Tumor nursing method combined with traditional medicine

Abstract

The invention provides a tumor nursing method combined with traditional medicine, which comprises the following steps: collecting physiological data such as meridian conductance, acupoint temperature and qi and blood running rate of a patient through a multi-modal sensor, and after multi-dimensional preprocessing, inputting a dynamic harmonic algorithm to generate a personalized nursing parameter set, including acupuncture intensity, cupping positioning and scraping time sequence parameters. And the intelligent acupuncture device and the negative pressure cupping device execute corresponding operations according to the information. Meanwhile, skin microcirculation indexes and local temperature distribution are monitored in real time, body surface thermodynamic characteristics are obtained through an infrared thermal imager, and when monitoring data exceed a threshold value, an adjustment algorithm is fed back to dynamically correct a nursing parameter set. And finally, generating a nursing scheme, and outputting comprehensive nursing suggestions of traditional Chinese medicine constitution classification and prognosis evaluation reports. The nursing effect can be improved, the risk is reduced, and patient rehabilitation is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of medical care, and more specifically, the present invention relates to a tumor nursing method combining traditional medicine. Background Art

[0002] In modern medicine, the treatment methods for tumors are becoming increasingly diverse, including surgery, radiotherapy, chemotherapy, etc. However, these methods are often accompanied by significant side effects, such as physical weakness, decreased immunity, etc. In order to alleviate these side effects and improve the quality of life of patients, traditional Chinese medicine nursing methods have gradually attracted attention. Traditional Chinese medicine nursing methods such as acupuncture, cupping, and scraping have the effects of regulating qi and blood in the human body and dredging meridians, but their operations rely on the experience of Chinese medicine practitioners and lack precise quantitative standards, making it difficult to achieve personalized nursing. In addition, traditional Chinese medicine nursing lacks a real-time monitoring and feedback regulation mechanism during the implementation process and cannot dynamically adjust nursing parameters according to the specific reactions of patients, resulting in unstable nursing effects.

[0003] In the process of implementing the embodiments of the present invention, the inventors found that there are at least the following problems or defects in the prior art: traditional Chinese medicine nursing methods are difficult to achieve precise quantification and personalized nursing, and lack a real-time monitoring and feedback regulation mechanism, which limits their application effects in tumor nursing. Summary of the Invention

[0004] The present invention provides a tumor nursing method combining traditional medicine, including: S1: Collect physiological characteristic data of the patient through a multi-modal sensor, where the physiological characteristic data includes meridian conductance data, acupoint temperature data, and qi and blood running rate data; S2: Perform multi-dimensional preprocessing on the physiological characteristic data, including noise filtering, feature normalization, and missing value imputation; S3: Input the preprocessed physiological characteristic data into a dynamic harmonic algorithm to generate a personalized nursing parameter set including acupuncture intensity parameters, cupping positioning parameters, and scraping timing parameters; S4: According to the personalized nursing parameter set, control an intelligent acupuncture device to perform pulsed acupoint stimulation operations, and synchronously control a negative pressure cupping device to perform surface gradient adsorption operations; S5: Real-time monitor the microcirculation index and local temperature distribution on the patient's skin surface, and obtain surface thermodynamic characteristics through an infrared thermal imager; S6: When the microcirculation index or local temperature distribution exceeds the set threshold, trigger a feedback regulation algorithm to dynamically correct the personalized nursing parameter set; S7: Generate a final nursing plan based on the corrected personalized nursing parameter set, and synchronously output a comprehensive nursing recommendation including traditional Chinese medicine constitution classification and prognosis assessment report.

[0005] Further, the dynamic harmonic algorithm performs the following operations: Calculate the meridian characteristic coefficient based on the patient's meridian conductance data , and the calculation formula is: Where, represents the conductivity measurement value of a specific acupoint, represents the conductivity reference threshold, represents the negative pressure value of the cupping area, represents the negative pressure safety threshold, represents the scraping intensity coefficient, represents the upper limit of scraping intensity, are the weight coefficients of conductivity, negative pressure value, and scraping intensity respectively, and .

[0006] Further, the step S3 includes: S31: Generate an initial care plan matrix M based on the meridian characteristic coefficient J, where the rows of the matrix M represent care items and the columns represent time series; S32: Exclude care elements that conflict with the patient's traditional Chinese medicine constitution through the taboo analysis module; S33: Calculate the implementation duration of each care element using the energy balance model : Where, represents the patient's current qi and blood energy value, represents the energy consumption reference value during the care process, and k is the duration adjustment coefficient.

[0007] Further, the feedback adjustment algorithm in the step S6 includes: S61: Extract the abnormal temperature zone feature quantity through the image segmentation algorithm ; S62: When exceeds the warning value, trigger the care parameter correction function: Where, represents the corrected care parameter, represents the original care parameter, is the correction rate coefficient, represents the temperature safety threshold.

[0008] Further, in the step S2: The noise filtering adopts the adaptive wavelet threshold method, the feature normalization adopts the Z-score standardization algorithm, and the missing value imputation adopts the K-nearest neighbor imputation method based on the meridian topological structure.

[0009] Furthermore, the weight coefficient is determined by the following method: Based on the traditional Chinese medicine syndrome differentiation of the patient, select the base value from the pre-stored coefficient mapping table; Dynamically adjust the base value according to the pulse condition data collected in real time, and the adjustment range does not exceed ±30% of the base value.

