An auxiliary acupuncture system for tumor based on acupoint conductivity feedback regulation

Abstract

The application relates to a tumor auxiliary acupuncture system based on acupoint conductivity feedback regulation. The system comprises: a stimulation determination module, which determines the stimulation coefficient of each person according to the time difference of the conductivity change in the acupoint group of each person, the conductivity change amplitude and the conductivity change polarity; an analysis module, which analyzes the correlation and difference of the conductivity change curve of the acupoint group of each person, obtains the coordination coefficient of each person, and determines the pathological coefficient of the patient according to the coordination coefficient difference; an activation determination module, which determines the activation coefficient of the acupoint according to the conductivity change amount and the required duration; a tolerance determination module, which determines the tolerance coefficient of the acupoint according to the required duration and the number of acupuncture methods in the current acupuncture; and an output module, which outputs the stimulation intensity of the next acupuncture of the acupoint according to the stimulation coefficient, the pathological coefficient, the activation coefficient of each acupoint and the tolerance coefficient of the acupoint. The application can realize dynamic optimization and individualized precise regulation of acupuncture stimulation intensity.

Description

Technical Field

[0001] This application relates to the field of acupuncture system technology, and in particular to a tumor-assisted acupuncture system based on acupoint conductivity feedback regulation. Background Technology

[0002] Acupuncture, a traditional Chinese medicine therapy, regulates the flow of Qi and blood and the functions of internal organs by stimulating specific acupoints. It has shown positive effects in relieving cancer pain, reducing the side effects of radiotherapy and chemotherapy, and improving immune function in cancer patients, becoming an important supplement to the comprehensive cancer treatment system. Studies have shown that the electrical conductivity of acupoints is closely related to local tissue metabolism and neuroendocrine activity. Due to changes in the pathological state of cancer patients, the electrical conductivity of relevant acupoints exhibits characteristic dynamic changes, providing quantifiable physiological indicators for acupuncture treatment.

[0003] However, due to factors such as fluctuations in tumor cell metabolism and anti-tumor treatment interventions, the electrical conductivity of acupoints in patients undergoes rapid and non-linear changes. Existing tumor-assisted acupuncture systems cannot capture these dynamic changes in real time and rely solely on preset fixed parameters for treatment. The lack of a monitoring and feedback mechanism for this key physiological indicator, acupoint electrical conductivity, leads to a mismatch between stimulation parameters and the patient's real-time physiological state. This not only causes problems such as diminished analgesic effects and local tissue damage but also makes it difficult to adapt to the dynamic evolution of electrophysiological characteristics during the pathological process of tumors, severely restricting the accuracy and safety of acupuncture-assisted therapy. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide a tumor-assisted acupuncture system based on acupoint conductivity feedback regulation. The specific technical solution adopted is as follows:

[0005] In a first aspect, a tumor-assisted acupuncture system based on acupoint conductivity feedback regulation is provided, the system comprising:

[0006] The stimulation determination module is used to determine the stimulation coefficient for each person after performing acupuncture on the main acupoints once, based on the time difference, amplitude, and polarity of the change in conductivity within each person's acupoint group; the acupoint group includes the main acupoints and their corresponding front acupoints;

[0007] The analysis module is used to analyze the correlation and differences of the conductivity change curves within the acupoint group for each person after one acupuncture session at the main acupoints, obtain the synergy coefficient for each person, and determine the pathological coefficient of the patient based on the difference in synergy coefficient between healthy individuals and patients.

[0008] The activation determination module is used to determine the activation coefficient of each acupoint after each acupuncture treatment for each patient, based on the change in conductivity of the acupoint when the conductivity reaches the preset conditions and the required time.

[0009] The tolerance determination module is used to determine the tolerance coefficient of each acupoint after performing one acupuncture session, based on the time required for the conductivity of the acupoint to reach the preset condition and the number of acupuncture techniques used in that session.

[0010] The output module is used to output the stimulation intensity of the next acupuncture session for the acupoint based on the stimulation coefficient, pathological coefficient, activation coefficient of each acupoint, and tolerance coefficient of the acupoint.

[0011] Optionally, the stimulus determination module is further configured to:

[0012] The electrical conductivity of each acupoint before acupuncture stimulation is determined as the reference electrical conductivity of that acupoint.

[0013] After performing acupuncture on each person's main acupoints once, the moment when the difference between the conductivity of the main acupoint and the reference conductivity of the main acupoint first reaches a first preset percentage threshold is defined as the first moment, and the moment when the difference between the conductivity of the corresponding acupoint and the reference conductivity of the acupoint first reaches a first preset percentage threshold is defined as the second moment.

[0014] The stimulation coefficient for each individual is determined based on the absolute difference between the first and second moments, the amplitude of the change in conductivity within each individual's acupoint group, and the polarity of the conductivity change.

[0015] Optionally, the stimulus determination module is further configured to:

[0016] After acupuncture is performed on each person's main acupoints, when the difference between the conductivity of the main acupoint and its baseline conductivity first reaches a second preset percentage threshold, and the conductivity change rate of the main acupoint is positive while the conductivity change rate of the corresponding associated acupoints is negative, the stress coefficient for each person is determined based on the first conductivity change of the main acupoint relative to its baseline conductivity and the second conductivity change of the associated acupoints relative to their baseline conductivity. The acupoint group includes the main acupoint, its corresponding front acupoint, and its corresponding associated acupoints. The associated acupoints indicate the acupoints located in the relevant meridian area of ​​the main acupoint. The stress coefficient indicates the degree of stimulation abnormality of the main acupoint and its related meridian area.

[0017] The stimulation coefficient for each person is determined based on the absolute difference between the first and second moments and the individual's stress coefficient; the stimulation coefficient indicates the intensity of the response of each person's main acupoints to the acupuncture treatment.

[0018] Optionally, the analysis module is further configured to:

[0019] After performing acupuncture on each person's main acupoints once, obtain the first conductivity change curve of the main acupoints within a preset time and the second conductivity change curve of the corresponding acupoints within a preset time.

[0020] Based on the definite integral of the overlapping region between the first conductivity change curve and the second conductivity change curve, and the definite integral of the first conductivity change curve, determine the percentage of the overlapping area between the first conductivity change curve and the second conductivity change curve.

[0021] Calculate the Pearson correlation coefficient between the first conductivity change curve and the second conductivity change curve to obtain the directional correlation coefficient;

[0022] The first conductivity change curve and the second conductivity change curve are aligned using the DTW algorithm to obtain all matching point pairs of the first conductivity change curve and the second conductivity change curve;

[0023] The time delay coefficient is obtained by taking the mean of the time difference between multiple sets of matching point pairs and the standard deviation of the time difference between multiple sets of matching point pairs.

