A method and system for processing rehabilitation data

Abstract

The application provides a rehabilitation assistance data processing method and system, which comprises the following steps: obtaining a corresponding rehabilitation level and an assistance treatment completion state based on the rehabilitation assistance data of each rehabilitation assistance treatment; performing completion state expansion based on the corresponding rehabilitation level and the assistance treatment completion state of each rehabilitation assistance treatment, and obtaining a first completion rate corresponding relationship of a target patient; determining a second completion rate corresponding relationship from the first completion rate corresponding relationship; obtaining a weighted completion rate corresponding to each target preset rehabilitation level based on each rehabilitation weight and the second completion rate corresponding relationship; determining a predicted rehabilitation level corresponding to the target patient from each target preset rehabilitation level based on each target preset rehabilitation level and the corresponding weighted completion rate through a preset rehabilitation level prediction model, and determining a treatment plan for the next rehabilitation assistance treatment of the target patient based on the predicted rehabilitation level. The scheme can obtain an accurate treatment plan, and is more beneficial to the rehabilitation of the patient.

Description

Technical Field

[0001] This application relates to the field of healthcare technology, and more specifically, to a method and system for assisting in rehabilitation data processing. Background Technology

[0002] Medical rehabilitation refers to the efforts to improve the physical or psychological damage caused by disease or injury, both physically and mentally, to the greatest extent possible, enabling patients to enhance their abilities and gradually restore their functions so they can return to normal life in their families and society. To enable patients to reintegrate into society, rehabilitation should not only be medical but also include psychological, social, economic, vocational, and educational aspects.

[0003] Rehabilitation therapy can be combined with various rehabilitation medical devices and corresponding treatment plans to treat patients. Generally, rehabilitation therapy is a continuous process. The treatment provider needs to collect various auxiliary rehabilitation data generated during the treatment process in a timely manner, and then revise the previous treatment plan based on this auxiliary rehabilitation data to form the subsequent treatment plan. Specifically, after each rehabilitation treatment, the patient's rehabilitation level is assessed, and then the next treatment plan is determined based on the rehabilitation level.

[0004] However, the current rehabilitation levels are determined based on the subjective experience of the therapists, which cannot accurately reflect the patient's rehabilitation status, thus leading to inaccurate subsequent treatment plans. Summary of the Invention

[0005] This application provides a method and system for processing auxiliary rehabilitation data to solve the technical problem that the treatment plan for auxiliary rehabilitation therapy is not accurate enough in the prior art.

[0006] In a first aspect, embodiments of this application provide an auxiliary rehabilitation data processing method, including:

[0007] Obtain auxiliary rehabilitation data from multiple auxiliary rehabilitation treatments for the target patient, and obtain the corresponding rehabilitation level and auxiliary treatment achievement status based on the auxiliary rehabilitation data from each auxiliary rehabilitation treatment;

[0008] Based on the rehabilitation level and target achievement status corresponding to each auxiliary rehabilitation treatment, the target achievement status is expanded to obtain the first target achievement rate correspondence for the target patient. The first target achievement rate correspondence indicates the target achievement rate of different preset auxiliary treatment courses under different preset rehabilitation levels. Different preset auxiliary treatment courses correspond to different consecutive auxiliary rehabilitation treatments.

[0009] Based on the rehabilitation impact attributes of the target patients, a second target achievement rate correspondence is determined from the first target achievement rate correspondence. The second target achievement rate correspondence indicates the achievement rate of different target preset auxiliary treatment courses under different target preset rehabilitation levels.

[0010] Obtain the rehabilitation weights corresponding to the preset auxiliary treatment courses for each target, and obtain the weighted achievement rate corresponding to the preset rehabilitation level for each target based on the correspondence between each rehabilitation weight and the second achievement rate;

[0011] Based on the preset rehabilitation levels and corresponding weighted achievement rates for each target, the predicted rehabilitation level for the target patient is determined from the preset rehabilitation levels using a preset rehabilitation level prediction model. Based on the predicted rehabilitation level, a treatment plan for the next auxiliary rehabilitation therapy is determined for the target patient.

[0012] In one optional embodiment of this application, the achievement status is expanded based on the rehabilitation level and achievement status of each assisted rehabilitation treatment to obtain the first achievement rate correspondence for the target patient, including:

[0013] For each pre-set auxiliary treatment course, obtain the corresponding rehabilitation level and auxiliary treatment achievement status for that auxiliary treatment;

[0014] If the target achievement status of the auxiliary treatment is not met, then the target achievement status of the auxiliary treatment course under different preset rehabilitation levels will be determined as not met.

[0015] If the target achievement status of the auxiliary treatment is achieved, then the target achievement status of the preset auxiliary treatment course under each preset rehabilitation level that is greater than the rehabilitation level corresponding to the auxiliary treatment is determined to be achieved, and the target achievement status of the preset auxiliary treatment course under each preset rehabilitation level that is less than the rehabilitation level corresponding to the auxiliary treatment is determined to be unachieved.

[0016] Based on the rehabilitation treatment achievement status of each preset auxiliary treatment course under each preset rehabilitation level, the corresponding relationship of the first achievement rate is obtained.

[0017] In one optional embodiment of this application, a first target achievement rate correspondence is obtained based on the rehabilitation treatment achievement status of each preset auxiliary treatment course under each preset rehabilitation level, including:

[0018] For each preset auxiliary treatment course at each preset rehabilitation level, the ratio of the number of times the target was achieved in each auxiliary treatment session of the preset auxiliary treatment course at that preset rehabilitation level to the total number of auxiliary treatment sessions is taken as the target achievement rate of the preset auxiliary treatment course at that preset rehabilitation level.

[0019] The corresponding relationship between the first target achievement rate of each preset auxiliary treatment course under each preset rehabilitation level is obtained.

[0020] In one optional embodiment of this application, the rehabilitation impact attributes include the age and basic physical condition data of the target patient;

[0021] Based on the rehabilitation impact attributes of the target patients, a second target achievement rate correspondence is determined from the first target achievement rate correspondence, including:

[0022] Based on the age of the target patient, at least one target pre-set auxiliary treatment course is determined from each pre-set auxiliary treatment course, and based on the physical condition data of the target patient, at least one target pre-set rehabilitation level is determined from each pre-set rehabilitation level;

[0023] Based on at least one target preset auxiliary treatment course and at least one target preset rehabilitation level, a second target achievement rate correspondence is determined from the first achievement rate correspondence.