[0010] Furthermore, the step S4 includes: S41: Control the intelligent acupuncture device to perform a stimulation operation at a pulse frequency f, and the pulse frequency satisfies: wherein, is the reference frequency, is the frequency adjustment coefficient, and J is the meridian characteristic coefficient; S42: Synchronously control the negative pressure cupping device to generate a gradient negative pressure distribution in the target area, and the negative pressure value in the central area and the negative pressure value in the edge area satisfy: wherein, is the negative pressure value in the central area, is the negative pressure value in the edge area.

[0011] Furthermore, the determination method of the correction rate coefficient includes: Establish a three-dimensional adjustment model including the patient's age A, disease course D, and body mass index B: wherein, is the reference correction rate, A is the age, D is the disease course, and B is the body mass index.

[0012] Furthermore, in the step S7, the prognosis evaluation report includes: S71: Calculate the qi and blood balance degree Q: wherein, represents the qi and blood energy value after nursing, represents the qi and blood energy value before nursing, represents the theoretical maximum qi and blood energy value; S72: Generate extended nursing suggestions including diet taboos, exercise plans, and psychological interventions based on the Q value.

[0013] Furthermore, it also includes: Establish a multi-dimensional safety monitoring mechanism, and start an emergency termination procedure when the following conditions are met simultaneously: (1) The skin impedance change rate 15%; (2) Local temperature gradient ; (3) Heart rate variability coefficient HRV < 70% of the normal value wherein, represents the difference between the real-time impedance and the reference impedance, represents the initial reference impedance value.

[0014] According to the above embodiments of the present invention, there are at least the following beneficial effects: First, the present invention first collects the physiological characteristic data of patients through multi-modal sensors and performs multi-dimensional preprocessing, and combines a dynamic harmonic algorithm to generate a personalized nursing parameter set, which can achieve precise and personalized traditional Chinese medicine nursing. This method can dynamically adjust the parameters of nursing operations such as acupuncture, cupping, and scraping according to the real-time physiological state of patients, ensuring that the nursing process is more in line with the actual needs of patients, thereby improving the nursing effect and reducing the risks caused by improper operations. Second, the present invention monitors the microcirculation index and local temperature distribution on the skin surface of patients in real time during the nursing process, and dynamically corrects the nursing parameter set through a feedback adjustment algorithm, which can effectively avoid skin damage or other adverse reactions caused by nursing operations. At the same time, a final nursing plan is generated based on the corrected nursing parameter set, and a comprehensive nursing advice including traditional Chinese medicine constitution classification and prognosis assessment report is synchronously output, providing comprehensive nursing guidance for patients and further promoting the recovery of patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] By referring to the detailed description below with reference to the accompanying drawings, the above and other objects, features, and advantages of the exemplary embodiments of the present invention will become readily understood. In the drawings, several embodiments of the present invention are shown by way of illustration and not limitation, wherein: Figure 1 is a schematic flow chart of a tumor nursing method combining traditional medicine provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] The principles and spirit of the present invention will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are provided only to enable those skilled in the art to better understand and then implement the present invention, and do not limit the scope of the present invention in any way. On the contrary, these embodiments are provided to make the present invention more thorough and complete, and to be able to fully convey the scope of the present invention to those skilled in the art.

[0017] Those skilled in the art know that the embodiments of the present invention can be implemented as a system, device, equipment, method, or computer program product. Therefore, the present invention can be specifically implemented in the following forms: completely hardware, completely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0018] It should be noted that the quantity of any element in the accompanying drawings is for illustration rather than limitation, and any naming is only for distinction and does not have any limiting meaning.

[0019] The following refers to Figure 1 , Figure 1 , which is a schematic flowchart of a tumor care method combining traditional medicine provided by an embodiment of the present invention. As Figure 1 shown, a tumor care method 100 combining traditional medicine includes: S1: Collect physiological characteristic data of the patient through a multimodal sensor, where the physiological characteristic data includes meridian conductance data, acupoint temperature data, and qi and blood running rate data; S2: Perform multi-dimensional preprocessing on the physiological characteristic data, including noise filtering, feature normalization, and missing value imputation; S3: Input the preprocessed physiological characteristic data into a dynamic reconciliation algorithm to generate a personalized care parameter set including acupuncture intensity parameters, cupping positioning parameters, and scraping timing parameters; S4: According to the personalized care parameter set, control an intelligent acupuncture device to perform pulsed acupoint stimulation operations, and synchronously control a negative pressure cupping device to perform surface gradient adsorption operations; S5: Real-time monitor the microcirculation index and local temperature distribution on the patient's skin surface, and obtain the surface thermodynamic characteristics through an infrared thermal imager; S6: When the microcirculation index or local temperature distribution exceeds the set threshold, trigger a feedback regulation algorithm to dynamically correct the personalized care parameter set; S7: Generate a final care plan based on the corrected personalized care parameter set, and synchronously output a comprehensive care recommendation including traditional Chinese medicine constitution classification and prognosis assessment report.

[0020] It should be noted that the present invention collects physiological characteristic data of the patient through a multimodal sensor, and these data include meridian conductance data, acupoint temperature data, and qi and blood running rate data. A multimodal sensor refers to a set of devices that can simultaneously collect multiple types of physiological signals. For example, meridian conductance data can be collected through a dedicated electrode sensor, which reflects the conductivity of the human meridian and is usually related to the running state of qi and blood; acupoint temperature data is obtained through a temperature sensor and is used to evaluate the blood circulation and metabolism around the acupoint; qi and blood running rate data can be measured through a non-invasive device such as an optical sensor, which reflects the flow rate of qi and blood in the body. The collection of these data provides a basic basis for subsequent personalized care, ensuring that care operations can be carried out based on the actual physiological state of the patient.

