Health data detection system, method and equipment based on traditional Chinese medicine diagnosis and treatment

Abstract

The invention belongs to the technical field of traditional Chinese medicine health diagnosis and treatment, and particularly relates to a health data detection system, method and equipment based on traditional Chinese medicine diagnosis and treatment. According to the method, tongue image information, pulse condition information and complexion information of a patient are comprehensively collected, deep analysis and comprehensive evaluation are carried out in combination with modern science and technology means, the health condition of the patient can be reflected more accurately, the accuracy and comprehensiveness of traditional Chinese medicine diagnosis and treatment are improved, and in addition, the diagnosis and treatment accuracy of the patient is improved through trend evaluation and correlation analysis of abnormal causes. According to the method, the development trend of the health condition of the patient can be predicted, correlation analysis among different causes can be introduced according to the correlation degree and the processing priority of the abnormal causes, the cause processing strategy is further optimized, the health risk caused by improper cause processing is avoided, and the patient experience is improved. Therefore, a doctor can formulate a more accurate and effective treatment scheme, the means of traditional Chinese medicine diagnosis and treatment are enriched, and the objectivity and scientificity of traditional Chinese medicine diagnosis and treatment are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of traditional Chinese medicine health diagnosis and treatment, and specifically relates to a health data detection system, method and equipment based on traditional Chinese medicine diagnosis and treatment. Background Art

[0002] With the continuous development of traditional Chinese medicine, the application of traditional Chinese medicine diagnosis and treatment techniques in health management and disease prevention is becoming more and more extensive. Combined with the rapid development of information technology, traditional Chinese medicine diagnosis and treatment is no longer limited to the traditional diagnosis and treatment methods of observation, auscultation, questioning and palpation, but can be combined with modern scientific and technological means to comprehensively and accurately collect and analyze patients' health data.

[0003] Traditional Chinese medicine diagnosis and treatment system in the prior art. Although the collection and analysis of health data have been achieved to a certain extent, there are still many deficiencies. For example, some systems rely only on a single traditional Chinese medicine diagnosis and treatment method, such as judging the patient's health status only by tongue diagnosis or pulse diagnosis. This single diagnosis method often lacks comprehensiveness and accuracy. In addition, some existing traditional Chinese medicine diagnosis and treatment systems also have limitations in data processing and analysis, and cannot conduct in-depth and detailed analysis of the patient's health data, thus affecting the accuracy of the diagnosis. In addition, it is more critical that when analyzing the data, multiple causes may be analyzed. Simply relying on the diagnosis and treatment system can only analyze the cause of the disease and prescribe or recommend solutions based on the cause of the disease. However, in the actual use process, there are problems of priority, or mutual dependence or mutual influence between various causes of the disease. Therefore, directly prescribing or recommending diagnosis solutions for the analyzed causes makes the diagnosis and treatment system too rigid and less applicable. Summary of the invention

[0004] The purpose of the present invention is to provide a health data detection system, method and equipment based on traditional Chinese medicine diagnosis and treatment, which can comprehensively and accurately collect and analyze the patient's health data and improve the accuracy and comprehensiveness of traditional Chinese medicine diagnosis and treatment.

[0005] The technical solution adopted by the present invention is as follows: A health data detection method based on traditional Chinese medicine diagnosis and treatment, comprising: Obtain the patient's health diagnosis and treatment data, and output health information based on the health diagnosis and treatment data, wherein the health information includes tongue health information, pulse health information and complexion health information; Assess the patient's health status based on the health information and simultaneously output an assessment index; The evaluation index is compared with the preset evaluation threshold, and when the evaluation index exceeds the preset evaluation threshold, a health trend map is output; when the evaluation index does not exceed the evaluation threshold, abnormal cause data analysis is triggered, and the cause treatment priority is output according to the analysis result; The correlation between the causes of abnormalities is confirmed, and the priority list is modified according to the correlation, wherein the correlation includes concurrent relationship, coexistence relationship and independent relationship.

[0006] In a preferred embodiment, after the tongue image information is output, the patient's tongue image health information is determined based on image recognition, and the specific process is as follows: Obtaining the patient's tongue image information, and performing feature extraction on the tongue image information to obtain tongue image features to be diagnosed; Obtain standard tongue image features in the standard image of TCM tongue diagnosis; Comparing the standard tongue image features with the tongue image features to be diagnosed, and synchronously outputting the deviation area between the standard tongue image features and the tongue image features to be diagnosed; All the deviation areas are extracted and summarized as tongue image health information.

[0007] In a preferred embodiment, after the pulse information is output, the patient's pulse health information is determined by waveform analysis, and the specific process is as follows: Acquiring the patient's pulse information, and performing waveform feature extraction on the pulse information to obtain pulse waveform features; Compare the pulse waveform feature with the standard pulse waveform feature of traditional Chinese medicine, and output the deviation section of the pulse waveform feature; The duration of the deviation segment and the frequency of deviation are counted and summarized as the patient's pulse health information.

