Ganglion measurement method and device based on impedance data

Abstract

The invention provides a ganglion measurement method and device based on impedance data. The method comprises the following steps: determining a crowd category to which a to-be-measured person belongs; a human body impedance value data atlas corresponding to the crowd type to which the to-be-tested person belongs is obtained, different crowd types correspond to different human body impedance value data atlas, and the human body impedance value data atlas comprises a human body reference ganglion and a human body impedance value reference range between different human body ganglions; and based on the human body impedance value data map, taking the point location of the human body reference ganglion as a negative electrode end, and measuring the point location of each human body ganglion of the to-be-measured person through a positive electrode end. According to the method, the human body resistance value characteristics of the to-be-measured person are accurately determined by acquiring the human body resistance value data graph corresponding to the belonging crowd category, and accurate point location is performed on the human body ganglions needing to be measured by the to-be-measured person by utilizing the human body resistance value reference range between the human body reference ganglion and different human body ganglions; therefore, the positioning accuracy of the human ganglion is improved.

Description

Technical Field

[0001] The invention relates to human ganglion measurement, and in particular to a ganglion measurement method and device based on impedance data. Background Art

[0002] The ganglion is where the neuron cells near the ganglion gather. It is connected to the brain, spinal cord, and nerve fibers, and its function is to transmit signals. The ganglion is composed of neuron cells with the same function, which gather in other areas outside the center. It is a connective tissue membrane composed of blood vessels, nerves, and fat cells. The membrane is connected to the outer membrane nerve bundle, and a mesh structure composed of ganglia is formed inside the ganglion. The fibers produced by the nerve cells in the ganglion are distributed in relevant parts of the human body and are called postganglionic fibers. According to their physiology and morphology, they can be divided into two types, one is the spinal ganglion and the other is the autonomic ganglion. The spinal ganglion is a functional sensory neuron, and its morphology is a pseudo-monopolar or bipolar neuron. The autonomic ganglion is mainly composed of sympathetic ganglia and parasympathetic ganglia, of which the sympathetic ganglia are on both sides of the spine, and the parasympathetic ganglia are around the controlled organs or on the walls of the organs.

[0003] The main function of the ganglion is to receive and process nerve signals and transmit them to other parts. Neuromodulation technology first requires precise targets, and precise positioning becomes the core key point of neuromodulation. At the same time, through long-term research, it is found that ganglia are highly consistent with TCM acupoints. Acupuncture treats diseases through acupoints and has been highly recognized domestically and internationally. TCM also urgently needs acupoint positioning equipment. However, the acupoint locators studied in the past have a very large gap in accuracy.

[0004] Therefore, how to accurately locate the ganglion is an urgent problem to be solved. Summary of the invention

[0005] The embodiment of the present invention provides a ganglion measurement method based on impedance data, aiming to solve the problem of how to accurately locate human ganglia. The present invention divides the persons to be measured according to the population categories to which they belong, and obtains the human impedance value data spectrum corresponding to the population categories to which they belong, so as to accurately determine the human resistance characteristics of the persons to be measured, and uses the human impedance value reference range between the human reference ganglion and different human ganglia to accurately locate the human ganglia that need to be measured by the persons to be measured, thereby improving the accuracy of locating the human ganglia.

[0006] In a first aspect, an embodiment of the present invention provides a ganglion measurement method based on impedance data, the method comprising: Determine the population category to which the person to be tested belongs; Acquire a human body impedance value data spectrum corresponding to the population category to which the person to be tested belongs, different population categories correspond to different human body impedance value data spectrums, and the human body impedance value data spectrum includes a human body reference ganglion and a human body impedance value reference range between different human body ganglia; Based on the human body impedance value data map, the point of the human reference ganglion is taken as the negative terminal, and the point of each human ganglion of the person to be measured is obtained through the positive terminal measurement.