[0021] Specifically, the settings of the multi-modal sensors need to be adjusted according to the patient's physical characteristics and nursing needs. For example, the acquisition of meridian conductance data can be achieved by placing electrodes at specific acupoints. The size and shape of the electrodes can be selected according to the position and area of the acupoints to ensure accurate signal acquisition. The acquisition of acupoint temperature data needs to consider the sensitivity and accuracy of the temperature sensor, as well as its stability in contact with the skin. The acquisition of qi and blood flow rate data requires the selection of a suitable optical sensor, whose working principle is to estimate the qi and blood flow velocity by detecting the absorption or reflection of specific wavelength light by blood. The data collected by these sensors will be transmitted to the data processing unit for further analysis and processing.

[0022] Preferably, when collecting physiological characteristic data, the placement position and acquisition frequency of the sensors can be optimized. For example, for the acquisition of meridian conductance data, key acupoints on the main meridians of the human body, such as Hegu acupoint and Zusanli acupoint, can be selected. The meridian conductance changes at these acupoints can better reflect the overall qi and blood state of the human body. The acquisition frequency can be adjusted according to the patient's condition and nursing needs. For patients with more severe conditions, the acquisition frequency can be appropriately increased to obtain physiological change information more timely. In addition, a data calibration mechanism can be introduced to regularly calibrate the data collected by the sensors to ensure the accuracy and reliability of the data.

[0023] In some embodiments, the dynamic reconciliation algorithm performs the following operations: Calculate the meridian characteristic coefficient based on the patient's meridian conductance data , and the calculation formula is: where represents the conductivity measurement value of a specific acupoint, represents the conductivity reference threshold, represents the negative pressure value in the cupping area, represents the negative pressure safety threshold, represents the scraping intensity coefficient, represents the upper limit of the scraping intensity, are the weight coefficients of conductivity, negative pressure value, and scraping intensity respectively, and .

[0024] It should be noted that the dynamic harmonization algorithm is the core algorithm in the present invention for generating personalized care parameter sets, which calculates meridian characteristic coefficients based on the meridian conductance data of patients. The meridian characteristic coefficients are calculated by comprehensively considering multiple factors such as the conductivity measurement values of specific acupoints, the negative pressure values in cupping areas, and the scraping intensity coefficients. Among them, the conductivity measurement value refers to the conductivity numerical value of a specific acupoint collected by a sensor, reflecting the smoothness of the meridian at this acupoint; the negative pressure value refers to the magnitude of the negative pressure formed in the cupping jar during cupping, used to evaluate the intensity of the cupping operation; the scraping intensity coefficient is a quantitative value set according to parameters such as the strength and frequency of the scraping operation. These parameters are weighted and calculated through specific weight coefficients, and finally the meridian characteristic coefficients are obtained, which are used to guide subsequent care operations.

[0025] Specifically, the weight coefficients in the dynamic harmonization algorithm are respectively the weight coefficients of conductivity, negative pressure value, and scraping intensity, and the sum of these three weight coefficients is 1. The setting of the weight coefficients can be adjusted according to traditional Chinese medicine theory and clinical experience. For example, if the smoothness of the patient's meridians is the main problem, the value of the conductivity weight coefficient can be increased; if it is necessary to focus on regulating the qi and blood circulation, the scraping intensity coefficient can be appropriately increased. In addition, parameters such as the conductivity reference threshold, negative pressure safety threshold, and scraping intensity upper limit are set according to clinical safety standards and the specific conditions of the patient. For example, the conductivity reference threshold can be set according to the average value of the meridian conductance of the normal human body, the negative pressure safety threshold is determined according to the safe range of the cupping operation, and the scraping intensity upper limit is set according to the tolerance of the patient's skin.

[0026] Preferably, when implementing the dynamic harmonization algorithm, a dynamic adjustment mechanism can be introduced to dynamically adjust the weight coefficients according to the physiological characteristic data collected in real time. For example, if abnormal fluctuations are found in the patient's meridian conductance data during the care process, the value of the conductivity weight coefficient can be appropriately increased to more precisely adjust the care parameters. In addition, the reference threshold can also be adjusted personalized according to factors such as the patient's age and constitution. For example, for elderly patients, the negative pressure safety threshold can be appropriately reduced to reduce the risk of the cupping operation.

[0027] In some embodiments, step S3 includes: S31: Generate an initial care plan matrix M based on the meridian characteristic coefficient J, where the rows of the matrix M represent care items and the columns represent time series; S32: Exclude care elements that conflict with the patient's traditional Chinese medicine constitution through a tabu analysis module; S33: Calculate the implementation duration of each care element using an energy balance model : Among them, Represents the current qi and blood energy value of the patient, Represents the energy consumption benchmark value during the nursing process, and k is the duration adjustment coefficient.

[0028] It should be noted that step S3 mentioned in the present invention is the key link for generating a personalized nursing plan. This step first generates an initial nursing plan matrix based on the meridian characteristic coefficients. The rows of this matrix represent nursing items, and the columns represent time series, which are used to plan the time arrangement of different nursing operations. Subsequently, the taboo analysis module excludes the nursing elements that conflict with the patient's traditional Chinese medicine constitution to ensure that the nursing plan conforms to the individual characteristics of the patient. Finally, an energy balance model is used to calculate the implementation duration of each nursing element, comprehensively considering the patient's current qi and blood energy value and the energy consumption during the nursing process, so as to formulate a scientific and reasonable nursing plan for the patient.

