CN118280520B - Orthopedic rehabilitation training data model construction method - Google Patents
Orthopedic rehabilitation training data model construction method Download PDFInfo
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- 238000012549 training Methods 0.000 title claims abstract description 75
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Abstract
The invention discloses a method for constructing an orthopedic rehabilitation training data model; according to the invention, through comprehensively evaluating the physiological, clinical and image information of the patient, a basic evaluation model of the patient is constructed, the overall health condition of the patient can be more intuitively understood, the physical state grade of the patient is further obtained by matching, the rehabilitation training model set suitable for the patient is obtained according to the obtained physical state grade, the rehabilitation training model with the top three using times is selected from the set to serve as the initial model set of the patient, the intelligent degree is improved, and the time of medical staff is saved; and sending the health evaluation index of the patient and the initial model set to a mobile terminal of a corresponding selected medical staff, and after the medical staff adjusts and optimizes, taking the adjusted and optimized model as a rehabilitation training model of the patient in a set rehabilitation training time period, so that the construction of a personalized rehabilitation training model of the patient is realized, and the subsequent training effect is improved.
Description
Technical Field
The invention relates to the technical field of orthopedic rehabilitation training, in particular to a method for constructing an orthopedic rehabilitation training data model.
Background
At present, the postoperative patient of the orthopedic surgery needs to perform rehabilitation training, and the life quality and the activity capacity of the patient are recovered through the rehabilitation training.
However, in the prior art, when a rehabilitation training plan is provided for a patient, a general training scheme is mostly adopted, an individualized rehabilitation training data model cannot be built according to the actual condition of the patient and the evaluation of doctors, and the individualized adjustment for individual differences is lacking, so that the training effect is poor and safety risks exist;
Meanwhile, the training model cannot be updated again at the end of each rehabilitation training time period according to the progress and feedback of the patient, so that the training scheme cannot be updated in time to adapt to the change of the patient, and the effect is poor.
Therefore, a method for constructing an orthopedic rehabilitation training data model is provided.
Disclosure of Invention
In view of the above, the present invention provides a method for constructing an orthopedic rehabilitation training data model to solve the problems set forth in the above background art.
The aim of the invention can be achieved by the following technical scheme: a method for constructing an orthopedic rehabilitation training data model comprises the following steps:
S1: acquiring rehabilitation training related data of a patient, wherein the rehabilitation training related data comprise personal information, physical examination information, physiological information, clinical information and image information of the patient;
S2: respectively carrying out comprehensive evaluation processing on physiological information, clinical information and image information of a patient to obtain a physiological value PL1, a clinical evaluation value PL2 and an image evaluation value PL3; taking a physiological value PL1, a clinical evaluation value PL2 and an image evaluation value PL3 of a patient as length, width and height values of a three-dimensional rectangle to construct a three-dimensional rectangle model, and taking the three-dimensional rectangle model as a basic evaluation model of the patient;
S3: performing comprehensive evaluation processing based on physical examination information of the patient to obtain a health evaluation index ST of the patient; meanwhile, matching basic evaluation models constructed by the patient, and selecting a rehabilitation training model with top three using times as an initial model set of the patient based on a matching result;
s4: transmitting the health assessment index ST of the patient and the initial model set to a preferential value On the largest medical staff mobile terminal, the medical staff comprehensively evaluates the selected initial model set and the actual condition of the patient, selects a group of models from the initial model set, and further adjusts and optimizes the selected models according to the health evaluation index ST of the patient; taking the adjusted and optimized model as a rehabilitation training model in a rehabilitation training time period set by the patient;
S5: and when the patient reaches the ending time point of the set rehabilitation training time period, the steps S1-S4 are repeated, and the training model in the next set rehabilitation training time period is selected again.
