Thalamus function connection network feature data management system for massage therapy of KOA patients

Abstract

The invention provides a thalamus function connection network feature data management system for a KOA patient in massage treatment. The system comprises a data acquisition module, a data processing module, a data management module and a thalamus feature database, wherein the data acquisition module is used for acquiring experimental data of each sample object; the data processing module is used for analyzing environment and tester performance data, evaluating sample object environment quality, tester performance and data validity, and screening effective samples; the data management module is used for performing comprehensive analysis according to the pain threshold data of each effective sample object to obtain a pain threshold state evaluation value of each effective sample object; performing comprehensive analysis according to the pain threshold state evaluation value of each effective sample object and the effectiveness evaluation value of each effective sample object to obtain a reference value evaluation value of each effective sample object, and managing the thalamus function connection network feature data according to the reference value evaluation value of each effective sample object.

Description

Technical Field

[0001] The present invention relates to the technical field of brain structure management, and in particular to a thalamus functional connection network characteristic data management system for massage treatment of KOA patients. Background Art

[0002] Knee osteoarthritis is a common degenerative joint disease, characterized by degenerative changes in articular cartilage and secondary bone hyperplasia, which can cause knee pain, dysfunction and deformity, and may be accompanied by bone friction sound. Currently, the preferred treatment for KOA is non-drug and non-surgical. At the same time, good pain management can effectively reduce the surgical rate of total knee replacement.

[0003] In recent years, researchers have gradually realized that the persistence and chronicity of KOA pain is closely related to the neural circuits that encode and process pathological pain information in the cerebral cortex. KOA pain affects the function and structure of the brain by changing the flow and integration of information between different brain regions.

[0004] For example, the patent application with publication number: CN118737365A discloses an intelligent diagnosis and treatment method and system for knee osteoarthritis based on machine learning technology, including: a data preprocessing module, used to obtain a KOA database; a feature extraction module, used to obtain multiple feature quantities in the KOA database; a KOA feature screening module, extracting key feature sets from multiple feature quantities; a KOA rehabilitation treatment effect simulation module, simulating the state of the patient at the next time point after adopting the initial treatment plan according to the key feature set; a KOA rehabilitation treatment decision module, which recommends the treatment plan that the patient should choose within a preset time through preset decision rules; and a KOA intelligent treatment auxiliary decision module, which optimizes the KOA rehabilitation treatment decision module by learning the optimal strategy function to obtain the optimal treatment plan.

[0005] For example, the invention patent with announcement number CN113952677B discloses a treatment and rehabilitation device for knee joint degenerative lesions based on KOAPT therapy, which includes: a positive and comfortable relationship data collection component, a movement volume collection component, a movement support component, a control component, and a feedback component. The positive and comfortable relationship data collection component is used to collect the positive and comfortable relationship data under the user's use status; the movement volume collection component is used to collect the movement volume data under the user's use status; the movement support component is used to provide the user with trunk support and / or waist support and / or elbow support; the control component is used to execute the KOAPT computer program deployed in the control device and output control instructions; the feedback component is used to send audio and / or video and / or tactile signals to the user according to the control instructions.

[0006] However, in the process of implementing the technical solution of the present invention, the present invention finds that the above technology has at least the following technical problems:

[0007] In the prior art, it is not fully considered that the pain tester will be affected differently in different environments, and there is a problem of low accuracy of the patient's thalamic functional connection network characteristic data. Summary of the invention

[0008] The present invention provides a thalamic functional connection network characteristic data management system for massage treatment of KOA patients, which is not only comprehensive, accurate, efficient, intelligent, scientific and standardized, but also can provide strong support for in-depth research on massage treatment of KOA, promote the progress and development of related medical technologies, and ultimately improve the accuracy of patients' thalamic functional connection network characteristic data.

[0009] The embodiment of the present invention provides a thalamic functional connection network characteristic data management system for massage treatment of KOA patients, comprising: a data acquisition module, a data processing module, a data management module and a thalamic characteristic database; wherein the data acquisition module is used to acquire experimental data of each sample object, including thalamic functional connection network characteristic data, pain tester performance data, experimental environment data and pain threshold data; the data processing module is used to obtain an environmental quality evaluation value of each sample object according to a comprehensive analysis of the experimental environment data, and obtain a validity evaluation correction value of each sample object data according to matching of the environmental quality evaluation value of each sample object, and obtain a tester performance evaluation value of each sample object according to a comprehensive analysis of the pain tester performance data, The effectiveness evaluation value of each sample object data is obtained by comprehensive analysis based on the environmental quality evaluation value of each sample object and the tester performance evaluation value of each sample object, and each valid sample object is screened based on the effectiveness evaluation value of each sample object data and the effectiveness evaluation correction value of each sample object data; the data management module is used to obtain the pain threshold state evaluation value of each valid sample object based on the pain threshold data of each valid sample object, obtain the reference value evaluation value of each valid sample object based on the pain threshold state evaluation value of each valid sample object and the effectiveness evaluation value of each valid sample object, and manage the thalamic functional connection network feature data according to the reference value evaluation value of each valid sample object.

[0010] Optionally, the step of obtaining the environmental quality assessment value of each sample object based on comprehensive analysis of the experimental environment data includes: the experimental environment data includes the experimental environment temperature, the experimental environment humidity and the experimental environment electromagnetic interference intensity; obtaining the reference experimental environment temperature, the allowable deviation experimental environment temperature, the reference experimental environment humidity, the allowable deviation experimental environment humidity and the critical experimental environment electromagnetic interference intensity from the thalamus feature database; and obtaining the environmental quality assessment value of each sample object through comprehensive analysis.

[0011] Optionally, the step of obtaining the performance evaluation value of the tester for each sample object through comprehensive analysis based on the performance data of the pain tester includes: the performance data of the pain tester includes working current, working voltage, response time and resolution; obtaining the reference working current, allowable deviation working current, reference working voltage, allowable deviation working voltage, critical response time and critical resolution from the thalamus feature database; and obtaining the performance evaluation value of the tester for each sample object through comprehensive analysis.

[0012] Optionally, the step of obtaining the validity evaluation value of each sample object data by comprehensive analysis based on the environmental quality evaluation value of each sample object and the tester performance evaluation value of each sample object includes: obtaining the critical experimental environment quality evaluation value and the critical tester performance evaluation value from the thalamus feature database; and obtaining the validity evaluation value of each sample object data by comprehensive analysis based on the critical experimental environment quality evaluation value, the critical tester performance evaluation value, the environmental quality evaluation value of each sample object and the tester performance evaluation value of each sample object.

