and the user's caregiver completing the corresponding intervention plan, so as to analyze the first sub-confidence of the user and the user's caregiver completing the execution process of the corresponding intervention plan. The second sub-confidence is obtained in the following manner: the client collects action data containing body movements of at least one of the user and the first type of user's caregiver according to the wearable sensor, and compares it with the sensor verification data to identify the second completion status of at least one of the user and the user's caregiver completing the corresponding intervention plan, so as to analyze the second sub-confidence of the user and the user's caregiver completing the execution process of the corresponding intervention plan.

[0022] Preferably, the client includes at least one of a first client and a second client, the first client being a client for a first type of user, and the second client being a client for a second type of user, wherein when a user selects on their client that the intervention plan they need is an intervention plan that includes at least two non-drug intervention items, the user is labeled by the server as a first type of user; when a user selects on their client that the intervention plan they need is an intervention plan that includes only one non-drug intervention item, the user is labeled by the server as a second type of user; according to changes in the intervention plan currently required by the user, the current type of user is interchanged between the first type of user and the second type of user; the server adjusts only the effect score of the corresponding intervention plan based on the intervention utility score of the corresponding intervention plan for the first type of user; the server adjusts both the effect score of the corresponding intervention plan and the effect score of the corresponding non-drug intervention item based on the intervention utility score of the corresponding intervention plan for the second type of user; when the effect scores of different intervention plans are the same, the server performs a secondary sorting of the different intervention plans based on the sum of the effect scores of the non-drug intervention items within the intervention plan, so that among different intervention plans with the same effect score, the intervention plan with a larger sum of the effect scores of all non-drug intervention items is ranked higher in effect score.

[0023] Preferably, before the server publishes the recommendation report on at least one social network, the server verifies whether the total number of sample individuals supporting the recommendation report, the number of sample individuals supporting the preferred recommended intervention plan for each population group, and the number of sample individuals supporting the preferred recommended non-drug intervention projects for each population group reach the corresponding preset number thresholds; the server will only publish the recommendation report on at least one social network when the total number of sample individuals supporting the recommendation report, the number of sample individuals supporting the preferred recommended intervention plan for each population group, and the number of sample individuals supporting the preferred recommended non-drug intervention projects for each population group all reach the corresponding preset number thresholds.

[0024] Preferably, when one of the total number of sample individuals supporting the recommendation report, the number of sample individuals supporting the preferred recommended intervention plan for each population, and the number of sample individuals supporting the preferred recommended non-drug intervention items for each population does not reach the corresponding preset number threshold, the server only retains the recommendation report locally for authorized access users to query.

[0025] Preferably, when the confidence level of the execution process of the corresponding intervention plan is lower than a preset confidence threshold, the server does not use the corresponding user's information, the adopted intervention plan and the intervention utility score after the adoption of the intervention plan as the server's sample individual, so that the server does not adjust at least one of the effect score of the intervention plan and the effect score of the non-drug intervention item based on the intervention utility score of the corresponding user. When the confidence level of the execution process of the corresponding intervention plan is greater than or equal to the preset confidence threshold, the server uses the corresponding user's information, the adopted intervention plan and the intervention utility score after the adoption of the intervention plan as the server's sample individual, so that the server adjusts at least one of the effect score of the intervention plan and the effect score of the non-drug intervention item based on the intervention utility score of the intervention plan for the corresponding user.

[0026] The present invention also provides a method for recommending intervention plans for patients with cognitive impairment, the method comprising at least: using a client and a server to assist in completing an evaluation process of the intervention effect of cognitive impairment intervention measures, wherein the server's knowledge base includes a plurality of non-drug intervention items and a plurality of intervention plans, each intervention plan employing at least one non-drug intervention item; the server selects an intervention plan for the user from the knowledge base based on the user's cognitive impairment condition and sends the plan to the client;

[0027] The server repeatedly performs the non-drug intervention items in the intervention plan from the server on at least one of the user and the user's caregiver until the intervention plan is completed, and obtains an intervention effectiveness score of the intervention plan in delaying the user's cognitive impairment from progressing to a more severe direction, based on at least the user's current test feedback information and historical test feedback information;

[0028] The server analyzes the confidence of at least one of the user and the user's caregiver in completing the execution process of the corresponding intervention plan based on the completion status of the corresponding intervention plan. The server selectively adjusts at least one of the effectiveness scores of the intervention plan and the effectiveness scores of the non-drug intervention items based on the confidence of the execution process of the corresponding intervention plan according to the intervention utility score of the corresponding intervention plan for the corresponding user. When a certain intervention plan has a poor intervention utility score for the user, the intervention plan is adjusted to find a suitable intervention plan for the user, wherein the confidence is obtained by adding the first sub-confidence multiplied by the first coefficient and the second sub-confidence multiplied by the second coefficient, and the sum of the first coefficient and the second coefficient is equal to 1.

[0029] Preferably, the recommendation method also includes: when the confidence level of the execution process of the corresponding intervention plan is lower than a preset confidence threshold, the server does not use the corresponding user's information, the adopted intervention plan and the intervention utility score after the adoption of the intervention plan as the server's sample individual, so that the server does not adjust at least one of the effect score of the intervention plan and the effect score of the non-drug intervention item based on the intervention utility score of the corresponding user; when the confidence level of the execution process of the corresponding intervention plan is greater than or equal to the preset confidence threshold, the server uses the corresponding user's information, the adopted intervention plan and the intervention utility score after the adoption of the intervention plan as the server's sample individual, so that the server adjusts at least one of the effect score of the intervention plan and the effect score of the non-drug intervention item based on the intervention utility score of the intervention plan for the corresponding user.

[0030] Preferably, the recommendation method also includes: the first sub-confidence is obtained in the following manner: the client collects image information containing body movements of at least one of the user and the user's caregiver according to the image acquisition element and compares it with the image of the instruction video containing the demonstrator's body movements to identify the first completion status of at least one of the user and the user's caregiver completing the corresponding intervention plan, so as to analyze the first sub-confidence of the user and the user's caregiver completing the execution process of the corresponding intervention plan; the second sub-confidence is obtained in the following manner: the client collects action data containing body movements of at least one of the user and the first type of user's caregiver according to the wearable sensor and compares it with the sensor verification data to identify the second completion status of at least one of the user and the user's caregiver completing the corresponding intervention plan, so as to analyze the second sub-confidence of the user and the user's caregiver completing the execution process of the corresponding intervention plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 1 is a schematic diagram of module connections of a preferred embodiment of the system of the present invention;

[0032] Figure 2 is a schematic diagram of an interface of a preferred embodiment of a client opening a video chat room with a multi-person video window; and

[0033] Figure 3 This is a simplified schematic diagram of module connection relationships of a system according to a preferred embodiment of the present invention.

[0034] Reference Signs List

[0035] 1: Treatment equipment; 2: Patient self-assessment module; 3: Training treatment module; 4: Caregiver self-assessment module; 5: Intervention module; 6: First user; 7: Second user = 100: Server; 200: Client = 300: Video chat room; 310: Video guidance window; 320: Video interaction window; 330: Rating bar; 340: Rating ball. DETAILED DESCRIPTION

[0036] The following is combined with Figure 1 、 2 First, some of the terms used in the present invention are explained:

[0037] Intervention means may refer to intervention measures or intervention methods. In the present invention, specifically, it may refer to non-drug intervention items and / or intervention plans.

[0038] A user profile refers to user information compiled based on user information or user interactions captured over a period of time. A user profile may include analysis results performed by an analysis module or profile compiler based on previous user information and user interactions. A user profile may include user tendencies (e.g., browsing tendencies), habits, predictions of future user activity, and predictions of user preferences (e.g., favorite colors, shapes, images, content, links, brands). A user profile may further include identification information that uniquely identifies the user, such as the device ID of the user's device (e.g., IP address, MAC address, IMSI, serial number), etc.

[0039] The client 200 may generally refer to at least one of a first client and a second client. The first client may be client 200 for a first type of user. The second client may be client 200 for a second type of user. The client may be an application installed on a smart device or a dedicated smart device with an application installed. For example, the smart device may be at least one of a mobile phone, a tablet computer, a laptop computer, a desktop computer, and a smart projector.

[0040] A user may generally refer to at least one of the first category of users and the second category of users. When a user selects on their client that the intervention plan they need is an intervention plan that includes at least two non-drug intervention items, the user is labeled as a first category user by the server. When a user selects on their client that the intervention plan they need is an intervention plan that only includes one non-drug intervention item, the user is labeled as a second category user by the server. Preferably, the user's current type can also be interchanged between the first category of users and the second category of users based on changes in the intervention plan currently required by the user.

[0041] In the present invention, dementia refers to cognitive disorder, and the expressions of dementia and cognitive disorder can be equivalently replaced with each other. It should be noted that the above-mentioned specific embodiments are exemplary, and those skilled in the art can come up with various solutions inspired by the disclosure of the present invention, and these solutions also belong to the disclosure scope of the present invention and fall within the protection scope of the present invention. Those skilled in the art should understand that the description of the present invention and its drawings are illustrative and do not constitute a limitation on the claims. The scope of protection of the present invention is defined by the claims and their equivalents. The description of the present invention contains multiple inventive concepts, such as "preferably", "according to a preferred embodiment" or "optionally", which means that the corresponding paragraph discloses an independent concept, and the applicant reserves the right to file a divisional application based on each inventive concept.

[0042] Example 1

[0043] This embodiment discloses a method for evaluating the efficacy of intervention for patients with cognitive impairment based on evidence-based practice, or a method for evaluating the intervention effect of an intervention means for cognitive impairment, or a method for evaluating the intervention effect of a patient with cognitive impairment based on evidence-based practice, or a method for evaluating the intervention effect of a patient with cognitive impairment, or a method for evaluating the intervention effect of an intervention plan, or a method for evaluating the intervention effect of an intervention on a patient with cognitive impairment, or a method for evaluating the efficacy of an intervention for a patient with cognitive impairment based on evidence-based practice, or a method for evaluating the efficacy of an intervention for a patient with cognitive impairment. The method can be implemented by the system of the present invention and / or other replaceable components. For example, the method of the present invention is implemented by using the various components in the system of the present invention. Without causing conflict or contradiction, the entire and / or partial contents of the preferred implementation methods of other embodiments can serve as supplements to this embodiment.