[0029] Specifically, the generation of the initial nursing plan matrix determines the nursing items and time series according to the meridian characteristic coefficients. For example, areas with higher meridian characteristic coefficients may require more frequent acupuncture or scraping operations, while areas with lower coefficients can appropriately reduce the number of operations. The role of the taboo analysis module is to exclude those nursing elements that may have an adverse impact on the patient according to traditional Chinese medicine theory. For example, for patients with weak constitutions, it is taboo to use overly strong scraping operations. In the formula for calculating the implementation duration of the energy balance model, the patient's current qi and blood energy value can be estimated from physiological characteristic data, and the energy consumption benchmark value during the nursing process is a standard value set according to clinical experience. The duration adjustment coefficient k can be dynamically adjusted according to the patient's recovery situation. For example, if the patient recovers well, the duration adjustment coefficient can be appropriately increased to extend the nursing time.

[0030] Preferably, when generating the initial nursing plan matrix, the priorities of nursing items can be sorted according to the severity of the patient's condition. For example, for cancer patients, nursing operations related to cancer-related meridians are given priority. In the taboo analysis module, a traditional Chinese medicine constitution classification database can be introduced to automatically identify taboo nursing elements according to the patient's constitution type. For example, for patients with damp-heat constitutions, it is taboo to use warm cupping operations. In the energy balance model, the duration adjustment coefficient k can be personalized according to the patient's age and constitution. For example, for elderly patients, the duration adjustment coefficient is appropriately reduced to reduce the nursing time and relieve the physical burden.

[0031] In some embodiments, the feedback adjustment algorithm in step S6 includes: S61: Extract the abnormal temperature zone feature quantity through an image segmentation algorithm ; S62: When exceeds the warning value, trigger the nursing parameter correction function: Among them, represents the corrected nursing parameters, represents the original nursing parameters, is the correction rate coefficient, represents the temperature safety threshold.

[0032] It should be noted that the feedback adjustment algorithm in step S6 is a key link in the present invention for dynamically correcting the personalized nursing parameter set. When the microcirculation index or local temperature distribution monitored in real time exceeds the set threshold, this algorithm can trigger the correction of nursing parameters in a timely manner. The feedback adjustment algorithm extracts the characteristic quantities of the abnormal temperature area through the image segmentation algorithm, and then dynamically adjusts the nursing parameters according to this characteristic quantity. The characteristic quantity of the abnormal temperature area here refers to the characteristic value corresponding to the area that exceeds the normal range in the body surface thermodynamic characteristics obtained by the infrared thermal imager, and the nursing parameter correction function is a function calculated according to this characteristic quantity for adjusting the intensity or frequency of nursing operations. The purpose of this algorithm is to ensure the safety and effectiveness of nursing operations and avoid causing harm to patients due to improper operations.

[0033] Specifically, the image segmentation algorithm is used to extract the abnormal temperature area from the body surface thermodynamic characteristic image obtained by the infrared thermal imager. This algorithm can identify the abnormal area according to the gradient change of the temperature distribution or a specific temperature threshold, and calculate the characteristic quantities of the abnormal temperature area, such as area, average temperature, etc. When the characteristic quantity of the abnormal temperature area exceeds the warning value, the nursing parameter correction function is triggered. The calculation method of the correction function is to adjust the nursing parameters according to the original nursing parameters and the correction rate coefficient, combined with the temperature safety threshold. For example, if the local temperature is too high, it may be necessary to reduce the pulse frequency of acupuncture or the negative pressure intensity of cupping. Among them, the correction rate coefficient is a dynamically adjusted parameter, which can be adjusted according to the individual characteristics and real-time physiological state of the patient to ensure that the corrected nursing parameters can effectively adjust the nursing intensity without causing adverse effects on the patient.

[0034] Preferably, the image segmentation algorithm can adopt advanced image processing techniques, such as the segmentation algorithm based on deep learning, to improve the accuracy and efficiency of abnormal temperature area recognition. When triggering the nursing parameter correction function, the correction strategy can be further refined. For example, for the situation of too high local temperature, in addition to reducing the nursing operation intensity, cooling measures can also be increased, such as using cold compress in the local area. In addition, more patient individual characteristics, such as age, body mass index, etc., can be introduced to determine the correction rate coefficient, and a three-dimensional adjustment model can be established to dynamically calculate the correction rate coefficient. For example, for elderly patients or patients with weak constitutions, the correction rate coefficient can be appropriately reduced to adjust the nursing parameters in a more gentle manner to ensure the safety and comfort of the patient.

[0035] In some embodiments, in step S2: The noise filtering adopts the adaptive wavelet threshold method, the feature normalization adopts the Z-score standardization algorithm, and the missing value imputation adopts the K-nearest neighbor imputation method based on the meridian topological structure.

[0036] It should be noted that the multi-dimensional preprocessing in step S2 is a key link to ensure the accurate implementation of subsequent nursing operations. This step includes three parts: noise filtering, feature normalization, and missing value imputation. Noise filtering is used to remove the interference signals in the collected physiological feature data. Feature normalization is to convert the data with different dimensions and ranges into a unified standard form for subsequent processing and analysis. And missing value imputation is to fill in the missing values through reasonable methods for the possible missing situations in the data collection process to ensure the integrity of the data. These preprocessing operations can effectively improve the data quality and provide guarantee for generating accurate personalized nursing parameter sets.