[0008] In a preferred embodiment, after the complexion information is output, the complexion health information of the patient is determined based on color analysis, and the specific process is as follows: Acquire the patient's complexion information, and perform color space conversion on the complexion information, converting the complexion information from the RGB color space to the HSV color space; In the HSV color space, the color information of the face is segmented and the main color components of the face color are extracted; The main color component is compared with the standard color of TCM complexion, and the color difference is output and simultaneously summarized as complexion health information.

[0009] In a preferred embodiment, the step of evaluating the patient's health status based on the health information and synchronously outputting the evaluation index includes: Obtaining the tongue health information, pulse health information and complexion health information; Assigning corresponding evaluation weights to the tongue image health information, pulse health information and complexion health information; A comprehensive evaluation function is obtained, and the tongue health information, pulse health information, complexion health information, and corresponding evaluation weights are input into the comprehensive evaluation function for fusion operation, and the output result of the comprehensive evaluation function is recorded as an evaluation index.

[0010] In a preferred embodiment, the outputting of the health trend graph includes the following steps: Sorting the tongue image information, pulse information and complexion information according to the time sequence of collection; Taking the current acquisition node of the tongue image information, pulse information and complexion information as a reference, reverse offset processing is performed to obtain a sample period; Collecting tongue image information, pulse information and complexion information within the sample period, and recording them as a first sample parameter, a second sample parameter and a third sample parameter respectively; Inputting the first sample parameter, the second sample parameter and the third sample parameter into a trend evaluation function, and recording the output result of the trend evaluation function as a sample trend parameter; Based on the sample trend parameters, a health trend map is constructed, in which a health trend curve is drawn with the time series as the horizontal axis and the sample trend parameters as the vertical axis; After the sample trend parameter is output, a preset trend evaluation threshold is introduced, and the trend evaluation threshold is compared with the sample trend parameter; When the sample trend parameter is less than the trend assessment threshold, it indicates that the patient's health condition is developing in a normal trend; When the sample trend parameter is greater than or equal to the trend evaluation threshold, it indicates that the patient's health condition development trend is abnormal, and a warning signal is issued simultaneously.

[0011] In a preferred embodiment, the step of outputting the etiology treatment priority according to the analysis result includes the following steps: Collect all abnormal causes corresponding to the tongue image health information, pulse health information and complexion health information; Obtaining the correlation between the tongue health information, pulse health information and complexion health information and the abnormal cause under each abnormal cause; Obtaining the association weights between the tongue health information, pulse health information, and complexion health information and the abnormal causes under each abnormal cause; According to the correlation degree and the correlation weight, the comprehensive correlation index of each abnormal cause is calculated, and the causes are sorted according to the comprehensive correlation index, and then the processing priority of the abnormal cause is output according to the sorting result.

[0012] In a preferred embodiment, the steps of confirming the correlation between the causes of abnormalities and modifying the priority list according to the correlation, wherein the correlation includes a concurrent relationship, a coexistence relationship and an independent relationship, include: Construct the correlation analysis matrix of abnormal causes and simultaneously calculate the matrix element values. The matrix dimension is n×n, where n is the total number of abnormal causes. Introducing a preset evaluation interval and combining the matrix element values ​​to determine the correlation between abnormal causes; When the matrix element value exceeds the upper limit of the evaluation interval, the correlation between the abnormal causes is recorded as a concurrent relationship, and the abnormal causes with low processing priority under the concurrent relationship are promoted to the same level as the abnormal causes with the highest processing priority. When the matrix element value belongs to the evaluation interval, the correlation between the abnormal causes is recorded as a coexistence relationship, and the processing priority under the coexistence relationship is kept unchanged in the original order; When the matrix element value is lower than the lower limit of the evaluation interval, the correlation between the abnormal causes is recorded as an independent relationship, and the processing priority under the independent relationship remains unchanged in the original order.

[0013] The present invention also provides a health data detection system based on TCM diagnosis and treatment, using the above-mentioned health data detection method based on TCM diagnosis and treatment, comprising: A data acquisition module, the data acquisition module is used to acquire the patient's health diagnosis and treatment data, and output health information based on the health diagnosis and treatment data, wherein the health information includes tongue health information, pulse health information and complexion health information; An information quantification module, the information quantification module is used to evaluate the health status of the patient based on the health information and synchronously output an evaluation index; An evaluation module is used to compare the evaluation index with a preset evaluation threshold, and when the evaluation index exceeds the preset evaluation threshold, output a health trend map, and when the evaluation index does not exceed the evaluation threshold, trigger abnormal etiology data analysis, and output etiology treatment priority according to the analysis results The priority correction module is used to confirm the correlation between the causes of abnormalities and correct the priority list according to the correlation, wherein the correlation includes concurrent relationship, coexistence relationship and independent relationship.

[0014] And, a health data detection device based on traditional Chinese medicine diagnosis and treatment, the detection device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; Among them, the memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the above-mentioned health data detection method based on traditional Chinese medicine diagnosis and treatment.