[0044] According to a preferred embodiment, the method can use a client and a server to assist in completing the evaluation process of the intervention effect of cognitive impairment intervention measures. The server's knowledge base may include a number of non-drug intervention items and a number of intervention plans. Each intervention plan may adopt at least one non-drug intervention item. The server can select an intervention plan for the user from the knowledge base based on the user's cognitive impairment and send it to the client. Preferably, the server can prioritize intervention plans with relatively high effectiveness scores for the user and send them to the client. After the server has at least one of the user and the user's caregiver repeatedly execute the non-drug intervention items in the intervention plan from the server until the intervention plan is completed, it can determine an intervention utility score of the intervention plan's effect on delaying the progression of the user's cognitive impairment to a more severe state based on at least the user's current test feedback information and historical test feedback information. The server can selectively adjust at least one of the intervention plan's effectiveness score and the non-drug intervention item's effectiveness score based on the intervention utility score of the corresponding intervention plan for the corresponding user. The present invention adopts this method to achieve at least the following beneficial technical effects: First, the present invention divides the intervention means for the user and the user into several non-drug intervention projects and several intervention plans, so that the intervention plan is formulated. Each non-drug intervention project is equivalent to an ingredient in a formula, the effect score of the intervention plan is equivalent to the efficacy score of the intervention plan, and the effect score of the non-drug intervention project is equivalent to the efficacy score of the non-drug intervention project. This enables the present invention to effectively evaluate the effects of various non-drug intervention means whose effects could not be effectively verified before; Second, the present invention selects a matching intervention plan for the user based on the user's cognitive impairment. After the intervention plan is completed, the intervention utility score is tested and selectively used by the server as a basis for adjusting at least one of the effect score of the intervention plan and the effect score of the non-drug intervention project. The server can obtain the intervention utility scores of the intervention plan for different sample individuals from a plurality of clients, so that the present invention can continuously accumulate data over time and adjust the effect score of the intervention plan and the effect score of the non-drug intervention project accordingly, so that the present invention can continuously improve and explore the effects of various intervention means, so as to provide better non-drug intervention plans and / or non-drug intervention projects for patients with cognitive impairment.

[0045] Preferably, the server can add new non-drug intervention items to the knowledge base in response to an add request. This allows for the continuous addition of new non-drug intervention items over time. The server can also delete at least some existing non-drug intervention items from the knowledge base in response to a delete instruction. This allows the operator to remove non-drug intervention items that may impair users' cognitive abilities based on their effectiveness scores and / or user feedback.

[0046] According to a preferred embodiment, the client can instruct at least one of the user and the user's caregiver to repeatedly perform the non-drug intervention items in the intervention plan from the server according to the intervention plan until the intervention plan is completed. After the user and at least one of the user's caregivers complete the intervention plan according to the client's instructions, the client can instruct the user to complete cognitive test items and send the user's feedback on the cognitive test items to the server as cognitive test feedback information. In response to its operation of receiving the cognitive test feedback information from the client, the server can evaluate the user's cognitive impairment based on the cognitive test feedback information from the client. The present invention adopts this method to achieve at least the following beneficial technical effects: First, the present invention instructs the user and at least one of the user's caregivers to complete the intervention plan through the client, rather than through on-site guidance by medical staff, which reduces the labor intensity of medical staff, avoids the inconvenience of having the user and / or caregiver running back and forth, and can reduce the nursing pressure and cost of the entire medical and nursing system; Second, the server responds to its operation of receiving cognitive test feedback information from the client and evaluates the user's cognitive impairment based on the cognitive test feedback information from the client, and the server can select an intervention plan for the user from the knowledge base based on the user's cognitive impairment and send it to the client, so that when a certain intervention plan has a poor intervention utility score for the user, the intervention plan can be adjusted to find a suitable intervention plan for the user.

[0047] According to a preferred embodiment, the cognitive impairment condition may include at least one of an optional interference factor, a cognitive impairment degree score, and an intervention utility score. The optional interference factor may include at least one of gender, age, and education level. Preferably, the optional interference factor may include at least one of gender, age, region, race, ethnicity, and education level. Each optional interference factor can be selectively enabled by the client according to the user's activation request. After the corresponding optional interference factor is enabled, the sample individuals that do not meet the corresponding optional interference factor will be selectively shielded by the server when the server selects an intervention plan for the client so that the shielded sample individuals are not used as the basis for the effectiveness score of the corresponding intervention plan and / or the effectiveness score of the non-drug intervention project. The cognitive impairment degree score can be a score reflecting the severity of the user's cognitive impairment obtained based on the user's test feedback information combined with the preset scoring mechanism of the cognitive test project. The higher the intervention utility score, the greater the effect of the intervention plan in delaying the user's cognitive impairment from developing in a more serious direction. The present invention adopts this method to achieve at least the following beneficial technical effects: first, the server can select appropriate intervention plans for different users based on their cognitive impairment conditions; second, the server can select sample individuals that better meet the user's requirements based on the user's activation request to evaluate the effectiveness score of the intervention plan and / or the effectiveness score of the non-drug intervention project, thereby selecting a more detailed and customized intervention plan for the user that is more in line with the characteristics of the user's population.

[0048] According to a preferred embodiment, the system may include at least one of a first client and a second client. The first client may be a client for a first category of users. The second client may be a client for a second category of users. When a user selects on their client that their desired intervention plan includes at least two non-drug intervention items, the user may be labeled by the server as a first category user. When a user selects on their client that their desired intervention plan includes only one non-drug intervention item, the user may be labeled by the server as a second category user. The server may adjust only the effectiveness score of the intervention plan based on the intervention utility score of the first category user. The server may adjust both the effectiveness score of the intervention plan and the effectiveness score of the non-drug intervention item based on the intervention utility score of the second category user. If different intervention plans have the same effectiveness score, the server may perform a secondary ranking of the different intervention plans based on the sum of the effectiveness scores of the non-drug intervention items within the intervention plan, so that among the different intervention plans with the same effectiveness score, the one with the greater sum of the effectiveness scores of all the non-drug intervention items within the intervention plan is ranked higher in effectiveness score. The present invention adopts this method to achieve at least the following beneficial technical effects: First, since different users have different needs, for example, some users may be afraid that the non-drug intervention items are too many and too troublesome, some users may be afraid that the non-drug intervention items are not effective, and some users may be afraid that the non-drug intervention items will take up too much time, etc. The server can customize the recommendation of an intervention plan that only includes a single non-drug intervention item or an intervention plan that includes at least two non-drug intervention items according to the needs of the user, so as to meet the needs of the user, and also reduce the user's resistance and the accuracy of the intervention utility score being affected by the resistance; second, the server marks users with different needs for the intervention plan into two categories. The intervention plan of one type of user includes two or more non-drug intervention items. The server scores the intervention utility of the first type of user according to the corresponding intervention plan and only adjusts the effect score of the corresponding intervention plan to make the score of the non-drug intervention item more accurate. Since the intervention plan of the second type of user only includes one non-drug intervention item, the server can score the intervention utility of the second type of user according to the corresponding intervention plan and simultaneously adjust the effect score of the corresponding intervention plan and the effect score of the corresponding non-drug intervention item, so that the present invention can more accurately obtain the effect score of the intervention plan and the effect score of the non-drug intervention item, and perform secondary sorting of different intervention plans with the same effect score according to the effect score of the non-drug intervention item.

[0049] According to a preferred embodiment, the client can collect body movements of at least one of the user and the user's caregiver to identify the completion status of the corresponding intervention plan by at least one of the user and the user's caregiver. The server can analyze the confidence level of the execution process of the corresponding intervention plan completed by at least one of the user and the user's caregiver based on the completion status of the corresponding intervention plan. The server can selectively adjust at least one of the effect score of the intervention plan and the effect score of the non-drug intervention project based on the intervention utility score of the corresponding intervention plan for the corresponding user according to the confidence level of the execution process of the corresponding intervention plan. When the confidence level of the execution process of the corresponding intervention plan is lower than a preset confidence threshold, the server may not use the information of the corresponding user, the intervention plan adopted, and the intervention utility score after adopting the intervention plan as the sample individual of the server, so that the server does not adjust at least one of the effect score of the intervention plan and the effect score of the non-drug intervention project based on the intervention utility score of the intervention plan for the corresponding user. When the confidence level of the execution process of the corresponding intervention plan is greater than or equal to a preset confidence threshold, the server can use the corresponding user's information, the intervention plan adopted, and the intervention utility score after adopting the intervention plan as the server's sample individuals, so that the server can adjust at least one of the intervention plan's effect score and the effect score of the non-drug intervention project based on the intervention plan's intervention utility score for the corresponding user. Preferably, after a user and the user's caregiver complete different intervention plans, the server can use the corresponding data after completing the different intervention plans as different sample individuals. The present invention adopts this method to at least achieve the following beneficial technical effects: in the process of instructing at least one of the user and the user's caregiver to complete the corresponding intervention plan, the confidence level of the execution process of the intervention plan is evaluated, so as to select some user information, the intervention plan adopted, and the intervention utility score after adopting the intervention plan as the server's sample individuals based on the confidence level, thereby allowing the server to continuously obtain sample individuals through different clients so that the server can continuously improve intervention plans for different groups.

[0050] According to a preferred embodiment, in the process in which the client instructs at least one of the user and the user's caregiver to repeatedly perform the non-drug intervention items in the intervention plan from the server according to the intervention plan, the client can identify the completion status of the corresponding intervention plan by at least one of the user and the user's caregiver based on the body movements of at least one of the user and the user's caregiver captured by the image acquisition element and the wearable sensor. Preferably, the image acquisition element can be, for example, a camera built into a mobile phone, tablet computer and / or laptop computer, or an external camera. The wearable sensor can be, for example, a sensor in at least one of a smart bracelet, a smart watch, a smart ring, a smart headband, a smart insole and a smart suit. For example, the wearable sensor can be, for example, at least one of a gyroscope, an accelerometer and a magnetometer.