In some embodiments, the physiological information of the patient is comprehensively evaluated, specifically:
Acquiring physiological information of a patient, including joint movement and muscle capacity of the patient; measuring the joint mobility of the same joint on both sides of the patient, and acquiring and recording the maximum buckling angle and the maximum stretching angle of each joint;
for each joint, calculating its range of motion; repeating the same measurement on the joints at both sides to obtain respective movable ranges; comparing the difference of the two-side joint movement ranges, and calculating through (larger movement range-lower movement range)/lower movement range multiplied by 100 percent to obtain the difference percentage of the target two-side joint;
Calculating the average value of the difference percentages obtained by calculation of the bilateral joints of each group, and taking the calculated average value as the joint shape value ga of the patient;
Performing strength test on muscle groups of a patient, recording the strength test result of each muscle group, extracting the gender and age of the patient from the personal data information of the patient, acquiring the passing strength value of each muscle group of the patient based on the gender and age of the patient, calculating the ratio of the recorded strength test result of each muscle group to the corresponding passing strength value, accumulating the calculated ratios of each group, and taking the accumulated value as the muscle-like value gb of the patient;
Setting reference values corresponding to the joint values and the muscle values based on the age and the sex of the patient, and marking as AndAnd substituting the above parameters into the formulaPerforming weighted calculation to obtain a physiological value PL1 of the patient; wherein the method comprises the steps ofAndThe influence weight factors of the joint value ga and the muscle value gb, respectively.
In some embodiments, the comprehensive evaluation process is performed on clinical information and image information of a patient, specifically:
Performing Katz evaluation on the patient to evaluate the daily life capacity and the capacity level of each activity item; and recording the ability scores of all the activity items; adding all scores to obtain total score, and matching the obtained total score with four preset value ranges to obtain the corresponding capability level of the patient; the corresponding capability level is specifically a full-dependence level, a partial-dependence level, a slight-dependence level and an independent self-care level, and corresponds to four value ranges respectively;
setting each capability level to correspond to a vitality value, wherein the vitality value range is set to 3-6 and is a positive integer, and the capability levels correspond to the capability levels respectively, and converting the corresponding capability level obtained by a patient into the vitality value as a clinical evaluation value PL2 of the patient;
Acquiring image data of a patient, transmitting the image data of the patient to a mobile terminal of medical staff with the least amount of image data to be processed at the current time point, performing grade assessment by the medical staff after acquiring the image data of the patient, dividing the assessment grade of the image data into severe damage, moderate damage, general damage and mild damage, setting image scores corresponding to the grades, wherein the setting range of the image scores is 1-4 and is a positive integer; the obtained image grade is converted into a corresponding image score as an image evaluation value PL3 of the patient.
In some embodiments, the comprehensive assessment process is performed based on physical examination information of the patient, specifically:
Extracting blood biochemical indexes from physical examination information of a patient; setting a normal reference value of a corresponding parameter in the blood biochemical index, marking the parameter of which the corresponding parameter is not in the set normal reference value in the blood biochemical index as an abnormal parameter, and marking all the abnormal parameters as abnormal index information; utilizing formula for abnormal index information Performing weighted calculation to obtain a blood test value Ph1; wherein Vk represents a value corresponding to a parameter number k in the abnormality index information, N represents a set of parameters in the abnormality index information,The weight factor corresponding to the parameter k in the abnormal index information is represented;
extracting psychological health detection results of each time of patient history from physical examination information of a patient; assessing the mental health detection report by using the mental health standardized assessment to obtain a heart health value; summing the heart health values of each group obtained by evaluation and taking an average value to obtain a heart detection value Ph2;
According to the formula Weighting calculation is carried out on the blood test value Ph1 and the heart test value Ph2 of the patient, and a health evaluation index ST of the patient is obtained; wherein the method comprises the steps ofAndThe influence weight factors of the blood test value Ph1 and the heart test value Ph2 of the patient are respectively.