[0024] Based on the overlap area ratio, directional correlation coefficient, and time delay coefficient, the synergy coefficient of each individual is obtained, and the pathological coefficient of the patient is obtained based on the difference in synergy coefficient between healthy individuals and patients.

[0025] Optionally, the activation determination module is further configured to:

[0026] After performing acupuncture on each acupoint for each patient, the change in conductivity of each acupoint when it rises to a stable level is obtained relative to the reference conductivity of that acupoint. The rise to a stable level indicates that the standard deviation of conductivity fluctuations at multiple consecutive time points is less than a preset fluctuation value. The reference conductivity of each acupoint indicates the conductivity of that acupoint before acupuncture stimulation.

[0027] The activation rate of acupoint is determined by the ratio of the change in the third conductivity of each acupoint to the time required for the conductivity of that acupoint to rise to a stable level.

[0028] The activation coefficient of an acupoint is determined based on the preset rate, the activation rate of each acupoint, the conductivity of the acupoint when it rises to a stable level, and the reference conductivity of the acupoint.

[0029] Optionally, the tolerance determination module is further configured to:

[0030] After performing acupuncture on each acupoint once, the time when the conductivity of the first acupoint in two adjacent acupoints first reaches its peak value is taken as the benchmark, and the difference between the time when the conductivity of the second acupoint first reaches its peak value and the benchmark is taken as the tolerance of the second acupoint.

[0031] The patient's initial tolerance coefficient is determined based on the average tolerance of multiple acupoints.

[0032] The tolerance coefficient of acupoint is determined based on the patient's initial tolerance coefficient, the time required for the conductivity of each acupoint to reach the preset conditions, and the number of needling techniques used in this session.

[0033] Optionally, the tolerance determination module is further configured to:

[0034] The real-time tolerance coefficient of each acupoint is determined by the ratio of the time required for the conductivity of each acupoint to rise to a stable level to the number of acupuncture techniques used in that session; the rise of conductivity to a stable level indicates that the standard deviation of conductivity fluctuation over multiple consecutive time periods is less than a preset fluctuation value.

[0035] The tolerance coefficient of each acupoint is determined by the difference between the ratio of the real-time tolerance coefficient of each acupoint to the patient's initial tolerance coefficient and the first preset value.

[0036] Optionally, the output module is further configured to:

[0037] The judgment factor is obtained based on the difference between the ratio of each patient's stimulation coefficient to pathological coefficient and the second preset value;

[0038] In response to a positive decision factor, the stimulation intensity of the next acupuncture session for that acupoint is output based on the decision factor, the activation coefficient of each acupoint, and the tolerance coefficient of that acupoint.

[0039] Optionally, the output module is further configured to:

[0040] In response to a positive decision factor, the ratio of the activation coefficient to the tolerance coefficient of each acupoint is calculated.

[0041] The stimulation regulation coefficient of an acupoint is determined based on the difference between the determination factor and the ratio of the activation coefficient to the tolerance coefficient of that acupoint.

[0042] Based on the stimulation adjustment coefficient of each acupoint and the needling plan for this session, determine and output the stimulation intensity for the next session of needling for that acupoint; the needling plan includes the insertion and withdrawal depth, duration, and angle for this session of needling.

[0043] Optionally, the output module is further configured to:

[0044] The needling plan for each acupoint in this session is input into a pre-trained neural network to output a stimulation intensity score for that acupoint.

[0045] Based on the stimulation intensity score of each acupoint, the stimulation adjustment coefficient of that acupoint, and the stimulation intensity of that acupuncture session, the stimulation intensity of the next acupuncture session for that acupoint is output.

[0046] Based on common knowledge in the field, the above-mentioned preferred conditions can be combined arbitrarily to obtain various preferred embodiments of this application.

[0047] This application has the following beneficial effects: It captures the dynamic response characteristics of acupoint conductivity in real time through a stimulation determination module, quantitatively analyzes the time difference, amplitude, and polarity of conductivity changes after needling of the main acupoint and its corresponding front acupoint, accurately identifies individualized Qi response patterns, and scientifically determines the stimulation coefficient. This effectively distinguishes between local acupoint stimulation abnormalities and internal organ pathological fluctuations, breaking through the limitations of traditional acupuncture's reliance on subjective feeling. A correlation and difference analysis model of acupoint group conductivity change curves is constructed, extracting individual Qi and blood synergy characteristics, calculating synergy coefficients, and quantitatively assessing pathological states by comparing the differences in synergy coefficients between healthy individuals and cancer patients, generating pathological coefficients. This achieves the digitalization and objectification of the TCM "syndrome differentiation" process, significantly improving the accuracy and repeatability of syndrome identification. The activation determination module monitors the dynamic change in conductivity of each acupoint after needling, tracking the amount of conductivity change and the required time to reach preset conditions, accurately assessing Qi activation efficiency, calculating activation coefficients, and achieving individualized quantitative characterization of acupoint Qi activity. The tolerance determination module combines the number of needling techniques used in a single acupuncture session with the time required for the conductivity response to reach steady state. It dynamically assesses the adaptive changes of acupoints to repeated stimulation, calculates the tolerance coefficient, and reveals the fatigue or adaptive trends in acupoint function, providing a scientific basis for long-term treatment. The output module integrates the stimulation coefficient, pathological coefficient, activation coefficient, and tolerance coefficient to construct a stimulation adaptation index model. This intelligently generates the stimulation intensity for the next acupuncture session, achieving dynamic optimization and individualized precise control of acupuncture stimulation parameters. Attached Figure Description

[0048] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a schematic diagram of the structure of a tumor-assisted acupuncture system based on acupoint conductivity feedback regulation in one embodiment;

[0050] Figure 2 This is a flowchart of a tumor-assisted acupuncture method based on acupoint conductivity feedback regulation in one embodiment;

[0051] Figure 3 This is a schematic diagram of the structure of an electronic device in one embodiment. Detailed Implementation

[0052] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a tumor-assisted acupuncture system based on acupoint conductivity feedback regulation proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0054] The following, with reference to the accompanying drawings, details a specific scheme for a tumor-assisted acupuncture system based on acupoint conductivity feedback regulation, as provided in this application. For example... Figure 1 As shown, the system includes:

[0055] The stimulation determination module 11 is used to determine the stimulation coefficient of each person after performing acupuncture on the main acupoints of each person once, based on the time difference of the change in conductivity within the acupoint group of each person, the amplitude of the change in conductivity, and the polarity of the change in conductivity.