[0007] Optionally, before the step of obtaining a human body impedance value data map corresponding to the population category to which the person to be measured belongs, the method further includes: By measuring the body resistance of different people, a resistance value table of different people is obtained; Based on the resistance value tables of different persons, a human body impedance data set is determined for constructing a human body impedance value data map, wherein the human body impedance data set includes human body impedance data of different persons; Based on the human body impedance data set, a human body impedance value data map corresponding to different population categories is constructed.

[0008] Optionally, the step of constructing a human body impedance value data map corresponding to different population categories based on the human body impedance data set includes: Preprocessing the human body impedance data set to construct a human body impedance data semantic network, wherein the human body impedance data semantic network includes the relationship between human body impedance value data and human body parts; Based on the human body impedance data semantic network, semantic extraction is performed on the human body impedance data in the human body impedance data set to obtain reference ranges of human body impedance values ​​for different groups of people for each body part; Based on the reference range of human body impedance values ​​for various parts of the human body for different population categories, a data map of human body impedance values ​​corresponding to different population categories is constructed.

[0009] Optionally, the step of constructing a human body impedance value data map corresponding to different population categories based on the human body impedance value reference range for each human body part for different population categories includes: Based on the reference range of human impedance values ​​for various human body parts for different population categories, typical feature values ​​of different population categories are learned under expert supervision; Based on the typical characteristic values ​​of different population categories and the pre-probability of the causal relationship between different population categories, crowdsourcing learning is carried out on different population categories. Through multiple one-to-one comparisons, the data maps of human body impedance values ​​corresponding to different population categories are obtained.

[0010] Optionally, the step of obtaining the points of each human ganglion of the person to be measured by measuring the points of the human reference ganglion as the negative terminal based on the human impedance value data map includes: Based on the human body impedance value data spectrum, determining a target human body impedance value reference range between a human body reference ganglion and a target human body ganglion for the person to be tested; The biopotential signal of the current point is obtained by measuring the positive terminal; Determine the human body impedance value at the current point based on the biopotential signal at the current point and the spontaneous biological discharge frequency of the person to be measured; If the human body impedance value of the current point belongs to the target human body impedance value reference range, then determining the current point as the point of the target human ganglion; If the human body impedance value at the current point does not belong to the target human body impedance value reference range, the positive terminal is moved to find a new point for measurement.

[0011] Optionally, the step of obtaining the points of each human ganglion of the person to be measured by measuring the points of the human reference ganglion as the negative terminal based on the human impedance value data map includes: Based on the human body impedance value data spectrum, determining a target human body impedance value reference range between a human body reference ganglion and a target human body ganglion for the person to be tested; By changing the AC excitation frequency between the negative terminal and the positive terminal, the human body impedance value at the current point is determined; If the human body impedance value of the current point belongs to the target human body impedance value reference range, then determining the current point as the point of the target human ganglion; If the human body impedance value at the current point does not belong to the target human body impedance value reference range, the positive terminal is moved to find a new point for measurement.

[0012] Optionally, the step of obtaining the points of each human ganglion of the person to be measured by measuring the points of the human reference ganglion as the negative terminal based on the human impedance value data map includes: Based on the human body impedance value data spectrum, determining a target human body impedance value reference range between a human body reference ganglion and a target human body ganglion for the person to be tested; Between the negative terminal and the positive terminal, an excitation signal is provided through a loop where a first voltage generator is located, and a common mode signal is provided through a loop where a second voltage generator is located; Extract the real part and imaginary part of the impedance between the negative terminal and the positive terminal to obtain the human body impedance value at the current point; If the human body impedance value of the current point belongs to the target human body impedance value reference range, then determining the current point as the point of the target human ganglion; If the human body impedance value at the current point does not belong to the target human body impedance value reference range, the positive terminal is moved to find a new point for measurement.

[0013] In the second aspect, an embodiment of the present invention further provides a ganglion measuring device based on impedance data, the ganglion measuring device based on impedance data comprising: a measuring device, a negative terminal, and a positive terminal, the negative terminal being connected to the negative port of the measuring device, the positive terminal being connected to the positive port of the measuring device, the measuring device being used to execute a ganglion measuring method based on impedance data as described in any one of the embodiments of the present invention.