[0051] According to a preferred embodiment, a client can download instructional videos and sensor verification data corresponding to corresponding non-drug intervention items from a server. The client can play the instructional video to instruct at least one of a user and the user's caregiver to repeatedly perform the non-drug intervention items in the intervention plan received from the server. The sensor verification data can be motion data including body movements of the demonstrator in the instructional video, measured by a wearable sensor worn by the demonstrator while performing the non-drug intervention item. The client can use an image capture component to capture image information including body movements of at least one of the user and the user's caregiver, and compare it with images from the instructional video containing the demonstrator's body movements to identify a first completion status of at least one of the user and the user's caregiver completing the corresponding intervention plan, thereby analyzing a first sub-confidence level that the at least one of the user and the user's caregiver has completed the corresponding intervention plan. The client can also use the wearable sensor to capture motion data including body movements of at least one of the user and the first-category user's caregiver, and compare it with the sensor verification data to identify a second completion status of at least one of the user and the user's caregiver completing the corresponding intervention plan, thereby analyzing a second sub-confidence level that the at least one of the user and the user's caregiver has completed the corresponding intervention plan. The server and / or client may multiply the first sub-confidence by a first coefficient and the second sub-confidence by a second coefficient, and then add them together to obtain the confidence of the corresponding intervention plan. The sum of the first coefficient and the second coefficient may be equal to 1.

[0052] Preferably, the client can dynamically adjust the first coefficient and the second coefficient by comparing the angle deviation, distance deviation, and image clarity of the image information captured by the image acquisition component with the standard angle. The greater the angle deviation, distance deviation, and / or image clarity of the image information captured by the image acquisition component, the greater the downward adjustment of the first coefficient. After adjusting the first coefficient, the client can correspondingly adjust the second coefficient. This approach can achieve at least the following beneficial technical effects: First, by confirming the confidence level of the corresponding intervention effectiveness score through both video action recognition and wearable sensors, the present invention can reduce or prevent the misuse of intervention effectiveness scores derived from users or caregivers failing to correctly perform corresponding non-drug interventions, resulting in inconsistencies between the effectiveness scores of the corresponding intervention plans and / or corresponding non-drug interventions and the actual effectiveness, thereby affecting the accuracy of the entire system. Second, because the first sub-confidence level is significantly affected by various factors associated with image acquisition, the first coefficient of the first sub-confidence level is adjusted based on these factors to increase the confidence level and ensure that the data from the sample individuals is more authentic and reliable.

[0053] According to a preferred embodiment, the server can regularly generate a recommendation report containing at least two intervention plans and at least two non-drug intervention projects that are preferably recommended for different populations based on the real-time effect scores of the intervention plans and the effect scores of the non-drug intervention projects. Different populations can be distinguished by population characteristics. The population characteristics may include at least one of gender, age and education level. Preferably, the population characteristics may include at least one of gender, age, region, race, ethnicity and education level. In the process of the server selecting the preferred intervention plans and preferred non-drug intervention projects suitable for the same population, the server can selectively block sample individuals that do not meet the population characteristics of the population so that the blocked sample individuals are not used as the basis for the effect scores of the intervention plans and / or the effect scores of the non-drug intervention projects. Preferably, when the server generates a recommendation report, it can overwrite the real identity information of the sample individuals and export them as a sample individual library corresponding to the recommendation report for query by authorized access users. The present invention adopts this method to achieve at least the following beneficial technical effects: first, the server of the present invention can regularly generate a recommendation report containing at least two preferred intervention plans and at least two preferred non-drug intervention projects suitable for different populations, so that people can see which intervention plan and non-drug intervention project should be better adopted for a certain type of population; second, operators or researchers can compare the data of newly added sample individuals according to the changes in the recommendation report, analyze the deep-seated reasons for the changes, so as to find intervention plans and / or non-drug intervention projects suitable for different populations more quickly.

[0054] According to a preferred embodiment, the server may request manual review in response to the action of generating a corresponding recommendation report. After the server receives the notification that the corresponding recommendation report has passed the manual review, the server may publish the corresponding recommendation report to at least one social network. The present invention can achieve at least the following beneficial technical effects by adopting this method: First, some people may not understand or have no opportunity to adopt the system of the present invention, so that they may have the wrong idea that cognitive impairment can only be left to develop freely. The present invention allows the server to publish recommendation reports on a regular basis, thereby influencing more people and allowing them to correctly understand the non-drug intervention methods for cognitive impairment, so that more patients with cognitive impairment can have their conditions effectively controlled and intervened; second, the recommendation report is published on the social network after manual review, reducing the adverse effects of errors in the recommendation report on numerous patients with cognitive impairment.

[0055] According to a preferred embodiment, before the server publishes the recommendation report to at least one social network, the server may verify whether the total number of sample individuals supporting the recommendation report, the number of sample individuals supporting the preferred recommended intervention plan for each population, and the number of sample individuals supporting the preferred recommended non-drug intervention projects for each population have reached the corresponding preset number thresholds. The server will only publish the recommendation report to at least one social network when the total number of sample individuals supporting the recommendation report, the number of sample individuals supporting the preferred recommended intervention plan for each population, and the number of sample individuals supporting the preferred recommended non-drug intervention projects for each population have all reached the corresponding preset number thresholds. When one of the total number of sample individuals supporting the recommendation report, the number of sample individuals supporting the preferred recommended intervention plan for each population, and the number of sample individuals supporting the preferred recommended non-drug intervention projects for each population has not reached the corresponding preset number threshold, the server may only retain the recommendation report locally for authorized access users to query. The present invention adopts this method to achieve at least the following beneficial technical effects: first, only recommendation reports with sufficient data support are published on social networks, making the published recommendation reports more authoritative; second, unpublished recommendation reports are retained locally for authorized access users to query, allowing operators or researchers to compare the data of newly added sample individuals according to changes in recommendation reports, analyze the deep-seated reasons for the changes, and strive to find intervention plans and / or non-drug intervention projects suitable for different populations more quickly.

[0056] Example 2

[0057] This embodiment may be a further improvement and / or supplement to embodiment 1, and repeated contents will not be repeated. In the absence of conflict or contradiction, the whole and / or part of the preferred implementation manner of other embodiments may serve as a supplement to this embodiment.

[0058] According to a preferred embodiment, see Figure 1 The method can use the client 200 and the server 100 to assist at least one of the user and the user's caregiver to complete a corresponding intervention plan.

[0059] According to a preferred embodiment, the server can evaluate the user's cognitive impairment according to the cognitive test feedback information from the client in response to its operation of receiving the cognitive test feedback information from the client. The server can select an intervention plan containing at least one non-drug intervention project from the knowledge base based on at least the user's cognitive impairment and send it to the client. The client can instruct the user and at least one of the user's caregivers to repeatedly execute the non-drug intervention projects in the intervention plan from the server according to the intervention plan until the intervention plan is completed. After at least one of the user and the user's caregiver completes the intervention plan according to the instructions of the client, the client can instruct the user to complete the cognitive test project and send the user's feedback on the cognitive test project as cognitive test feedback information to the server. Preferably, in the present invention, the instruction can be equivalent to guidance, guidance or instruction. That is, the client instructs, guides or directs the user or the user's caregiver to complete the corresponding project. The present invention adopts this method to achieve at least the following beneficial technical effects: first, the server and the client assume the role of professional medical staff, instructing users and / or caregivers with behavioral abilities to complete the corresponding intervention plan, thereby reducing the labor intensity of medical staff and sharing more pressure on scarce medical resources; second, after completing the intervention plan, the user's cognitive impairment is tested, and then the server may adjust the intervention plan based on the cognitive impairment of the tested user, in order to find an intervention plan for the user that can have a good intervention effect on his or her condition.

[0060] According to a preferred embodiment, the server 100 can evaluate the cognitive impairment of the first category of users based on the cognitive test feedback information from the first client in response to its operation of receiving the cognitive test feedback information from the first client. The server 100 selects an intervention plan containing at least two non-drug intervention items from the knowledge base based on at least the cognitive impairment of the first category of users and sends it to the first client. The first client can instruct the first category of users and at least one of the caregivers of the first category of users to repeatedly perform the non-drug intervention items in the intervention plan from the server 100 according to the intervention plan until the intervention plan is completed. After at least one of the first category of users and the caregivers of the first category of users completes the intervention plan according to the instructions of the first client, the first client can instruct the first category of users to complete the cognitive test items and send the first category of users' feedback on the cognitive test items as cognitive test feedback information to the server 100.

[0061] According to a preferred embodiment, the system may include a second client. The server 100 may evaluate the cognitive impairment of the second category of users based on the cognitive test feedback information from the second client in response to its operation of receiving the cognitive test feedback information from the second client. The server 100 may select an intervention plan that only includes one non-drug intervention project from the knowledge base based on at least the cognitive impairment of the second category of users and send it to the second client. The second client may instruct the second category of users and one of the caregivers of the second category of users to repeatedly execute the non-drug intervention project in the intervention plan from the server 100 according to the intervention plan until the intervention plan is completed. After the second category of users and one of the caregivers of the second category of users complete the intervention plan according to the instructions of the second client, the second client may instruct the second category of users to complete the cognitive test project and send the second category of users' feedback on the cognitive test project as cognitive test feedback information to the server 100.