[0015] The technical effects achieved by the present invention are: The present invention can more accurately reflect the patient's health status by comprehensively collecting the patient's tongue image information, pulse information and complexion information, and combining it with modern scientific and technological means for in-depth analysis and comprehensive evaluation, thereby improving the accuracy and comprehensiveness of Chinese medicine diagnosis and treatment. In addition, the present invention can not only predict the development trend of the patient's health status through trend evaluation and correlation analysis of abnormal causes, providing doctors with more accurate diagnostic basis, but also can introduce correlation analysis between different causes based on the correlation and treatment priority of abnormal causes, further optimize the strategy of cause treatment, avoid health risks caused by improper cause treatment, and help doctors formulate more accurate and effective treatment plans, thereby enriching the means of Chinese medicine diagnosis and treatment, and at the same time, it can also avoid the influence of human subjective factors to a certain extent, and improve the objectivity and scientificity of Chinese medicine diagnosis and treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic flow chart of the method of the present invention; Figure 2 It is a schematic diagram of the system module of the present invention; Figure 3 It is a schematic diagram of the structure of the detection equipment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0018] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0019] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The term "in a preferred embodiment" that appears in different places in this specification does not refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0020] See also Figure 1 As shown, the present invention provides a health data detection method based on traditional Chinese medicine diagnosis and treatment, comprising: S1. Obtain the patient's health diagnosis and treatment data, and output health information based on the health diagnosis and treatment data, wherein the health information includes tongue health information, pulse health information, and complexion health information; In step S1, when conducting a health diagnosis and treatment assessment on a patient, it is first necessary to fully obtain the patient's health diagnosis and treatment data. The health diagnosis and treatment data covers multiple dimensions of physiological indicators of the patient, such as tongue image information, pulse information, and complexion information. After the health diagnosis and treatment data is output, a preprocessing operation is performed simultaneously. The preprocessing steps include: Perform denoising and image enhancement operations on tongue image information in health diagnosis and treatment data to improve the clarity and recognition of tongue image information; Filter the pulse information in the health diagnosis and treatment data to reduce the noise interference in the pulse information; Perform color correction on the complexion information in health diagnosis and treatment data, and smooth out areas with uneven skin color to enhance the readability of complexion information; Specifically, after the health diagnosis and treatment data is output, first of all, the tongue image information contained in the health diagnosis and treatment data is subjected to corresponding denoising and image enhancement operations, the purpose of which is to effectively remove various types of noise interference in the tongue image, and at the same time improve the clarity and recognition of the tongue image through image enhancement technology, so that the tongue image information is more accurate and reliable in subsequent analysis. For the pulse information in the health diagnosis and treatment data, the corresponding filtering processing technology is adopted, which can significantly reduce the noise interference in the pulse information, ensure the purity and accuracy of the pulse data, and provide a basis for subsequent pulse analysis. For the complexion information in the health diagnosis and treatment data, detailed color correction processing will be performed, and smoothing processing will be performed on areas with uneven skin color. Color correction aims to restore the true complexion information and avoid color deviation caused by shooting environment or equipment differences, while smoothing processing can effectively improve the uneven skin color phenomenon and further improve the readability and reference value of complexion information.

[0021] Secondly, after the tongue image information is output, the patient's tongue image health information is determined based on image recognition. The specific process is as follows: Obtain the patient's tongue image information, and perform feature extraction on the tongue image information to obtain the tongue image features to be diagnosed; Obtain standard tongue image features in the standard image of TCM tongue diagnosis; Compare the standard tongue image features with the tongue image features to be diagnosed, and synchronously output the deviation area between the standard tongue image features and the tongue image features to be diagnosed; Extract all deviation areas and summarize them into tongue health information; Specifically, when performing image recognition on tongue image information, the purpose is to obtain the patient's tongue image health information. First, the patient's tongue image information is obtained through professional image acquisition equipment, and then the collected tongue image information is carefully extracted. This process involves analysis of color, texture, morphology and other aspects, so as to obtain the tongue image feature data to be diagnosed. Secondly, the corresponding standard tongue image features are extracted from the pre-established standard image library of traditional Chinese medicine tongue diagnosis. The standard features have been clinically verified and recognized by experts. Then, the extracted standard tongue image features are compared and analyzed in detail with the tongue image features to be diagnosed. In this process, the deviation area between the standard tongue image features and the tongue image features to be diagnosed will be output synchronously. The area of ​​the deviation area can reflect the patient's health problems. Here, when determining the area of ​​the deviation area, it is first necessary to extract the edge curve of the deviation area, which can be achieved through an edge detection algorithm. The edge detection algorithm can accurately identify and outline the outline of the deviation area, and then calculate the area of ​​the deviation area. The area measurement formula is; , where represents the area of ​​the deviation region, Indicates the number of inflection points at the edge of the deviation area, and Both represent the horizontal coordinates of the edge inflection points. and The ordinate represents the edge inflection point. The size of the deviation area can directly reflect the degree of deviation between the tongue image characteristics and the standard characteristics, thereby judging the patient's tongue health status. Finally, all identified deviation areas are comprehensively extracted and sorted to obtain tongue health information.