[0056] The acupoint group includes the main acupoints and their corresponding front-mu points. Acupoints can be selected using the Shu-Mu therapy method, with back-shu points primarily used for diseases of the internal organs and front-mu points primarily used for diseases of the viscera. Therefore, during acupuncture, acupoints are selected based on the combination of Shu-Mu points and the patient's symptoms. The corresponding back-shu point is selected according to the tumor location; for example, the lung-shu point is selected as the main acupoint for lung cancer, and the stomach-shu point is selected as the main acupoint for stomach cancer. Then, the corresponding front-mu points are determined based on the main acupoints; for example, the front-mu point for the stomach is Zhongwan, and the front-mu point for the spleen is Zhangmen. Further, related acupoint groups of Shu-Mu points are obtained, such as stomach-shu point—Zhongwan—Neiguan—Zusanli, kidney-shu point—Jingmen—Guanyuan—Sanyinjiao, etc.

[0057] In this application, acupuncture instructions are given for each acupoint of each individual: each or any acupuncture session can trigger the collection of conductivity-related data. The stimulation coefficient indicates the instantaneous sensitivity of each individual to acupuncture, that is, the stimulation coefficient indicates the response intensity of each individual's main acupoints to that acupuncture session.

[0058] In this application, the patient is placed in a quiet, warm, and private environment, choosing a comfortable position that facilitates the exposure of acupoints. After the doctor disinfects the skin, the acupuncture treatment is performed. The initial needling of each acupoint is to stimulate the flow of Qi, known as "deqi" (obtaining Qi). Multiple needling operations are required during the acupuncture treatment. Generally, during the 20-30 minute needle retention period, the doctor may perform several to ten needling operations on the same acupoint to maintain and strengthen the stimulation based on the patient's sensations and changes in condition.

[0059] Non-invasive conductivity sensors (such as Ag / AgCl flexible electrodes) are attached to specific acupoints of the patient, such as Feishu and Zusanli for lung cancer patients. The electrodes integrate miniature temperature sensors to synchronously collect the conductivity and local temperature of the acupoints at a sampling frequency of 100Hz. The patient needs to be in a quiet treatment position and avoid strenuous activity to reduce noise.

[0060] The sensor collects conductivity data (unit: μS / cm) once per second, forming a time-series data stream. The data includes timestamps and conductivity values. The data is transmitted to the data processing host via shielded cable to reduce electromagnetic interference. The host performs two-stage filtering on the raw data: first, a 50Hz notch filter removes power frequency interference; then, a moving average filter smooths high-frequency noise. A window size of 5 sampling points is set to obtain stable effective conductivity values, retaining three decimal places. Data with temperatures above 38℃ are discarded to exclude outliers caused by inflammation. Three basic conductivity features are extracted from the preprocessed data: the current real-time conductivity value, the conductivity change within 5 seconds before and after any given time (conductivity range within 5 seconds), and the conductivity change rate (conductivity change / time).

[0061] In one embodiment, the stimulus determination module is further configured to:

[0062] The electrical conductivity of each acupoint before acupuncture stimulation is determined as the reference electrical conductivity of that acupoint.

[0063] After performing acupuncture on each person's main acupoints once, the moment when the difference between the conductivity of the main acupoint and the reference conductivity of the main acupoint first reaches a first preset percentage threshold is defined as the first moment, and the moment when the difference between the conductivity of the corresponding acupoint and the reference conductivity of the acupoint first reaches a first preset percentage threshold is defined as the second moment.

[0064] The stimulation coefficient for each individual is determined based on the absolute difference between the first and second moments, the amplitude of the change in conductivity within each individual's acupoint group, and the polarity of the conductivity change.

[0065] The first preset percentage threshold can be set according to the actual situation, for example, 5%.

[0066] In Traditional Chinese Medicine (TCM) theory, tumor lesions can affect the electrical conductivity of specific acupoints through the pathway of Zang-Fu organs → Meridians → Acupoints. For example, liver cancer can cause an abnormal correlation in the electrical conductivity of the Liver Shu (BL18) and Qimen (LR14) acupoints. Therefore, the electrical conductivity of each acupoint before stimulation (i.e., before acupuncture stimulation) can be taken as the baseline electrical conductivity for each acupoint in the morning. There is a time difference between the changes in electrical conductivity of the main acupoint and its corresponding front acupoint. A deviation of more than 5% from the baseline electrical conductivity is considered a significant change. After one acupuncture session at each person's main acupoint, the first moment t1 when a significant change occurs at the main acupoint and the second moment t2 when a significant change occurs in the same direction at the corresponding front acupoint are recorded. The absolute difference between the first and second moments is defined as the acupoint response delay. If the tumor causes meridian blockage, the acupoint response delay will be prolonged.

[0067] In one embodiment, the stimulus determination module is further configured to:

[0068] After acupuncture is performed on each person's main acupoints, when the difference between the conductivity of the main acupoint and its baseline conductivity first reaches a second preset percentage threshold, and the conductivity change rate of the main acupoint is positive while the conductivity change rate of the corresponding associated acupoints is negative, the stress coefficient for each person is determined based on the first conductivity change of the main acupoint relative to its baseline conductivity and the second conductivity change of the associated acupoints relative to their baseline conductivity. The acupoint group includes the main acupoint, its corresponding front acupoint, and its corresponding associated acupoints. The associated acupoints indicate the acupoints located in the relevant meridian area of ​​the main acupoint. The stress coefficient indicates the degree of stimulation abnormality of the main acupoint and its related meridian area.

[0069] The stimulation coefficient for each person is determined based on the absolute difference between the first and second moments and the individual's stress coefficient; the stimulation coefficient indicates the intensity of the response of each person's main acupoints to the acupuncture treatment.

[0070] The second preset percentage threshold can be set according to the actual situation, for example, 10%.

[0071] When cancer patients experience an acute attack of cancer pain, triggering a stress response, such as abdominal colic caused by cancer, it is due to tangible pathogens obstructing the meridians. The body instinctively causes qi and blood to gather towards the affected area, dilates peripheral blood vessels in the affected area, and constricts peripheral blood vessels in non-affected areas. This causes the conductivity of the main acupoints to increase, accompanied by a reverse fluctuation in 2-3 related acupoints, i.e., a downward trend. The amplitude of the fluctuation is positively correlated with the degree of pain.