[0013] Optionally, the step of screening and obtaining each valid sample object according to the validity evaluation value of each sample object data and the validity evaluation correction value of each sample object data includes: obtaining a data validity evaluation threshold from a thalamus feature database; comparing the final validity evaluation value of each sample object data with the data validity evaluation threshold, if the final validity evaluation value of a sample object data is greater than or equal to the data validity evaluation threshold, marking the sample object as a valid sample object, if the final validity evaluation value of a sample object data is less than the data validity evaluation threshold, marking the sample object as an invalid sample object, and obtaining each valid sample object by statistics.

[0014] Optionally, the step of obtaining the pain threshold state evaluation value of each valid sample object by comprehensive analysis based on the pain threshold data of each valid sample object includes: the pain threshold data includes the patella center strength value, the medial strength value of the midpoint of the medial edge of the patella, the lateral strength value of the midpoint of the lateral edge of the patella and the upper limb deltoid muscle belly strength value; obtaining the critical patella center strength value, the critical medial strength value of the midpoint of the medial edge of the patella, the critical lateral strength value of the midpoint of the lateral edge of the patella and the critical upper limb deltoid muscle belly strength value from the thalamus feature database; obtaining the pain threshold data of each valid sample object, and comprehensively analyzing to obtain the pain threshold state evaluation value of each valid sample object.

[0015] Optionally, the step of obtaining a reference value evaluation value of each valid sample object by comprehensively analyzing the pain threshold state evaluation value of each valid sample object and the effectiveness evaluation value of each valid sample object includes: dividing the pain threshold state evaluation value into a pain threshold state evaluation value before treatment and a pain threshold state evaluation value after treatment according to the massage treatment time point, performing a difference operation on the pain threshold state evaluation value after treatment and the pain threshold state evaluation value before treatment of each valid sample object, marking the difference result as the pain threshold evaluation difference of each valid sample object, and performing sample classification according to the pain threshold evaluation difference of each valid sample object; and obtaining a reference value evaluation value of each valid sample object by comprehensively analyzing the pain threshold evaluation difference of each valid sample object and the data effectiveness evaluation value of each valid sample object.

[0016] Optionally, the step of classifying samples according to the difference in pain threshold assessment of each valid sample object includes: obtaining an allowable deviation range of the pain threshold state assessment value from a thalamus feature database, and marking the maximum value of the allowable deviation range of the pain threshold state assessment value as the upper limit of the allowable deviation of the pain threshold state assessment value, and marking the minimum value of the allowable deviation range of the pain threshold state assessment value as the lower limit of the allowable deviation of the pain threshold state assessment value; comparing the pain threshold assessment difference of each valid sample object with the allowable deviation range of the pain threshold state assessment value, and if the pain threshold assessment difference of a valid sample object is greater than the pain threshold state assessment value, If the difference in the pain threshold evaluation value of a valid sample object is within the allowable deviation range of the pain threshold state evaluation value, the valid sample object will be marked as a sample object with no effect; if the difference in the pain threshold evaluation value of a valid sample object is less than the allowable deviation lower limit of the pain threshold state evaluation value, the valid sample object will be marked as a sample object with abnormal effect; the expected effect sample objects, the sample objects with no effect and the sample objects with abnormal effect will be counted separately, and marked as each expected effect sample object, each sample object with no effect and each sample object with abnormal effect respectively.

[0017] Optionally, the reference value evaluation value of each valid sample object is obtained as follows:

[0018]

[0019] In the formula, ξR i represents the reference value evaluation value of the i-th valid sample object, α1 represents the reference value evaluation influencing factor corresponding to the pain threshold evaluation difference, α2 represents the reference value evaluation influencing factor corresponding to the effectiveness evaluation value, ξS 0i represents the difference in pain threshold assessment of the i-th valid sample object, ξV 1irepresents the validity evaluation value of the i-th valid sample object, where i is the number of each valid sample object, i=1, 2, 3, ..., N, and N is the total number of valid sample objects.

[0020] Optionally, the step of managing the thalamic functional connection network characteristic data according to the reference value evaluation value of each valid sample object includes: obtaining the thalamic functional connection network characteristic data of each valid sample object; for each expected effect sample object, sorting the thalamic functional connection network characteristic data of each expected effect sample object in descending order according to the reference value evaluation value of each expected effect sample object; for each ineffective sample object and each abnormal effect sample object, screening and detecting the experimental process of each ineffective sample object and each abnormal effect sample object.

[0021] One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:

[0022] 1. The present invention provides a thalamic functional connection network characteristic data management system for massage treatment of KOA patients, so as to efficiently collect and integrate the experimental data of each sample object, realize accurate evaluation of the environmental quality and tester performance of each sample object, and strictly screen the validity of the data, thereby ensuring the accuracy and reliability of subsequent analysis.

[0023] 2. The present invention screens the data of each sample object according to its validity evaluation value, thereby eliminating sample objects with incomplete, inaccurate or interfered data, ensuring that only high-quality data is used for subsequent analysis, thereby improving the accuracy and reliability of data analysis.

[0024] 3. The present invention manages the thalamic functional connection network feature data according to the reference value evaluation value of each valid sample object, so as to organize and classify these data in a targeted manner, make them more orderly and easy to retrieve, and thus improve the efficiency and convenience of data processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A schematic diagram of the structure of a thalamus functional connection network characteristic data management system for massage treatment of KOA patients provided by an embodiment of the present invention;

[0026] Figure 2 A graph showing changes in effectiveness evaluation values ​​of the thalamus functional connection network characteristic data management system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] The embodiment of the present invention solves the problems in the prior art by providing a thalamic functional connection network characteristic data management system for massage treatment of KOA patients, obtains an environmental quality evaluation value of each sample object according to a comprehensive analysis of experimental environment data, obtains a validity evaluation correction value of each sample object data according to matching of the environmental quality evaluation value of each sample object, obtains a tester performance evaluation value of each sample object according to a comprehensive analysis of pain tester performance data, obtains a validity evaluation value of each sample object data according to a comprehensive analysis of the environmental quality evaluation value of each sample object and the tester performance evaluation value of each sample object, and screens each valid sample object according to the validity evaluation value of each sample object data and the validity evaluation correction value of each sample object data; obtains a pain threshold state evaluation value of each valid sample object according to a comprehensive analysis of the pain threshold data of each valid sample object, obtains a reference value evaluation value of each valid sample object according to a comprehensive analysis of the pain threshold state evaluation value of each valid sample object and the validity evaluation value of each valid sample object, and manages the thalamic functional connection network characteristic data according to the reference value evaluation value of each valid sample object, thereby realizing accurate management and effective use of the thalamic functional connection network characteristic data.