[0022] Secondly, after the pulse information is output, the patient's pulse health information is determined through waveform analysis. The specific process is as follows: Acquire the patient's pulse information, and extract the waveform features of the pulse information to obtain the pulse waveform features; Compare the pulse waveform characteristics with the standard pulse waveform characteristics of traditional Chinese medicine, and output the deviation section of the pulse waveform characteristics; Count the duration of the deviation segment and the frequency of deviation, and summarize them as the patient's pulse health information; Here, when performing waveform analysis on the pulse information, first, professional pulse detection equipment is used to carefully obtain the patient's pulse information to ensure the accuracy and completeness of the data. Then, the acquired pulse information is subjected to in-depth waveform feature extraction to analyze the waveform characteristics of the pulse, thereby obtaining detailed pulse waveform feature data. Then, the pulse waveform characteristics are compared and analyzed with the standard pulse waveform characteristics in traditional Chinese medicine theory, so that the deviated segments in the pulse waveform characteristics can be identified and the specific positions of the deviated segments are clearly marked. Subsequently, the duration of each deviated segment is accurately counted, and the frequency of occurrence of these deviated segments is recorded to ensure the comprehensiveness and reliability of the data. Finally, all the statistically obtained duration lengths and deviation frequencies of the deviated segments are summarized and organized to form a pulse health information report for the patient.

[0023] And, after the complexion information is output, the complexion health information of the patient is determined based on color analysis. The specific process is as follows: Obtain the patient's complexion information, and perform color space conversion on the complexion information, converting the complexion information from the RGB color space to the HSV color space; In the HSV color space, the color information of the face is segmented and the main color components of the face color are extracted; Compare the main color components with the standard color of TCM complexion, output the color difference, and simultaneously summarize it into complexion health information; Here, the specific steps for performing a detailed color analysis on the facial color information to obtain the patient's complexion health information are as follows: first, the patient's complexion information is obtained through a high-precision image acquisition device to ensure that the acquired image is clear and accurate; then, the acquired complexion information is converted into a color space, and the original RGB color space data is converted into an HSV color space that is more suitable for color analysis, so as to more accurately capture color features; in the HSV color space, the corresponding image processing algorithm is used to perform color segmentation on the facial color information, so that the main color components of the complexion can be extracted to ensure the accuracy and reliability of the extraction results; then, the extracted main color components are compared in detail with the TCM complexion standard color library, and then the color difference can be output, which can intuitively reflect the health status of the patient's complexion; finally, all comparison results and color difference data are synchronously summarized to form a patient's complexion health information report, which provides a scientific basis for subsequent TCM diagnosis and treatment.

[0024] S2. Evaluate the patient's health status based on the health information and output the evaluation index simultaneously; In step S2, after the patient's health information is output, a corresponding evaluation process is performed on the patient's health status, and each of the patient's health information is quantified into an evaluation index that can be intuitively understood. The steps of evaluating the patient's health status based on the health information and outputting the evaluation index synchronously include: Obtain tongue health information, pulse health information and complexion health information; Assign corresponding evaluation weights to tongue image health information, pulse image health information and complexion health information; Obtain a comprehensive evaluation function, and input the tongue image health information, pulse health information, complexion health information, and corresponding evaluation weights into the comprehensive evaluation function for fusion operation, and record the output result of the comprehensive evaluation function as an evaluation index; Specifically, we first need to obtain the patient's tongue health information, pulse health information and complexion health information, which respectively reflect the patient's health status at different physiological levels. Secondly, in order to ensure the accuracy and scientificity of the evaluation, we will assign corresponding evaluation weights to the tongue health information, pulse health information and complexion health information. The weight allocation function is: , where Indicates The evaluation weight of each indicator (tongue image / pulse condition / complexion) is and They respectively represent Indicators and The information entropy of the indicators, among which, ( Indicates The sample in The normalized value of each indicator is obtained), and then a comprehensive evaluation function is introduced to perform corresponding fusion operations on the tongue health information, pulse health information, and complexion health information. The expression of the comprehensive evaluation function is: , where represents the evaluation index, Indicates the tongue image health information score, Indicates the pulse health information score, Represents the facial health information score. The evaluation index output by the above formula will be used as a comprehensive quantitative indicator of the patient's health status, providing a corresponding reference for subsequent health management and treatment plans; In addition, it should be made clear that when the tongue image health information, pulse health information and complexion health information are output, an independent evaluation will also be conducted, that is, separate evaluation and analysis will be conducted on the tongue image, pulse and complexion respectively, so as to further ensure the accuracy and comprehensiveness of the evaluation results. During the independent evaluation process, the tongue image health information, pulse health information and complexion health information will be analyzed according to the professional knowledge and standards in their respective fields, and possible abnormalities or pathological characteristics will be identified, and corresponding evaluation conclusions and suggestions will be given. This is the more conventional evaluation method currently available and will not be further elaborated in this plan.