[0062] According to a preferred embodiment, the intervention plan selected by the server 100 from the knowledge base can be matched to the user's cognitive impairment. The cognitive impairment situation can include at least one of optional interference factors, a cognitive impairment severity score, and an intervention effectiveness score. Preferably, the optional interference factors can include at least one of gender, age, and education level. Each optional interference factor can be selectively enabled by the client based on the user's activation request. After the corresponding optional interference factor is enabled, sample individuals that do not meet the corresponding optional interference factor will be selectively blocked by the server 100 when selecting an intervention plan for the client, so that the blocked sample individuals are not used as a basis for the effectiveness score of the intervention plan and / or the effectiveness score of the non-drug intervention project. Preferably, gender can be male or female. Alternatively, gender can be at least one of male, female, and a third gender. The third gender is transgender, intersex, and / or transsexual individuals. The education level of the sample individuals in the server 100 can be divided and adjusted as needed. For example, the education level of the sample individuals in the server 100 can be divided into a first level and a second level. The first level can represent a sample individual with a high school education or below. The second level may represent that the sample individuals have a high school education or above. For another example, the educational levels of the sample individuals within server 100 can be divided into first, second, and third levels. The first level may represent that the sample individuals have a high school education or below. The second level may represent that the sample individuals have a high school education or above and a bachelor's degree or below. The third level may represent that the sample individuals have a bachelor's degree or above. Alternatively, for another example, the educational levels of the sample individuals within server 100 can be divided into eight levels: none, elementary school, junior high school, technical secondary school / high school, junior college, bachelor's degree, master's degree, and doctoral degree. Age, for example, can be at least one of 20 to 120 years old. Preferably, after the corresponding optional interference factor is activated, server 100 first confirms whether the number of available sample individuals is sufficient. If the number of available sample individuals is insufficient, server 100 rejects the user's activation request. For example, when a user requests to activate the optional interference factors of age 30 and gender being male, there is no or only one sample individual that meets the optional interference factors of age 30 and gender being male in server 100, and the sample individual number threshold preset by server 100 is 100, that is, the number of available sample individuals is considered sufficient only when the number of available sample individuals reaches 100. Therefore, currently server 100 cannot select an intervention plan for the user well, and server 100 can only reject the user's request to activate the optional interference factors of age 30 and gender being male.For another example, when a user requests to enable the optional interference factors of age 50, gender female, and primary school education, there are 1,000 sample individuals in server 100 that meet the optional interference factors of age 50, gender female, and primary school education, and the threshold number of sample individuals preset by server 100 is 200. Therefore, server 100 can currently select an intervention plan for the user better. Server 100 receives the user's request to enable the optional interference factors of age 50, gender female, and primary school education. Assuming that there are 20,000 sample individuals in server 100, after enabling the optional interference factors of age 50, gender female, and primary school education, the remaining 19,000 sample individuals will be selectively blocked by server 100 when server 100 selects an intervention plan for the client, so that the blocked sample individuals are not used as the basis for the effectiveness score of the intervention plan and / or the effectiveness score of the non-drug intervention project. Thus, the server 100 can select an intervention plan that is more suitable for the user among the population to which it is adapted, which may have a better effect on alleviating the rapid deterioration of cognitive impairment.

[0063] Preferably, the cognitive impairment degree score can be a score reflecting the severity of the user's cognitive impairment based on the user's test feedback information combined with the preset scoring mechanism of the cognitive test items. The granularity of the division can be adjusted according to actual needs. For example, the degree of cognitive impairment can be divided into mild cognitive impairment, moderate cognitive impairment and severe cognitive impairment, corresponding to 1, 2 and 3 points in the cognitive impairment degree score respectively. For another example, the degree of cognitive impairment can be divided more finely. The cognitive impairment degree score ranges from 0 to 9 points, with higher scores indicating more severe cognitive impairment. 0 indicates that the cognitive ability of the first category of users is normal. 1 to 3 points can indicate that the first category of users has mild cognitive impairment. 4 to 6 points can indicate that the first category of users has moderate cognitive impairment. 7 to 9 points can indicate that the first category of users has severe cognitive impairment. The intervention effectiveness score can be a score of the effect of the intervention plan on the development of the user's cognitive impairment, obtained by comparing the user's current test feedback information with historical test feedback information.

[0064] Preferably, the intervention effectiveness score can be a score of the intervention program's effectiveness in delaying the progression of the user's cognitive impairment toward a more severe state, derived at least from the user's current test feedback information and historical test feedback information. A higher intervention effectiveness score indicates a greater effectiveness of the intervention program in delaying the progression of the user's cognitive impairment toward a more severe state. For example, the intervention effectiveness score can be the difference between the current cognitive level score derived from the current test feedback information and the historical average cognitive level score derived from the historical test feedback information, divided by the sum of the current cognitive level score derived from the current test feedback information and the historical average cognitive level score derived from the historical test feedback information. For another example, the intervention effectiveness score can be the difference between the current cognitive level score derived from the current test feedback information and the previous cognitive level score derived from the historical test feedback information, divided by the sum of the current cognitive level score derived from the current test feedback information and the previous cognitive level score derived from the historical test feedback information. The "previous" score can refer to the previous time before the current one. Preferably, the server can continuously adjust the intervention program based on the user's intervention effectiveness score until a suitable intervention program is found for the user.

[0065] According to an optional preferred embodiment, the server can continuously adjust the intervention plan based on the intervention utility score of the intervention plan for the user until an intervention plan is found for the user that effectively delays the user's cognitive impairment from developing in a more serious direction. Preferably, the intervention plan that effectively delays the user's cognitive impairment from developing in a more serious direction may mean that the intervention plan can keep the user's cognitive ability stable or gradually decline in a relatively stable manner. Preferably, the intervention plan that effectively delays the user's cognitive impairment from developing in a more serious direction may mean that the intervention plan can keep the user's cognitive ability stable or gradually decline in a relatively stable manner rather than a cliff-like decline. The server 100 can judge the user's cognitive ability by scoring the degree of cognitive impairment. The server continuously adjusts the intervention plan according to the intervention utility score of the user until an intervention plan that effectively delays the user's cognitive impairment from developing in a more serious direction is found for the user. The processing may include: when the server 100 first receives cognitive test feedback information of a first-category user, the server 100 identifies the first-category user as a new user and selects an intervention plan containing at least two non-drug intervention items for the new user according to the cognitive impairment degree score and the preset rules; when the server 100 receives cognitive test feedback information of a first-category user again, the server 100 identifies the first-category user as an old user and performs the first adjustment process of the intervention plan at least according to the cognitive impairment degree score and the intervention utility score, and selects the intervention plan according to the preset rules; The intervention plan that has undergone the adjustment process will be sent to the first client only after the first adjustment process is completed; when the server 100 receives cognitive test feedback information from a second-category user for the first time, the server 100 identifies the second-category user as a new user and selects an intervention plan that only includes one non-drug intervention item from the knowledge base for the new user according to the cognitive impairment degree score and the preset rules and sends it to the second client; when the server 100 receives cognitive test feedback information from a second-category user again, the server 100 identifies the second-category user as an old user and the server 100 performs a second adjustment process of the intervention plan at least based on the cognitive impairment degree score and the intervention utility score, and sends the intervention plan that has undergone the second adjustment process to the second client only after the second adjustment process is completed.The first adjustment process may include at least one of the following processes: when the intervention utility score is within a first intervention utility threshold range, selecting a replacement intervention plan with a second best effect score according to the effect score ranking of the intervention plans and selectively shielding the non-drug intervention items contained in the previously used intervention plan so that at least two non-drug intervention items contained in the replacement intervention plan are different from any non-drug intervention items contained in the previously used intervention plan; when the intervention utility score is within a second intervention utility threshold range, selecting a replacement intervention plan with a second best effect score according to the effect score ranking of the intervention plans in a manner not to shield the non-drug intervention items contained in the previously used intervention plan; and when the intervention utility score is within a third intervention utility threshold range, retaining the previously used intervention plan without making any changes. The second adjustment process may include at least one of the following: when the intervention utility score is within a first intervention utility threshold range, selecting an alternative intervention plan with a suboptimal effect score and containing only one non-drug intervention item based on the intervention plan's effect score ranking, such that the non-drug intervention item included in the alternative intervention plan is different from the non-drug intervention item included in the previously used intervention plan; when the intervention utility score is within a second intervention utility threshold range, receiving a decision from the second category user or randomly selecting by the second client whether to select an alternative intervention plan with a suboptimal effect score and containing only one non-drug intervention item based on the intervention plan's effect score ranking; and when the intervention utility score is within a third intervention utility threshold range, retaining the previously used intervention plan without modification. The value within the first intervention utility threshold range may be smaller than the value within the second intervention utility threshold range. The value within the second intervention utility threshold range may be smaller than the value within the third intervention utility threshold range. Preferably, if the user is a new user, server 100 may allow the user to create a user profile. The user profile may record the user's personal information. For example, the user profile may include at least one of the user's nickname, name, age, education level, gender, height, weight, and medical history.

[0066] According to another optional embodiment, the first adjustment process may include at least one of the following processes: when the intervention utility score is within a first intervention utility threshold range, completely replacing all non-drug intervention items adopted in the previously used intervention plan with non-drug intervention items that the user has not performed to completely change the intervention plan; when the intervention utility score is within a second intervention utility threshold range, randomly selecting some non-drug intervention items from at least two non-drug intervention items adopted in the previously used intervention plan and replacing them with non-drug intervention items that the user has not performed to partially change the intervention plan; and when the intervention utility score is within a third intervention utility threshold range, retaining the previously used intervention plan without making any changes. The second adjustment process may include at least one of the following processes: when the intervention utility score is within the first intervention utility threshold range, replacing a non-drug intervention item adopted in the previously used intervention plan with another non-drug intervention item that the user has not performed to change the intervention plan; when the intervention utility score is within the second intervention utility threshold range, receiving the decision selection of the second type of user by the second client or randomly selecting by the second client whether to replace the non-drug intervention item adopted in the previously used intervention plan with another non-drug intervention item that the second type of user has not performed to randomly change the intervention plan; and when the intervention utility score is within the third intervention utility threshold range, retaining the previously used intervention plan without change.