[0072] Therefore, when conductivity is abnormal, i.e., the instantaneous conductivity change exceeds 10% of the baseline conductivity, it is necessary to track this characteristic of a sudden increase in the main acupoint combined with the linkage of related acupoints. When the conductivity change rate of the main acupoint is positive and the conductivity change rate of the corresponding related acupoints is negative, calculate the first conductivity change of the main acupoint relative to its baseline conductivity, and the multiple second conductivity changes of the corresponding related acupoints relative to their baseline conductivity. Then calculate the absolute value of the ratio of the first conductivity change to the multiple second conductivity changes, and average the absolute values ​​of these ratios to obtain the stress coefficient for each individual. A large stress coefficient indicates that the conductivity change of the main acupoint is mainly caused by abnormal local stimulation, rather than systemic physiological fluctuations.

[0073] If the instantaneous conductivity change exceeds 10% of the baseline conductivity, but does not meet the requirement that the conductivity change rate of the main acupoint is positive or the conductivity change rate of the corresponding associated acupoint is negative, then the stress coefficient is set to 1 by default.

[0074] The product of the acupoint response delay and the stress coefficient is used as the stimulation coefficient.

[0075] The analysis module 12 is used to analyze the correlation and differences of the conductivity change curves within the acupoint group for each person after one acupuncture treatment of the main acupoints, obtain the synergy coefficient for each person, and determine the pathological coefficient of the patient based on the difference in synergy coefficient between healthy individuals and patients.

[0076] The synergy coefficient indicates the degree of coordination of Qi and blood circulation between back-shu points and front-mu points in the same meridian, while the pathology coefficient indicates the severity of tumor pathological fluctuations.

[0077] In one embodiment, the analysis module is also used for:

[0078] After performing acupuncture on each person's main acupoints once, obtain the first conductivity change curve of the main acupoints within a preset time and the second conductivity change curve of the corresponding acupoints within a preset time.

[0079] Based on the definite integral of the overlapping region between the first conductivity change curve and the second conductivity change curve, and the definite integral of the first conductivity change curve, determine the percentage of the overlapping area between the first conductivity change curve and the second conductivity change curve.

[0080] Calculate the Pearson correlation coefficient between the first conductivity change curve and the second conductivity change curve to obtain the directional correlation coefficient;

[0081] The first conductivity change curve and the second conductivity change curve are aligned using the DTW algorithm to obtain all matching point pairs of the first conductivity change curve and the second conductivity change curve;

[0082] The time delay coefficient is obtained by taking the mean of the time difference between multiple sets of matching point pairs and the standard deviation of the time difference between multiple sets of matching point pairs.

[0083] Based on the overlap area ratio, directional correlation coefficient, and time delay coefficient, the synergy coefficient of each individual is obtained, and the pathological coefficient of the patient is obtained based on the difference in synergy coefficient between healthy individuals and patients.

[0084] The preset duration can be set according to the actual situation, for example, it can be 1 minute.

[0085] After performing acupuncture on each person's main acupoints once, obtain the first conductivity change curve of the main acupoints within 1 minute and the second conductivity change curve of the corresponding acupoints within 1 minute. Then, calculate the definite integral of the overlapping area between the first conductivity change curve and the second conductivity change curve. Divide the definite integral of the overlapping area by the definite integral of the first conductivity change curve to obtain the percentage of the overlapping area between the first conductivity change curve and the second conductivity change curve.

[0086] Then, the Pearson correlation coefficient between the first and second conductivity change curves is calculated to obtain the directional correlation coefficient. Next, the DTW (Dynamic Time Warping) algorithm is used to align the first and second conductivity change curves, obtaining all matching point pairs. Each matching point pair yields a time difference value. The average of the time differences between all matching point pairs is used to obtain the alignment delay. Finally, the alignment delay is divided by the standard deviation of the time differences between all matching point pairs to obtain the time delay coefficient.

[0087] The product of each individual's overlapping area ratio, directional correlation coefficient, and time lag coefficient is used as each individual's synergy coefficient. In cancer patients, due to organ dysfunction and when chemotherapy leads to qi and blood deficiency, the synergy coefficient decreases significantly. The synergy coefficients of multiple healthy individuals are then averaged to obtain the healthy synergy coefficient. The difference between the healthy synergy coefficient and the patient's synergy coefficient is used as the patient's pathological coefficient. The larger the pathological coefficient, the weaker the patient's organs and qi and blood.

[0088] The activation determination module 13 is used to determine the activation coefficient of each acupoint after each acupuncture treatment for each patient, based on the change in conductivity of the acupoint when the conductivity reaches the preset conditions and the required duration.

[0089] The activation coefficient of each acupoint indicates the efficiency or speed at which the meridian energy of that acupoint is activated during this acupuncture session.

[0090] The preset conditions can be: after acupuncture is performed on each acupoint for each patient, the conductivity of that acupoint rises to a stable level. The rise to a stable level indicates that the standard deviation of conductivity fluctuation over multiple consecutive time periods is less than a preset fluctuation value. Multiple time periods can be 5 time periods, and the preset fluctuation value can be 0.005. For example, the standard deviation of conductivity fluctuation over 5 time periods can be less than 0.005.

[0091] In one embodiment, the activation determination module is further configured to:

[0092] After performing acupuncture on each acupoint for each patient, the change in conductivity of each acupoint when it rises to a stable level is obtained relative to the reference conductivity of that acupoint. The rise to a stable level indicates that the standard deviation of conductivity fluctuations at multiple consecutive time points is less than a preset fluctuation value. The reference conductivity of each acupoint indicates the conductivity of that acupoint before acupuncture stimulation.

[0093] The activation rate of acupoint is determined by the ratio of the change in the third conductivity of each acupoint to the time required for the conductivity of that acupoint to rise to a stable level.

[0094] The activation coefficient of an acupoint is determined based on the preset rate, the activation rate of each acupoint, the conductivity of the acupoint when it rises to a stable level, and the reference conductivity of the acupoint.

[0095] Traditional Chinese medicine believes that the effectiveness of acupuncture depends on the degree of activation of meridian qi. Changes in electrical conductivity can reflect the activity of meridian qi. When meridian qi is abundant, local metabolism is active and electrical conductivity increases; when meridian qi is deficient, the opposite is true.

[0096] With the patient at rest, after one acupuncture session at each acupoint for each patient, the conductivity of the acupoint was stabilized (i.e., the standard deviation of conductivity fluctuation was less than 0.005 over five consecutive time points). The change in third conductivity of the acupoint relative to its baseline conductivity was then measured. The baseline conductivity for each acupoint indicates its conductivity before acupuncture stimulation. The activation rate of the acupoint was determined by the ratio of the change in third conductivity to the time required for the conductivity to stabilize.