[0029] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0030] like Figure 1As shown, an embodiment of the present invention provides a thalamic functional connection network characteristic data management system for massage treatment of KOA patients, including a data acquisition module, a data processing module, a data management module and a thalamic characteristic database; wherein the data acquisition module is used to acquire the experimental data of each sample object, including thalamic functional connection network characteristic data, pain tester performance data, experimental environment data and pain threshold data; the data processing module is used to obtain the environmental quality evaluation value of each sample object according to the comprehensive analysis of the experimental environment data, and obtain the validity evaluation correction value of each sample object data according to the matching of the environmental quality evaluation value of each sample object, and obtain the tester performance evaluation value of each sample object according to the comprehensive analysis of the pain tester performance data , obtain the validity evaluation value of each sample object data according to the comprehensive analysis of the environmental quality evaluation value of each sample object and the performance evaluation value of the tester of each sample object, and screen each valid sample object according to the validity evaluation value of each sample object data and the validity evaluation correction value of each sample object data; the data management module is used to obtain the pain threshold state evaluation value of each valid sample object according to the comprehensive analysis of the pain threshold data of each valid sample object, obtain the reference value evaluation value of each valid sample object according to the comprehensive analysis of the pain threshold state evaluation value of each valid sample object and the validity evaluation value of each valid sample object, and manage the thalamic functional connection network feature data according to the reference value evaluation value of each valid sample object.

[0031] In this embodiment, KOA refers to knee osteoarthritis, which is a joint degenerative disease characterized by wear and degeneration of articular cartilage and regeneration of joint margin and subchondral bone. It is an asymmetric, non-inflammatory disease without systemic signs. This system adopts the functional connectivity (FC) analysis method, focusing on the thalamus, an important brain area for pain signal transmission, and combines clinical behavioral indicators to explore the characteristic changes of the thalamic functional connection network of KOA patients before and after massage intervention, revealing the central mechanism of massage treatment of KOA pain under the guidance of the three-point syndrome differentiation theory (focusing on the combination of lesion site targets, peri-target points and overall symptom characteristics of patients), providing comprehensive and systematic data support for the study of the characteristics of the thalamic functional connection network of KOA patients treated with massage, and providing new clues for the study of the mechanism of action of massage intervention for KOA pain. When the validity assessment correction value of each sample object data is obtained by matching the environmental quality assessment value of each sample object, the environmental quality assessment value of each sample object can be matched with the validity assessment correction value corresponding to each environmental quality assessment value interval preset in the thalamus feature database to obtain the validity assessment correction value of each sample object data. Based on the data and analysis results provided by this system, clinicians can more accurately evaluate the effect of massage therapy and provide support for the formulation of personalized treatment plans.

[0032] In addition, the thalamic feature database is used to store relevant data of the thalamic functional connection network feature data management system of patients with massage therapy for KOA, including: reference experimental environment temperature, allowable deviation experimental environment temperature, reference experimental environment humidity, allowable deviation experimental environment humidity, critical experimental environment electromagnetic interference intensity, experimental environment humidity corresponding to the experimental environment assessment influencing factor and the validity assessment threshold of the sample object data, etc. The data in the thalamic feature database can be obtained by directly summarizing and entering a large number of measurements using advanced neuroimaging technology (such as functional magnetic resonance imaging, electroencephalogram, etc.), or by referring to the research progress and latest results of relevant literature on the impact of massage therapy for KOA on thalamic function.

[0033] Among them, the step of obtaining the environmental quality assessment value of each sample object through comprehensive analysis of the experimental environment data includes: the experimental environment data includes the experimental environment temperature, the experimental environment humidity and the experimental environment electromagnetic interference intensity; obtaining the reference experimental environment temperature, the allowable deviation experimental environment temperature, the reference experimental environment humidity, the allowable deviation experimental environment humidity and the critical experimental environment electromagnetic interference intensity from the thalamus feature database; and obtaining the environmental quality assessment value of each sample object through comprehensive analysis.

[0034] The environmental quality assessment value of each sample object is obtained as follows:

[0035]

[0036] In the formula, ξE 1j represents the experimental environment quality evaluation value of the jth sample object, β1 represents the experimental environment evaluation influencing factor corresponding to the experimental environment temperature, β2 represents the experimental environment evaluation influencing factor corresponding to the experimental environment humidity, β3 represents the experimental environment evaluation influencing factor corresponding to the experimental environment electromagnetic interference intensity, T 1j represents the experimental environment temperature of the jth sample object, T0 represents the reference experimental environment temperature, T2 represents the allowable deviation experimental environment temperature, H 1j represents the experimental environment humidity of the jth sample object, H0 represents the reference experimental environment humidity, H2 represents the allowable deviation experimental environment humidity, and D 1j represents the electromagnetic interference intensity of the experimental environment of the jth sample object, D0 represents the critical electromagnetic interference intensity of the experimental environment, where j is the number of each sample object, j=1, 2, 3, ..., M, and M is the total number of sample objects.

[0037] β1, β2 and β3 are experimental environment assessment influencing factors corresponding to the experimental environment temperature, experimental environment humidity and experimental environment electromagnetic interference intensity preset in the thalamus feature database, respectively, and represent the numerical values ​​of the degree of influence of the experimental environment temperature, experimental environment humidity and experimental environment electromagnetic interference intensity on the experimental environment quality assessment value, and can be directly obtained from the thalamus feature database when used. For example, the experimental environment temperature and the experimental environment assessment influencing factors corresponding to the experimental environment temperature preset in the thalamus feature database form a mapping set, and the experimental environment assessment influencing factors corresponding to the experimental environment temperature are obtained by inputting the mapping set according to the experimental environment temperature; the experimental environment humidity and the experimental environment assessment influencing factors corresponding to the experimental environment humidity preset in the thalamus feature database form a mapping set, and the experimental environment assessment influencing factors corresponding to the experimental environment humidity are obtained by inputting the mapping set according to the experimental environment humidity; the experimental environment electromagnetic interference intensity and the experimental environment assessment influencing factors corresponding to the experimental environment electromagnetic interference intensity preset in the thalamus feature database form a mapping set, and the experimental environment assessment influencing factors corresponding to the experimental environment electromagnetic interference intensity are obtained by inputting the mapping set according to the experimental environment electromagnetic interference intensity, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the influencing factor in this embodiment is between 0 and 1.