In some embodiments, the matching of the patient-constructed basic assessment model is performed, in particular:
Acquiring a three-dimensional rectangular model constructed by a patient, calculating the surface area of the three-dimensional rectangular model, and matching the calculated surface area with a preset value range of each area; each area value range corresponds to a physical state grade of a patient; obtaining a physical state grade of the patient; physical status grades include good, general, poor, and critical; and extracting a rehabilitation training model set applicable to the physical state grade from the database, and selecting a rehabilitation training model with the top three using times from the set as an initial model set of the patient.
In some embodiments, a healthcare worker preference value is obtainedThe method comprises the following steps:
Acquiring the physical state grade of the patient, setting each physical state grade to correspond to a medical care personnel reference set respectively, and matching the physical state grade obtained by the patient to obtain the medical care personnel reference set for providing services for the patient;
Extracting the number of the initial model sets to be processed of each medical staff in the medical staff reference set and marking the number as Ea; further acquiring the continuous working time of each medical staff and marking as Eb; extracting patient evaluation data of each medical staff from a database, scoring the medical staff providing service by the patient based on a scoring range of 1-5 when the visit is completed, counting the total number of patient evaluations of each medical staff and each evaluation scoring value, taking the average value of each evaluation scoring value as an evaluation average value, setting weight coefficients of the evaluation average value and the evaluation total number, multiplying the evaluation average value and the evaluation total number by the set weight coefficients respectively, and then summing to obtain a kernel evaluation value Ec of the medical staff;
According to the formula Calculating to obtain the preference value of each medical staff; Wherein the method comprises the steps of、AndThe influence weight factors of the number Ea of the initial model sets to be processed, the duration Eb and the kernel evaluation value Ec are respectively;
Selecting a preferred value of the current time point The largest medical staff is used as the target staff for sending the patient health assessment index ST and the initial model set, and the number of the initial model sets to be processed of the medical staff is increased by one.
Compared with the prior art, the invention has the beneficial effects that:
According to the invention, through comprehensively evaluating the physiological, clinical and image information of the patient, a basic evaluation model of the patient is constructed, the overall health condition of the patient can be more intuitively understood, the physical state grade of the patient is further obtained by matching, the rehabilitation training model set suitable for the patient is obtained according to the obtained physical state grade, the rehabilitation training model with the top three using times is selected from the set to serve as the initial model set of the patient, the intelligent degree is improved, and the time of medical staff is saved; the health evaluation index and the initial model set of the patient are sent to the mobile terminal of the corresponding selected medical staff, after the medical staff adjusts and optimizes, the adjusted and optimized model is used as a rehabilitation training model of the patient in a set rehabilitation training time period, so that the construction of a personalized rehabilitation training model of the patient is realized, and the subsequent training effect is improved;
According to the invention, the corresponding medical staff reference sets are matched according to the physical state level of the patient, so that the patient is ensured to obtain corresponding experience and level medical service, the accuracy of follow-up optimization and adjustment of the models is improved, the rehabilitation effect of the patient is improved, the quantity of the initial model sets to be processed and the lasting working time of the medical staff are considered, the intelligent patient distribution is realized, and meanwhile, the kernel evaluation value of the medical staff is added, so that the medical staff with the best performance can be selected, and the satisfaction degree and the trust degree of the patient on the medical service are improved;
According to the invention, through the set rehabilitation training time period, the constructed model can be updated in real time according to the rehabilitation training state of the patient, so that the degree of intelligence is improved.
Drawings
Further details, features and advantages of the application are disclosed in the following description of exemplary embodiments with reference to the following drawings, in which:
FIG. 1 is a flow chart of the present invention.