[0037] Specifically, the noise filtering adopts the adaptive wavelet threshold method. This method can adaptively select the wavelet basis and threshold according to the characteristics of the signal, so as to effectively remove the high-frequency interference components in the noise signal while retaining the useful information of the signal. The feature normalization adopts the Z-score standardization algorithm. This algorithm eliminates the influence brought by different data dimensions and ranges by converting the data into a standardized form with a mean of 0 and a standard deviation of 1, enabling different types of physiological feature data to be compared and analyzed on the same scale. The missing value imputation adopts the K-nearest neighbor imputation method based on the meridian topological structure. This method uses the topological structure relationship of the meridian system, combines the data information of the surrounding adjacent acupoints or meridians, and calculates the missing values through the K-nearest neighbor algorithm to fill in the blanks in the data and ensure the integrity and accuracy of the data.

[0038] Preferably, in the process of noise filtering, appropriate wavelet bases and thresholds can be selected according to the characteristics of different physiological feature data. For example, for meridian conductance data, wavelet bases suitable for processing high-frequency signals can be selected, while for acupoint temperature data, wavelet bases more suitable for processing low-frequency signals can be selected. In feature normalization, the distribution characteristics of the data can be further considered. For non-normal distributed data, other normalization methods such as Min-Max normalization can be adopted to scale the data to the interval [0,1]. In terms of missing value imputation, the individual characteristics of the patient, such as age and physique, can be combined to optimize the K-nearest neighbor imputation method. For example, for elderly patients, due to the particularity of their physiological characteristics, the K value can be appropriately adjusted to fill in the missing values more accurately. In addition, machine learning algorithms, such as imputation models based on deep learning, can be introduced to further improve the accuracy and reliability of missing value imputation.

[0039] In some embodiments, the determination method of the weight coefficient includes: Select a base value from a pre-stored coefficient mapping table based on the traditional Chinese medicine syndrome differentiation type of the patient; Dynamically adjust the base value according to the pulse condition data collected in real time, and the adjustment range does not exceed ±30% of the base value.

[0040] It should be noted that the method for determining the weight coefficient mentioned in the present invention is dynamically adjusted based on the traditional Chinese medicine syndrome differentiation type of the patient and the pulse condition data collected in real time. The traditional Chinese medicine syndrome differentiation type refers to classifying the constitution and condition of the patient according to traditional Chinese medicine theory, such as qi deficiency, blood stasis, damp-heat, etc. The pulse condition data is collected by a pulse diagnosis device and reflects the state of qi and blood circulation of the patient. The dynamic adjustment mechanism of the weight coefficient can optimize the calculation of the meridian characteristic coefficient according to the individual differences and real-time physiological state of the patient, thereby improving the accuracy of the personalized nursing plan.

[0041] Specifically, the initial value of the weight coefficient is selected from a pre-stored coefficient mapping table according to the traditional Chinese medicine syndrome differentiation type. For example, for a patient with qi deficiency constitution, a set of weight coefficients that tend to enhance qi and blood circulation may be selected. Subsequently, the base values are dynamically adjusted according to the pulse condition data collected in real time. The collection of pulse condition data can be achieved through pulse diagnosis sensors, which can detect characteristics such as the frequency, intensity, and rhythm of the pulse. The adjustment range is limited within ±30% of the base value to ensure that the adjusted weight coefficient still conforms to traditional Chinese medicine theory and clinical experience. This dynamic adjustment mechanism can better adapt to the real-time physiological changes of the patient and improve the adaptability and effectiveness of the nursing plan.

[0042] Preferably, when determining the weight coefficient, the classification criteria of the traditional Chinese medicine syndrome differentiation type can be further refined, and more subdivided constitution types can be introduced to more accurately select the initial weight coefficient. For example, in addition to the common types such as qi deficiency and blood stasis, compound constitution types such as qi stagnation and blood stasis, and phlegm-dampness blockage can also be considered. In the dynamic adjustment process, various physiological characteristic data, such as meridian conductance data and qi and blood circulation rate data, can be combined to comprehensively evaluate the physiological state of the patient, so as to more accurately adjust the weight coefficient. In addition, machine learning algorithms, such as decision trees or neural networks, can be introduced to automatically learn the adjustment rules of the weight coefficient according to a large amount of clinical data, further improving the accuracy and reliability of the dynamic adjustment.

[0043] In some embodiments, step S4 includes: S41: Control the intelligent acupuncture device to perform a stimulation operation at a pulse frequency f, and the pulse frequency satisfies: Wherein, is the reference frequency, is the frequency adjustment coefficient, and J is the meridian characteristic coefficient; S42: Synchronously control the negative pressure cupping device to generate a gradient negative pressure distribution in the target area, where the negative pressure value in the central area and the negative pressure value in the edge area satisfy: wherein, is the negative pressure value in the central area, is the negative pressure value in the edge area.