[0067] According to a preferred embodiment, the client can instruct at least one of the user and the user's caregiver to repeatedly perform non-drug intervention items in the intervention plan from server 100 through at least one of video, audio, and dynamic subtitles until the intervention plan is completed. The knowledge base can include two types of non-drug intervention items, one of which can be instructed by the client to complete by the user, and the other of which can be instructed by the client to complete by the user's caregiver. In other words, preferably, the knowledge base can include two types of non-drug intervention items. The first type of non-drug intervention item can be an item that needs to be completed by the user. For example, the first type of non-drug intervention item can include a puzzle training intervention item, a finger exercise intervention item, a music intervention item, and a memory training intervention item. The second type of non-drug intervention item can be an item that needs to be completed by the user's caregiver. For example, the second type of non-drug intervention item can include a touch intervention item and a dietary intervention item. Before the server 100 selects an intervention plan containing at least two non-drug intervention items from the knowledge base based on at least the cognitive impairment of the first type of user and sends it to the first client, the server 100 can first confirm that the caregiver of the first type of user has confirmed their participation in the intervention process. If the caregiver of the first category user confirms participation in the intervention process, the server 100 may select an intervention plan from the knowledge base that includes at least one non-drug intervention project that needs to be completed by the first category user and at least one non-drug intervention project that needs to be completed by the caregiver of the first category user, and send it to the first client. If the caregiver of the first category user confirms not participating in the intervention process, the server 100 may select an intervention plan from the knowledge base that includes at least two non-drug intervention projects that need to be completed by the first category user, and send it to the first client. Before the server 100 selects an intervention plan from the knowledge base that includes only one non-drug intervention project based on at least the cognitive impairment of the second category user and sends it to the second client, the server 100 may first confirm the confirmation of the caregiver of the second category user to participate in the intervention process. If the caregiver of the second category user confirms participation in the intervention process, the server 100 may select an intervention plan from the knowledge base that includes one non-drug intervention project that needs to be completed by the caregiver of the second category user, and send it to the second client. When the caregiver of the second category user confirms not to participate in the intervention process, the server 100 may select an intervention plan including a non-drug intervention project that needs to be completed by the second category user from the knowledge base and send it to the second client.The present invention adopts this method to achieve at least the following beneficial technical effects: First, based on the confirmation of the user and caregiver to participate in the intervention process, an appropriate intervention plan is selectively selected for them, and intervention is performed on at least one of the user and caregiver to provide more diverse intervention means and evaluate the effects of more diverse intervention means, so that the effects of various non-drug intervention means for patients with cognitive impairment can be more comprehensively evaluated; Second, caregivers who have the opportunity to participate in the intervention process are allowed to participate. Participation in the intervention process will enhance communication and interaction between the user and caregiver. The two parties may discuss some matters in the intervention process, supervise each other, and collaborate to complete the corresponding non-drug intervention projects, so that both parties actively participate in the intervention plan, thereby playing a positive role in controlling the condition of patients with cognitive impairment.

[0068] According to a preferred embodiment, when the client instructs at least one of the user and the user's caregiver to repeatedly perform non-drug intervention items in the intervention plan from server 100 according to the intervention plan, the client can identify the completion status of the at least one of the user and the user's caregiver based on the body movements of at least one of the user and the user's caregiver captured by the image capture element and the wearable sensor. The client and / or server can analyze the confidence level of at least one of the user and the user's caregiver in completing the execution of the intervention plan based on the completion status of the intervention plan. If the confidence level of the completion of the intervention plan is lower than a preset confidence threshold, the intervention utility score corresponding to the intervention plan may not be used as a basis for the server to adjust the effectiveness score of the intervention plan and / or the effectiveness scores of the non-drug intervention items within the intervention plan. In other words, the intervention utility score corresponding to the intervention plan is used as a basis for adjusting the effectiveness score of the intervention plan and / or the effectiveness scores of the non-drug intervention items within the intervention plan only when the confidence level of the execution of the intervention plan is greater than or equal to the preset confidence threshold. Preferably, in response to receiving cognitive test feedback information from a client, the server can selectively use the user's information, the intervention plan adopted, and the intervention effectiveness score after adopting the intervention plan as sample individuals for server 100. The sample individuals can serve as a basis for adjusting the intervention plan's effectiveness score and / or the effectiveness scores of the non-drug intervention items within the intervention plan. Preferably, the sample individuals corresponding to the first category of users can only serve as a basis for adjusting the intervention plan's effectiveness score and / or the effectiveness scores of the non-drug intervention items within the intervention plan, because the first category of users adopted an intervention plan that included at least two non-drug intervention items. Preferably, the sample individuals corresponding to the second category of users can serve as a basis for adjusting the intervention plan's effectiveness score and / or the effectiveness scores of the non-drug intervention items within the intervention plan, because the second category of users adopted an intervention plan that included only one non-drug intervention item. Only when the confidence level of the corresponding intervention plan's execution process is greater than or equal to a preset confidence threshold will the corresponding user's information, the intervention plan adopted, and the intervention effectiveness score after adopting the intervention plan be used as sample individuals for server 100. This prevents sample individual data from improperly operated samples from affecting the accuracy of the overall effectiveness score.

[0069] According to a preferred embodiment, server 100 can be configured to accept batches of imported sample individuals. For example, the operator of server 100 can identify a group of subjects to conduct trials on corresponding intervention plans and obtain corresponding intervention utility scores. The information of the subjects who meet the requirements, the intervention plans adopted, and the intervention utility scores after adopting the intervention plans will then be used as sample individuals for server 100. This approach can initially increase the number of sample individuals in server 100.

[0070] According to a preferred embodiment, see Figure 2In the process in which the client can instruct at least one of the user and the user's caregiver to repeatedly perform the non-drug intervention items in the intervention plan from the server 100 according to the intervention plan, the server 100 can open a video chat room with a multi-person video window in response to the interaction requests of multiple users who have adopted exactly the same intervention plan. The video chat room can include a video guidance window and at least two video interaction windows. The client can instruct at least one of the user and the user's caregiver to repeatedly perform the non-drug intervention items in the intervention plan from the server 100 in at least one of video, audio, and dynamic subtitles through the video guidance window and the audio output element. The at least two video interaction windows can display image information of at least one of the user and the user's caregiver captured by the image capture element from at least two clients, so that different users and caregivers can communicate and interact with each other through video calls. Preferably, when the number of members in the video chat room is greater than or equal to four and the number of members is an integer multiple of two, the server 100 may ask each member in the chat room whether they agree to start the joint participation mode. When all members in the chat room agree to start the joint participation mode, the server 100 may divide the members in the video chat room into two groups, and the video interaction window displays the group total accuracy score of each group in real time. The total accuracy score may be equal to the sum of the member accuracy scores of each member in the group in the process of completing the current non-drug intervention project according to the instructions of the video guidance window. The member's member accuracy score in the process of completing the current non-drug intervention project according to the instructions of the video guidance window may be displayed on the member's video interaction window. The group total accuracy score and / or the member accuracy score may be presented in at least one of a numerical value, a score bar 330 whose length is positively correlated with the score, and a score ball 340 whose size is positively correlated with the score. The present invention adopts this method to achieve at least the following beneficial technical effects: first, it increases the fun of the intervention process to encourage active participation of all members, so that non-drug intervention projects can be better implemented and have a better intervention effect on the patient's condition; second, different members can exchange experiences with each other, so that some members with low accuracy scores can more correctly implement the corresponding non-drug intervention projects and improve in the interactive process.

[0071] According to a preferred embodiment, before the corresponding client displays the image information of at least one of the user and the user's caregiver captured by the image capture component in the video interaction window, the client can perform image processing on the image information of at least one of the user and the user's caregiver in a manner that prevents the identification features of at least one of the user and the user's caregiver from being identified in the video interaction window. This prevents the user's privacy from being transmitted to the server. Preferably, image processing of the image information of at least one of the user and the user's caregiver in a manner that the identity characteristics of at least one of the user and the user's caregiver cannot be identified on the video interaction window is achieved in one of the following ways: identifying facial features of at least one of the user and the user's caregiver and coding the facial features of at least one of the user and the user's caregiver; identifying facial features of at least one of the user and the user's caregiver and replacing the facial features of at least one of the user and the user's caregiver with a cartoon character's avatar; and identifying facial features, neck features, torso features and limb features of at least one of the user and the user's caregiver and replacing the facial features, neck features, torso features and limb features of at least one of the user and the user's caregiver with the facial features, neck features, torso features and limb features of at least one of the user and the user's caregiver. The present invention adopts this method to achieve at least the following beneficial technical effects: the image is processed on the client to avoid the problem of privacy leakage when the private personal image is uploaded to the server 100 or stored on the server 100. Once this problem occurs, it may cause resistance from the majority of users and caregivers, thereby reducing their willingness to use the multi-person video window. Without the process of exchanging experiences with others, the enthusiasm and accuracy of the user to complete the intervention plan may be affected, thereby greatly affecting the effect of the intervention.

[0072] According to a preferred embodiment, the server 100 may use the intervention utility scores of at least a portion of the first category of users after using the corresponding intervention plan as a basis for evaluating the effect score of the corresponding intervention plan rather than as a basis for evaluating the effect scores of at least two non-drug intervention items included in the corresponding intervention plan. The server 100 may use the intervention utility scores of at least a portion of the second category of users after using the corresponding intervention plan as a basis for evaluating the effect scores of the non-drug intervention items included in the corresponding intervention plan and as a basis for evaluating the effect score of the corresponding intervention plan. The present invention adopts this method to achieve at least the following beneficial technical effects: after completing the corresponding intervention plan, the corresponding first category of users and the corresponding second category of users use the corresponding data as sample individuals of the optimization system to continuously improve the system.

[0073] According to a preferred embodiment, before the corresponding client displays the image information of at least one of the user and the user's caregiver captured by the image capture element on the video interaction window, the client can, in response to an image processing request from at least one of the user and the user's caregiver, choose whether to perform image processing on the image information of at least one of the user and the user's caregiver in a manner that makes it impossible to identify the identity characteristics of at least one of the user and the user's caregiver on the video interaction window. The image processing request can include at least one of not performing image processing on the identity characteristics of both the user and the user's caregiver, performing image processing only on the identity characteristics of the user, performing image processing only on the identity characteristics of the user's caregiver, and performing image processing on the identity characteristics of both the user and the user's caregiver. The present invention adopts this method to achieve at least the following beneficial technical effects: First, some users may not want to display their identity characteristics, but other users may need to display their identity characteristics. Therefore, respecting the user's choice is also an important way to allow the user to actively participate in the intervention process; second, some caregivers may be professional caregivers or professionals, and they may also need to identify themselves to others and show their identities, so as to use their professional skills to quickly help others master the correct way to implement the corresponding non-drug intervention projects; third, some users and / or caregivers may be familiar people, such as relatives, neighbors or friends. They trust each other and hope to communicate with each other directly through video to complete the non-drug intervention project and make progress together. Meeting their needs can also greatly improve their enthusiasm and is very helpful in delaying the development of cognitive impairment in a more serious direction.