Detailed Description
Several embodiments of the present application will be described in more detail below with reference to the accompanying drawings in order to enable those skilled in the art to practice the application. The present application may be embodied in many different forms and objects and should not be limited to the embodiments set forth herein. These embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the application to those skilled in the art. The examples do not limit the application.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and/or the present specification and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
Referring to fig. 1, a method for constructing an orthopedic rehabilitation training data model includes:
S1: acquiring rehabilitation training related data of a patient, wherein the rehabilitation training related data comprise personal information, physical examination information, physiological information, clinical information and image information of the patient;
S2: respectively carrying out comprehensive evaluation processing on physiological information, clinical information and image information of a patient to obtain a physiological value PL1, a clinical evaluation value PL2 and an image evaluation value PL3; further correlating the physiological value PL1, the clinical evaluation value PL2 and the image evaluation value PL3 of the patient, thereby constructing a basic evaluation model of the patient;
The method comprises the following steps:
S2-101: acquiring physiological information of a patient, including joint movement and muscle capacity of the patient; measuring the joint mobility of the same joint on both sides of the patient, and acquiring and recording the maximum buckling angle and the maximum stretching angle of each joint;
For each joint, calculating its range of motion; the angular difference of the finger joint from full extension to full flexion, for example, if the maximum flexion angle of the left knee joint is 120 degrees and the maximum extension angle is 0 degrees, the range of motion is 120 degrees; repeating the same measurement on the joints at both sides to obtain respective movable ranges; comparing the difference of the two-side joint movement ranges, and calculating through (larger movement range-lower movement range)/lower movement range multiplied by 100 percent to obtain the difference percentage of the target two-side joint;
Calculating the average value of the difference percentages obtained by calculation of the bilateral joints of each group, and taking the calculated average value as the joint shape value ga of the patient;
It should be noted that, the larger the calculated articulation value is, the larger the degree of difference between the bilateral joints is, and the limitation exists on the joint function; the calculated articulation value is used as one of evaluation standards of rehabilitation training, so that the accuracy of model construction is improved.
Performing a strength test on a critical muscle group of the patient; key muscle groups include hip abductor groups, hip flexor groups, and knee flexor groups; recording the strength test result of each muscle group, extracting the sex and age of the patient from the personal data information of the patient, acquiring the passing strength value of each muscle group of the patient based on the sex and age of the patient, calculating the ratio of the recorded strength test result of each muscle group to the corresponding passing strength value, accumulating the calculated ratios of each group, and taking the accumulated value as the muscle-like value gb of the patient;
it should be noted that, the larger the calculated muscle-like value is, the passing value of the corresponding age and sex is represented by the exceeding of each muscle strength of the patient; the calculated muscle-like value is used as one of evaluation standards of rehabilitation training, so that the accuracy of model construction is further improved.
Setting reference values corresponding to the joint values and the muscle values based on the age and the sex of the patient, and marking asAndAnd substituting the above parameters into the formulaPerforming weighted calculation to obtain a physiological value PL1 of the patient; wherein the method comprises the steps ofAndThe influence weight factors of the joint value ga and the muscle value gb are respectively set to be 1.035 and 1.039 respectively;
It should be noted that, by comprehensively considering the articular value and the muscular value and weighting and calculating to obtain the physiological value, the physiological condition of the patient can be estimated more accurately, so as to improve the accuracy and reliability of model construction.
S2-102: performing Katz evaluation on the patient to evaluate the daily life capacity and the capacity level of each activity item; the activity items include bathing, dressing, toilet, getting up and down, eating and controlling excretion; and recording the ability scores of all the activity items; the capacity grading range of each activity item is set to be 1-3 and is a positive integer; adding all scores to obtain total score, and matching the obtained total score with four preset value ranges to obtain the corresponding capability level of the patient; the corresponding capability level is specifically a full-dependence level, a partial-dependence level, a slight-dependence level and an independent self-care level, and corresponds to four value ranges respectively;
For example, the total score may be specifically set to "6-9 to be classified as a full dependency level", "10-13 to be classified as a partial dependency level", "13-15 to be classified as a mild dependency level", "15-18 to be classified as an independent self-care level";
setting each capability level to correspond to a vitality value, wherein the vitality value range is set to 3-6 and is a positive integer, and the capability levels correspond to the capability levels respectively, and converting the corresponding capability level obtained by a patient into the vitality value as a clinical evaluation value PL2 of the patient; wherein the higher the total score, the higher the corresponding activity value;
It should be noted that, the clinical evaluation value is used as one of the evaluation criteria, which can objectively reflect the living state of the patient and provide scientific basis for the construction of the subsequent model.