[0024] In one optional embodiment of this application, the more consecutive auxiliary treatments included in each target preset auxiliary treatment course, the older the target patient is; the better the target patient's physical condition data indicates, the higher the corresponding target preset rehabilitation level.

[0025] In one optional embodiment of this application, a second target achievement rate correspondence is determined from a first target achievement rate correspondence based on at least one target preset auxiliary treatment course and at least one target preset rehabilitation level, including:

[0026] Retain the achievement rates corresponding to at least one target preset auxiliary treatment course and at least one target preset rehabilitation level in the first achievement rate correspondence, and set the other achievement rates to zero or delete the correspondences corresponding to other achievement rates to obtain the second achievement rate correspondence.

[0027] In one optional embodiment of this application, obtaining the rehabilitation weight corresponding to each target preset auxiliary treatment course includes:

[0028] Based on the number of times the target was achieved in each auxiliary treatment state corresponding to each preset auxiliary treatment course, the rehabilitation weight corresponding to each preset auxiliary treatment course was obtained.

[0029] Based on the correspondence between each rehabilitation weight and the second achievement rate, the weighted achievement rate corresponding to each preset rehabilitation level is obtained, including:

[0030] For each preset rehabilitation level, the achievement rate of the preset rehabilitation level under each preset auxiliary treatment course is weighted and summed according to the corresponding rehabilitation weights to obtain the weighted achievement rate corresponding to the preset rehabilitation level.

[0031] In one optional embodiment of this application, the greater the number of times the target is met in each auxiliary treatment state corresponding to the target preset auxiliary treatment course, the greater the rehabilitation weight corresponding to the target preset auxiliary treatment course.

[0032] In one optional embodiment of this application, the method further includes:

[0033] Obtain the correspondence between treatment plans. The treatment plan correspondence stores the correspondence between different preset rehabilitation levels and treatment plans.

[0034] Based on the predicted rehabilitation level, a treatment plan for the next auxiliary rehabilitation therapy is determined for the target patient, including:

[0035] Based on the predicted rehabilitation level, the corresponding treatment plan is obtained from the treatment plan correspondence, and the treatment plan is used as the target patient to determine the next auxiliary rehabilitation treatment plan.

[0036] Secondly, embodiments of this application provide an auxiliary rehabilitation data processing system, including:

[0037] The auxiliary rehabilitation data acquisition module is used to acquire auxiliary rehabilitation data of multiple auxiliary rehabilitation treatments of the target patient, and to obtain the corresponding rehabilitation level and auxiliary treatment achievement status based on the auxiliary rehabilitation data of each auxiliary rehabilitation treatment.

[0038] The first target achievement rate correspondence acquisition module is used to expand the target achievement status based on the rehabilitation level and target achievement status of each auxiliary rehabilitation treatment, and to obtain the first target achievement rate correspondence for the target patient. The first target achievement rate correspondence indicates the target achievement rate of different preset auxiliary treatment courses under different preset rehabilitation levels. Different preset auxiliary treatment courses correspond to different consecutive auxiliary rehabilitation treatments.

[0039] The second target achievement rate correspondence acquisition module is used to determine the second target achievement rate correspondence from the first target achievement rate correspondence based on the rehabilitation impact attributes of the target patient. The second target achievement rate correspondence indicates the target achievement rate of different target preset auxiliary treatment courses under different target preset rehabilitation levels.

[0040] The weighted achievement rate acquisition module is used to obtain the rehabilitation weights corresponding to each target preset auxiliary treatment course, and to obtain the weighted achievement rate corresponding to each target preset rehabilitation level based on the correspondence between each rehabilitation weight and the second achievement rate.

[0041] The treatment plan acquisition module is used to determine the predicted rehabilitation level of the target patient from the preset rehabilitation levels of each target based on the preset rehabilitation level of each target and the corresponding weighted achievement rate, and to determine the treatment plan for the next auxiliary rehabilitation treatment for the target patient based on the predicted rehabilitation level.

[0042] In one optional embodiment of this application, the first compliance rate correspondence acquisition module is specifically used for:

[0043] For each pre-set auxiliary treatment course, obtain the corresponding rehabilitation level and auxiliary treatment achievement status for that auxiliary treatment;

[0044] If the target achievement status of the auxiliary treatment is not met, then the target achievement status of the auxiliary treatment course under different preset rehabilitation levels will be determined as not met.

[0045] If the target achievement status of the auxiliary treatment is achieved, then the target achievement status of the preset auxiliary treatment course under each preset rehabilitation level that is greater than the rehabilitation level corresponding to the auxiliary treatment is determined to be achieved, and the target achievement status of the preset auxiliary treatment course under each preset rehabilitation level that is less than the rehabilitation level corresponding to the auxiliary treatment is determined to be unachieved.

[0046] Based on the rehabilitation treatment achievement status of each preset auxiliary treatment course under each preset rehabilitation level, the corresponding relationship of the first achievement rate is obtained.

[0047] In one optional embodiment of this application, the first compliance rate correspondence acquisition module is specifically used for:

[0048] For each preset auxiliary treatment course at each preset rehabilitation level, the ratio of the number of times the target was achieved in each auxiliary treatment session of the preset auxiliary treatment course at that preset rehabilitation level to the total number of auxiliary treatment sessions is taken as the target achievement rate of the preset auxiliary treatment course at that preset rehabilitation level.

[0049] The corresponding relationship between the first target achievement rate of each preset auxiliary treatment course under each preset rehabilitation level is obtained.

[0050] In one optional embodiment of this application, the rehabilitation impact attributes include the age and basic physical condition data of the target patient;

[0051] The module for obtaining the second pass rate correspondence is specifically used for:

[0052] Based on the age of the target patient, at least one target pre-set auxiliary treatment course is determined from each pre-set auxiliary treatment course, and based on the physical condition data of the target patient, at least one target pre-set rehabilitation level is determined from each pre-set rehabilitation level;

[0053] Based on at least one target preset auxiliary treatment course and at least one target preset rehabilitation level, a second target achievement rate correspondence is determined from the first achievement rate correspondence.

[0054] In one optional embodiment of this application, the more consecutive auxiliary treatments included in each target preset auxiliary treatment course, the older the target patient is; the better the target patient's physical condition data indicates, the higher the corresponding target preset rehabilitation level.