[0014] Optionally, a four-wire configuration is used between the negative terminal and the positive terminal to form a loop where a first voltage generator is located and a loop where a second voltage generator is located. The loop where the first voltage generator is located is used to provide an excitation signal, and the loop where the second voltage generator is located is used to provide a common-mode signal.

[0015] In an embodiment of the present invention, the category of the population to which the person to be tested belongs is determined; a human body impedance value data spectrum corresponding to the category of the population to which the person to be tested belongs is obtained, different population categories correspond to different human body impedance value data spectrums, and the human body impedance value data spectrum includes a human body impedance value reference range between a human body reference ganglion and different human body ganglia; based on the human body impedance value data spectrum, the point position of the human body reference ganglion is taken as the negative extreme point, and the point position of each human body ganglion of the person to be tested is obtained by measuring the positive extreme point. The present invention divides the person to be tested according to the category of the population to which they belong, and obtains a human body impedance value data spectrum corresponding to the category of the population to which they belong, thereby accurately determining the human body resistance characteristics of the person to be tested, and using the human body impedance value reference range between the human body reference ganglion and different human body ganglia to accurately point the human body ganglia that need to be measured by the person to be tested, thereby improving the positioning accuracy of the human body ganglia, and the ganglia are key biological targets for neural regulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 is a flow chart of a ganglion measurement method based on impedance data provided by an embodiment of the present invention; Figure 2 It is a schematic diagram of the complexity of a human body impedance value data spectrum provided by an embodiment of the present invention; Figure 3 It is a schematic diagram of supervised learning based on an artificial intelligence large model provided by an embodiment of the present invention; Figure 4 This is a schematic diagram of the relationship between impedance values ​​at different distances between a measurement point and a ganglion provided by an embodiment of the present invention; Figure 5 It is a structural schematic diagram of a ganglion measurement device based on impedance data provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] like Figure 1 As shown, Figure 1 : is a method flow chart of a ganglion measurement method based on impedance data provided by an embodiment of the present invention. The ganglion measurement method based on impedance data comprises the steps of: 101. Determine the population category to which the person to be tested belongs.

[0020] In an embodiment of the present invention, the above-mentioned ganglion measurement method based on impedance data can be applied to a ganglion measurement device based on impedance data, specifically for accurately measuring the position of the ganglion. It should be noted that bioimpedance is a measurement method that can provide useful information about the body's state. Impedance measurement provides information about the electrochemical activity, body composition, and hydration status of the human body. Different people have specific differences in the information about the electrochemical activity, body composition, and hydration status of the human body.

[0021] The above-mentioned persons to be tested are persons who need to have ganglia positioned. The physical information of the persons to be tested and the population category to which the persons to be tested belong can be determined based on their physiological information. The above-mentioned physiological information may include weight, height, gender, age, etc., such as: thin people, fat people, etc., for example, a 45-year-old male with a weight of 60kg and a height of 178cm, and a 25-year-old female with a weight of 50kg and a height of 165cm.

[0022] 102. Obtain a human body impedance value data spectrum corresponding to the population category to which the person to be tested belongs.

[0023] In an embodiment of the present invention, a database can be constructed to store different human body impedance value data spectra corresponding to different population categories. In the database, different population categories and corresponding human body impedance value data spectra are used as key-value pairs. By inputting the attribute population category of the person to be tested or directly inputting the physiological information of the person to be tested, the human body impedance value data spectra corresponding to the category to which the person to be tested belongs can be found.

[0024] The above human body impedance value data spectrum includes the human body impedance value reference range between the human body reference ganglion and different human body ganglia. The above human body reference neural node refers to a more accurate negative reference point, such as a neural node at the left wrist of the human body. That is, the above human body impedance value data spectrum includes the human body impedance value reference range between the neural node at the left wrist of the human body and different human body ganglia.

[0025] The above human body impedance value reference range is used to indicate whether the current positive terminal point is near the target human body nerve point.