[0038] In this embodiment, the experimental environment temperature can be measured using a temperature sensor, the experimental environment humidity can be measured using a humidity sensor, and the experimental environment electromagnetic interference intensity can be obtained by directly measuring the pain tester sensor monitoring point using an electromagnetic field strength meter. The experimental environment temperature, humidity and electromagnetic interference intensity jointly affect the overall quality and stability of the experimental environment. High temperature and high humidity may cause the performance of electronic equipment to decline and increase the risk of electromagnetic interference, and electromagnetic interference may affect the accuracy and reliability of the pain tester, thereby affecting the accuracy of the experimental results. By comprehensively analyzing the values ​​of the experimental environment temperature, humidity and electromagnetic interference intensity, the environmental quality assessment value of each sample object can be accurately obtained, which reflects the overall quality and stability of the experimental environment, thereby providing a reliable basis for subsequent data analysis and processing.

[0039] Among them, the step of obtaining the performance evaluation value of the tester for each sample object through comprehensive analysis of the performance data of the pain tester includes: the performance data of the pain tester includes working current, working voltage, response time and resolution; obtaining the reference working current, allowable deviation working current, reference working voltage, allowable deviation working voltage, critical response time and critical resolution from the thalamus feature database; and obtaining the performance evaluation value of the tester for each sample object through comprehensive analysis.

[0040] The performance evaluation value of each sample object tester is obtained as follows:

[0041]

[0042] Where ξP 1j represents the tester performance evaluation value of the jth sample object, β4 represents the tester performance evaluation influencing factor corresponding to the response time, β5 represents the tester performance evaluation influencing factor corresponding to the resolution, β6 represents the tester performance evaluation influencing factor corresponding to the working current, β7 represents the tester performance evaluation influencing factor corresponding to the working voltage, R 1j represents the response time of the jth sample object, R0 represents the critical response time, P 1j represents the resolution of the jth sample object, P0 represents the critical resolution, E 1j represents the working current of the jth sample object, E0 represents the reference working current, E2 represents the allowable deviation working current, V 1j represents the working voltage of the jth sample object, V0 represents the reference working voltage, and V2 represents the allowable deviation working voltage.

[0043] β4, β5, β6 and β7 are the tester performance evaluation influencing factors corresponding to the working current, working voltage, response time and resolution preset in the thalamus feature database, respectively representing the numerical values ​​of the influence of the working current, working voltage, response time and resolution on the tester performance evaluation value, and can be directly obtained from the thalamus feature database when used. For example, a working current and a tester performance evaluation influencing factor corresponding to the working current preset in the thalamus feature database form a mapping set, and the tester performance evaluation influencing factor corresponding to the working current is obtained according to the working current input mapping set; a working voltage and a tester performance evaluation influencing factor corresponding to the working voltage preset in the thalamus feature database form a mapping set, and the tester performance evaluation influencing factor corresponding to the working voltage is obtained according to the working voltage input mapping set; a response time and a tester performance evaluation influencing factor corresponding to the response time preset in the thalamus feature database form a mapping set, and the tester performance evaluation influencing factor corresponding to the response time is obtained according to the response time input mapping set; a resolution and a tester performance evaluation influencing factor corresponding to the resolution preset in the thalamus feature database form a mapping set, and the tester performance evaluation influencing factor corresponding to the resolution is obtained according to the resolution input mapping set, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the influencing factor in this embodiment is between 0 and 1.

[0044] In this embodiment, the working current is usually measured by an ammeter or a current monitoring function built into the tester, the working voltage can be measured by a voltmeter or a voltage monitoring function built into the tester, the response time refers to the time required for the tester to generate a detectable output signal from receiving an input signal, which can be directly measured by a built-in timer. Since it takes a certain amount of time for the signal to propagate in a physical medium, the response time cannot be 0; the resolution is the minimum signal change that the tester can distinguish, which is directly obtained by looking up the device manual. Among them, the working current and the working voltage jointly determine the power consumption and performance stability of the tester. Excessive current or voltage may cause the tester to overheat or degrade in performance; the response time reflects the sensitivity and reaction speed of the tester, which is crucial for applications that require fast response; the resolution determines the measurement accuracy of the tester and the minimum signal change that can be detected. By comprehensively considering multiple performance parameters of the tester, the overall performance of the tester can be evaluated more comprehensively, and a reliable basis can be provided for subsequent data analysis and processing.

[0045] Among them, the step of obtaining the validity evaluation value of each sample object data by comprehensive analysis based on the environmental quality evaluation value of each sample object and the tester performance evaluation value of each sample object includes: obtaining the critical experimental environmental quality evaluation value and the critical tester performance evaluation value from the thalamus feature database; and obtaining the validity evaluation value of each sample object data by comprehensive analysis based on the critical experimental environmental quality evaluation value, the critical tester performance evaluation value, the environmental quality evaluation value of each sample object and the tester performance evaluation value of each sample object.

[0046] The validity evaluation value of each sample object data is obtained in the following manner:

[0047]

[0048] Where, ξV 1j represents the effectiveness evaluation value of the jth sample object, β8 represents the effectiveness evaluation influencing factor corresponding to the experimental environment quality evaluation value, β9 represents the effectiveness evaluation influencing factor corresponding to the tester performance evaluation value, ξE 1j represents the experimental environment quality evaluation value of the jth sample object, ξE0 represents the critical experimental environment quality evaluation value, ξP 1j represents the tester performance evaluation value of the jth sample object, and ξP0 represents the critical tester performance evaluation value.

[0049] β8 and β9 are respectively the validity assessment influencing factors corresponding to the experimental environment quality assessment value and the tester performance assessment value preset in the thalamus feature database, which respectively represent the numerical values ​​of the degree of influence of the experimental environment quality assessment value and the tester performance assessment value on the validity assessment value, and can be directly obtained from the thalamus feature database when used. For example, the experimental environment quality assessment value and the validity assessment influencing factors corresponding to the experimental environment quality assessment value preset in the thalamus feature database form a mapping set, and the validity assessment influencing factors corresponding to the experimental environment quality assessment value are obtained by inputting the mapping set according to the experimental environment quality assessment value; the tester performance assessment value and the validity assessment influencing factors corresponding to the tester performance assessment value preset in the thalamus feature database form a mapping set, and the validity assessment influencing factors corresponding to the tester performance assessment value are obtained by inputting the mapping set according to the tester performance assessment value, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the influencing factor in this embodiment is between 0 and 1.