[0097] Based on big data analysis of healthy individuals, the health activation rate of Qi at various acupoints was statistically analyzed. For example, the health activation rate of the meridian qi at the Zusanli acupoint is approximately... preset rate The stable activation rate of acupoints can be determined when the patient wakes up in the morning without stimulation. Then, the activation coefficient of each acupoint can be calculated. The calculation method for the activation coefficient of each acupoint is as follows:

[0098] ;

[0099] in, The initial activation coefficient for each acupoint. The conductivity of this acupoint rises to a stable level at time t. This is the reference conductivity for this acupoint. This is the preset rate for this acupoint. This refers to the health activation rate of this acupoint. Represents the real-time activity level of electrical conductivity. This represents the activation rate of Qi in the meridians. The larger the product of the two, the more abundant the Qi in the meridians and the more active the metabolism. Conversely, the lower the product, the less Qi in the meridians (which may be negative).

[0100] After normalizing the initial activation coefficients by mean, the activation coefficient of the acupoint is obtained. .

[0101] The tolerance determination module 14 is used to determine the tolerance coefficient of each acupoint after performing acupuncture once, based on the time required for the conductivity of the acupoint to reach the preset condition and the number of acupuncture techniques used in that acupuncture session.

[0102] The tolerance coefficient for each acupoint indicates the degree of fatigue or desensitization that acupoint undergoes with repeated acupuncture.

[0103] Each needle insertion includes multiple techniques, such as lifting and thrusting, twisting, flicking, and retaining the needle.

[0104] In one embodiment, the tolerance determination module is further configured to:

[0105] After performing acupuncture on each acupoint once, the time when the conductivity of the first acupoint in two adjacent acupoints first reaches its peak value is taken as the benchmark, and the difference between the time when the conductivity of the second acupoint first reaches its peak value and the benchmark is taken as the tolerance of the second acupoint.

[0106] The patient's initial tolerance coefficient is determined based on the average tolerance of multiple acupoints.

[0107] The tolerance coefficient of an acupoint is determined based on the patient's initial tolerance coefficient, the time required for the conductivity of each acupoint to reach the preset conditions, and the number of needling techniques used in that session.

[0108] Excessive activation of Qi can lead to acupoint tolerance. For example, continuous strong stimulation can cause nerve ending desensitization. If the peak conductivity occurs with a time delay during continuous stimulation, it indicates that acupoint tolerance is enhanced.

[0109] Therefore, when needles are first inserted into two acupoints consecutively, the moment when the conductivity curve of each pair of adjacent acupoints first reaches its peak conductivity can be obtained. The difference between these two moments is recorded as the tolerance of the subsequent acupoint. Based on the average tolerance of multiple acupoints, the patient's initial tolerance coefficient can be determined. That is, when acupoints are continuously needled, the Qi is already being continuously activated, and the conductivity of the subsequent acupoint will rise at a higher rate than that of the previous acupoint. Therefore, the time difference between the peak conductivity of adjacent acupoints reflects the initial rate of increase in nerve sensitivity of the subsequent acupoint when these two acupoints are activated sequentially. By comparing the rate of increase in sensitivity, the degree of subsequent decrease in sensitivity can also be reflected, indicating the acupoint tolerance.

[0110] In one embodiment, the tolerance determination module is further configured to:

[0111] The real-time tolerance coefficient of each acupoint is determined by the ratio of the time required for the conductivity of each acupoint to rise to a stable level to the number of acupuncture techniques used in that session; the rise of conductivity to a stable level indicates that the standard deviation of conductivity fluctuation over multiple consecutive time periods is less than a preset fluctuation value.

[0112] The tolerance coefficient of each acupoint is determined by the difference between the ratio of the real-time tolerance coefficient of each acupoint to the patient's initial tolerance coefficient and the first preset value.

[0113] The first preset value can be set according to the actual situation, and can be (0.05, 0.5). Acupoints with low sensitivity have high tolerance, so the first preset value can be reduced; acupoints with high sensitivity have low tolerance, so the first preset value can be increased.

[0114] The needling techniques in acupuncture include multiple lifting and thrusting, twisting, flicking, and retaining the needle. Different depths and angles will produce different intensities of stimulation. Therefore, a camera is used to synchronously identify the needling techniques. For any continuous needling, the time from the moment the needle touches the needle to the moment the conductivity stabilizes is obtained. Since each needling may have multiple consecutive needling actions, it is necessary to identify the number of consecutive needling actions that occur at each acupoint from the moment the needle touches the needle to the moment the needling stops. Continuous needling indicates that the interval between two needling actions is less than 10 seconds.

[0115] The real-time tolerance coefficient of each acupoint is determined by the ratio of the time required for the conductivity of each acupoint to stabilize to the number of needling techniques used in that session. The tolerance coefficient of each acupoint is then determined by the difference between the ratio of the real-time tolerance coefficient of each acupoint to the patient's initial tolerance coefficient and a first preset value. In other words, (real-time tolerance coefficient / initial tolerance coefficient) - first preset coefficient is used as the tolerance coefficient of that acupoint. .

[0116] The first preset coefficient ranges from 0.05 to 0.5. Adjusting this coefficient adapts to different patients and the characteristics of different acupoints. For example, highly sensitive acupoints like the Yintang acupoint on the face have high sensitivity and dense nerve endings, resulting in a strong response to stimulation, while the Zusanli acupoint on the lower limbs has relatively high tolerance to stimulation. Acupoints with lower sensitivity have higher tolerance, so the first preset value can be decreased; conversely, highly sensitive acupoints have lower tolerance, so the first preset value can be increased. A tolerance coefficient greater than 1 and the larger it is, the greater the increase in tolerance; conversely, a tolerance coefficient less than 1 and the smaller it is, the more continuously the sensitivity increases, and there may be overstimulation of nerve endings.

[0117] The output module 15 is used to output the stimulation intensity of the next acupuncture session for the acupoint based on the stimulation coefficient, pathological coefficient, activation coefficient of each acupoint and tolerance coefficient of the acupoint.

[0118] In one embodiment, the output module is also used for:

[0119] The judgment factor is obtained based on the difference between the ratio of each patient's stimulation coefficient to pathological coefficient and the second preset value;

[0120] In response to a positive decision factor, the stimulation intensity of the next acupuncture session for that acupoint is output based on the decision factor, the activation coefficient of each acupoint, and the tolerance coefficient of that acupoint.