[0026] It should be noted that since different people have different information about human electrochemical activity, body composition and hydration status, it will affect the accuracy of the impedance value between nerve nodes. The same people have similar information about human electrochemical activity, body composition and hydration status. Therefore, matching different population categories with different human impedance value data maps can provide a more accurate reference, and then accurately measure the various nerve nodes of the person to be tested.

[0027] 103. Based on the human body impedance value data spectrum, the point of the human reference ganglion is taken as the negative pole, and the point of each human ganglion of the person to be tested is obtained through the positive pole measurement.

[0028] In the embodiment of the present invention, the above human body impedance value data map includes a human body impedance value reference range between a human body reference ganglion and different human body ganglia, with the point of the human body reference ganglion as the negative extreme point.

[0029] The reference ganglion can be determined first, which can be the left wrist of the human body, and then the target human ganglion to be measured can be determined. Then, based on the reference ganglion and the target human ganglion, the reference range of human impedance values ​​between the reference human ganglion and the target human ganglion can be determined in the human impedance data map.

[0030] The electrode at the negative end is attached to the reference nerve node of the human body, and the positive end is a ganglion measuring pen. The ganglion measuring pen is used to measure near the human ganglion of the person to be tested, and then determine whether the point where the ganglion measuring pen is located is the point of the target human ganglion.

[0031] For example, the electrode sheet at the negative end is attached to the left wrist of the person to be tested, and the target human ganglion point is found on the person to be tested by moving the ganglion measuring pen. In the process of moving the ganglion measuring pen, the impedance value measured by the ganglion measuring pen at the current point is compared with the human body impedance value reference range between the human body reference ganglion and the target human body ganglion. If the measured impedance value is within the human body impedance value reference range between the human body reference ganglion and the target human body ganglion, the current point where the ganglion measuring pen is located can be determined as the target human body ganglion point.

[0032] In an embodiment of the present invention, the category of the population to which the person to be tested belongs is determined; a human body impedance value data spectrum corresponding to the category of the population to which the person to be tested belongs is obtained, different population categories correspond to different human body impedance value data spectrums, and the human body impedance value data spectrum includes a human body impedance value reference range between a human body reference ganglion and different human body ganglia; based on the human body impedance value data spectrum, the point position of the human body reference ganglion is taken as the negative extreme point, and the point position of each human body ganglion of the person to be tested is obtained by measuring the positive extreme point. The present invention divides the person to be tested according to the category of the population to which they belong, and obtains a human body impedance value data spectrum corresponding to the category of the population to which they belong, thereby accurately determining the human body resistance characteristics of the person to be tested, and using the human body impedance value reference range between the human body reference ganglion and different human body ganglia to accurately point the human body ganglia that need to be measured by the person to be tested, thereby improving the accuracy of positioning the human body ganglia.

[0033] It can be understood that in the specific implementation of the present application, related data such as the physiological data of the person to be tested and user data are involved. When the embodiments in the present application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of relevant data, as well as the training, deployment and calling of data models, must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0034] Optionally, before the step of obtaining the human body impedance value data map corresponding to the population category to which the person to be measured belongs, the human body resistance of different persons can be measured to obtain a resistance value table for different persons; based on the resistance value table for different persons, a human body impedance data set for constructing the human body impedance value data map is determined, and the human body impedance data set includes the human body impedance data of different persons; based on the human body impedance data set, a human body impedance value data map corresponding to different population categories is constructed.

[0035] In an embodiment of the present invention, human body resistance can be measured for a large number of people in standard body positions (lying, standing, sitting, etc.), and a large number of resistance value tables can be obtained, and each person corresponds to a resistance value table. The above human body resistance measurement is to measure the resistance value between two parts of the human body with a specific excitation signal. For one person, multiple groups of resistance values ​​can be measured, and each group of resistance values ​​is the resistance value between two parts. There are differences in physiological information such as weight, height, gender, and age among the above large number of people.

[0036] The resistance value table is preprocessed by screening, filtering, deduplication and other preprocessing operations to form a triplet of (site 1, site 2, resistance value). If site 1 is the largest site of the reference ganglion, a binary group of (site 2, resistance value) can be formed.