S2-103: acquiring image data of a patient; the image data is X-ray, MRI or CT scanning image data; transmitting the acquired image data of the patient to a mobile terminal of medical staff with the least amount of image data to be processed at the current time point, performing grade assessment on the image data of the patient by the medical staff, dividing the assessment grade of the image data into severe damage, moderate damage, general damage and mild damage, setting image scores corresponding to the grades, wherein the setting range of the image scores is 1-4 and is a positive integer; wherein the lower the injury level of the patient, the higher the corresponding image score;
converting the obtained image grade into a corresponding image score to be used as an image estimated value PL3 of the patient;
it should be noted that, taking the image data of the patient as one of the evaluation standards for constructing the rehabilitation training model improves the comprehensiveness of the data analysis and the later rehabilitation effect.
S2-104: taking a physiological value PL1, a clinical evaluation value PL2 and an image evaluation value PL3 of a patient as length, width and height values of a three-dimensional rectangle to construct a three-dimensional rectangle model, and taking the three-dimensional rectangle model as a basic evaluation model of the patient;
It should be noted that, by integrating a plurality of evaluation indexes into a three-dimensional rectangular model, the overall health condition of the patient can be more intuitively understood; the surface area of the three-dimensional rectangular model reflects the physical state of the patient, and the larger the surface area is, the worse the overall state of the patient is represented.
S3: performing comprehensive evaluation processing based on physical examination information of the patient to obtain a health evaluation index ST of the patient; meanwhile, matching basic evaluation models constructed by the patient, and selecting a rehabilitation training model with top three using times as an initial model set of the patient based on a matching result;
The method comprises the following steps:
s3-101: extracting blood biochemical indexes from physical examination information of a patient; the biochemical indexes of blood comprise corresponding values of blood fat, blood sugar, red blood cells, hemoglobin and white blood cells; setting a normal reference value of a corresponding parameter in the blood biochemical index, marking the parameter of which the corresponding parameter is not in the set normal reference value in the blood biochemical index as an abnormal parameter, and marking all the abnormal parameters as abnormal index information; utilizing formula for abnormal index information Performing weighted calculation to obtain a blood test value Ph1; wherein Vk represents a value corresponding to a parameter number k in the abnormality index information, N represents a set of parameters in the abnormality index information,The weight factor corresponding to the parameter k in the abnormal index information is represented;
It should be noted that the blood test value Ph1 reflects the current biochemical level and health condition of the patient, and provides a basis for subsequent adjustment and optimization of the rehabilitation model. For example, if the patient's blood glucose level is high, more aerobic exercises may need to be added to the training to help control blood glucose.
Extracting psychological health detection results of each time of patient history from physical examination information of a patient; assessing the mental health detection report by using the mental health standardized assessment to obtain a heart health value; summing the heart health values of each group obtained by evaluation and taking an average value to obtain a heart detection value Ph2; the higher the cardiac value Ph2, the better the psychological state of health of the patient;
It should be noted that, the good psychological state is crucial to the rehabilitation training effect, and the psychological health state of the patient is analyzed, so that a basis is provided for the adjustment and optimization of the follow-up rehabilitation model.