[0044] It should be noted that step S4 involves controlling the intelligent acupuncture device and the negative pressure cupping device to perform corresponding nursing operations according to the personalized nursing parameter set. The intelligent acupuncture device is a device that can automatically perform acupuncture operations according to preset parameters and adjusts the stimulation intensity of acupuncture by controlling the pulse frequency. The negative pressure cupping device forms a gradient adsorption on the body surface by controlling the negative pressure value to achieve the purpose of dredging meridians and regulating qi and blood. The core of this step is to achieve personalized and precise traditional Chinese medicine nursing operations by accurately controlling the parameters of these devices, ensuring the nursing effect while reducing the discomfort of patients.

[0045] Specifically, the pulse frequency control of the intelligent acupuncture device is dynamically adjusted according to the meridian characteristic coefficient. The reference frequency is a basic value set according to traditional Chinese medicine theory and clinical experience and is usually used for acupuncture operations under normal circumstances. The frequency adjustment coefficient is adjusted according to the meridian characteristic coefficient J to adapt to the meridian states of different patients. For example, when the meridian characteristic coefficient is high, it may be necessary to increase the pulse frequency to enhance the stimulation effect. For the negative pressure cupping device, the relationship between the negative pressure value in the central area and the negative pressure value in the edge area is controlled by setting a fixed ratio, that is, the negative pressure value in the central area is 1.5 times that in the edge area. This gradient negative pressure distribution can better simulate the traditional cupping technique and reduce the excessive compression on the skin at the same time.

[0046] Preferably, when controlling the intelligent acupuncture device, more physiological characteristic data can be introduced to dynamically adjust the pulse frequency. For example, by combining the real-time collected data of the qi and blood running rate, if it is found that the qi and blood circulation is not smooth, the pulse frequency can be appropriately increased to promote qi and blood circulation. For the negative pressure cupping device, in addition to controlling the negative pressure ratio between the central and edge areas, the negative pressure value can also be dynamically adjusted according to the skin sensitivity and tolerance of the patient. For example, for patients with sensitive skin, the negative pressure value can be appropriately reduced to reduce the risk of skin damage. In addition, an intelligent monitoring system can be introduced to provide real-time feedback on the physiological reactions of the patient, such as skin temperature changes or heart rate changes, so as to further optimize the setting of nursing parameters.

[0047] In some embodiments, the method for determining the correction rate coefficient includes: Establish a three-dimensional adjustment model including the patient's age A, disease course D, and body mass index B: Among them, is the reference correction rate, A is the age, D is the disease course, and B is the body mass index.

[0048] It should be noted that the method for determining the correction rate coefficient is based on a three-dimensional adjustment model including the patient's age, disease course, and body mass index. By comprehensively considering the influence of these factors on the physiological response and recovery ability during the patient care process, the correction rate coefficient is dynamically adjusted. The age (A) reflects the patient's physiological function and recovery ability, the disease course (D) represents the length of time the patient has been ill, and the body mass index (B) is a comprehensive indicator measuring the patient's physical condition. Through the comprehensive consideration of these factors, the nursing parameters can be adjusted more accurately to ensure the safety and effectiveness of the care process.

[0049] Specifically, in the calculation formula of the correction rate coefficient, the reference correction rate is a base value set according to clinical experience and nursing standards. The age factor 0.01A takes into account the influence of the patient's age on nursing tolerance. Generally, the older the patient, the weaker the physiological function, and more cautious adjustment of nursing parameters is required. The disease course factor -0.05D reflects the influence of the disease course length on the patient's physical state. The longer the disease course, the slower the adjustment of the nursing intensity may be required. The body mass index factor 0.02B adjusts the correction rate according to the patient's weight and height ratio. Patients with a higher or lower body mass index may require special nursing adjustments. These factors work together to dynamically adjust the correction rate coefficient to adapt to the individual differences of different patients.

[0050] Preferably, when determining the correction rate coefficient, the weights of each factor can be further refined. For example, for elderly patients, the weight of the age factor can be appropriately increased to more cautiously adjust the nursing parameters. For patients with a long-term illness, the weight of the disease course factor can be appropriately adjusted to avoid too rapid adjustment of the nursing intensity due to a long disease course. In addition, the body mass index factor can be adjusted in layers according to the patient's gender and age, because the influence of the body mass index on nursing tolerance may be different for different genders and age groups. Machine learning algorithms can also be introduced to automatically learn and optimize the weights of these factors based on a large amount of clinical data, further improving the accuracy of the correction rate coefficient.

[0051] In some embodiments, the prognosis evaluation report in step S7 includes: S71: Calculate the qi-blood balance degree Q: Among them, represents the qi-blood energy value after nursing, Indicates the qi and blood energy value before nursing, Indicates the theoretical maximum qi and blood energy value; S72: Generate extended nursing suggestions including diet taboos, exercise plans, and psychological interventions based on the Q value.

[0052] It should be noted that the prognosis assessment report in step S7 is generated based on the qi and blood balance degree Q, and the qi and blood balance degree Q reflects the change in the qi and blood state of the patient before and after nursing. This indicator calculates by comparing the qi and blood energy values before and after nursing and combining with the theoretical maximum qi and blood energy value, so as to quantitatively evaluate the nursing effect. The prognosis assessment report not only includes the calculation result of the qi and blood balance degree Q, but also generates extended nursing suggestions including diet taboos, exercise plans, and psychological interventions according to this result. These suggestions aim to provide comprehensive rehabilitation guidance for patients and promote the overall health recovery of patients.