[0037] The resistance value is converted into the impedance value. The human body can be regarded as a complex circuit system, which includes the comprehensive effects of capacitance, inductance, and resistance. Therefore, under the action of the excitation signal, an impedance value will be generated. The impedance value can be regarded as the comprehensive effect of the resistance value and the reactance. The resistance value can be converted into the impedance value by constantizing the human body reactance value. In some possible embodiments, due to the existence of the self-discharge frequency in the ganglion part, the reactance of the ganglion is reduced. Therefore, when the resistance value of the ganglion is accurately collected, the above resistance value can be determined as the impedance value.

[0038] The impedance values ​​corresponding to the ganglia of different persons are added to the set to obtain a human body impedance data set, which includes a large amount of human body impedance value data.

[0039] The basic framework of the human body group impedance value data map has two elements, one is the conceptual object (human body part or human ganglion), and the other is the relationship (direct connection or indirect connection).

[0040] The connectivity map between different parts can be constructed, and the connectivity map between different ganglia can also be constructed. Each node in the above connectivity map corresponds to a part or a ganglion. Figure 2 As shown, A is the reference ganglion, BCDE are human ganglia directly connected to the reference ganglion, FGHIJKLM are slave ganglia indirectly connected to the reference ganglion, among which FGHI is the ganglion directly connected to ganglion B, JKLM is the ganglion directly connected to ganglion C, 11, 12, 9, 7 are ganglia directly connected to ganglion F, 15 is the ganglion directly connected to ganglion G, 13 is the ganglion directly connected to ganglion H, 17 is the ganglion directly connected to ganglion I, NOPQ is the ganglion directly connected to ganglion J, etc. The connectivity relationship between these ganglia constitutes a connectivity map.

[0041] For each node in the connectivity graph, an impedance value is added. Each node can add at least one impedance value, that is, each ganglion can correspond to at least one impedance value. Multiple impedance values ​​can form a range of minimum impedance value and maximum impedance value, and the range can be determined as a human reference impedance value reference range between a human reference ganglion and different human ganglia. In this way, a ganglion-impedance value range tuple is formed, which serves as a node.

[0042] Multiple connectivity maps are copied according to different populations, each population corresponds to a connectivity map, and the impedance values ​​corresponding to the ganglia of different populations are added to the corresponding nodes to form a human body impedance value data map corresponding to different population categories.

[0043] In a possible embodiment, the resistance value table can be analyzed by applying the principle of 12-lead electrocardiogram, and combined with traditional Chinese medicine consultation technology, a bioimpedance spectrum and the best accurate negative end of the reference ganglion (the left wrist of the human body) can be formed. Artificial intelligence feedback is then used to expand the reinforcement learning technology from human feedback to obtain a human group impedance value data spectrum.

[0044] In one possible embodiment, a variety of different unsupervised machine learning algorithms can be used to learn a large amount of data value ranges from tens of thousands of human impedance data.

[0045] Optionally, in the step of constructing a human impedance value data map corresponding to different population categories based on the human impedance data set, the human impedance data set can be preprocessed to construct a human impedance data semantic network, which includes the relationship between human impedance value data and human body parts; based on the human impedance data semantic network, the human impedance data in the human impedance data set is semantically extracted to obtain a reference range of human impedance values ​​for each body part for different population categories; based on the reference range of human impedance values ​​for each body part for different population categories, a human impedance value data map corresponding to different population categories is constructed.

[0046] In the embodiment of the present invention, one human body part corresponds to one ganglion. The human body impedance data set includes a large amount of human body impedance value data, and the big data can be used to find the negative end of a specific ganglion measurement (reference ganglion) through a super-order abstract algorithm in a large model, and calculate and obtain the impedance value data map corresponding to different population categories.