[0025] S3, comparing the evaluation index with a preset evaluation threshold, and when the evaluation index exceeds the preset evaluation threshold, outputting a health trend map, and when the evaluation index does not exceed the evaluation threshold, triggering abnormal cause data analysis, and outputting the cause treatment priority according to the analysis result; In step S3, after the evaluation index is output, it can be compared with the pre-set evaluation threshold to determine the patient's health status, which can be specifically divided into a healthy state and an abnormal state. When the evaluation index exceeds the evaluation threshold, the health state will be determined as a healthy state. At this time, a health trend map will be output, which can intuitively show the development trend of the patient's health status and potential health risks, providing strong support for subsequent health management. When the evaluation index does not exceed the evaluation threshold, it indicates that the patient may have certain health hazards or disease risks. At this time, the abnormal cause data will be triggered for analysis to determine the priority of intervention treatment of the abnormal cause. Among them, when the health trend map is output, the following steps are included: Sorting the tongue image information, pulse information and complexion information according to the time sequence of collection; Based on the current acquisition node of tongue image information, pulse information and complexion information, reverse offset processing is performed to obtain the sample period; Collect tongue image information, pulse information and complexion information within the sample period, and record them as the first sample parameter, the second sample parameter and the third sample parameter respectively; Inputting the first sample parameter, the second sample parameter and the third sample parameter into a trend evaluation function, and recording the output result of the trend evaluation function as a sample trend parameter; Based on the sample trend parameters, a health trend map is constructed. In the health trend map, a health trend curve is drawn with the time series as the horizontal axis and the sample trend parameters as the vertical axis; After the sample trend parameter is output, a preset trend evaluation threshold is introduced, and the trend evaluation threshold is compared with the sample trend parameter; When the sample trend parameter is less than the trend assessment threshold, it indicates that the patient's health condition is developing normally; When the sample trend parameter is greater than or equal to the trend assessment threshold, it indicates that the patient's health condition is developing abnormally, and a warning signal is issued simultaneously; Specifically, in the process of generating a health trend map, the collected tongue image information, pulse information and complexion information are first systematically sorted according to the specific time sequence of their respective collections. Then, the time node of the currently collected tongue image information, pulse information and complexion information is used as a reference point to perform a reverse time offset operation, thereby determining a specific sample period. Within this sample period, the tongue image information, pulse information and complexion information within the period are recollected and recorded in detail, and these information are marked as the first sample parameter, the second sample parameter and the third sample parameter, respectively. Subsequently, these three types of sample parameters are sequentially input into the corresponding trend evaluation function, wherein the expression of the trend evaluation function is: , where represents the sample trend parameter, represents the length of the sample period, Indicates the number of samples of the first sample parameter, the second sample parameter, and the third sample parameter collected during the sample period. and It represents the first sample parameter, the second sample parameter and the third sample parameter under the adjacent collection nodes within the sample period. Then, based on the sample trend parameters, a health trend map is constructed. In the health trend map, the time series is used as the horizontal axis and the sample trend parameters are used as the vertical axis to draw a trend curve reflecting health changes. It is particularly important to note that after the sample trend parameters are output, a pre-set trend evaluation threshold needs to be introduced, and this threshold is carefully compared and analyzed with the sample trend parameters. If the value of the sample trend parameter is less than the trend evaluation threshold, it can be determined that the patient's health status development trend is within the normal range. On the contrary, if the value of the sample trend parameter is greater than or equal to the trend evaluation threshold, it indicates that there is an abnormality in the patient's health status development trend. At this time, the system will simultaneously issue an early warning signal to prompt relevant medical staff to take timely intervention measures.

[0026] Secondly, when outputting the cause treatment priority based on the analysis results, the following steps are included: Collect all abnormal causes corresponding to tongue health information, pulse health information and complexion health information; Obtain the correlation between tongue health information, pulse health information and complexion health information and the abnormal cause under each abnormal cause; Obtain the correlation weights between tongue health information, pulse health information, and complexion health information and the abnormal causes under each abnormal cause; According to the correlation degree and correlation weight, the comprehensive correlation index of each abnormal cause is calculated, and the causes are sorted according to the comprehensive correlation index, and then the processing priority of the abnormal causes is output according to the sorting results; Specifically, in an abnormal state, it is necessary to collect various information related to the health status, including tongue health information, pulse health information and complexion health information, and extract all possible abnormal causes. This can be achieved through data mining and machine learning algorithms to comprehensively cover the possible range of causes. Subsequently, for each abnormal cause, the correlation between the tongue health information, pulse health information and complexion health information and the abnormal cause is calculated. This correlation reflects the degree of match between the information characteristics and the cause. The correlation calculation method can use statistical methods such as Pearson correlation coefficient and Spearman rank correlation coefficient to ensure the accuracy and reliability of the calculation results. At the same time, it is also necessary to obtain the correlation weights between the tongue health information, pulse health information and complexion health information and the abnormal cause under each abnormal cause. The size of the correlation weight can be calculated according to the theory of traditional Chinese medicine. The theory and clinical practice experience are used to set it to reflect the importance of different information features to the diagnosis of abnormal causes. Here, after obtaining the correlation degree and correlation weight, the comprehensive correlation index of each abnormal cause can be calculated based on the weighted combination of the two. The expression of the comprehensive correlation index is: I=∑(Di*Wi), where I represents the comprehensive correlation index, Di represents the correlation degree of the ith abnormal cause, Wi represents the correlation weight of the ith abnormal cause, and the value range of i is the number of all abnormal causes. Subsequently, they are sorted according to the size of the comprehensive correlation index. The larger the comprehensive correlation index, the stronger the correlation between the abnormal cause and the patient's current health status. Therefore, when outputting the processing priority of the abnormal cause, the abnormal cause with a higher comprehensive correlation index should be given priority, so that medical staff can concentrate on dealing with the most critical health problems and improve the pertinence and effectiveness of diagnosis and treatment.