[0121] The second preset value can be set according to the actual situation, for example, it can be 1.

[0122] First, a large sample of healthy individuals is statistically analyzed. Each sample represents the conductivity data of an acupoint on a healthy person. The average level and fluctuation range of the stimulation coefficient and pathological coefficient for healthy individuals are obtained and used as a benchmark. Then, the stimulation coefficient and pathological coefficient of the current patient are compared with this healthy benchmark to calculate the relative deviation, thereby obtaining the normalized stimulation coefficient E and normalized pathological coefficient R corresponding to that patient, used for subsequent abnormality assessment. Judgment Factor The calculation formula is:

[0123] ;

[0124] in, H is the normalized stimulation coefficient, and R is the normalized pathological coefficient. If the judgment factor is positive, it means that there is a local stimulation abnormality in the patient during the acupuncture process. If the judgment factor is negative, it means that there is a fluctuation in the pathology of the patient's internal organs. The absolute value of the judgment factor H can be used as the degree of local stimulation abnormality or the degree of fluctuation in the pathology of the internal organs.

[0125] In one embodiment, the output module is also used for:

[0126] In response to a positive decision factor, the ratio of the activation coefficient to the tolerance coefficient of each acupoint is calculated.

[0127] The stimulation regulation coefficient of an acupoint is determined based on the difference between the determination factor and the ratio of the activation coefficient to the tolerance coefficient of that acupoint.

[0128] Based on the stimulation adjustment coefficient of each acupoint and the needling plan for this session, determine and output the stimulation intensity for the next session of needling for that acupoint; the needling plan includes the insertion and withdrawal depth, duration, and angle for this session of needling.

[0129] If the judgment factor is positive, it indicates local stimulation abnormality, and the stimulation intensity of the acupoint is considered unsuitable. The intensity of subsequent needling should be adjusted based on the real-time response of each acupoint during needling. If the judgment factor is negative, there is no need to adjust the acupuncture intensity.

[0130] If the judgment factor is positive, the activation coefficient of that acupoint is normalized, and then the stimulation regulation coefficient of each acupoint is calculated. The calculation formula is: Where S is the normalized activation coefficient. As a decision factor, This represents the patient's tolerance coefficient. Each acupuncture session involves multiple needling manipulations. The activation coefficient is a fixed value obtained at the start of acupuncture, while the judgment factor and tolerance coefficient are dynamic values ​​obtained after each needling manipulation. The resulting stimulation adjustment coefficient is used to adjust the stimulation intensity for the next needling manipulation.

[0131] The ratio of the judgment factor to the tolerance coefficient indicates that the more abnormal the local stimulation and the lower the tolerance coefficient, the more likely there is overstimulation. The activation coefficient S represents the theoretical acupuncture effect corresponding to the patient's meridian qi state. Therefore, the difference between the two can accurately link the dynamic relationship between meridian qi state, stimulation intensity, and acupoint tolerance, and intuitively reflect the degree of suitability of acupuncture stimulation intensity.

[0132] If it is a positive value, it means The acupuncture stimulation may be insufficient, possibly due to high activity of Qi in the meridians, leading to increased tolerance of the acupoint. In this case, it is necessary to increase the stimulation intensity of the acupoint. If it is negative, it means If the stimulation intensity is too high, even exceeding the patient's Qi activity level, it indicates overstimulation. In this case, the stimulation intensity of the acupoint should be reduced. The stimulation regulation coefficient K for each acupoint is obtained after each needling session.

[0133] In one embodiment, the output module is also used for:

[0134] The needling plan for each acupoint in this session is input into a pre-trained neural network to output a stimulation intensity score for that acupoint.

[0135] Based on the stimulation intensity score of each acupoint, the stimulation adjustment coefficient of that acupoint, and the stimulation intensity of that acupuncture session, the stimulation intensity of the next acupuncture session for that acupoint is output.

[0136] Each acupuncture session involves multiple needling manipulations, therefore, it's crucial to quantify the stimulation intensity for each manipulation. This can be achieved by pre-training a neural network to quantify the theoretical stimulation intensity for each manipulation. First, it's necessary to collect parameters related to the needling technique, such as the amplitude of insertion and withdrawal, the angle and frequency of twisting, the retention time, the needling depth, and three basic features: electrical conductivity. These parameters are used as input features. Simultaneously, a professional physician labels the corresponding stimulation intensity score (0-10 points, with higher scores indicating greater intensity) based on the acupoint response and treatment needs. The data is standardized to eliminate dimensional differences, and after dividing the training and validation sets in a 7:3 ratio, a neural network is constructed containing an input layer, 2-3 fully connected hidden layers, and an output layer. The model is trained using mean squared error as the loss function and an Adam optimizer (learning rate 0.001). An early stopping mechanism monitors the validation set loss to prevent overfitting. Finally, a model that accurately fits the mapping relationship between "needling technique + electrical conductivity features" and "stimulation intensity score" is saved. This allows for the direct output of the stimulation intensity score for each needling scheme after inputting new technique and electrical conductivity data.

[0137] After needling each acupoint, the system will automatically output the completed needling plan, including the depth of insertion and withdrawal, time, angle, etc., and input the needling plan into the pre-trained neural network to output the stimulation intensity score of each acupoint needling plan.

[0138] Then, based on the stimulation regulation coefficient K of the acupoint, the stimulation regulation value for the next acupuncture session is obtained. The stimulation regulation coefficient is then non-linearly transformed using the Sigmoid function to avoid excessively drastic fluctuations in continuous stimulation intensity regulation. ,Will Multiplying this by the stimulus intensity score gives the stimulus adjustment value that should be increased or decreased for the next acupuncture session. The stimulation intensity and stimulation adjustment value of the acupoint during this acupuncture session were compared. The sum of these values ​​determines the stimulation intensity for the next acupuncture session. Based on the adjusted stimulation intensity, the system simulates and matches the acupuncture plan for the next session to match the patient's meridian energy and acupoint status, thereby improving the acupuncture effect.

[0139] It should be noted that this system only collects, quantifies, and calculates the electrical conductivity of acupoints in real time, and provides suggested stimulation intensities to licensed TCM physicians. All acupuncture techniques (insertion, lifting and thrusting, twisting, withdrawal, etc.) are still to be independently judged and performed by the physician. The system does not participate in or replace any actual treatment actions.