[0053] Specifically, in the calculation formula of the qi and blood balance degree Q, the qi and blood energy value after nursing ( ) is estimated by collecting the physiological characteristic data of the patient after nursing, reflecting the qi and blood state after nursing; the qi and blood energy value before nursing ( ) is the initial state before nursing; the theoretical maximum qi and blood energy value ( ) is an ideal value set according to the qi and blood state of the normal human body. By calculating the qi and blood balance degree Q, the improvement degree of nursing on the patient's qi and blood state can be intuitively evaluated. For example, the higher the Q value, the better the nursing effect. Based on the Q value, the generated diet taboo suggestions can guide patients to avoid certain foods that are not conducive to qi and blood recovery; the exercise plan recommends suitable exercise types and intensities according to the patient's physical condition and qi and blood balance degree; the psychological intervention suggestions focus on the patient's mental health and provide methods to relieve stress and anxiety.

[0054] Preferably, when generating the prognosis assessment report, the diet taboos and exercise plans can be further refined according to the specific numerical range of the qi and blood balance degree Q. For example, if the Q value is low, it indicates that the patient's qi and blood recovery is not good. In the diet taboos, more food suggestions for tonifying qi and nourishing blood can be added, and the exercise plan is mainly low-intensity restorative exercise. For patients with a higher Q value, the diet restrictions can be appropriately relaxed, and some moderate-intensity exercises such as tai chi or yoga can be recommended to promote the further circulation of qi and blood. In addition, the psychological intervention suggestions can be customized according to the patient's psychological assessment results. For example, for patients with more severe anxiety, methods such as meditation or psychological counseling can be recommended. Artificial intelligence algorithms can also be introduced to automatically optimize the content of the prognosis assessment report based on a large amount of clinical data and patient feedback, improving its scientificity and practicality.

[0055] In some embodiments, it further includes: Establish a multi-dimensional safety monitoring mechanism, and start the emergency termination procedure when the following conditions are met simultaneously: (1) Skin impedance change rate 15%; (2) Local temperature gradient ; (3) Heart rate variability coefficient HRV < 70% of the normal value Among them, represents the difference between the real-time impedance and the reference impedance, represents the initial reference impedance value.

[0056] It should be noted that the multi-dimensional safety monitoring mechanism established in the present invention is a key link to ensure the safety of the nursing process. This mechanism monitors physiological parameters such as skin impedance change rate, local temperature gradient, and heart rate variability coefficient in real time. When these parameters exceed the set safety thresholds, the emergency termination procedure is started. The skin impedance change rate is the ratio of the difference between the real-time impedance and the reference impedance to the initial reference impedance value, which is used to monitor the change of the physiological state of the skin; the local temperature gradient is the change amount of the local temperature per unit time, which is used to evaluate whether the nursing operation causes local overheating; the heart rate variability coefficient is an index to measure the heart rate stability, which is used to evaluate the overall physiological state of the patient. The monitoring of these parameters can timely detect potential safety risks and ensure the safety of the nursing process.

[0057] Specifically, the monitoring of the skin impedance change rate is achieved by placing electrode sensors on the patient's skin surface. The initial reference impedance value ( ) is the normal skin impedance value measured before the start of the nursing, and the real-time impedance (R) is the value continuously monitored during the nursing process. When the skin impedance change rate exceeds 15%, it may indicate abnormal reactions of the skin, such as allergies or local injuries. The monitoring of the local temperature gradient is carried out by an infrared thermal imager. When the local temperature gradient exceeds 3 °C / min, it may mean local overheating and the nursing operation needs to be adjusted immediately. The heart rate variability coefficient (HRV) is measured by a heart rate monitoring device. When the HRV is lower than 70% of the normal value, it may indicate that the patient is in a stress state and the nursing operation needs to be stopped to avoid further risks.

[0058] Preferably, when implementing the multi-dimensional security monitoring mechanism, the monitoring methods and threshold settings of each parameter can be further refined. For example, for the skin impedance change rate, a temperature compensation mechanism can be introduced because skin impedance is greatly affected by temperature. For the local temperature gradient, the threshold can be adjusted according to the specific conditions of the patient (such as skin type, nursing site, etc.) to improve the accuracy of monitoring. In the monitoring of the heart rate variability coefficient, personalized thresholds can be set in combination with the patient's age and health status. In addition, an intelligent early warning system can be introduced. When any parameter approaches the threshold, an early warning signal is sent in advance to remind the nursing staff to adjust the nursing operation in time, thereby further improving the safety and reliability of the nursing process.

[0059] The above-mentioned various embodiments of the present invention have the following beneficial effects: The present invention collects the physiological characteristic data of the patient through multi-modal sensors and performs preprocessing, and combines the dynamic harmonic algorithm to generate a personalized nursing parameter set, which can achieve precise and personalized traditional Chinese medicine nursing. This method can dynamically adjust the parameters of nursing operations such as acupuncture, cupping, and scraping according to the real-time physiological state of the patient, ensuring that the nursing process is more in line with the actual needs of the patient, thereby improving the nursing effect and reducing the risks caused by improper operations. At the same time, the present invention monitors the microcirculation index on the skin surface and the local temperature distribution of the patient in real time during the nursing process, and dynamically corrects the nursing parameter set through the feedback adjustment algorithm, which can effectively avoid skin damage or other adverse reactions caused by nursing operations. In addition, based on the corrected nursing parameter set, a final nursing plan is generated, and a comprehensive nursing advice including traditional Chinese medicine constitution classification and prognosis evaluation report is synchronously output, providing comprehensive nursing guidance for the patient and further promoting the patient's recovery. By establishing a multi-dimensional security monitoring mechanism, the present invention can also promptly initiate an emergency termination procedure in case of abnormal situations to ensure the safety of the patient.