S3-102: according to the formulaWeighting calculation is carried out on the blood test value Ph1 and the heart test value Ph2 of the patient, and a health evaluation index ST of the patient is obtained; wherein the method comprises the steps ofAndThe influence weight factors of the blood test value Ph1 and the heart test value Ph2 of the patient are respectively set to be 1.135 and 1.124 respectively;
It should be noted that the health evaluation index ST integrates the biochemical level and psychological health state of the patient, and provides a comprehensive health condition index, and this comprehensive evaluation helps to understand the overall health condition of the patient more accurately, and provides scientific basis for rehabilitation training.
S3-103: acquiring a three-dimensional rectangular model constructed by a patient, calculating the surface area of the three-dimensional rectangular model, and matching the calculated surface area with a preset value range of each area; each area value range corresponds to the physical state grade of a patient, and the larger the surface area is, the higher the matched physical state grade is; obtaining a physical state grade of the patient; physical status grades include good, general, poor, and critical; extracting a rehabilitation training model set applicable to the physical state grade from a database, and selecting a rehabilitation training model with top three using times from the set as an initial model set of a patient; the area value range is set by medical staff based on historical data and professional medical knowledge, and the set time period can be updated; the database comprises rehabilitation training models with multiple physical state levels, and each model has a targeted training target and method;
S4: the health evaluation index ST of the patient and the initial model set are sent to a mobile terminal of a medical staff selected correspondingly; the transmission of data is accomplished through an encrypted network connection and a data processing protocol conforming to healthcare standards; the medical staff comprehensively evaluates the selected initial model set and the actual condition of the patient, selects a group of models from the initial model set, and further adjusts and optimizes the selected models according to the health evaluation index ST of the patient; the adjustment and optimization specifically adjusts and optimizes the training targets and methods of the patient; taking the adjusted and optimized model as a rehabilitation training model in a rehabilitation training time period set by the patient; meanwhile, the model after adjustment and optimization is used as a newly established rehabilitation training model and is integrated into a database;
obtain the optimal value of medical staff The method comprises the following steps:
S4-101: acquiring the physical state grade of the patient, and setting each physical state grade to correspond to a medical care personnel reference set respectively; the higher the physical state level of the patient is, the higher the experience and level of the medical staff in the corresponding medical staff reference set is; matching the physical state grades of the patients to obtain a medical staff reference set for providing services for the patients;
S4-102: extracting the number of the initial model sets to be processed of each medical staff in the medical staff reference set and marking the number as Ea; further acquiring the continuous working time of each medical staff and marking as Eb and unit hour; extracting patient evaluation data of each medical staff from a database, scoring the medical staff providing service by the patient based on a scoring range of 1-5 when the visit is completed, counting the total number of patient evaluations of each medical staff and each evaluation scoring value, taking the average value of each evaluation scoring value as an evaluation average value, setting weight coefficients of the evaluation average value and the evaluation total number, multiplying the evaluation average value and the evaluation total number by the set weight coefficients respectively, and then summing to obtain a kernel evaluation value Ec of the medical staff;
S4-103: according to the formula Calculating to obtain the preference value of each medical staff; Wherein the method comprises the steps of、AndThe number Ea of the initial model sets to be processed, the duration Eb and the kernel evaluation value Ec are respectively set as the influence weight factors, and the values are respectively set as 1.235, 1.238 and 1.314;
S4-104: selecting a preferred value of the current time point The largest medical staff is used as a target staff for sending the patient health evaluation index ST and the initial model set, and meanwhile, the number of the initial model sets to be processed of the medical staff is increased by one;
It should be noted that, by matching the corresponding reference sets of medical staff according to the physical state level of the patient, the patient is ensured to obtain corresponding experience and level medical service, meanwhile, the accuracy of the follow-up optimization and adjustment of the model is improved, the rehabilitation effect of the patient is improved, the quantity Ea of the initial model sets to be processed and the lasting working time Eb of the medical staff are considered, the intelligent patient distribution is realized, meanwhile, the kernel evaluation value Ec of the medical staff is added, and the medical staff with the best performance can be selected, so that the satisfaction degree and the trust degree of the patient on the medical service are improved.