[0027] S4. confirming the correlation between the causes of each abnormality, and revising the priority list according to the correlation, wherein the correlation includes concurrent relationship, coexistence relationship and independent relationship; In step S4, after the processing priority of the abnormal causes is determined, it is necessary to perform priority correction according to the correlation between the abnormal causes, so as to further ensure the accuracy and effectiveness of the cause processing. The steps of confirming the correlation between the abnormal causes and correcting the priority list according to the correlation include: Construct the correlation analysis matrix of abnormal causes and simultaneously calculate the matrix element values. The matrix dimension is n×n, where n is the total number of abnormal causes. Introducing a preset evaluation interval and combining the matrix element values ​​to determine the correlation between abnormal causes; When the matrix element value exceeds the upper limit of the evaluation interval, the correlation between the abnormal causes is recorded as a concurrent relationship, and the abnormal causes with low processing priority under the concurrent relationship are promoted to the same level as the abnormal causes with the highest processing priority. When the matrix element value belongs to the evaluation interval, the correlation between the abnormal causes is recorded as a coexistence relationship, and the processing priority under the coexistence relationship remains unchanged; When the matrix element value is lower than the lower limit of the evaluation interval, the correlation between the abnormal causes is recorded as an independent relationship, and the processing priority under the independent relationship remains unchanged; In order to confirm the correlation between the causes of abnormalities, first, a matrix for analyzing the correlation between the causes of abnormalities is constructed. The dimension of the matrix is ​​n×n, where n represents the total number of abnormal causes. While constructing the matrix, the value of each element in the matrix (matrix element value) is calculated synchronously to ensure the accuracy and real-time performance of the data. The formula for determining the matrix element value is: , where represents the matrix element value, and represents the adjustment factor, and + =1, Indicates tongue, pulse and complexion in the cause of the disease and The correlation coefficient between and Respectively indicate the cause of abnormality and The associated historical case data set, indicating Indicates unusual causes in historical cases and The co-occurrence frequency of is then introduced into the preset evaluation interval, which is used to determine the correlation between abnormal causes in combination with the matrix element values. The specific determination method is as follows: When the value of an element in the matrix exceeds the upper limit of the evaluation interval, it indicates that there is a strong correlation between the corresponding two abnormal causes. At this time, this correlation is recorded as a concurrent relationship. In this case, in order to ensure the efficiency and effect of the processing, the abnormal cause with a lower processing priority under the concurrent relationship is promoted to the same level as the abnormal cause with the highest processing priority so that they can be processed at the same time; If the matrix element value is within the evaluation interval, it indicates that the corresponding abnormal causes have a certain correlation, but it is not strong. At this time, this correlation is recorded as a coexistence relationship. Under the coexistence relationship, the processing priority of each abnormal cause remains unchanged in the original order and is processed in the established order. If there are sufficient resources, parallel processing can also be considered. In addition, if the coexistence relationship appears frequently in historical cases, medical staff also need to pay certain attention to ensure that the condition does not worsen. It can also be converted into a concurrent relationship. On the contrary, when the frequency is low, the original coexistence relationship is maintained unchanged; When the matrix element value is lower than the lower limit of the evaluation interval, it means that there is almost no correlation between the corresponding two abnormal causes. At this time, this correlation is recorded as an independent relationship. Under the independent relationship, the processing priority of each abnormal cause remains unchanged in the original order, and each is processed independently.