[0055] In one optional embodiment of this application, the second compliance rate correspondence acquisition module is specifically used for:

[0056] Retain the achievement rates corresponding to at least one target preset auxiliary treatment course and at least one target preset rehabilitation level in the first achievement rate correspondence, and set the other achievement rates to zero or delete the correspondences corresponding to other achievement rates to obtain the second achievement rate correspondence.

[0057] In one optional embodiment of this application, the weighted compliance rate acquisition module is specifically used for:

[0058] Based on the number of times the target was achieved in each auxiliary treatment state corresponding to each preset auxiliary treatment course, the rehabilitation weight corresponding to each preset auxiliary treatment course was obtained.

[0059] Based on the correspondence between each rehabilitation weight and the second achievement rate, the weighted achievement rate corresponding to each preset rehabilitation level is obtained, including:

[0060] For each preset rehabilitation level, the achievement rate of the preset rehabilitation level under each preset auxiliary treatment course is weighted and summed according to the corresponding rehabilitation weights to obtain the weighted achievement rate corresponding to the preset rehabilitation level.

[0061] In one optional embodiment of this application, the greater the number of times the target is met in each auxiliary treatment state corresponding to the target preset auxiliary treatment course, the greater the rehabilitation weight corresponding to the target preset auxiliary treatment course.

[0062] In an optional embodiment of this application, the device further includes a treatment plan correspondence acquisition module, used for:

[0063] Obtain the correspondence between treatment plans. The treatment plan correspondence stores the correspondence between different preset rehabilitation levels and treatment plans.

[0064] The treatment plan acquisition module is specifically used for:

[0065] Based on the predicted rehabilitation level, the corresponding treatment plan is obtained from the treatment plan correspondence, and the treatment plan is used as the target patient to determine the next auxiliary rehabilitation treatment plan.

[0066] Thirdly, embodiments of this application provide an electronic device, including a memory and a processor;

[0067] The memory contains computer programs;

[0068] A processor for executing computer programs to implement the methods provided in the first aspect embodiment or any alternative embodiment of the first aspect.

[0069] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method provided in the first aspect embodiment or any optional embodiment of the first aspect.

[0070] Fifthly, embodiments of this application provide a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method provided in the first aspect embodiment or any optional embodiment of the first aspect.

[0071] The beneficial effects of the technical solution provided in this application are:

[0072] By expanding the auxiliary treatment achievement status of multiple auxiliary rehabilitation treatments for target patients, a first achievement rate correspondence is obtained, representing the achievement rate of different preset auxiliary treatment courses under different preset rehabilitation levels. Then, based on the rehabilitation impact of the target patient, a second achievement rate correspondence, representing the achievement rate of different target preset auxiliary treatment courses under different target preset rehabilitation levels, is obtained. Then, based on the second achievement rate correspondence, the weighted achievement rate corresponding to each target preset rehabilitation level is obtained. Then, based on each target preset rehabilitation level and the corresponding weighted achievement rate, a neural network is used to predict the target patient's predicted rehabilitation level. Finally, based on the predicted rehabilitation level, a treatment plan for the next auxiliary rehabilitation treatment is obtained. This scheme obtains the predicted rehabilitation level by considering the target patient's rehabilitation level and corresponding auxiliary treatment achievement status in the previous auxiliary rehabilitation treatments, making the obtained rehabilitation level more accurate, and thus making the treatment plan determined based on the predicted rehabilitation level more accurate and more conducive to the patient's rehabilitation.

[0073] Other beneficial effects of this scheme in one or more aspects will be described in the specific implementation. Attached Figure Description

[0074] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below.

[0075] Figure 1 A flowchart illustrating an assisted rehabilitation data processing method provided in an embodiment of this application;

[0076] Figure 2 A structural block diagram of an assisted rehabilitation data processing system provided in an embodiment of this application;

[0077] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0078] The embodiments of this application are described below with reference to the accompanying drawings. It should be understood that the embodiments described below with reference to the accompanying drawings are exemplary descriptions for explaining the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions of the embodiments of this application.

[0079] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the terms “comprising” and “including” as used in embodiments of this application mean that the corresponding feature can be implemented as the presented feature, information, data, step, operation, element, and / or component, but do not exclude implementation as other features, information, data, step, operation, element, component, and / or combinations thereof supported by the art. It should be understood that when we say that an element is “connected” or “coupled” to another element, the one element can be directly connected or coupled to the other element, or it can mean that the one element and the other element establish a connection relationship through an intermediate element. Furthermore, “connected” or “coupled” as used herein can include wireless connection or wireless coupling. The term “and / or” as used herein indicates at least one of the items defined by the term; for example, “A and / or B” can be implemented as “A,” or as “B,” or as “A and B.”

[0080] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0081] Figure 1 This is a flowchart illustrating an assisted rehabilitation data processing method provided in an embodiment of this application, as shown below. Figure 1 As shown, the method may include:

[0082] Step S101: Obtain auxiliary rehabilitation data of the target patient from multiple auxiliary rehabilitation treatments, and obtain the corresponding rehabilitation level and auxiliary treatment achievement status based on the auxiliary rehabilitation data of each auxiliary rehabilitation treatment.

[0083] The target patients are those who need corresponding auxiliary rehabilitation treatment after suffering from a specific disease.

[0084] Among them, the status of achievement of auxiliary treatment includes whether the target is met or not. This status is determined based on the treatment results and relevant standards. In other words, it is determined based on auxiliary rehabilitation data and relevant standards.

[0085] Specifically, the process involves acquiring auxiliary rehabilitation data from multiple completed auxiliary rehabilitation treatments of the target patient. This data can originate from various medical devices used in the auxiliary rehabilitation treatments or from diagnoses provided by the medical personnel involved. After preprocessing, this data is compared with relevant standards to determine the target patient's rehabilitation level and treatment achievement status after each auxiliary rehabilitation treatment. It should be noted that multiple preset rehabilitation levels can be determined based on relevant standards.

[0086] For example, for a specific target patient, the rehabilitation level and achievement status of multiple auxiliary rehabilitation treatments can be shown in Table 1:

[0087]

[0088] Step S102: Based on the rehabilitation level and target achievement status corresponding to each auxiliary rehabilitation treatment, expand the target achievement status to obtain the first target achievement rate correspondence for the target patient. The first target achievement rate correspondence indicates the target achievement rate of different preset auxiliary treatment courses under different preset rehabilitation levels. Different preset auxiliary treatment courses correspond to different consecutive auxiliary rehabilitation treatment times.