S5: and when the patient reaches the ending time point of the set rehabilitation training time period, the steps S1-S4 are repeated, and the training model in the next set rehabilitation training time period is selected again.
It is to be noted that, the real-time update can be performed according to the rehabilitation training state of the patient, and the intelligent degree is improved.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (2)
1. The method for constructing the orthopedic rehabilitation training data model is characterized by comprising the following steps of:
S1: acquiring rehabilitation training related data of a patient, wherein the rehabilitation training related data comprise personal information, physical examination information, physiological information, clinical information and image information of the patient;
S2: respectively carrying out comprehensive evaluation processing on physiological information, clinical information and image information of a patient to obtain a physiological value PL1, a clinical evaluation value PL2 and an image evaluation value PL3; taking a physiological value PL1, a clinical evaluation value PL2 and an image evaluation value PL3 of a patient as length, width and height values of a three-dimensional rectangle to construct a three-dimensional rectangle model, and taking the three-dimensional rectangle model as a basic evaluation model of the patient;
the physiological information of the patient is comprehensively evaluated, and the method specifically comprises the following steps:
Acquiring physiological information of a patient, including joint movement and muscle capacity of the patient; measuring the joint mobility of the same joint on both sides of the patient, and acquiring and recording the maximum buckling angle and the maximum stretching angle of each joint;
for each joint, calculating its range of motion; repeating the same measurement on the joints at both sides to obtain respective movable ranges; comparing the difference of the two-side joint movement ranges, and calculating through (larger movement range-lower movement range)/lower movement range multiplied by 100 percent to obtain the difference percentage of the target two-side joint;
Calculating the average value of the difference percentages obtained by calculation of the bilateral joints of each group, and taking the calculated average value as the joint shape value ga of the patient;
Performing strength test on muscle groups of a patient, recording the strength test result of each muscle group, extracting the gender and age of the patient from the personal data information of the patient, acquiring the passing strength value of each muscle group of the patient based on the gender and age of the patient, calculating the ratio of the recorded strength test result of each muscle group to the corresponding passing strength value, accumulating the calculated ratios of each group, and taking the accumulated value as the muscle-like value gb of the patient;
Setting reference values corresponding to the joint values and the muscle values based on the age and the sex of the patient, and marking as AndAnd substituting the above parameters into the formulaPerforming weighted calculation to obtain a physiological value PL1 of the patient; wherein the method comprises the steps ofAndInfluence weight factors of the joint value ga and the muscle value gb, respectively;
the comprehensive evaluation processing is carried out on the clinical information and the image information of the patient, and specifically comprises the following steps:
Performing Katz evaluation on the patient to evaluate the daily life capacity and the capacity level of each activity item; and recording the ability scores of all the activity items; adding all scores to obtain total score, and matching the obtained total score with four preset value ranges to obtain the corresponding capability level of the patient; the corresponding capability level is specifically a full-dependence level, a partial-dependence level, a slight-dependence level and an independent self-care level, and corresponds to four value ranges respectively;
setting each capability level to correspond to a vitality value, wherein the vitality value range is set to 3-6 and is a positive integer, and the capability levels correspond to the capability levels respectively, and converting the corresponding capability level obtained by a patient into the vitality value as a clinical evaluation value PL2 of the patient;
Acquiring image data of a patient, transmitting the image data of the patient to a mobile terminal of medical staff with the least amount of image data to be processed at the current time point, performing grade assessment by the medical staff after acquiring the image data of the patient, dividing the assessment grade of the image data into severe damage, moderate damage, general damage and mild damage, setting image scores corresponding to the grades, wherein the setting range of the image scores is 1-4 and is a positive integer; converting the obtained image grade into a corresponding image score to be used as an image estimated value PL3 of the patient;
S3: performing comprehensive evaluation processing based on physical examination information of the patient to obtain a health evaluation index ST of the patient; meanwhile, matching basic evaluation models constructed by the patient, and selecting a rehabilitation training model with top three using times as an initial model set of the patient based on a matching result;