[0074] Preferably, the cognitive test items may include a test scale for testing the user's cognitive level. The test scale may be, for example, the MoCA scale and / or the MMSE scale. Preferably, the cognitive test items may include a recall test item. In the recall test item, the client selects at least two different words and distracting items from a preset vocabulary based on the user's cognitive impairment score. The client may output at least two different words for the user to memorize in a first time period. The client may output distracting items to divert the user's attention in a second time period. The client may at least instruct the user to input at least two different words as feedback for the recall test item in a third time period. The first time period may be earlier than the second time period. The second time period may be earlier than the third time period. Preferably, the cognitive impairment level can be divided into at least three cognitive impairment stages using at least two cognitive impairment score thresholds. When the user's cognitive impairment level score indicates that the user is in a more severe cognitive impairment stage, the client may select fewer and / or simpler words from the preset vocabulary based on the user's cognitive impairment level score in the recall test item. When the user's cognitive impairment score indicates that the user is in a more severe cognitive impairment stage, the client may select less distracting items from a preset vocabulary based on the user's cognitive impairment score in the recall test. For example, when the cognitive impairment level is divided into at least three cognitive impairment stages, the number of words selected from the mildest to the most severe cognitive impairment stage may be 4, 3, and 2, or 5, 3, and 2, or 6, 4, and 2, respectively.

[0075] Preferably, before the client outputs the distraction items in the second time period to divert the user's attention, the client may first instruct the user to answer the distraction item-related questions related to the distraction items in the third stage. In the third time period, the client may instruct the user to input the answers to the distraction item-related questions as feedback on the recall test items. Preferably, the user's feedback on various cognitive test items may be completed by at least one of voice input, handwriting input, typing input and checking input from a plurality of options to be selected. Preferably, the user's feedback on various cognitive test items may be completed by at least one input device connected to the client in at least one of voice input, handwriting input, typing input and checking input from a plurality of options to be selected.

[0076] According to a preferred embodiment, server 100 may, in response to receiving test feedback information from a client, assess the user's level of cognitive impairment based on the test feedback information received from the client and update the user's user profile accordingly. Server 100 may select, based at least on the user's user profile, at least one non-drug intervention item suitable for the user's level of cognitive impairment from a knowledge base storing a plurality of non-drug intervention items, form an intervention plan for the user, and transmit the plan to the client.

[0077] According to a preferred embodiment, the non-drug intervention project can be, for example, a calculation problem intervention project, a chess and card training intervention project, a calligraphy practice intervention project, a knitting training intervention project, a painting intervention project, a maze intervention project, a paper tearing intervention project, a graphic recognition intervention project, a picture naming intervention project, a puzzle training intervention project, a dart intervention project, a finger exercise intervention project, a fitness exercise intervention project, a music intervention project, a touch intervention project, a diet intervention project, and a memory training intervention project. All non-drug intervention projects can be completed under the instructions of the corresponding video, audio or subtitles. For example, in the calligraphy practice intervention project, the client instructs the user to practice calligraphy through video teaching. For example, in the finger exercise intervention project, the client instructs the user to do finger exercises through video and audio teaching. For example, the client instructs the user to complete the following actions in sequence: 1. Hit the knuckles flatly 36 times; 2. Hit the palms sideways 36 times; 3. Hit the wrists together 36 times; 4. Hit the knuckles crosswise 36 times; 5. Hit the wrists crosswise 36 times; 6. Hit the right palm with the left fist 36 times; 7. Hit the left palm with the right fist 36 times; 8. Hit the backs of the hands together 36 times; and 9. Rub the ears 36 times. For example, in a music intervention program, the client plays corresponding music and some guiding words, asking the user to close their eyes and meditate to relax their body and mind. Another example is a touch intervention program, where the client can instruct a caregiver to massage the user. It should be noted that various non-drug intervention programs may be existing or subsequently added. This invention only lists a portion of them. This invention does not intend to include these specific non-drug intervention programs within the scope of protection of this invention. Instead, it aims to provide a platform for evaluating the effectiveness of various non-drug intervention programs and intervention programs that use corresponding non-drug intervention programs, thereby selecting non-drug intervention programs and / or intervention programs that are more effective in delaying the progression of cognitive impairment in patients from a large number of known or unknown non-drug intervention programs and / or intervention programs. Preferably, each intervention program can record the non-drug intervention program used, the intervention period of each non-drug intervention program, the target of each non-drug intervention program, and the course of the intervention program. Preferably, two different intervention programs represent a difference in at least one of the non-drug intervention program used, the intervention period of each non-drug intervention program, the target of each non-drug intervention program, and the course of the intervention program. The intervention period of each non-drug intervention program can be, for example, once a day, twice a day, every two days, or every three days. The target of the program can be the user or the user's caregiver. The course of the intervention program can be, for example, one week, two weeks, one month, one quarter, or six months. For example, assume that an intervention plan includes two non-drug intervention items, one of which may be applied to a user, and the intervention cycle may be once a day.Another non-drug intervention program is implemented for the user's caregiver, and the intervention cycle may be once every two days, for example.

[0078] Example 3

[0079] The present embodiment may be a further improvement and / or supplement to embodiment 1, 2 or a combination thereof, and repeated contents will not be repeated. Without causing conflict or contradiction, the overall and / or partial contents of the preferred implementation modes of other embodiments may serve as a supplement to the present embodiment. The present embodiment discloses a system for evaluating the intervention efficacy of cognitive impairment patients based on evidence-based practice, or a system for evaluating the intervention effect of cognitive impairment intervention means, or a system for evaluating the intervention effect of cognitive impairment patients based on evidence-based practice, or a system for evaluating the intervention efficacy of cognitive impairment patients, or a system for evaluating the intervention efficacy of cognitive impairment patients, or a system for evaluating the intervention effect of cognitive impairment patients, or a system for evaluating the intervention effect of intervention on cognitive impairment patients. The system is suitable for executing the various method steps recorded in the present invention to achieve the expected technical effect.

[0080] According to a preferred embodiment, the system may include a client 200 and a server 100 .

[0081] According to a preferred embodiment, the knowledge base of the server 100 may include several non-drug intervention items and several intervention plans. Each intervention plan may adopt at least one non-drug intervention item.

[0082] Example 4

[0083] This embodiment may be a further improvement and / or supplement to Embodiments 1, 2, 3, or a combination thereof, and repeated contents will not be repeated. In the absence of conflict or contradiction, the entirety and / or part of the preferred implementation methods of other embodiments may serve as a supplement to this embodiment.

[0084] like Figure 3 As shown, a dementia care system integrating multiple intervention pathways includes at least a treatment device 1, a patient self-assessment module 2, and a training and treatment module 3, and further includes a caregiver self-assessment module 4 and an intervention module 5 that interacts with the patient self-assessment module 2, the caregiver assessment module, and the training and treatment module 3, wherein the intervention module 5 is configured as follows:

[0085] Based on the needs assessment result of the first user 6 after completing at least one needs scale obtained by the patient self-assessment module 2, determining whether the first user 6 has cognitive impairment and cognitive impairment symptoms, performing the training treatment module 3 at least once in combination with the treatment device 1 using a non-drug intervention plan associated with the needs assessment result;

[0086] After each execution of the training and treatment module 3, the first assessment result of the first user 6 after completing at least one disease scale obtained by the patient self-assessment module 2 and the second assessment result of the second user 7 after completing at least one caregiver needs assessment form obtained by the caregiver self-assessment module 4, together with the patient self-assessment module 2, the caregiver assessment module, and the training and treatment module 3, constitute a multi-intervention path fusion care system, so that the multi-intervention path fusion care system can complete at least one non-active execution intervention of the non-drug intervention plan on the basis of completing the intervention path effect evaluation.

[0087] The dementia care system provided by the present invention conducts continuous phased and follow-up evaluations of the intervened subjects based on the introduced Logit model, and makes reliable and credible evaluations of the effects of social work intervention and smart terminal intervention in the self-health management of elderly patients with chronic diseases. In addition, through the cooperation between relevant workers involved in the intervention process (such as community-related geriatric medical institutions or professional geriatric social work institutions) and the intervened subjects, it integrates multi-party resources to analyze the best health management intervention methods for chronic disease patients from multiple angles, which can effectively help the intervened subjects to manage their own health, thereby reducing the incidence of chronic diseases and improving the self-efficacy, life satisfaction and social support level of the elderly in disease control.

[0088] Preferably, the non-active intervention includes at least a non-drug intervention program for the second user. At present, the vast majority of dementia patients are cared for at home. The memory and daily living ability of dementia patients are deteriorating day by day, and abnormal behaviors appear, which cause great pain to caregivers and bring serious burdens. Research on dementia caregivers suggests that understanding the difficulties and burdens of caregivers, assessing their mental and physical health, providing health education and care counseling, and providing service facilities are realistic ways to help. Studies have shown that abnormal behavior of dementia patients and long time spent on care are also one of the important reasons for excessive burden and increased psychological pressure. Especially when the workload of caregivers is increased without improving the symptoms of dementia patients, it not only increases the workload of caregivers in vain and ineffectively, but also seriously affects the execution of care work by caregivers and even affects the treatment effect of dementia patients.

[0089] Since non-drug intervention plans are often obtained through statistical analysis with the highest probability of being beneficial to delaying the patient's condition, it ignores the individual differences among the subjects and executors of the non-drug intervention plan. Different tolerance and / or execution capabilities of the non-drug intervention plan often lead to the actual intervention effect not meeting expectations. Therefore, the present invention completes at least one non-active execution intervention of the non-drug intervention plan by simultaneously evaluating the capabilities of both patients and caregivers, and establishes a system of raising questions-finding evidence-identifying evidence-applying identification results-evaluation. By integrating multiple resources to analyze the optimal health management intervention method for chronic disease patients with individual differences from multiple angles, it avoids irrelevant cognitive load of nursing-related personnel and futile and ineffective increase in their working time.