[0089] In this embodiment, multiple preset rehabilitation levels can be set in advance, such as preset rehabilitation levels 1-6. The higher the preset rehabilitation level, the better the rehabilitation status. Multiple preset auxiliary treatment courses can also be set in advance. Each preset auxiliary treatment course includes multiple consecutive auxiliary rehabilitation treatments, and each preset auxiliary treatment course is determined by taking values ​​consecutively from the most recent auxiliary rehabilitation treatment to an earlier time. For example, three preset auxiliary treatment courses X1, X2, and X3 are preset. X1 includes two consecutive auxiliary rehabilitation treatments (the 3rd and 4th in Table 1), X2 includes three consecutive auxiliary rehabilitation treatments (the 2nd, 3rd, and 4th in Table 1), and X3 includes four consecutive auxiliary rehabilitation treatments (the 1st, 2nd, 3rd, and 4th in Table 1).

[0090] Specifically, the first correspondence table is obtained, that is, the achievement rate of each preset auxiliary treatment course under different preset rehabilitation levels is obtained. However, as shown in Table 1, the rehabilitation level of the target patient corresponding to each auxiliary rehabilitation treatment in a preset auxiliary treatment course does not cover the preset rehabilitation levels. Therefore, it is necessary to expand the achievement status based on the rehabilitation level and achievement status of each auxiliary rehabilitation treatment.

[0091] Specifically, based on the rehabilitation level and achievement status of each auxiliary rehabilitation treatment, the achievement status is expanded to obtain the first achievement rate correspondence for the target patient. This includes: for each auxiliary treatment in each preset auxiliary treatment course, obtaining the rehabilitation level and achievement status of that auxiliary treatment; if the achievement status of the auxiliary treatment is non-achievement, then the achievement status of the auxiliary treatment course under different preset rehabilitation levels is determined to be non-achievement; if the achievement status of the auxiliary treatment is achievement, then the achievement status of the rehabilitation treatment course under each preset rehabilitation level greater than the rehabilitation level of the auxiliary treatment is determined to be achievement, and the achievement status of the rehabilitation treatment course under each preset rehabilitation level less than the rehabilitation level of the auxiliary treatment is determined to be non-achievement.

[0092] Based on the rehabilitation treatment achievement status of each preset auxiliary treatment course under each preset rehabilitation level, the first achievement rate correspondence is obtained.

[0093] For example, by expanding, we can obtain Table 2:

[0094]

[0095] In Table 1, for the first assisted rehabilitation treatment, the corresponding rehabilitation level is level 2, and the assisted treatment achievement status is "achieved". Following the principles of this application, all rehabilitation levels below level 2 correspond to "unachieved" assisted treatment achievement status, while all rehabilitation levels of level 2 and above correspond to "achieved". For the second assisted rehabilitation treatment, the corresponding rehabilitation level is level 3, and the assisted treatment achievement status is "unachieved". Following the principles of this application, all rehabilitation levels correspond to "unachieved" assisted treatment achievement status. Therefore, after obtaining Table 2, the achievement rate of each preset assisted treatment course at each preset rehabilitation level can be obtained. For example, the achievement rate of X1 at rehabilitation level 1 is 0, and the achievement rate of X4 at rehabilitation level 2 is 0.25. The first achievement rate correspondence can be shown in Table 3.

[0096]

[0097] Step S103: Based on the rehabilitation impact attributes of the target patient, determine the second target achievement rate correspondence from the first target achievement rate correspondence. The second target achievement rate correspondence indicates the achievement rate of different target preset auxiliary treatment courses under different target preset rehabilitation levels.

[0098] The rehabilitation impact attributes of the target patient can include intrinsic attributes such as the patient's age and basic physical condition data that influence their assisted rehabilitation treatment. Generally, older patients require more consecutive assisted rehabilitation treatments, and better basic physical condition data corresponds to a higher rehabilitation level. Specifically, basic physical condition data can be obtained by accessing the target patient's routine medical examination results.

[0099] Specifically, based on the rehabilitation impact attributes of the target patient, a partial achievement rate, along with the corresponding preset auxiliary treatment course (i.e., the target preset auxiliary treatment course) and preset rehabilitation level (i.e., the target preset rehabilitation level) are obtained from the first achievement rate correspondence, thus forming the second achievement rate correspondence for the target patient. Compared to the first achievement rate correspondence, this second achievement rate correspondence has a stronger correlation with the target patient and can improve the accuracy of subsequent rehabilitation level prediction.

[0100] For example, the corresponding relationship of the second compliance rate determined from Table 3 above can be shown in Table 4:

[0101]

[0102] Step S104: Obtain the rehabilitation weight corresponding to each target preset auxiliary treatment course, and obtain the weighted achievement rate corresponding to each target preset rehabilitation level based on the correspondence between each rehabilitation weight and the second achievement rate.

[0103] Specifically, after obtaining the correspondence between the second target attainment rates, the weighted attainment rate corresponding to each preset rehabilitation level can be obtained. For example, for Table 4, if the rehabilitation weight of X2 is determined to be 0.1 and the rehabilitation weight of X3 is determined to be 0.9, then the weighted attainment rates corresponding to each preset rehabilitation level are shown in Table 5:

[0104]

[0105] Step S105: Based on the preset rehabilitation levels of each target and the corresponding weighted achievement rate, the predicted rehabilitation level of the target patient is determined from the preset rehabilitation levels of each target through the preset rehabilitation level prediction model, and the treatment plan for the next auxiliary rehabilitation treatment is determined for the target patient based on the predicted rehabilitation level.

[0106] The rehabilitation level prediction model can be a pre-set and trained neural network model. Its purpose is to determine the predicted rehabilitation level and the corresponding treatment plan. After implementing the corresponding treatment plan for assisted rehabilitation, the model aims to ensure that the target patient's rehabilitation indicators for a specific disease reach the optimal state under the predicted rehabilitation level. This model may include a preprocessing module and a fully connected module. The preprocessing module preprocesses the input target preset rehabilitation levels and their corresponding weighted achievement rates. Then, the fully connected layer executes the aforementioned optimization logic, outputting the probability of each target preset rehabilitation level as the predicted rehabilitation level. The target preset rehabilitation level with the highest probability is selected as the predicted rehabilitation level.