The comprehensive evaluation processing is carried out based on physical examination information of patients, specifically:
Extracting blood biochemical indexes from physical examination information of a patient; setting a normal reference value of a corresponding parameter in the blood biochemical index, marking the parameter of which the corresponding parameter is not in the set normal reference value in the blood biochemical index as an abnormal parameter, and marking all the abnormal parameters as abnormal index information; utilizing formula for abnormal index information Performing weighted calculation to obtain a blood test value Ph1; wherein Vk represents a value corresponding to a parameter number k in the abnormality index information, N represents a set of parameters in the abnormality index information,The weight factor corresponding to the parameter k in the abnormal index information is represented;
extracting psychological health detection results of each time of patient history from physical examination information of a patient; assessing the mental health detection report by using the mental health standardized assessment to obtain a heart health value; summing the heart health values of each group obtained by evaluation and taking an average value to obtain a heart detection value Ph2;
According to the formula Weighting calculation is carried out on the blood test value Ph1 and the heart test value Ph2 of the patient, and a health evaluation index ST of the patient is obtained; wherein the method comprises the steps ofAndThe influence weight factors of the blood test value Ph1 and the heart test value Ph2 of the patient are respectively;
s4: transmitting the health assessment index ST of the patient and the initial model set to a preferential value On the largest medical staff mobile terminal, the medical staff comprehensively evaluates the selected initial model set and the actual condition of the patient, selects a group of models from the initial model set, and further adjusts and optimizes the selected models according to the health evaluation index ST of the patient; taking the adjusted and optimized model as a rehabilitation training model in a rehabilitation training time period set by the patient;
obtain the preferred value of each medical staff The specific steps of (a) are as follows:
Acquiring the physical state grade of the patient, setting each physical state grade to correspond to a medical care personnel reference set respectively, and matching the physical state grade obtained by the patient to obtain the medical care personnel reference set for providing services for the patient;
Extracting the number of the initial model sets to be processed of each medical staff in the medical staff reference set and marking the number as Ea; further acquiring the continuous working time of each medical staff and marking as Eb; extracting patient evaluation data of each medical staff from a database, scoring the medical staff providing service by the patient based on a scoring range of 1-5 when the visit is completed, counting the total number of patient evaluations of each medical staff and each evaluation scoring value, taking the average value of each evaluation scoring value as an evaluation average value, setting weight coefficients of the evaluation average value and the evaluation total number, multiplying the evaluation average value and the evaluation total number by the set weight coefficients respectively, and then summing to obtain a kernel evaluation value Ec of the medical staff;
According to the formula Calculating to obtain the preference value of each medical staff; Wherein the method comprises the steps of、AndThe influence weight factors of the number Ea of the initial model sets to be processed, the duration Eb and the kernel evaluation value Ec are respectively;
Selecting a preferred value of the current time point The largest medical staff is used as a target staff for sending the patient health evaluation index ST and the initial model set, and meanwhile, the number of the initial model sets to be processed of the medical staff is increased by one;
S5: and when the patient reaches the ending time point of the set rehabilitation training time period, the steps S1-S4 are repeated, and the training model in the next set rehabilitation training time period is selected again.
2. The method for constructing an orthopedic rehabilitation training data model according to claim 1, wherein the matching of the basic evaluation model constructed by the patient is specifically as follows:
Acquiring a three-dimensional rectangular model constructed by a patient, calculating the surface area of the three-dimensional rectangular model, and matching the calculated surface area with a preset value range of each area; each area value range corresponds to a physical state grade of a patient; obtaining a physical state grade of the patient; physical status grades include good, general, poor, and critical; and extracting a rehabilitation training model set applicable to the physical state grade from the database, and selecting a rehabilitation training model with the top three using times from the set as an initial model set of the patient.
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