[0140] This application utilizes a stimulation determination module to capture the dynamic response characteristics of acupoint conductivity in real time. It quantitatively analyzes the time difference, amplitude, and polarity of conductivity changes after needling of the main acupoint and its corresponding front acupoints, accurately identifying individualized Qi response patterns. This allows for the scientific determination of stimulation coefficients, effectively distinguishing between local acupoint stimulation abnormalities and internal organ pathological fluctuations, overcoming the limitations of traditional acupuncture's reliance on subjective feeling. A correlation and difference analysis model of acupoint conductivity change curves is constructed, extracting individual Qi and blood synergy characteristics, calculating synergy coefficients, and quantitatively assessing pathological states by comparing the differences in synergy coefficients between healthy individuals and cancer patients. This generates pathological coefficients, digitizing and objectifying the TCM "syndrome differentiation" process, significantly improving the accuracy and repeatability of syndrome identification. The activation determination module monitors the dynamic conductivity changes of each acupoint after needling, tracking the amount of conductivity change and the required time to reach preset conditions. This accurately assesses Qi activation efficiency, calculates activation coefficients, and achieves individualized quantitative characterization of acupoint Qi activity. The tolerance determination module combines the number of needling techniques used in a single acupuncture session with the time required for the conductivity response to reach steady state. It dynamically assesses the adaptive changes of acupoints to repeated stimulation, calculates the tolerance coefficient, and reveals the fatigue or adaptive trends in acupoint function, providing a scientific basis for long-term treatment. The output module integrates the stimulation coefficient, pathological coefficient, activation coefficient, and tolerance coefficient to construct a stimulation adaptation index model. This intelligently generates the stimulation intensity for the next acupuncture session, achieving dynamic optimization and individualized precise control of acupuncture stimulation parameters.

[0141] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs.

[0142] This application also provides a tumor-adjuvant acupuncture method based on acupoint conductivity feedback regulation, such as... Figure 2 As shown, the method includes:

[0143] S21. After performing acupuncture on each person's main acupoints once, determine the stimulation coefficient for each person based on the time difference, amplitude, and polarity of the change in conductivity within each person's acupoint group; the acupoint group includes the main acupoints and their corresponding front acupoints;

[0144] S22. After performing acupuncture on the main acupoints once, analyze the correlation and differences of the conductivity change curves within the acupoint group for each person, obtain the synergy coefficient for each person, and determine the pathological coefficient of the patient based on the difference in synergy coefficient between healthy individuals and patients.

[0145] S23. After performing acupuncture on each acupoint for each patient, determine the activation coefficient of the acupoint based on the change in conductivity when the conductivity of the acupoint reaches the preset conditions and the required time.

[0146] S24. After performing acupuncture on each acupoint once, determine the tolerance coefficient of the acupoint based on the time required for the conductivity of the acupoint to reach the preset condition and the number of acupuncture techniques used in that session.

[0147] S25. Based on the stimulation coefficient, pathological coefficient, activation coefficient of each acupoint, and tolerance coefficient of the acupoint, output the stimulation intensity of the next acupuncture session for that acupoint.

[0148] For the method embodiments, since they are basically corresponding to the system embodiments, the relevant parts can be referred to in the description of the system embodiments.

[0149] It should be understood that, although Figure 2 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 2 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0150] Figure 3 This is a schematic diagram of the structure of an electronic device according to an example embodiment of this application. The electronic device includes a memory, a processor, and a computer program stored in the memory and used to run on the processor. When the processor executes the computer program, it implements the method described in any of the above embodiments. Figure 3 The electronic device 30 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0151] like Figure 3As shown, the electronic device 30 can be manifested as a general-purpose computing device, such as a server device. The components of the electronic device 30 may include, but are not limited to: at least one processor 31, at least one memory 32, and a bus 33 connecting different system components (including memory 32 and processor 31).

[0152] Bus 33 includes a data bus, an address bus, and a control bus.

[0153] The memory 32 may include volatile memory, such as random access memory (RAM) 321 and / or cache memory 322, and may further include read-only memory (ROM) 323.

[0154] The memory 32 may also include a program tool 325 (or utility) having a set (at least one) program module 324, such program module 324 including but not limited to: an operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0155] The processor 31 executes various functional applications and data processing, such as the methods provided in any of the above embodiments, by running computer programs stored in the memory 32.

[0156] Electronic device 30 can also communicate with one or more external devices 34 (e.g., keyboard, pointing device, etc.). This communication can be performed via input / output (I / O) interface 35. Furthermore, electronic device 30 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public network, such as the Internet) via network adapter 36. As shown, network adapter 36 communicates with other modules of electronic device 30 via bus 33. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with electronic device 30, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems.

[0157] It should be noted that although several units / modules or sub-units / modules of the electronic device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0158] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method provided in any of the above embodiments.

[0159] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0160] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0161] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the method described in any of the above embodiments.

[0162] The program code for executing the computer program product of this application can be written in any combination of one or more programming languages. The program code can be executed entirely on the user device, partially on the user device, as a standalone software package, partially on the user device and partially on a remote device, or entirely on a remote device.

[0163] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0164] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these modifications and improvements all fall within the protection scope of this application.

[0165] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A tumor-assisted acupuncture system based on acupoint conductivity feedback regulation, characterized in that, The system includes: The stimulation determination module is used to determine the stimulation coefficient for each person after performing acupuncture on the main acupoints once, based on the time difference, amplitude, and polarity of the change in conductivity within each person's acupoint group; the acupoint group includes the main acupoints and their corresponding front acupoints; The analysis module is used to analyze the correlation and differences of the conductivity change curves within the acupoint group for each person after one acupuncture session at the main acupoints, obtain the synergy coefficient for each person, and determine the pathological coefficient of the patient based on the difference in synergy coefficient between healthy individuals and patients. The activation determination module is used to determine the activation coefficient of each acupoint after each acupuncture treatment for each patient, based on the change in conductivity of the acupoint when the conductivity reaches the preset conditions and the required time. The tolerance determination module is used to determine the tolerance coefficient of each acupoint after performing one acupuncture session, based on the time required for the conductivity of the acupoint to reach the preset condition and the number of acupuncture techniques used in that session. The output module is used to output the stimulation intensity of the next acupuncture session for the acupoint based on the stimulation coefficient, pathological coefficient, activation coefficient of each acupoint, and tolerance coefficient of the acupoint.