[0107] Specifically, after obtaining the predicted recovery level, that is, the accurate recovery level of the target patient, the corresponding treatment plan is determined based on the predicted recovery level.

[0108] The solution provided in this application expands upon the target patient's achievement status during multiple auxiliary rehabilitation treatments to obtain a first achievement rate correspondence representing the achievement rate of different preset auxiliary treatment courses under different preset rehabilitation levels. Then, based on the target patient's rehabilitation impact, a more relevant second achievement rate correspondence representing the achievement rate of different target preset auxiliary treatment courses under different target preset rehabilitation levels is obtained. Next, based on the second achievement rate correspondence, a weighted achievement rate corresponding to each target preset rehabilitation level is obtained. Then, based on each target preset rehabilitation level and its corresponding weighted achievement rate, a neural network is used to predict the target patient's predicted rehabilitation level. Finally, based on this predicted rehabilitation level, a treatment plan for the next auxiliary rehabilitation treatment is obtained. This solution obtains the predicted rehabilitation level by considering the target patient's rehabilitation level and corresponding auxiliary treatment achievement status during previous auxiliary rehabilitation treatments, making the obtained rehabilitation level more accurate. Consequently, the treatment plan determined based on the predicted rehabilitation level is also more accurate and more beneficial to the patient's rehabilitation.

[0109] In one optional embodiment of this application, the achievement status is expanded based on the rehabilitation level and achievement status of each assisted rehabilitation treatment to obtain the first achievement rate correspondence for the target patient, including:

[0110] For each pre-set auxiliary treatment course, obtain the corresponding rehabilitation level and auxiliary treatment achievement status for that auxiliary treatment;

[0111] If the target achievement status of the auxiliary treatment is not met, then the target achievement status of the auxiliary treatment course under different preset rehabilitation levels will be determined as not met.

[0112] If the target achievement status of the auxiliary treatment is achieved, then the target achievement status of the preset auxiliary treatment course under each preset rehabilitation level that is greater than the rehabilitation level corresponding to the auxiliary treatment is determined to be achieved, and the target achievement status of the preset auxiliary treatment course under each preset rehabilitation level that is less than the rehabilitation level corresponding to the auxiliary treatment is determined to be unachieved.

[0113] Based on the rehabilitation treatment achievement status of each preset auxiliary treatment course under each preset rehabilitation level, the corresponding relationship of the first achievement rate is obtained.

[0114] Specifically, based on the rehabilitation treatment attainment status of each preset auxiliary treatment course under each preset rehabilitation level, a first attainment rate correspondence is obtained, including: for each preset auxiliary treatment course under each preset rehabilitation level, the ratio of the number of attainment times in the auxiliary treatment status of each preset auxiliary treatment course under that preset rehabilitation level to the total number of auxiliary treatments is used as the attainment rate of that preset auxiliary treatment course under that preset rehabilitation level; and the first attainment rate correspondence is obtained for each preset auxiliary treatment course under each preset rehabilitation level.

[0115] In one optional embodiment of this application, the rehabilitation impact attributes include the age and basic physical condition data of the target patient;

[0116] Based on the rehabilitation impact attributes of the target patients, a second target achievement rate correspondence is determined from the first target achievement rate correspondence, including:

[0117] Based on the age of the target patient, at least one target pre-set auxiliary treatment course is determined from each pre-set auxiliary treatment course, and based on the physical condition data of the target patient, at least one target pre-set rehabilitation level is determined from each pre-set rehabilitation level;

[0118] Based on at least one target preset auxiliary treatment course and at least one target preset rehabilitation level, a second target achievement rate correspondence is determined from the first achievement rate correspondence.

[0119] Specifically, the older the target patient, the weaker their recovery ability, and the more consecutive auxiliary treatments are required; conversely, the younger the patient, the stronger their recovery ability, and the fewer consecutive auxiliary treatments are required. The better the target patient's physical condition data indicates, the higher the corresponding rehabilitation level; conversely, the lower the corresponding rehabilitation level. In other words, the corresponding target-preset auxiliary treatment courses and target-preset rehabilitation levels can be selected based on the target patient's age and physical condition data, thus determining the second target achievement rate. In other words, the older the target patient, the more consecutive auxiliary treatments are included in each target-preset auxiliary treatment course; the better the target patient's physical condition data indicates, the higher the corresponding target-preset rehabilitation level.

[0120] Specifically, based on at least one target preset auxiliary treatment course and at least one target preset rehabilitation level, a second target achievement rate correspondence is determined from the first achievement rate correspondence, including: retaining the achievement rates corresponding to at least one target preset auxiliary treatment course and at least one target preset rehabilitation level in the first achievement rate correspondence, and setting other achievement rates to zero or deleting other achievement rate correspondences to obtain the second achievement rate correspondence.

[0121] For example, the corresponding relationship of the second compliance rate in Table 4 can also be shown in Table 6 below:

[0122]

[0123] In one optional embodiment of this application, obtaining the rehabilitation weight corresponding to each target preset auxiliary treatment course includes:

[0124] Based on the number of times the target was achieved in each auxiliary treatment state corresponding to each preset auxiliary treatment course, the rehabilitation weight corresponding to each preset auxiliary treatment course was obtained.

[0125] Based on the correspondence between each rehabilitation weight and the second achievement rate, the weighted achievement rate corresponding to each preset rehabilitation level is obtained, including:

[0126] For each preset rehabilitation level, the achievement rate of the preset rehabilitation level under each preset auxiliary treatment course is weighted and summed according to the corresponding rehabilitation weights to obtain the weighted achievement rate corresponding to the preset rehabilitation level.

[0127] Specifically, when obtaining the predicted rehabilitation level of the target patient using a neural network model, it is necessary to select one from different preset rehabilitation levels as the prediction result. This allows us to obtain the achievement rate corresponding to different preset rehabilitation levels. When obtaining this achievement rate, the rehabilitation weights of different preset auxiliary treatment courses need to be considered, and then a weighted average is calculated to obtain the corresponding weighted achievement rate. Specifically, the greater the number of times the target is achieved in each auxiliary treatment state within the target preset auxiliary treatment course, the greater the rehabilitation weight corresponding to the target preset auxiliary treatment course.

[0128] In one optional embodiment of this application, the method further includes:

[0129] Obtain the correspondence between treatment plans. The treatment plan correspondence stores the correspondence between different preset rehabilitation levels and treatment plans.