[0090] The intervention module 5 is also configured to: interact with other chronic disease management cloud service platforms and / or health management cloud service platforms through the Internet of Things, perform typological analysis based on the acquired historical data of multiple users, and generate a first non-active execution intervention including at least information such as operation functions, usage preferences, and operation paths; construct a Logit model of multiple intervention paths and intervention effectiveness, and perform a predictive test based on the first non-active execution intervention using the Logit model to determine the predictive empirical evidence and predicted intervention effectiveness associated with the first non-active execution intervention; display the obtained first non-active execution intervention and the predictive empirical evidence and predicted intervention effectiveness associated with the first non-active execution intervention, and determine the execution of the first non-active execution intervention on the non-drug intervention plan based on the input instructions of the first user 6 and / or the second user 7.

[0091] After presenting the predictive empirical evidence and predicted intervention results obtained from the analysis to patients and caregivers, the non-active intervention must be confirmed by the patients themselves and / or caregivers before it can be implemented, realizing the "whole-person assessment-whole-person management-whole-person intervention-health empowerment" for elderly patients with chronic diseases, emphasizing the subjectivity of patients' own participation in health management. Social workers connect other professionals with elderly patients to jointly manage diseases and health, provide them with health information, and empower them to take an active role in managing their own diseases, thereby enhancing the autonomy of elderly patients and strengthening their ability to self-manage their diseases.

[0092] Preferably, the intervention module 5 can use a systematic literature method and meta-analysis to systematically review existing literature and public networks on software that discusses health management for elderly patients with chronic diseases, sort out existing popular chronic disease management and health management smart APP terminals, namely, the other chronic disease management cloud service platform and / or health management cloud service platform, summarize and evaluate the functions, results, and user preferences of the APPs with high social usage rates, and focus on sorting out the efficacy of health smart APPs in intervening in the health management of the elderly, and then conduct a typological analysis of the functions, usage preferences, and operation paths of these software. This is mainly to prepare for the improvement and localization of the selected software.

[0093] On the second aspect, the intervention module 5 uses a systematic literature method and meta-analysis to sort out the paths and effectiveness of traditional social work interventions in the health management of chronic diseases in the elderly based on the Logit model, and systematically summarizes the empirical evidence on the impact of this model and path on the health management of elderly patients with chronic diseases. This step can present the integrated paths and effectiveness of social work interventions in the health management of elderly patients with chronic diseases, and provide experience and evidence for the integration of social work interventions in the experimental method.

[0094] Therefore, in today's deeply aging society, the health problems of the elderly are becoming increasingly prominent. Their ability to care for themselves is declining, and their prevalence of health problems, especially chronic diseases, is increasing, leading to more problems. Furthermore, the elderly have fewer opportunities for social participation, fewer venues for activities, fewer hobbies, and a low participation rate, ultimately making them the largest marginalized group in society (Hu Angang and Hao Xiaoning, 2008). On the other hand, traditional medical and health resources are no longer sufficient to meet the health needs of the elderly. However, health self-management through smart terminal apps has attracted significant attention as a new healthcare model and is of great significance for promoting healthy aging (Tang Qiqun, 2015). Through systematic literature review and meta-analysis, this paper first reviews the existing popular smart terminal apps for chronic disease management and health management. It then summarizes and evaluates the functions, effectiveness, and user preferences of the most popular apps in society. Furthermore, it focuses on the mechanisms and efficacy of smart health apps in intervening in health management for the elderly, providing a reference for the localized improvements in this paper.

[0095] According to a preferred embodiment, the patient self-assessment module 2 is configured to: perform training treatment on at least one of the first users 6 according to the non-drug intervention plan after the first non-active intervention has been performed, and based on the baseline parameters determined by the baseline measurement of the first user 6 before the training treatment, combined with the measurement parameters determined by three repeated measurements of the first user 6 at preset time nodes;

[0096] A time series interface analysis method is used to conduct a multi-level comparative analysis on the generated panel data and to construct an intervention process stability model and an intervention process consistency model, thereby completing the evaluation of the effect of the training treatment on the first user 6;

[0097] The measurement process includes at least one or more of a life satisfaction scale, a self-evaluation scale, a chronic disease health management scale, and a social support scale, and the preset time nodes may include one or more of a short-term intervention time node, a mid-term intervention time node, and a late-term intervention time node. Preferably, the short-term intervention time node, the mid-term intervention time node, and the late-term intervention time node may be one or more of 6 months, 12 months, or 18 months, respectively.

[0098] According to a preferred embodiment, the first users 6 include at least control group users who receive intervention with a locally improved chronic disease risk management application and experimental group users who receive intervention with a social work integrated health management method, wherein the patient self-assessment module 2 compares and analyzes the intervention process stability model and / or intervention process consistency model corresponding to the experimental group users with the intervention process stability model and / or intervention process consistency model corresponding to the control group users, and combines the comparative analysis with individual structured interviews to obtain the first evaluation results corresponding to the control group users and the experimental group users during the intervention process at the mid-term time node of the intervention and at the end of the intervention process.

[0099] The recent surge in evidence-based social work research has focused particularly on the accumulation of evidence regarding social work interventions in the healthcare sector. Western research indicates that the emergence of a multidisciplinary, multifaceted health model presents significant challenges and unique opportunities for the social work profession, and that social work can play a crucial role within this model. Its holistic approach to health services, focusing on the biopsychosocial dimension, can complement the medical model's inability to consider patients' psychosocial needs or even their natural environment (Hoffman & Stovall, 2006). Data-based, clinical research has demonstrated that social work interventions to provide services and support to geriatric patients during treatment and recovery are crucial for improving the quality of life of these patients and their families (Freeman, 2006; Marcus, 2006; Rust & Davis, 2011). However, evidence-based social work research in China has largely focused on theoretical and introductory aspects (He Xuesong, 2004; Wang Yizhi, 2016), and a research framework focusing on practice-based evidence is yet to be established (Yang Wendeng, 2014). Therefore, the present invention provides information system support for the application of evidence-based research to practical decision-making by specifically monitoring the stability and consistency of the intervention process. It can provide systematic and effective evidence for the effectiveness and cost of social work intervention, and further make better decisions on treatment plans based on a reliable evidence level.

[0100] According to a preferred embodiment, the intervention module 5 is further configured to: based on different preset time nodes, combine the first evaluation result corresponding to the preset time node and the second evaluation result corresponding to the preset time node, and perform statistics and analysis to generate a phased evaluation and final conclusion between the control group users and the experimental group users, thereby realizing an evidence-based comparison of traditional social work intervention methods and modern health management software intervention methods.

[0101] Preferably, the research effects are compared at the initial intervention time node of 6 months, the mid-intervention time node of 12 months, and the late intervention time node of 18 months. The health status and morbidity of the two groups of elderly people are tracked, and the aforementioned life satisfaction scale SWLS, self-evaluation scale C-DES_SF, chronic disease health management scale T2DHBS and social support scale LSNS are used to conduct phased measurement and post-test on all elderly people, and the panel data of several follow-up surveys are analyzed by time series cross-sectional analysis method; phased structured interviews and participant observations are conducted on the two groups of elderly people, and qualitative research methods are used to evaluate the intervention effects of the two groups of elderly people; at the same time, focus interviews are conducted on the offline monitoring personnel of the control group and the implementation personnel of the intervention team of the experimental group in the mid- and late stages of the intervention to collect opinions and suggestions on the implementation of the intervention and analyze the intervention effect, which is the second evaluation result; according to the logical model project design and evaluation framework, the three measurement data and baseline data of the experimental group and the control group are subjected to multi-level comparative analysis to evaluate the intervention effect, which is the first evaluation result; the research results of the above two multi-angle methods are combined for analysis to draw the phased and final conclusions of the comparison of the intervention effects of the two groups.

[0102] This paper is based on evidence-based practice, evaluates and compares the results of interventions combined with modern health management intelligent terminal tools and traditional social work clinical professional interventions, finds the best evidence of social work practice interventions for chronic diseases in the elderly that meets the client's values, and establishes a reliable "practice-evidence research-practice" system.

[0103] According to a preferred embodiment, the caregiver needs assessment form includes at least one or more of a caregiver basic information form, a caregiver burden scale, a caregiver needs assessment form, a self-efficacy form and a simple coping style form, wherein the caregiver self-assessment module 4 obtains the second assessment results of the second user 7 corresponding to the control group user and the experimental group user during the intervention process at the mid-term time node and the late time node of the intervention, respectively, by combining focus group interviews and the caregiver needs assessment form.

[0104] Preferably, the focus group interview field study can be based on long-term follow-up observation, and focus group interviews can be conducted on social workers and interdisciplinary teams implementing the intervention, which can be conducted twice in the middle and late stages of the experiment to collect opinions and suggestions from service providers, improve and analyze the intervention.

[0105] According to a preferred embodiment, the intervention module 5 is further configured to: determine empirical evidence of effectiveness based on the staged evaluation and final conclusion of the first user 6 and the second user 7, and a second non-active execution intervention corresponding to the empirical evidence, including at least information such as operation function, usage preference, and operation path;

[0106] Performing a predictive test using the Logit model based on the second inactive implementation intervention to determine predictive empirical evidence associated with the second inactive implementation intervention and predictive intervention effectiveness;

[0107] Display the obtained second non-active execution intervention and the predicted empirical evidence and predicted intervention effectiveness associated with the second non-active execution intervention, and determine whether to execute the second non-active execution intervention on the non-drug intervention plan that has already executed the second non-active execution intervention based on the input instructions of the first user 6 and / or the second user 7.

[0108] After improving the non-drug intervention plan by executing the first non-active intervention, the plan is determined as the second non-active intervention for the next execution of the training treatment module 3, and the newly obtained predictive empirical evidence and predicted intervention results are used to further improve the non-drug intervention plan, so as to iteratively form a recursive cycle of the non-drug intervention plan, and then continuously and dynamically improve the non-drug intervention plan to adapt to the intervened persons and caregivers in different risk periods and / or different risk sizes.