[0050] The validity evaluation factor corresponding to the experimental environment quality evaluation value is set to 0.4, the validity evaluation factor corresponding to the tester performance evaluation value is set to 0.6, the experimental environment quality evaluation value of the jth sample object is set to 1.5, the critical experimental environment quality evaluation value is set to 1.4, and the critical tester performance evaluation value is set to 1.6. When the tester performance evaluation value of the jth sample object is constantly changing, the validity evaluation value of the jth sample object is calculated. As shown in Table 1, the validity evaluation value data table of the thalamic functional connection network feature data management system.

[0051] Table 1. Validity evaluation value data table of thalamus functional connectivity network characteristic data management system

[0052] serial number <![CDATA[ξP 1j ]]> <![CDATA[ξV 1j ]]> 1 1.5 0.830 2 1.55 0.835 3 1.6 0.841 4 1.65 0.846 5 1.7 0.852

[0053] like Figure 2 As shown in Table 1 and Figure 2 It can be seen that when the validity evaluation influencing factor corresponding to the experimental environment quality evaluation value, the validity evaluation influencing factor corresponding to the tester performance evaluation value, the experimental environment quality evaluation value of the j-th sample object, the critical experimental environment quality evaluation value, and the critical tester performance evaluation value remain unchanged, and the tester performance evaluation value of the j-th sample object continues to increase, the validity evaluation value also continues to increase.

[0054] In this embodiment, there is a close correlation between the experimental environment quality evaluation value and the tester performance evaluation value. The experimental environment quality evaluation value reflects the potential impact that the experimental environment may have on the experimental results, while the tester performance evaluation value directly reflects the accuracy and reliability of the tester during the measurement process. By comprehensively analyzing the experimental environment quality evaluation value and the tester performance evaluation value, the validity evaluation value of each sample object data can be accurately obtained, reflecting the degree of influence of the experimental environment and the tester performance on the experimental results, as well as the accuracy and reliability of the experimental data, and the accuracy and reliability of the experimental data can be more comprehensively evaluated, providing a reliable basis for subsequent data analysis and processing.

[0055] Among them, the step of screening and obtaining each valid sample object according to the validity evaluation value of each sample object data and the validity evaluation correction value of each sample object data includes: obtaining a data validity evaluation threshold from a thalamus feature database; comparing the final validity evaluation value of each sample object data with the data validity evaluation threshold, if the final validity evaluation value of the sample object data is greater than or equal to the data validity evaluation threshold, then marking the sample object as a valid sample object, if the final validity evaluation value of a sample object data is less than the data validity evaluation threshold, then marking the sample object as an invalid sample object, and obtaining each valid sample object by statistics.

[0056] In this embodiment, the data validity evaluation threshold is a numerical limit for judging whether the sample object data is valid. By comparing with the validity evaluation value of each sample object data, each sample object can be classified. Effective data screening is the basis of scientific research work. Using the data validity evaluation threshold for screening can quickly identify valid and invalid sample objects, avoiding tedious manual screening processes; by screening to obtain valid sample objects, the influence of invalid data on the analysis results can be eliminated, thereby improving the accuracy and credibility of data analysis.

[0057] Among them, the step of comprehensively analyzing the pain threshold data of each valid sample object to obtain the pain threshold state evaluation value of each valid sample object includes: the pain threshold data includes the patella center strength value, the medial strength value of the midpoint of the medial edge of the patella, the lateral strength value of the midpoint of the lateral edge of the patella and the upper limb deltoid muscle belly strength value; obtaining the critical patella center strength value, the critical medial strength value of the midpoint of the medial edge of the patella, the critical lateral strength value of the midpoint of the lateral edge of the patella and the critical upper limb deltoid muscle belly strength value from the thalamus feature database; obtaining the pain threshold data of each valid sample object, and comprehensively analyzing to obtain the pain threshold state evaluation value of each valid sample object.

[0058] The pain threshold state evaluation value of each valid sample object is obtained in the following manner:

[0059]

[0060] Where ξS 1i represents the pain threshold state evaluation value of the i-th valid sample object, α3 represents the pain threshold evaluation influence factor corresponding to the patella center strength value, α4 represents the pain threshold evaluation influence factor corresponding to the medial strength value of the medial edge of the patella, α5 represents the pain threshold evaluation influence factor corresponding to the lateral strength value of the lateral edge of the patella, α6 represents the pain threshold evaluation influence factor corresponding to the deltoid muscle belly strength value of the upper limb, C 1i represents the patella center strength value of the i-th valid sample object, C0 represents the critical patella center strength value, I 1i represents the medial strength value of the medial edge of the patella of the i-th valid sample object, I0 represents the medial strength value of the medial edge of the patella at the critical point, O 1i represents the lateral strength value of the midpoint of the lateral edge of the patella of the i-th valid sample object, O0 represents the lateral strength value of the midpoint of the lateral edge of the critical patella, and A i1 represents the upper limb deltoid muscle belly strength value of the i-th valid sample object, and A0 represents the critical upper limb deltoid muscle belly strength value.