[0028] See also Figure 2 , a health data detection system based on TCM diagnosis and treatment, using the above-mentioned health data detection method based on TCM diagnosis and treatment, comprising: A data acquisition module, which is used to acquire the patient's health diagnosis and treatment data and output health information based on the health diagnosis and treatment data, wherein the health information includes tongue health information, pulse health information and complexion health information; Information quantification module: The information quantification module is used to evaluate the health status of patients based on health information and simultaneously output the evaluation index; The evaluation module is used to compare the evaluation index with the preset evaluation threshold, and when the evaluation index exceeds the preset evaluation threshold, the health trend map is output; when the evaluation index does not exceed the evaluation threshold, the abnormal cause data analysis is triggered, and the cause treatment priority is output according to the analysis results. A priority correction module, which is used to confirm the correlation between the causes of abnormalities and correct the priority list according to the correlation, wherein the correlation includes concurrent relationship, coexistence relationship and independent relationship; In the above, the main function of the data acquisition module is to collect the patient's health diagnosis and treatment data, and based on these health diagnosis and treatment data, systematically output detailed health information. The health information not only covers tongue health information, such as tongue quality, tongue coating and other details, but also includes pulse health information, such as pulse rate, pulse rhythm and other characteristics, and complexion health information, such as complexion color, gloss and other manifestations. The role of the information quantification module is to conduct a scientific and systematic evaluation of the patient's current health status based on the above-mentioned health information, convert complex health information into quantitative evaluation indexes, and synchronously output these evaluation indexes for further processing by subsequent modules. The main task of the evaluation module is to output the information quantification module The evaluation index is carefully compared with the evaluation threshold preset by the system. When the evaluation index exceeds the preset evaluation threshold, the system will automatically generate and output a health trend map to intuitively display the patient's health change trend. When the evaluation index does not exceed the evaluation threshold, the system will trigger the abnormal cause data analysis function, deeply analyze potential health problems, and scientifically output the priority of cause treatment based on the analysis results. The function of the priority correction module is to confirm the complex correlation between the abnormal causes. By comprehensively analyzing the concurrent relationship, coexistence relationship and independent relationship between the causes, the system accurately corrects the priority list based on these correlations to ensure that the order and strategy of cause treatment are more reasonable and efficient.

[0029] See also Figure 3 , a health data detection device based on traditional Chinese medicine diagnosis and treatment, the detection device includes: at least one processor; and a memory communicatively coupled to the at least one processor; Among them, the memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the above-mentioned health data detection method based on traditional Chinese medicine diagnosis and treatment.

[0030] The processor of the above-mentioned detection device can be a central processing unit (CPU), a graphics processing unit (GPU) or a digital signal processor (DSP), etc. The memory can include a high-speed random access memory (RAM) and can also include a non-volatile memory (NVM), such as at least one disk storage. In some embodiments, the memory can also be a memory array. The memory can store various data, including but not limited to computer program codes for system operation and application. At least one processor and memory can be connected via a bus or other means so that the processor can access the memory. The electronic device can also include an operator, an input device and an output device, etc. The operator can be an arithmetic logic unit (ALU), which is responsible for performing various arithmetic and logical operations; the input device can be a keyboard, a touch screen or a mouse, etc., which is used to receive user input instructions; the output device can be a display screen, a printer, etc., which is used to display processing results or print reports.

[0031] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0032] The above is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the protection scope of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention shall be implemented according to the conventional means in the art unless otherwise specified and limited.

Claims

1. A health data detection method based on traditional Chinese medicine diagnosis and treatment, characterized by: include: Obtain the patient's health diagnosis and treatment data, and output health information based on the health diagnosis and treatment data, wherein the health information includes tongue health information, pulse health information, and complexion health information; Assess the patient's health status based on the health information and simultaneously output an assessment index; The evaluation index is compared with the preset evaluation threshold, and when the evaluation index exceeds the preset evaluation threshold, a health trend map is output; when the evaluation index does not exceed the evaluation threshold, abnormal cause data analysis is triggered, and the cause treatment priority is output according to the analysis result; The correlation between the causes of abnormalities is confirmed, and the priority list is modified according to the correlation, wherein the correlation includes concurrent relationship, coexistence relationship and independent relationship.

2. A health data detection method based on TCM diagnosis and treatment according to claim 1, characterized in that: After the tongue image information is output, the patient's tongue image health information is determined based on image recognition. The specific process is as follows: Obtaining the patient's tongue image information, and performing feature extraction on the tongue image information to obtain tongue image features to be diagnosed; Obtain standard tongue image features in the standard image of TCM tongue diagnosis; Comparing the standard tongue image features with the tongue image features to be diagnosed, and synchronously outputting the deviation area between the standard tongue image features and the tongue image features to be diagnosed; All the deviation areas are extracted and summarized as tongue image health information.

3. The health data detection method based on traditional Chinese medicine diagnosis and treatment according to claim 1 is characterized by: After the pulse information is output, the patient's pulse health information is determined by waveform analysis, and the specific process is as follows: Acquiring the patient's pulse information, and performing waveform feature extraction on the pulse information to obtain pulse waveform features; Compare the pulse waveform feature with the standard pulse waveform feature of traditional Chinese medicine, and output the deviation section of the pulse waveform feature; The duration of the deviation segment and the frequency of deviation are counted and summarized as the patient's pulse health information.

4. The method for detecting health data based on TCM diagnosis and treatment according to claim 1, characterized in that: After the complexion information is output, the complexion health information of the patient is determined based on color analysis. The specific process is as follows: Acquire the patient's complexion information, and perform color space conversion on the complexion information, converting the complexion information from the RGB color space to the HSV color space; In the HSV color space, the color information of the face is segmented and the main color components of the face color are extracted; The main color component is compared with the standard color of TCM complexion, and the color difference is output and simultaneously summarized as complexion health information.