[0130] Based on the predicted rehabilitation level, a treatment plan for the next auxiliary rehabilitation therapy is determined for the target patient, including:

[0131] Based on the predicted rehabilitation level, the corresponding treatment plan is obtained from the treatment plan correspondence, and the treatment plan is used as the target patient to determine the next auxiliary rehabilitation treatment plan.

[0132] Specifically, in the process of obtaining the rehabilitation level, the neural network model also needs to call the corresponding relationship of the treatment plan to obtain the treatment plan corresponding to each different preset rehabilitation level.

[0133] Figure 2 This application provides a structural block diagram of an assisted rehabilitation data processing system. The system 200 includes: an assisted rehabilitation data acquisition module 201, a first target achievement rate correspondence acquisition module 202, a second target achievement rate correspondence acquisition module 203, a weighted target achievement rate acquisition module 204, and a treatment plan acquisition module 205, wherein:

[0134] The auxiliary rehabilitation data acquisition module 201 is used to acquire auxiliary rehabilitation data of multiple auxiliary rehabilitation treatments of the target patient, and to acquire the corresponding rehabilitation level and auxiliary treatment achievement status based on the auxiliary rehabilitation data of each auxiliary rehabilitation treatment.

[0135] The first target achievement rate correspondence acquisition module 202 is used to expand the target achievement status based on the rehabilitation level and target achievement status of each auxiliary rehabilitation treatment, and to obtain the first target achievement rate correspondence for the target patient. The first target achievement rate correspondence indicates the target achievement rate of different preset auxiliary treatment courses under different preset rehabilitation levels. Different preset auxiliary treatment courses correspond to different consecutive auxiliary rehabilitation treatments.

[0136] The second achievement rate correspondence acquisition module 203 is used to determine the second achievement rate correspondence from the first achievement rate correspondence based on the rehabilitation impact attributes of the target patient. The second achievement rate correspondence indicates the achievement rate of different target preset auxiliary treatment courses under different target preset rehabilitation levels.

[0137] The weighted achievement rate acquisition module 204 is used to acquire the rehabilitation weights corresponding to each target preset auxiliary treatment course, and to acquire the weighted achievement rate corresponding to each target preset rehabilitation level based on the correspondence between each rehabilitation weight and the second achievement rate.

[0138] The treatment plan acquisition module 205 is used to determine the predicted rehabilitation level of the target patient from the preset rehabilitation levels of each target based on the preset rehabilitation level and the corresponding weighted achievement rate, and to determine the treatment plan for the next auxiliary rehabilitation treatment for the target patient based on the predicted rehabilitation level.

[0139] The solution provided in this application expands upon the target patient's achievement status during multiple auxiliary rehabilitation treatments to obtain a first achievement rate correspondence representing the achievement rate of different preset auxiliary treatment courses under different preset rehabilitation levels. Then, based on the target patient's rehabilitation impact, a second achievement rate correspondence is obtained, representing the achievement rate of different target preset auxiliary treatment courses under different target preset rehabilitation levels. Next, based on the second achievement rate correspondence, a weighted achievement rate corresponding to each target preset rehabilitation level is obtained. Then, based on each target preset rehabilitation level and its corresponding weighted achievement rate, a neural network is used to predict the target patient's predicted rehabilitation level. Finally, based on this predicted rehabilitation level, a treatment plan for the next auxiliary rehabilitation treatment is obtained. This solution obtains the predicted rehabilitation level by considering the target patient's rehabilitation level and corresponding auxiliary treatment achievement status during previous auxiliary rehabilitation treatments, making the obtained rehabilitation level more accurate. Consequently, the treatment plan determined based on the predicted rehabilitation level is also more accurate and more beneficial to the patient's rehabilitation.

[0140] In one optional embodiment of this application, the first compliance rate correspondence acquisition module is specifically used for:

[0141] For each pre-set auxiliary treatment course, obtain the corresponding rehabilitation level and auxiliary treatment achievement status for that auxiliary treatment;

[0142] If the target achievement status of the auxiliary treatment is not met, then the target achievement status of the auxiliary treatment course under different preset rehabilitation levels will be determined as not met.

[0143] If the target achievement status of the auxiliary treatment is achieved, then the target achievement status of the preset auxiliary treatment course under each preset rehabilitation level that is greater than the rehabilitation level corresponding to the auxiliary treatment is determined to be achieved, and the target achievement status of the preset auxiliary treatment course under each preset rehabilitation level that is less than the rehabilitation level corresponding to the auxiliary treatment is determined to be unachieved.

[0144] Based on the rehabilitation treatment achievement status of each preset auxiliary treatment course under each preset rehabilitation level, the corresponding relationship of the first achievement rate is obtained.

[0145] In one optional embodiment of this application, the first compliance rate correspondence acquisition module is specifically used for:

[0146] For each preset auxiliary treatment course at each preset rehabilitation level, the ratio of the number of times the target was achieved in each auxiliary treatment session of the preset auxiliary treatment course at that preset rehabilitation level to the total number of auxiliary treatment sessions is taken as the target achievement rate of the preset auxiliary treatment course at that preset rehabilitation level.

[0147] The corresponding relationship between the first target achievement rate of each preset auxiliary treatment course under each preset rehabilitation level is obtained.

[0148] In one optional embodiment of this application, the rehabilitation impact attributes include the age and basic physical condition data of the target patient;

[0149] The module for obtaining the second pass rate correspondence is specifically used for:

[0150] Based on the age of the target patient, at least one target pre-set auxiliary treatment course is determined from each pre-set auxiliary treatment course, and based on the physical condition data of the target patient, at least one target pre-set rehabilitation level is determined from each pre-set rehabilitation level;

[0151] Based on at least one target preset auxiliary treatment course and at least one target preset rehabilitation level, a second target achievement rate correspondence is determined from the first achievement rate correspondence.

[0152] In one optional embodiment of this application, the more consecutive auxiliary treatments included in each target preset auxiliary treatment course, the older the target patient is; the better the target patient's physical condition data indicates, the higher the corresponding target preset rehabilitation level.

[0153] In one optional embodiment of this application, the second compliance rate correspondence acquisition module is specifically used for:

[0154] Retain the achievement rates corresponding to at least one target preset auxiliary treatment course and at least one target preset rehabilitation level in the first achievement rate correspondence, and set the other achievement rates to zero or delete the correspondences corresponding to other achievement rates to obtain the second achievement rate correspondence.