[0061] α3, α4, α5 and α6 are the pain threshold assessment influencing factors corresponding to the patella center strength value, the medial strength value of the midpoint of the medial edge of the patella, the lateral strength value of the midpoint of the lateral edge of the patella and the deltoid muscle belly strength value of the upper limb preset in the thalamic feature database, respectively, which represent the numerical values ​​of the influence of the patella center strength value, the medial strength value of the midpoint of the medial edge of the patella, the lateral strength value of the midpoint of the lateral edge of the patella and the deltoid muscle belly strength value of the upper limb on the pain threshold state assessment value, and can be directly obtained from the thalamic feature database when used. For example, the patella center strength value and the pain threshold assessment influencing factor corresponding to the patella center strength value preset in the thalamus feature database form a mapping set, and the pain threshold assessment influencing factor corresponding to the patella center strength value is obtained by inputting the mapping set according to the patella center strength value; the medial strength value of the medial edge midpoint of the patella and the pain threshold assessment influencing factor corresponding to the medial strength value of the medial edge midpoint of the patella preset in the thalamus feature database form a mapping set, and the pain threshold assessment influencing factor corresponding to the medial strength value of the medial edge midpoint of the patella is obtained by inputting the mapping set according to the medial strength value of the medial edge midpoint of the patella; the lateral strength value of the lateral edge midpoint of the patella and the lateral strength value of the lateral edge midpoint of the patella preset in the thalamus feature database The pain threshold assessment influencing factors corresponding to the lateral strength value of the midpoint of the lateral edge of the patella form a mapping set, and the pain threshold assessment influencing factors corresponding to the lateral strength value of the midpoint of the lateral edge of the patella are obtained by inputting the mapping set according to the lateral strength value of the midpoint of the lateral edge of the patella; the pain threshold assessment influencing factors corresponding to the upper limb deltoid muscle belly strength value and the upper limb deltoid muscle belly strength value preset in the thalamus feature database form a mapping set, and the pain threshold assessment influencing factors corresponding to the upper limb deltoid muscle belly strength value are obtained by inputting the mapping set according to the upper limb deltoid muscle belly strength value, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the influencing factor in this embodiment is between 0 and 1.

[0062] In this embodiment, the patellar center strength value, the medial strength value of the midpoint of the medial edge of the patella, the lateral strength value of the midpoint of the lateral edge of the patella and the upper limb deltoid muscle belly strength value are obtained by measuring the tenderness threshold using a portable pain tester, wherein the medial point of the midpoint of the medial edge of the patella is 3 cm inside the midpoint of the medial edge of the patella of the affected knee joint. It is located on the medial side of the knee joint, close to the medial edge of the patella. It is an important area of ​​the knee joint and is closely related to the stability and function of the knee joint; the patellar center point is located in the center of the patella, which is the most prominent part of the patella. It is not only an important part of the knee joint, but also one of the stimulation points commonly used in massage therapy; the lateral point of the midpoint of the lateral edge of the patella is located on the outside of the knee joint, close to the lateral edge of the patella. Corresponding to the medial point, it is also a key area for knee stability and function; the upper limb deltoid muscle belly point is located in the deltoid muscle belly of the affected upper limb. Although it has no direct connection with the knee joint, massage therapy sometimes requires systemic conditioning, so the test points of the upper limb are also taken into consideration. The intensity value of each point represents the minimum value when the patient feels pain at that point when the portable pain tester applies force to each point. By testing the pain thresholds of these four points, the therapeutic effect of massage therapy on KOA patients can be intuitively evaluated, and changes in the condition of KOA patients can be monitored. If the pain threshold continues to decrease, it may mean that the condition is worsening and the treatment plan needs to be adjusted in time.

[0063] Among them, the step of comprehensively analyzing the pain threshold state evaluation value of each valid sample object and the effectiveness evaluation value of each valid sample object to obtain the reference value evaluation value of each valid sample object includes: dividing the pain threshold state evaluation value into the pain threshold state evaluation value before treatment and the pain threshold state evaluation value after treatment according to the massage treatment time point, and performing difference operation on the pain threshold state evaluation value after treatment and the pain threshold state evaluation value before treatment of each valid sample object, marking the difference result as the pain threshold evaluation difference of each valid sample object, and performing sample classification according to the pain threshold evaluation difference of each valid sample object; and comprehensively analyzing the pain threshold evaluation difference of each valid sample object and the data effectiveness evaluation value of each valid sample object to obtain the reference value evaluation value of each valid sample object.

[0064] In this embodiment, the pain threshold evaluation difference reflects the degree of improvement of the pain threshold by massage therapy. A comprehensive analysis combining the data validity evaluation value and the pain threshold evaluation difference can further improve the reliability of the reference value evaluation value and enhance the authority of the reference value evaluation value.

[0065] Among them, the step of classifying samples according to the difference in pain threshold assessment of each valid sample object includes: obtaining the allowable deviation range of the pain threshold state assessment value from the thalamus feature database, and marking the maximum value of the allowable deviation range of the pain threshold state assessment value as the upper limit of the allowable deviation of the pain threshold state assessment value, and marking the minimum value of the allowable deviation range of the pain threshold state assessment value as the lower limit of the allowable deviation of the pain threshold state assessment value; comparing the pain threshold assessment difference of each valid sample object with the allowable deviation range of the pain threshold state assessment value, if the pain threshold assessment difference of a valid sample object is greater than the pain threshold state assessment value, If the difference in the pain threshold evaluation value of a valid sample object is within the allowable deviation range of the pain threshold state evaluation value, the valid sample object will be marked as a sample object with no effect; if the difference in the pain threshold evaluation value of a valid sample object is less than the allowable deviation lower limit of the pain threshold state evaluation value, the valid sample object will be marked as a sample object with abnormal effect; the expected effect sample objects, the sample objects with no effect and the sample objects with abnormal effect will be counted separately, and marked as each expected effect sample object, each sample object with no effect and each sample object with abnormal effect respectively.

[0066] In this embodiment, by setting the allowable deviation range of the pain threshold state evaluation value, the standardization and consistency of the evaluation process can be ensured. This helps to reduce the subjectivity and uncertainty in the evaluation process and improve the accuracy and reliability of the evaluation results. According to the comparison results of the pain threshold evaluation difference and the allowable deviation range, the effective sample objects can be accurately divided into expected effect sample objects, no effect sample objects and abnormal effect sample objects, which helps to more deeply understand the impact of massage therapy on different patients and provide strong support for the formulation of personalized treatment plans. By collecting and analyzing the data of sample objects of different classifications, the mechanism of the influence of massage therapy on the pain threshold can be further revealed, which helps to promote the development of scientific research in related fields and provide new ideas and methods for future research and treatment.

[0067] The reference value evaluation value of each valid sample object is obtained as follows:

[0068]

[0069] In the formula, ξR i represents the reference value evaluation value of the i-th valid sample object, α1 represents the reference value evaluation influencing factor corresponding to the pain threshold evaluation difference, α2 represents the reference value evaluation influencing factor corresponding to the effectiveness evaluation value, ξS 0i represents the difference in pain threshold assessment of the i-th valid sample object, ξV 1irepresents the validity evaluation value of the i-th valid sample object, where i is the number of each valid sample object, i=1, 2, 3, ..., N, and N is the total number of valid sample objects.