5. The health data detection method based on TCM diagnosis and treatment according to claim 1 is characterized by: The step of evaluating the patient's health status based on the health information and synchronously outputting an evaluation index includes: Obtaining the tongue health information, pulse health information and complexion health information; Assigning corresponding evaluation weights to the tongue image health information, pulse health information and complexion health information; A comprehensive evaluation function is obtained, and the tongue health information, pulse health information, complexion health information, and corresponding evaluation weights are input into the comprehensive evaluation function for fusion operation, and the output result of the comprehensive evaluation function is recorded as an evaluation index.

6. The method for detecting health data based on TCM diagnosis and treatment according to claim 1, characterized in that: The output of the health trend graph includes the following steps: Sorting the tongue image information, pulse information and complexion information according to the time sequence of collection; Taking the current acquisition node of the tongue image information, pulse information and complexion information as a reference, reverse offset processing is performed to obtain a sample period; Collecting tongue image information, pulse information and complexion information within the sample period, and recording them as a first sample parameter, a second sample parameter and a third sample parameter respectively; Inputting the first sample parameter, the second sample parameter and the third sample parameter into a trend evaluation function, and recording the output result of the trend evaluation function as a sample trend parameter; Based on the sample trend parameters, a health trend map is constructed, in which a health trend curve is drawn with the time series as the horizontal axis and the sample trend parameters as the vertical axis; After the sample trend parameter is output, a preset trend evaluation threshold is introduced, and the trend evaluation threshold is compared with the sample trend parameter; When the sample trend parameter is less than the trend assessment threshold, it indicates that the patient's health condition is developing in a normal trend; When the sample trend parameter is greater than or equal to the trend evaluation threshold, it indicates that the patient's health condition development trend is abnormal, and a warning signal is issued simultaneously.

7. The health data detection method based on TCM diagnosis and treatment according to claim 1, characterized in that: When outputting the cause treatment priority according to the analysis result, the following steps are included: Collect all abnormal causes corresponding to the tongue image health information, pulse health information and complexion health information; Obtaining the correlation between the tongue health information, pulse health information and complexion health information and the abnormal cause under each abnormal cause; Obtaining the association weights between the tongue health information, pulse health information, and complexion health information and the abnormal causes under each abnormal cause; According to the correlation degree and the correlation weight, the comprehensive correlation index of each abnormal cause is calculated, and the causes are sorted according to the comprehensive correlation index, and then the processing priority of the abnormal cause is output according to the sorting result.

8. The method for detecting health data based on TCM diagnosis and treatment according to claim 1, characterized in that: The step of confirming the correlation between the causes of abnormalities and revising the priority list according to the correlation includes: Construct the correlation analysis matrix of abnormal causes and simultaneously calculate the matrix element values. The matrix dimension is n×n, where n is the total number of abnormal causes. Introducing a preset evaluation interval and combining the matrix element values ​​to determine the correlation between abnormal causes; When the matrix element value exceeds the upper limit of the evaluation interval, the correlation between the abnormal causes is recorded as a concurrent relationship, and the abnormal causes with low processing priority under the concurrent relationship are promoted to the same level as the abnormal causes with the highest processing priority. When the matrix element value belongs to the evaluation interval, the correlation between the abnormal causes is recorded as a coexistence relationship, and the processing priority under the coexistence relationship is kept unchanged in the original order; When the matrix element value is lower than the lower limit of the evaluation interval, the correlation between the abnormal causes is recorded as an independent relationship, and the processing priority under the independent relationship remains unchanged in the original order.

9. A health data detection system based on traditional Chinese medicine diagnosis and treatment, characterized by: The health data detection method based on TCM diagnosis and treatment according to any one of claims 1 to 8 comprises: A data acquisition module, the data acquisition module is used to acquire the patient's health diagnosis and treatment data, and output health information based on the health diagnosis and treatment data, wherein the health information includes tongue health information, pulse health information and complexion health information; An information quantification module, the information quantification module is used to evaluate the health status of the patient based on the health information and synchronously output an evaluation index; An evaluation module is used to compare the evaluation index with a preset evaluation threshold, and when the evaluation index exceeds the preset evaluation threshold, output a health trend map, and when the evaluation index does not exceed the evaluation threshold, trigger abnormal etiology data analysis, and output etiology treatment priority according to the analysis results The priority correction module is used to confirm the correlation between the causes of abnormalities and correct the priority list according to the correlation, wherein the correlation includes concurrent relationship, coexistence relationship and independent relationship.

10. A health data detection device based on traditional Chinese medicine diagnosis and treatment, characterized by: The detection equipment comprises: at least one processor; and a memory communicatively coupled to the at least one processor; Among them, the memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the health data detection method based on traditional Chinese medicine diagnosis and treatment as described in any one of claims 1 to 8.

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