[0060] Furthermore, the storage medium of the embodiment of the present application stores program instructions capable of implementing all the above methods. Among them, the program instructions can be stored in the above storage medium in the form of a software product, including several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods described in various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs, or terminal devices such as computers, servers, mobile phones, and tablets.

[0061] The above description is only some preferred embodiments of the present invention and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present invention is not limited to the technical solutions formed by the specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above inventive concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions disclosed in the embodiments of the present invention.

Claims

1. A tumor nursing method combined with traditional medicine, characterized in that: The following steps are involved: S1: collecting physiological characteristic data of the patient through a multimodal sensor, wherein the physiological characteristic data includes meridian conductance data, acupoint temperature data, and qi and blood circulation rate data; S2: performing multi-dimensional preprocessing on the physiological characteristic data, including noise filtering, feature normalization and missing value interpolation; S3: Input the preprocessed physiological characteristic data into the dynamic reconciliation algorithm to generate a personalized nursing parameter set including acupuncture intensity parameters, cupping positioning parameters and scraping timing parameters; S4: According to the personalized care parameter set, the intelligent acupuncture device is controlled to perform a pulsed acupoint stimulation operation, and the negative pressure cupping device is synchronously controlled to perform a body surface gradient adsorption operation; S5: Real-time monitoring of the patient's skin surface microcirculation index and local temperature distribution, and acquisition of body surface thermodynamic characteristics through infrared thermal imaging; S6: When the microcirculation index or local temperature distribution exceeds a set threshold, triggering a feedback adjustment algorithm to dynamically modify the personalized care parameter set; S7: Generate the final nursing plan based on the revised personalized nursing parameter set, and simultaneously output comprehensive nursing recommendations including TCM constitution classification and prognosis assessment report.

2. The method according to claim 1, characterized in that: The dynamic reconciliation algorithm performs the following operations: Calculate meridian characteristic coefficients based on the patient's meridian conductance data , the calculation formula is: in, Indicates the conductivity measurement value of a specific acupuncture point, represents the conductivity reference threshold, Indicates the negative pressure value in the cupping area. Indicates the negative pressure safety threshold, Indicates the scraping intensity coefficient, Indicates the upper limit of scraping intensity. are the weight coefficients of conductivity, negative pressure value, and scraping intensity, respectively, and .

3. The method according to claim 1, characterized in that The step S3 comprises: S31: generating an initial nursing plan matrix M based on the meridian characteristic coefficient J, wherein the rows of the matrix M represent nursing items and the columns represent time series; S32: Eliminate nursing elements that conflict with the patient's TCM constitution through the contraindication analysis module; S33: Using the energy balance model to calculate the implementation time of each nursing element : in, Indicates the patient's current Qi and blood energy value. It represents the energy consumption benchmark value of the nursing process, and k is the duration adjustment coefficient.

4. The method according to claim 1, characterized in that The feedback adjustment algorithm in step S6 includes: S61: Extract abnormal temperature zone features through image segmentation algorithm ; S62: When When the warning value is exceeded, the nursing parameter correction function is triggered: in, represents the modified nursing parameters, represents the original nursing parameters, is the correction rate coefficient, Indicates the temperature safety threshold.

5. The method according to claim 1, characterized in that: In step S2: The noise filtering adopts an adaptive wavelet threshold method, the feature normalization adopts a Z-score standardization algorithm, and the missing value interpolation adopts a K-nearest neighbor interpolation method based on the meridian topological structure.

6. The method according to claim 2, characterized in that: The weight coefficient Methods for determining include: Based on the patient's TCM syndrome differentiation, a basic value is selected from a pre-stored coefficient mapping table; The basic value is dynamically adjusted according to the pulse data collected in real time, and the adjustment range does not exceed ±30% of the basic value.

7. The method according to claim 1, characterized in that The step S4 comprises: S41: Control the intelligent acupuncture device to perform stimulation operation at a pulse frequency f, where the pulse frequency satisfies: in, is the reference frequency, is the frequency adjustment coefficient, J is the meridian characteristic coefficient; S42: Synchronously control the negative pressure cupping device to generate a gradient negative pressure distribution in the target area, and the negative pressure value in the central area and the negative pressure value in the edge area satisfy: in, is the negative pressure value of the central area, is the negative pressure value of the edge area.

8. The method according to claim 4, characterized in that The modified rate factor Methods for determining include: A three-dimensional regulatory model including patient age A, disease course D, and body mass index B was established: in, is the baseline correction rate, A is age, D is disease duration, and B is body mass index.

9. The method according to claim 1, characterized in that: The prognosis assessment report in step S7 includes: S71: Calculate the Qi and Blood Balance Q: in, Indicates the energy value of Qi and blood after care. Indicates the energy value of Qi and blood before care. Indicates the theoretical maximum energy value of Qi and blood; S72: Generate extended care recommendations including dietary taboos, exercise plans and psychological interventions based on Q values.

10. The method according to claim 1, characterized in that Also includes: Establish a multi-dimensional safety monitoring mechanism to initiate an emergency termination procedure when the following conditions are met simultaneously: (1) Skin impedance change rate 15%; (2) Local temperature gradient ; (3) Heart rate variability coefficient HRV < 70% of normal value in, Indicates the difference between the real-time impedance and the reference impedance. Indicates the initial reference impedance value.

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