[0047] The implementation principle of the super-order abstract algorithm is: Complexity of human body impedance data spectrum: Number of human bodies (C): 200,000; Human body classification similarity relationship (R): 100; Body part dimension (D): 50; Graph complexity = C*R*D=10 9 ; Complexity = NP complete. Polynomial-time reduction can be used to prove that this problem belongs to the NP complete class.

[0048] Specifically, the abstract human body impedance data semantic network is established: the relationship between the complete human body impedance data and the human body parts is constructed. The human body impedance data includes the differences in body positions (lying, standing, sitting, etc.), the differences between different types of people, and the slight changes between 10 megohms and 60 megohms. The data is huge. Various technologies (such as data vector clustering, vector clustering) can be used to comprehensively process, classify, and eliminate data noise, and gradually complete the human body impedance data semantic network. ).

[0049] The human body impedance data semantic network includes the relationship between human body impedance value data and human body parts. After reading and understanding the massive human body impedance data in the human body impedance data set through machine learning, hundreds of thousands of rules can be summarized for a certain data semantics based on abstract medical extraction. For example, for the relationship between "impedance value-part", the description method in semantic extraction is: "Dx part has impedance ranges such as S1...S22", "(male Dx part) impedance value is (S1, S5 impedance value range)", "(female Dx part) is more present in (S3, S11 impedance value range)", etc. "Semantic rules are automatically discovered and extracted to obtain the reference range of human body impedance values ​​for different population categories for each human body part.

[0050] After obtaining the reference range of human body impedance values ​​for each body part for different population categories, the reference range of human body impedance values ​​for each body part is added to the nodes corresponding to each body part in the connectivity graph of the corresponding population, so as to construct a data graph of human body impedance values ​​corresponding to different population categories.

[0051] Optionally, in the step of constructing a data map of human impedance values ​​corresponding to different population categories based on the reference range of human impedance values ​​for each body part of different population categories, typical characteristic values ​​of different population categories can be learned under expert supervision based on the reference range of human impedance values ​​for each body part of different population categories; crowdsourcing learning is performed on different population categories based on the typical characteristic values ​​of different population categories and the prior probability of causal relationships between different population categories, and through multiple one-to-one comparisons, data maps of human impedance values ​​corresponding to different population categories are obtained.

[0052] In the embodiment of the present invention, the typical feature value is used to represent the feature of a crowd category, and is a feature value that is different from other crowd categories.

[0053] The links of similar correlations between population categories and the relationships between similar groups of humans (for example, a typical characteristic value of impedance for a thin type of human being is in the range of 12M-33M, and a typical characteristic value of impedance for a fat type of human being may be between 14M-39.6M) expand exponentially. Due to the extremely high noise ratio and the overlap of impedance data maps of multiple groups, the relationship vector is more difficult to obtain. Therefore, the system can complete learning under the supervision of experts to improve the accuracy of the human impedance data map corresponding to each category of people.

[0054] Typical eigenvalue learning can use the following formula to model group characteristics: The input of the population characteristic model is: impedance time series data of each part (for example, dimension D=50).

[0055] The output of the group characteristic model is: a multidimensional feature vector of each group (such as containing mean, variance, frequency domain characteristics, etc.).

[0056] x t The impedance observation value at time step t is a multidimensional vector, s t represents the implicit state at time step t, which is a discrete variable. M represents the number of Gaussian mixture components, which is an integer and can be set to M=3. im Represents the weight of the mth component under state i, used to represent the probability value, μ im Represents the mean vector of the mth Gaussian component in state i, which is a data in vector form, ∑ im Represents the covariance matrix of the mth Gaussian component under state i, which is a matrix form of data. is a constant.

[0057] The pre-probability is used to represent the causal relationship between population categories, such as the causal relationship between obese people and diabetic people. The accurate pre-probability of the causal relationship between groups is extremely important for the accurate expression of impedance values, but this type of information does not exist in any literature. Therefore, this application can successively conduct crowdsourcing learning on thousands of groups, and it takes many years to compare them one by one to complete the human body impedance value data map of different population categories.