[0155] In one optional embodiment of this application, the weighted compliance rate acquisition module is specifically used for:

[0156] Based on the number of times the target was achieved in each auxiliary treatment state corresponding to each preset auxiliary treatment course, the rehabilitation weight corresponding to each preset auxiliary treatment course was obtained.

[0157] Based on the correspondence between each rehabilitation weight and the second achievement rate, the weighted achievement rate corresponding to each preset rehabilitation level is obtained, including:

[0158] For each preset rehabilitation level, the achievement rate of the preset rehabilitation level under each preset auxiliary treatment course is weighted and summed according to the corresponding rehabilitation weights to obtain the weighted achievement rate corresponding to the preset rehabilitation level.

[0159] In one optional embodiment of this application, the greater the number of times the target is met in each auxiliary treatment state corresponding to the target preset auxiliary treatment course, the greater the rehabilitation weight corresponding to the target preset auxiliary treatment course.

[0160] In an optional embodiment of this application, the device further includes a treatment plan correspondence acquisition module, used for:

[0161] Obtain the correspondence between treatment plans. The treatment plan correspondence stores the correspondence between different preset rehabilitation levels and treatment plans.

[0162] The treatment plan acquisition module is specifically used for:

[0163] Based on the predicted rehabilitation level, the corresponding treatment plan is obtained from the treatment plan correspondence, and the treatment plan is used as the target patient to determine the next auxiliary rehabilitation treatment plan.

[0164] The following is for reference. Figure 3 It illustrates an electronic device suitable for implementing embodiments of the present disclosure (e.g., performing...). Figure 1 The diagram shows the structure of the terminal device or server 300 of the method shown. The electronic devices in this disclosure may include, but are not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), wearable devices, etc., as well as fixed terminals such as digital TVs, desktop computers, etc. Figure 3The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0165] The electronic device includes a memory and a processor. The memory stores a program for executing the methods described in the various method embodiments above. The processor is configured to execute the program stored in the memory. The processor may be referred to as processing device 301 as described below. The memory may include at least one of read-only memory (ROM) 302, random access memory (RAM) 303, and storage device 308 as described below, as follows:

[0166] like Figure 3 As shown, the electronic device 300 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the electronic device 300. The processing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0167] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic device 300 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have alternatively.

[0168] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 309, or installed from storage device 308, or installed from ROM 302. When the computer program is executed by processing device 301, it performs the functions defined in the methods of embodiments of this disclosure.

[0169] It should be noted that the computer-readable storage medium described in this disclosure can be a computer-readable signal medium, a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0170] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0171] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0172] The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to:

[0173] The process involves acquiring auxiliary rehabilitation data from multiple auxiliary rehabilitation treatments for the target patient, and obtaining the corresponding rehabilitation level and achievement status based on the data from each auxiliary rehabilitation treatment. Based on the rehabilitation level and achievement status of each auxiliary rehabilitation treatment, the achievement status is expanded to obtain a first achievement rate correspondence for the target patient. This first achievement rate correspondence indicates the achievement rate of different preset auxiliary treatment courses at different preset rehabilitation levels, with different preset auxiliary treatment courses corresponding to different consecutive auxiliary rehabilitation treatments. Based on the rehabilitation impact attributes of the target patient, a second achievement rate correspondence is determined from the first achievement rate correspondence. This second achievement rate correspondence indicates the achievement rate of different target preset auxiliary treatment courses at different target preset rehabilitation levels. The process involves acquiring the rehabilitation weights corresponding to each target preset auxiliary treatment course, and obtaining the weighted achievement rate corresponding to each target preset rehabilitation level based on the rehabilitation weights and the second achievement rate correspondence. Based on each target preset rehabilitation level and the corresponding weighted achievement rate, a preset rehabilitation level prediction model is used to determine the predicted rehabilitation level for the target patient from each target preset rehabilitation level, and a treatment plan for the next auxiliary rehabilitation treatment is determined based on the predicted rehabilitation level.

[0174] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0175] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0176] The modules or units described in the embodiments of this disclosure can be implemented in software or hardware. The names of the modules or units do not necessarily limit the specific unit itself.

[0177] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), and so on.

[0178] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0179] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific methods implemented by the computer-readable medium described above when executed by an electronic device can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0180] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0181] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0182] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A method for processing rehabilitation data, characterized in that, include: Obtain auxiliary rehabilitation data from multiple auxiliary rehabilitation treatments for the target patient, and obtain the corresponding rehabilitation level and auxiliary treatment achievement status based on the auxiliary rehabilitation data from each auxiliary rehabilitation treatment; Based on the rehabilitation level and target achievement status corresponding to each auxiliary rehabilitation treatment, the target achievement status is expanded to obtain the first target achievement rate correspondence relationship for the target patient. The first target achievement rate correspondence relationship indicates the target achievement rate of different preset auxiliary treatment courses under different preset rehabilitation levels. Different preset auxiliary treatment courses correspond to different consecutive auxiliary rehabilitation treatment times. Based on the rehabilitation impact attributes of the target patients, a second target achievement rate correspondence is determined from the first target achievement rate correspondence. The second target achievement rate correspondence indicates the achievement rate of different target preset auxiliary treatment courses under different target preset rehabilitation levels. Obtain the rehabilitation weights corresponding to each target preset auxiliary treatment course, and obtain the weighted achievement rate corresponding to each target preset rehabilitation level based on the correspondence between each rehabilitation weight and the second achievement rate; Based on the preset rehabilitation levels of each target and the corresponding weighted achievement rate, the predicted rehabilitation level of the target patient is determined from the preset rehabilitation levels of each target through a preset rehabilitation level prediction model, and a treatment plan for the next auxiliary rehabilitation treatment is determined for the target patient based on the predicted rehabilitation level. Based on the rehabilitation level and achievement status corresponding to each assisted rehabilitation treatment, the achievement status is expanded to obtain the first achievement rate correspondence for the target patient, including: For each adjuvant therapy session in each preset adjuvant therapy course, obtain the corresponding rehabilitation level and adjuvant therapy achievement status for that adjuvant therapy session; If the target achievement status of the auxiliary treatment is not met, then the target achievement status of the auxiliary treatment course under different preset rehabilitation levels will be determined as not met. If the target achievement status of the auxiliary treatment is achieved, then the target achievement status of the preset auxiliary treatment course under each preset rehabilitation level that is greater than the rehabilitation level corresponding to the auxiliary treatment is determined to be achieved, and the target achievement status of the preset auxiliary treatment course under each preset rehabilitation level that is less than the rehabilitation level corresponding to the auxiliary treatment is determined to be unachieved. Based on the rehabilitation treatment achievement status of each preset auxiliary treatment course under each preset rehabilitation level, the first achievement rate correspondence is obtained.