[0070] In this embodiment, α1 and α2 are reference value assessment influencing factors corresponding to the pain threshold assessment difference and the effectiveness assessment value preset in the thalamus feature database, respectively, and represent the numerical values ​​of the degree of influence of the pain threshold assessment difference and the effectiveness assessment value on the reference value assessment value, respectively, and can be directly obtained from the thalamus feature database when used. For example, the pain threshold assessment difference and the reference value assessment influencing factors corresponding to the pain threshold assessment difference preset in the thalamus feature database form a mapping set, and the reference value assessment influencing factors corresponding to the pain threshold assessment difference are obtained by inputting the mapping set according to the pain threshold assessment difference; the effectiveness assessment value and the reference value assessment influencing factors corresponding to the effectiveness assessment value preset in the thalamus feature database form a mapping set, and the reference value assessment influencing factors corresponding to the effectiveness assessment value are obtained by inputting the mapping set according to the effectiveness assessment value, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the influencing factor in this embodiment is between 0 and 1.

[0071] Among them, the step of managing the thalamic functional connection network characteristic data according to the reference value evaluation value of each valid sample object includes: obtaining the thalamic functional connection network characteristic data of each valid sample object; for each expected effect sample object, sorting the thalamic functional connection network characteristic data of each expected effect sample object in descending order according to the reference value evaluation value of each expected effect sample object; for each ineffective sample object and each abnormal effect sample object, screening and detecting the experimental process of each ineffective sample object and each abnormal effect sample object.

[0072] In this embodiment, the thalamus is the main relay station for pain signals transmitted along the medial pain system and the lateral pain system to the limbic system and the cerebral cortex. At the same time, the thalamus also plays an important role in the descending regulatory pathway. After the cerebral cortex processes the pain signal, it transmits it to the periphery via the dorsolateral prefrontal cortex, PAG, etc., so the thalamic functional connection network characteristic data includes the pain signal pathway and the descending regulatory pathway. For each expected effect sample object, by sorting, priority can be given to those sample objects with larger reference value assessment values. These objects may change more significantly in the experiment, and these sample objects are also more reliable, making it easier to discover potential rules or trends, and making the analysis work more orderly and efficient. When screening and testing the experimental process of each ineffective sample object and each abnormal effect sample object, first screen and test the pain signal pathway, use functional magnetic resonance imaging and other technologies to analyze the functional connection between the thalamus and the cerebral cortex, pay attention to the connection strength and pattern between the thalamic nuclei and the cerebral cortical area to identify abnormalities in the pain signal pathway, and then use electrophysiological recording methods such as electroencephalogram or field potential recording to detect the electrophysiological response of the thalamus to pain stimulation; when screening and testing the descending regulatory pathway, use univariate analysis of variance and other statistical methods to analyze the connection strength and pattern between the thalamic subregions and different brain regions, pay attention to the difference in connection strength and the similarity of connection pattern, so as to identify abnormalities in the descending regulatory pathway, and then use animal model experiments, such as optogenetics, pharmacogenetics and other methods to verify the function of the descending regulatory pathway. The screening test results of the pain signal pathway and the descending regulatory pathway are integrated to form comprehensive thalamic functional connectivity network characteristic data. The thalamic functional connectivity network characteristic data of effective sample subjects are compared with those of ineffective or abnormal effect sample subjects, the abnormal characteristics are analyzed, and the parameters that may lead to differences in experimental results are identified based on the screening test results, such as reducing the experimental duration and reducing the stimulation frequency to optimize the experimental results.

[0073] To summarize, this embodiment obtains the environmental quality evaluation value of each sample object through comprehensive analysis based on the experimental environment data, and obtains the validity evaluation correction value of each sample object data according to the matching of the environmental quality evaluation value of each sample object, obtains the tester performance evaluation value of each sample object according to the comprehensive analysis of the pain tester performance data, obtains the validity evaluation value of each sample object data according to the comprehensive analysis of the environmental quality evaluation value of each sample object and the tester performance evaluation value of each sample object, and screens each valid sample object according to the validity evaluation value of each sample object data and the validity evaluation correction value of each sample object data; obtains the pain threshold state evaluation value of each valid sample object according to the comprehensive analysis of the pain threshold data of each valid sample object, obtains the reference value evaluation value of each valid sample object according to the comprehensive analysis of the pain threshold state evaluation value of each valid sample object and the validity evaluation value of each valid sample object, and manages the thalamic functional connection network feature data according to the reference value evaluation value of each valid sample object, thereby realizing the precise management and effective utilization of the thalamic functional connection network feature data.

[0074] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems and methods, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0075] The present invention is described with reference to the flowcharts and / or block diagrams of the systems and methods, devices (systems and methods), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0076] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1A function specified in one or more boxes.

[0077] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0078] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0079] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A thalamic functional connection network characteristic data management system for massage treatment of KOA patients, characterized in that: It includes a data acquisition module, a data processing module and a data management module; The data acquisition module is used to acquire experimental data of each sample subject, including thalamic functional connection network feature data, pain tester performance data, experimental environment data and pain threshold data; The data processing module is used to obtain an environmental quality evaluation value of each sample object according to a comprehensive analysis of the experimental environment data, and obtain a validity evaluation correction value of each sample object data according to the matching of the environmental quality evaluation value of each sample object, obtain a tester performance evaluation value of each sample object according to a comprehensive analysis of the pain tester performance data, obtain a validity evaluation value of each sample object data according to a comprehensive analysis of the environmental quality evaluation value of each sample object and the tester performance evaluation value of each sample object, and screen each valid sample object according to the validity evaluation value of each sample object data and the validity evaluation correction value of each sample object data; The data management module is used to obtain the pain threshold state evaluation value of each valid sample object based on a comprehensive analysis of the pain threshold data of each valid sample object, obtain the reference value evaluation value of each valid sample object based on a comprehensive analysis of the pain threshold state evaluation value of each valid sample object and the effectiveness evaluation value of each valid sample object, and manage the thalamic functional connection network feature data based on the reference value evaluation value of each valid sample object.

2. According to the thalamus functional connection network characteristic data management system for massage treatment of KOA patients in claim 1, it is characterized in that: The step of obtaining the environmental quality assessment value of each sample object based on comprehensive analysis of the experimental environmental data includes: The experimental environment data includes the experimental environment temperature, the experimental environment humidity and the experimental environment electromagnetic interference intensity; Obtain the reference experimental environment temperature, the allowable deviation experimental environment temperature, the reference experimental environment humidity, the allowable deviation experimental environment humidity and the critical experimental environment electromagnetic interference intensity from the thalamus feature database; Comprehensive analysis was performed to obtain the environmental quality assessment value of each sample object.