2. The tumor-assisted acupuncture system based on acupoint conductivity feedback regulation as described in claim 1, characterized in that, The stimulus determination module is also used for: The electrical conductivity of each acupoint before acupuncture stimulation is determined as the reference electrical conductivity of that acupoint. After performing acupuncture on each person's main acupoints once, the moment when the difference between the conductivity of the main acupoint and the reference conductivity of the main acupoint first reaches a first preset percentage threshold is defined as the first moment, and the moment when the difference between the conductivity of the corresponding acupoint and the reference conductivity of the acupoint first reaches a first preset percentage threshold is defined as the second moment. The stimulation coefficient for each person is determined based on the absolute difference between the first and second moments, the amplitude of the change in conductivity within each person's acupoint group, and the polarity of the change in conductivity.

3. The tumor-assisted acupuncture system based on acupoint conductivity feedback regulation as described in claim 2, characterized in that, The stimulus determination module is also used for: After acupuncture is performed on each person's main acupoints, when the difference between the conductivity of the main acupoint and its baseline conductivity first reaches a second preset percentage threshold, and the conductivity change rate of the main acupoint is positive while the conductivity change rate of the corresponding associated acupoints is negative, the stress coefficient for each person is determined based on the first conductivity change of the main acupoint relative to its baseline conductivity and the second conductivity change of the associated acupoints relative to their baseline conductivity. The acupoint group includes the main acupoint, its corresponding front acupoint, and its corresponding associated acupoints. The associated acupoints indicate the acupoints located in the relevant meridian area of ​​the main acupoint. The stress coefficient indicates the degree of stimulation abnormality of the main acupoint and its related meridian area. The stimulation coefficient for each person is determined based on the absolute difference between the first and second moments and the individual's stress coefficient; the stimulation coefficient indicates the intensity of the response of each person's main acupoints to the acupuncture treatment.

4. The tumor-assisted acupuncture system based on acupoint conductivity feedback regulation as described in claim 1, characterized in that, The analysis module is also used for: After performing acupuncture on each person's main acupoints once, obtain the first conductivity change curve of the main acupoints within a preset time and the second conductivity change curve of the corresponding acupoints within a preset time. Based on the definite integral of the overlapping region between the first conductivity change curve and the second conductivity change curve, and the definite integral of the first conductivity change curve, determine the percentage of the overlapping area between the first conductivity change curve and the second conductivity change curve. Calculate the Pearson correlation coefficient between the first conductivity change curve and the second conductivity change curve to obtain the directional correlation coefficient; The first conductivity change curve and the second conductivity change curve are aligned using the DTW algorithm to obtain all matching point pairs of the first conductivity change curve and the second conductivity change curve; The time delay coefficient is obtained by taking the mean of the time difference between multiple sets of matching point pairs and the standard deviation of the time difference between multiple sets of matching point pairs. Based on the overlap area ratio, directional correlation coefficient, and time delay coefficient, the synergy coefficient of each individual is obtained, and the pathological coefficient of the patient is obtained based on the difference in synergy coefficient between healthy individuals and patients.

5. The tumor-assisted acupuncture system based on acupoint conductivity feedback regulation as described in claim 1, characterized in that, The activation determination module is also used for: After performing acupuncture on each acupoint for each patient, the change in conductivity of each acupoint when it rises to a stable level is obtained relative to the reference conductivity of that acupoint. The rise to a stable level indicates that the standard deviation of conductivity fluctuations at multiple consecutive time points is less than a preset fluctuation value. The reference conductivity of each acupoint indicates the conductivity of that acupoint before acupuncture stimulation. The activation rate of acupoint is determined by the ratio of the change in the third conductivity of each acupoint to the time required for the conductivity of that acupoint to rise to a stable level. The activation coefficient of an acupoint is determined based on the preset rate, the activation rate of each acupoint, the conductivity of the acupoint when it rises to a stable level, and the reference conductivity of the acupoint.

6. The tumor-assisted acupuncture system based on acupoint conductivity feedback regulation as described in claim 1, characterized in that, The tolerance determination module is also used for: After performing acupuncture on each acupoint once, the time when the conductivity of the first acupoint in two adjacent acupoints first reaches its peak value is taken as the benchmark, and the difference between the time when the conductivity of the second acupoint first reaches its peak value and the benchmark is taken as the tolerance of the second acupoint. The patient's initial tolerance coefficient is determined based on the average tolerance of multiple acupoints. The tolerance coefficient of acupoint is determined based on the patient's initial tolerance coefficient, the time required for the conductivity of each acupoint to reach the preset conditions, and the number of needling techniques used in this session.

7. The tumor-assisted acupuncture system based on acupoint conductivity feedback regulation as described in claim 6, characterized in that, The tolerance determination module is also used for: The real-time tolerance coefficient of each acupoint is determined by the ratio of the time required for the conductivity of each acupoint to rise to a stable level to the number of acupuncture techniques used in that session; the rise of conductivity to a stable level indicates that the standard deviation of conductivity fluctuation over multiple consecutive time periods is less than a preset fluctuation value. The tolerance coefficient of each acupoint is determined by the difference between the ratio of the real-time tolerance coefficient of each acupoint to the patient's initial tolerance coefficient and the first preset value.

8. The tumor-assisted acupuncture system based on acupoint conductivity feedback regulation as described in claim 1, characterized in that, The output module is also used for: The judgment factor is obtained based on the difference between the ratio of each patient's stimulation coefficient to pathological coefficient and the second preset value; In response to a positive decision factor, the stimulation intensity of the next acupuncture session for that acupoint is output based on the decision factor, the activation coefficient of each acupoint, and the tolerance coefficient of that acupoint.

9. The tumor-assisted acupuncture system based on acupoint conductivity feedback regulation as described in claim 8, characterized in that, The output module is also used for: In response to a positive decision factor, the ratio of the activation coefficient to the tolerance coefficient of each acupoint is calculated. The stimulation regulation coefficient of an acupoint is determined based on the difference between the determination factor and the ratio of the activation coefficient to the tolerance coefficient of that acupoint. Based on the stimulation adjustment coefficient of each acupoint and the needling plan for this session, determine and output the stimulation intensity for the next session of needling for that acupoint; the needling plan includes the insertion and withdrawal depth, duration, and angle of this session of needling.

10. The tumor-assisted acupuncture system based on acupoint conductivity feedback regulation as described in claim 9, characterized in that, The output module is also used for: The needling plan for each acupoint in this session is input into a pre-trained neural network to output a stimulation intensity score for that acupoint. Based on the stimulation intensity score of each acupoint, the stimulation adjustment coefficient of that acupoint, and the stimulation intensity of that acupuncture session, the stimulation intensity of the next acupuncture session for that acupoint is output.

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