2. The method according to claim 1, characterized in that, The process of obtaining the first achievement rate correspondence based on the rehabilitation treatment achievement status of each preset auxiliary treatment course at each preset rehabilitation level includes: For each preset auxiliary treatment course at each preset rehabilitation level, the ratio of the number of times the target was achieved in each auxiliary treatment session of the preset auxiliary treatment course at that preset rehabilitation level to the total number of auxiliary treatment sessions is taken as the target achievement rate of the preset auxiliary treatment course at that preset rehabilitation level. The rehabilitation treatment attainment status of each preset auxiliary treatment course under each preset rehabilitation level is used to obtain the first attainment rate correspondence.

3. The method according to claim 1, characterized in that, The rehabilitation impact attributes include the age and basic physical condition data of the target patient; The step of determining a second target achievement rate correspondence from the first target achievement rate correspondence based on the rehabilitation impact attributes of the target patient includes: Based on the age of the target patient, at least one target preset auxiliary treatment course is determined from each preset auxiliary treatment course, and based on the physical condition data of the target patient, at least one target preset rehabilitation level is determined from each preset rehabilitation level; Based on the at least one target preset auxiliary treatment course and the at least one target preset rehabilitation level, the second target attainment rate correspondence is determined from the first attainment rate correspondence.

4. The method according to claim 3, characterized in that, The older the target patient is, the more consecutive auxiliary treatments are included in each target preset auxiliary treatment course; the better the target patient's physical condition data indicates, the higher the corresponding target preset rehabilitation level.

5. The method according to claim 3, characterized in that, The step of determining the second achievement rate correspondence from the first achievement rate correspondence based on the at least one target preset auxiliary treatment course and the at least one target preset rehabilitation level includes: The first achievement rate correspondence relationship is obtained by retaining the achievement rates corresponding to at least one target preset auxiliary treatment course and at least one target preset rehabilitation level, and setting other achievement rates to zero or deleting the correspondence relationships corresponding to other achievement rates.

6. The method according to claim 1, characterized in that, The step of obtaining the rehabilitation weights corresponding to each target preset auxiliary treatment course includes: Based on the number of times the target was achieved in each auxiliary treatment state corresponding to each preset auxiliary treatment course, the rehabilitation weight corresponding to each preset auxiliary treatment course was obtained. The step of obtaining the weighted attainment rate corresponding to each preset rehabilitation level based on the correspondence between each rehabilitation weight and the second attainment rate includes: For each preset rehabilitation level, the achievement rate of the preset rehabilitation level under each preset auxiliary treatment course is weighted and summed according to the corresponding rehabilitation weights to obtain the weighted achievement rate corresponding to the preset rehabilitation level.

7. The method according to claim 6, characterized in that, The greater the number of times the target is met in each auxiliary treatment state during the target preset auxiliary treatment course, the greater the rehabilitation weight corresponding to the target preset auxiliary treatment course.

8. The method according to claim 1, characterized in that, The method further includes: Obtain the treatment plan correspondence, which stores the correspondence between different preset rehabilitation levels and treatment plans; The process of determining the next adjunctive rehabilitation treatment plan for the target patient based on the predicted rehabilitation level includes: Based on the predicted rehabilitation level, the corresponding treatment plan is obtained from the treatment plan correspondence, and the treatment plan is used as the treatment plan for the next auxiliary rehabilitation treatment of the target patient.

9. A data processing system for assisting rehabilitation, characterized in that, include: The auxiliary rehabilitation data acquisition module is used to acquire auxiliary rehabilitation data of multiple auxiliary rehabilitation treatments of the target patient, and to obtain the corresponding rehabilitation level and auxiliary treatment achievement status based on the auxiliary rehabilitation data of each auxiliary rehabilitation treatment. The first achievement rate correspondence acquisition module is used to expand the achievement status based on the rehabilitation level and achievement status of each auxiliary rehabilitation treatment, and to obtain the first achievement rate correspondence for the target patient. The first achievement rate correspondence indicates the achievement rate of different preset auxiliary treatment courses under different preset rehabilitation levels. Different preset auxiliary treatment courses correspond to different consecutive auxiliary rehabilitation treatments. The second target achievement rate correspondence acquisition module is used to determine the second target achievement rate correspondence from the first target achievement rate correspondence based on the rehabilitation impact attributes of the target patient. The second target achievement rate correspondence indicates the target achievement rate of different target preset auxiliary treatment courses under different target preset rehabilitation levels. The weighted achievement rate acquisition module is used to acquire the rehabilitation weights corresponding to each target preset auxiliary treatment course, and to acquire the weighted achievement rate corresponding to each target preset rehabilitation level based on the correspondence between each rehabilitation weight and the second achievement rate. The treatment plan acquisition module is used to determine the predicted rehabilitation level of the target patient from the preset rehabilitation levels of each target patient based on each preset rehabilitation level and the corresponding weighted achievement rate, and to determine the treatment plan for the next auxiliary rehabilitation treatment for the target patient based on the predicted rehabilitation level. Based on the rehabilitation level and achievement status corresponding to each assisted rehabilitation treatment, the achievement status is expanded to obtain the first achievement rate correspondence for the target patient, including: For each adjuvant therapy session in each preset adjuvant therapy course, obtain the corresponding rehabilitation level and adjuvant therapy achievement status for that adjuvant therapy session; If the target achievement status of the auxiliary treatment is not met, then the target achievement status of the auxiliary treatment course under different preset rehabilitation levels will be determined as not met. If the target achievement status of the auxiliary treatment is achieved, then the target achievement status of the preset auxiliary treatment course under each preset rehabilitation level that is greater than the rehabilitation level corresponding to the auxiliary treatment is determined to be achieved, and the target achievement status of the preset auxiliary treatment course under each preset rehabilitation level that is less than the rehabilitation level corresponding to the auxiliary treatment is determined to be unachieved. Based on the rehabilitation treatment achievement status of each preset auxiliary treatment course under each preset rehabilitation level, the first achievement rate correspondence is obtained.

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