3. The thalamus functional connection network characteristic data management system for massage treatment of KOA patients according to claim 1, characterized in that: The step of obtaining the performance evaluation value of the pain tester for each sample object based on comprehensive analysis of the pain tester performance data comprises: The performance data of the pain tester, including operating current, operating voltage, response time and resolution; Obtaining a reference operating current, an allowable deviation operating current, a reference operating voltage, an allowable deviation operating voltage, a critical response time and a critical resolution from a thalamus feature database; Comprehensive analysis is performed to obtain the performance evaluation value of the tester for each sample object.

4. The thalamus functional connection network characteristic data management system for massage treatment of KOA patients according to claim 1, characterized in that: The step of obtaining the validity evaluation value of each sample object data by comprehensive analysis based on the environmental quality evaluation value of each sample object and the performance evaluation value of each sample object tester comprises: Obtain critical experimental environment quality assessment values ​​and critical tester performance assessment values ​​from the thalamus feature database; The validity evaluation value of each sample object data is obtained by comprehensive analysis based on the critical experimental environment quality evaluation value, the critical tester performance evaluation value, the environment quality evaluation value of each sample object and the tester performance evaluation value of each sample object.

5. The thalamus functional connection network characteristic data management system for massage treatment of KOA patients according to claim 1, characterized in that: The step of screening and obtaining each valid sample object according to the validity evaluation value of each sample object data and the validity evaluation correction value of each sample object data comprises: Obtain data validity assessment thresholds from the thalamus feature database; Adding the validity evaluation value of each sample object data to the validity evaluation correction value of each sample object data to obtain the final validity evaluation value of each sample object data; The final validity evaluation value of each sample object data is compared with the data validity evaluation threshold. If the final validity evaluation value of a sample object data is greater than or equal to the data validity evaluation threshold, the sample object is marked as a valid sample object. If the final validity evaluation value of a sample object data is less than the data validity evaluation threshold, the sample object is marked as an invalid sample object, and the valid sample objects are statistically obtained.

6. The thalamus functional connection network characteristic data management system for massage treatment of KOA patients according to claim 1, characterized in that: The step of obtaining the pain threshold state evaluation value of each valid sample object based on comprehensive analysis of the pain threshold data of each valid sample object comprises: The pain threshold data include the patella center strength value, the medial strength value of the midpoint of the medial edge of the patella, the lateral strength value of the midpoint of the lateral edge of the patella, and the strength value of the deltoid muscle belly of the upper limb; The critical patella center strength value, the critical patella medial edge midpoint medial strength value, the critical patella lateral edge midpoint lateral strength value and the critical upper limb deltoid muscle belly strength value are obtained from the thalamus feature database; The pain threshold data of each valid sample object is obtained, and the pain threshold state evaluation value of each valid sample object is obtained through comprehensive analysis.

7. The thalamus functional connection network characteristic data management system for massage treatment of KOA patients according to claim 1, characterized in that: The step of obtaining the reference value evaluation value of each valid sample object by comprehensive analysis based on the pain threshold state evaluation value of each valid sample object and the effectiveness evaluation value of each valid sample object comprises: According to the massage treatment time point, the pain threshold state assessment value is divided into the pain threshold state assessment value before treatment and the pain threshold state assessment value after treatment, and the pain threshold state assessment value after treatment and the pain threshold state assessment value before treatment of each valid sample object are difference calculated, and the difference result is marked as the pain threshold assessment difference of each valid sample object, and the samples are classified according to the pain threshold assessment difference of each valid sample object; Based on the pain threshold assessment difference of each valid sample object and the data validity assessment value of each valid sample object, a comprehensive analysis is performed to obtain the reference value assessment value of each valid sample object.

8. The thalamus functional connection network characteristic data management system for massage treatment of KOA patients according to claim 7, characterized in that: The step of classifying samples according to the difference in pain threshold assessment of each valid sample object comprises: Obtaining an allowable deviation range of a pain threshold state assessment value from a thalamus feature database, marking a maximum value of the allowable deviation range of the pain threshold state assessment value as an upper limit of the allowable deviation of the pain threshold state assessment value, and marking a minimum value of the allowable deviation range of the pain threshold state assessment value as a lower limit of the allowable deviation of the pain threshold state assessment value; The pain threshold assessment difference of each valid sample object is compared with the allowable deviation range of the pain threshold state assessment value. If the pain threshold assessment difference of a valid sample object is greater than the upper limit of the allowable deviation of the pain threshold state assessment value, the valid sample object is marked as an expected effect sample object. If the pain threshold assessment difference of a valid sample object is within the allowable deviation range of the pain threshold state assessment value, the valid sample object is marked as a no-effect sample object. If the pain threshold assessment difference of a valid sample object is less than the lower limit of the allowable deviation of the pain threshold state assessment value, the valid sample object is marked as an abnormal effect sample object. The expected effect sample objects, the no-effect sample objects and the abnormal effect sample objects are counted respectively, and are marked as each expected effect sample object, each no-effect sample object and each abnormal effect sample object respectively.

9. The thalamus functional connection network characteristic data management system for massage treatment of KOA patients according to claim 7, characterized in that: The reference value evaluation value of each valid sample object is obtained as follows: In the formula, ξR i represents the reference value evaluation value of the i-th valid sample object, α1 represents the reference value evaluation influencing factor corresponding to the pain threshold evaluation difference, α2 represents the reference value evaluation influencing factor corresponding to the effectiveness evaluation value, ξS 0i represents the difference in pain threshold assessment of the i-th valid sample object, ξV 1i represents the validity evaluation value of the i-th valid sample object, where i is the number of each valid sample object, i=1, 2, 3, ..., N, and N is the total number of valid sample objects.

10. The thalamus functional connection network characteristic data management system for massage treatment of KOA patients according to claim 1, characterized in that: The step of managing the thalamus functional connection network characteristic data according to the reference value evaluation value of each valid sample object includes: Obtain thalamic functional connection network characteristic data of each valid sample object; For each expected effect sample object, the thalamus functional connection network characteristic data of each expected effect sample object is sorted in descending order according to the reference value evaluation value of each expected effect sample object; For each sample object with no effect and each sample object with abnormal effect, the experimental process of each sample object with no effect and each sample object with abnormal effect is screened and tested.

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