[0109] According to a preferred embodiment, the needs scale includes at least one or more of the Mini-Mental State Examination, the Montreal Cognitive Assessment, the Daily Living Ability Scale, the Geriatric Depression Scale, the Pittsburgh Sleep Scale and the Social Support Scale, and the non-drug intervention program can be a fusion of multiple intervention paths formed by a combination of at least one or more of executive ability training, cognitive intervention, touch therapy, music therapy, creative story therapy, nostalgia therapy and retrospective summary.

[0110] As used herein, the term "module" describes any piece of hardware, software, or a combination of hardware and software that is capable of performing the functionality associated with the "module."

[0111] It should be noted that the above-described specific embodiments are illustrative only. Those skilled in the art may devise various solutions based on the disclosure of the present invention, and such solutions fall within the scope of the present invention and are intended to be protected by the present invention. Those skilled in the art should understand that the present description and its accompanying drawings are intended to be illustrative only and are not intended to limit the scope of the claims. The scope of protection of the present invention is defined by the claims and their equivalents.

Claims

1. A recommendation system for intervention plans for patients with cognitive impairment, comprising at least a client and a server, characterized in that: The system uses a client and a server to assist in completing the evaluation process of the intervention effect of cognitive impairment intervention means, wherein the knowledge base of the server includes a number of non-drug intervention items and a number of intervention plans, and each intervention plan adopts at least one non-drug intervention item; The server selects an intervention plan for the user from the knowledge base based on the user's cognitive impairment and sends it to the client; The server repeatedly executes the non-drug intervention items in the intervention plan from the server on at least one of the user and the caregiver of the user until, after the intervention plan is completed, an intervention effectiveness score of the intervention plan in delaying the progression of the user's cognitive impairment to a more severe direction is obtained based on at least the current test feedback information and the historical test feedback information of the user; The server analyzes the confidence level of at least one of the user and the user's caregiver in completing the execution process of the corresponding intervention plan based on the completion status of the corresponding intervention plan. The server selectively adjusts at least one of the effect score of the intervention plan and the effect score of the non-drug intervention item based on the intervention utility score of the corresponding intervention plan for the corresponding user according to the confidence level of the execution process of the corresponding intervention plan. When a certain intervention plan has a poor intervention utility score for the user, the intervention plan is adjusted to find a suitable intervention plan for the user. The confidence level is obtained by multiplying the first sub-confidence level by a first coefficient and multiplying the second sub-confidence level by a second coefficient, and then adding the two together. The sum of the first coefficient and the second coefficient is equal to 1.

2. The intervention plan recommendation system for patients with cognitive impairment according to claim 1, characterized in that: The server regularly generates a recommendation report containing at least two intervention plans and at least two non-drug intervention projects that are preferably recommended for different groups of people based on the real-time effect scores of the intervention plans and the effect scores of the non-drug intervention projects. In the process of the server selecting the preferred recommended intervention plan and the preferred recommended non-drug intervention project suitable for the same population, the server will selectively block sample individuals that do not meet the population characteristics of the population, so that the blocked sample individuals are not used as the basis for scoring the effectiveness of the intervention plan and / or the effectiveness of the non-drug intervention project.

3. The intervention plan recommendation system for patients with cognitive impairment according to claim 2, characterized in that: The first sub-confidence is obtained by: the client collects image information containing body movements of at least one of the user and the user's caregiver using an image acquisition component, and compares it with an image of an instruction video containing the body movements of a demonstrator to identify a first completion status of at least one of the user and the user's caregiver completing a corresponding intervention plan, and accordingly analyzes the first sub-confidence of the execution process of at least one of the user and the user's caregiver completing the corresponding intervention plan. The second sub-confidence is obtained as follows: the client collects motion data including body movements of at least one of the user and the caregiver of the first type of user based on the wearable sensor and compares it with the sensor verification data to identify the second completion status of at least one of the user and the caregiver of the user completing the corresponding intervention plan, so as to analyze the second sub-confidence of the execution process of at least one of the user and the caregiver of the user completing the corresponding intervention plan.

4. The intervention plan recommendation system for patients with cognitive impairment according to any one of claims 1 to 3, characterized in that: The client includes at least one of a first client and a second client, the first client is a client of a first type of user, and the second client is a client of a second type of user. When a user selects on their client that the intervention plan they need is an intervention plan that includes at least two non-drug intervention items, the user is marked by the server as a first-category user; when a user selects on their client that the intervention plan they need is an intervention plan that only includes one non-drug intervention item, the user is marked by the server as a second-category user; according to changes in the intervention plan currently required by the user, the user's current type is interchangeable between the first-category user and the second-category user; The server adjusts only the effect score of the corresponding intervention plan according to the intervention utility score of the corresponding intervention plan for the first category of users; the server adjusts both the effect score of the corresponding intervention plan and the effect score of the corresponding non-drug intervention item according to the intervention utility score of the corresponding intervention plan for the second category of users; When the effect scores of different intervention plans are the same, the server performs secondary sorting of the different intervention plans according to the sum of the effect scores of the non-drug intervention items within the intervention plans, so that among the different intervention plans with the same effect scores, the intervention plan with a larger sum of the effect scores of all non-drug intervention items has a higher effect score ranking.

5. The intervention plan recommendation system for patients with cognitive impairment according to claim 4, characterized in that: Before the server publishes the recommendation report to at least one social network, the server verifies whether the total number of sample individuals supporting the recommendation report, the number of sample individuals supporting the preferred recommended intervention plan for each population group, and the number of sample individuals supporting the preferred recommended non-drug intervention project for each population group meet corresponding preset number thresholds; The server will only publish the recommendation report to at least one social network when the total number of sample individuals supporting the recommendation report, the number of sample individuals supporting the preferred recommended intervention plan for each population, and the number of sample individuals supporting the preferred recommended non-drug intervention project for each population all reach the corresponding preset number thresholds.

6. The intervention plan recommendation system for patients with cognitive impairment according to claim 4, characterized in that: When one of the total number of sample individuals supporting the recommendation report, the number of sample individuals supporting the preferred recommended intervention plan for each population, and the number of sample individuals supporting the preferred recommended non-drug intervention items for each population does not reach the corresponding preset number threshold, the server will only retain the recommendation report locally for authorized access users to query.

7. The intervention plan recommendation system for patients with cognitive impairment according to claim 4, characterized in that: When the confidence level of the completion of the execution process of the corresponding intervention plan is lower than a preset confidence threshold, the server does not use the corresponding user information, the adopted intervention plan, and the intervention utility score after adopting the intervention plan as a sample individual of the server, so that the server does not adjust at least one of the effect score of the intervention plan and the effect score of the non-drug intervention item according to the intervention utility score of the intervention plan for the corresponding user. When the confidence level of the execution process of the corresponding intervention plan is greater than or equal to a preset confidence threshold, the server uses the information of the corresponding user, the adopted intervention plan and the intervention utility score after adopting the intervention plan as the sample individual of the server, so that the server adjusts at least one of the effect score of the intervention plan and the effect score of the non-drug intervention project according to the intervention utility score of the corresponding user of the intervention plan.

8. A method for recommending an intervention plan for patients with cognitive impairment, characterized in that: The method at least comprises: Using a client and a server to assist in completing the evaluation process of the intervention effect of cognitive impairment intervention means, wherein the knowledge base of the server includes a number of non-drug intervention items and a number of intervention plans, and each intervention plan adopts at least one non-drug intervention item; The server selects an intervention plan for the user from the knowledge base based on the user's cognitive impairment and sends it to the client; The server repeatedly executes the non-drug intervention items in the intervention plan from the server on at least one of the user and the caregiver of the user until, after the intervention plan is completed, an intervention effectiveness score of the intervention plan in delaying the progression of the user's cognitive impairment to a more severe direction is obtained based on at least the current test feedback information and the historical test feedback information of the user; The server analyzes the confidence level of at least one of the user and the user's caregiver in completing the execution process of the corresponding intervention plan based on the completion status of the corresponding intervention plan. The server selectively adjusts at least one of the effect score of the intervention plan and the effect score of the non-drug intervention item based on the intervention utility score of the corresponding intervention plan for the corresponding user according to the confidence level of the execution process of the corresponding intervention plan. When a certain intervention plan has a poor intervention utility score for the user, the intervention plan is adjusted to find a suitable intervention plan for the user. The confidence level is obtained by multiplying the first sub-confidence level by a first coefficient and multiplying the second sub-confidence level by a second coefficient, and then adding the two together. The sum of the first coefficient and the second coefficient is equal to 1.

9. The method for recommending an intervention plan for patients with cognitive impairment according to claim 8, characterized in that: The method further comprises: When the confidence level of the completion of the execution process of the corresponding intervention plan is lower than a preset confidence threshold, the server does not use the corresponding user information, the adopted intervention plan, and the intervention utility score after adopting the intervention plan as a sample individual of the server, so that the server does not adjust at least one of the effect score of the intervention plan and the effect score of the non-drug intervention item according to the intervention utility score of the intervention plan for the corresponding user. When the confidence level of the execution process of the corresponding intervention plan is greater than or equal to a preset confidence threshold, the server uses the information of the corresponding user, the adopted intervention plan and the intervention utility score after adopting the intervention plan as the sample individual of the server, so that the server adjusts at least one of the effect score of the intervention plan and the effect score of the non-drug intervention project according to the intervention utility score of the corresponding user of the intervention plan.

10. The method for recommending an intervention plan for patients with cognitive impairment according to claim 8 or 9, characterized in that: The method further includes: obtaining the first sub-confidence by: the client collecting, using an image acquisition component, image information containing body movements of at least one of the user and the user's caregiver, and comparing it with an image of an instructional video containing the body movements of a demonstrator to identify a first completion status of at least one of the user and the user's caregiver completing a corresponding intervention plan, thereby analyzing the first sub-confidence of the execution process of at least one of the user and the user's caregiver completing the corresponding intervention plan. The second sub-confidence is obtained as follows: the client collects motion data including body movements of at least one of the user and the caregiver of the first type of user based on the wearable sensor and compares it with the sensor verification data to identify the second completion status of at least one of the user and the caregiver of the user completing the corresponding intervention plan, so as to analyze the second sub-confidence of the execution process of at least one of the user and the caregiver of the user completing the corresponding intervention plan.

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