[0058] For example, the pre-probability of obese people and diabetic people can be expressed by the following formula: in, represents the pre-probability between obese people and diabetic people, N represents the total sample size of obese people, I (•) is the indicator function, I (condition) = 1 (established) or 0 (not established), represents the i-th sample in the obese population, Indicates that the i-th sample in the obese population suffers from diabetes. K represents the total sample size of the diabetic population, I (•) is the indicator function, I (condition) = 1 (established) or 0 (not established), represents the jth sample in the diabetic population, Indicates that the jth sample in the diabetic population is obese.

[0059] Each population category corresponds to a typical characteristic value or a typical characteristic value range, and there is a pre-probability corresponding to a causal relationship between every two population categories. Through crowdsourcing learning, multiple one-to-one comparisons can be performed in a large amount of human impedance value data to obtain human impedance value data maps corresponding to different population categories, thereby improving the accuracy of human impedance value data maps corresponding to different population categories.

[0060] In a possible embodiment, after obtaining the human body impedance value data map corresponding to different population categories, multi-layer human feedback learning can be performed on each part of the negative pole in the supervised learning of the artificial intelligence large model to determine the most accurate negative pole reference point. The most accurate negative pole reference point determined by this application is the left wrist. The negative pole reference point is the human reference ganglion. Figure 3As shown, the supervised learning of the above-mentioned artificial intelligence large model may include Prompts Dataset, Sample many prompts, Initial Language Model, Train on {sample, reward} pairs, Reward (Preference) Model, Generated text, Human Scoring, Outputs are ranked (outputs are ranked (relative ranking, Elo rating system ELO, etc.)). Specifically, a prompt dataset is first collected in the ganglion field, and multiple prompts are sampled from the prompt dataset and input into the initial language model. The initial language model outputs the generated text, which is manually scored by experts. Combined with the manual scoring, the text is input into the reward (preference) model in a {sample, reward} pair-based manner. The output of the reward (preference) model is ranked (relative ranking, Elo ranking system, etc.), and the output results are used in combination with {sample, reward} pairs for training. The model parameters of the initial language model and the reward (preference) model are adjusted according to the results of manual scoring until the accuracy conditions are met.

[0061] Optionally, in the step of obtaining the points of each human ganglion of the person to be tested by measuring the positive end based on the human impedance value data map and taking the point of the human reference ganglion as the negative end, the target human impedance value reference range between the human reference ganglion and the target human ganglion of the person to be tested can be determined based on the human impedance value data map; the biopotential signal of the current point is obtained by measuring the positive end; the human body impedance value of the current point is determined based on the biopotential signal of the current point and the biological spontaneous discharge frequency of the person to be tested; if the human body impedance value of the current point belongs to the target human body impedance value reference range, the current point is determined to be the point of the target human ganglion; if the human body impedance value of the current point does not belong to the target human body impedance value reference range, the positive end is moved to find a new point for measurement.

[0062] In an embodiment of the present invention, the target human ganglion to be located can be input, and the target human impedance value reference range between the human reference ganglion and the target human ganglion can be found in the human impedance value data map. The target human impedance value reference range is used to indicate whether the human point where the positive end is located is the target ganglion.

[0063] In a possible embodiment, based on the reference range of the target human body impedance value between the human reference ganglion and the target human body ganglion, the corresponding relationship between the distance from the target human body ganglion and the human body impedance value can be further calculated, such as Figure 4 As shown, when the distance from the target human ganglion is 0.00mm, the human body impedance value is 12.5M, when the distance from the target human ganglion is 0.50mm, the human body impedance value is 13.5M, when the distance from the target human ganglion is 1.00mm, the human body impedance value is 19M, when the distance from the target human ganglion is 1.50mm, the human body impedance value is 22.5M, and when the distance from the target human ganglion is 2.00mm, the human body impedance value is 47.5M. The positive end can be moved according to the measured impedance value through the corresponding relationship between the distance from the target human ganglion and the human body impedance value to find the point with a smaller distance from the target human ganglion.

[0064] The embodiment of the present invention can adopt a measurement method based on biopotential, which is an electrical signal caused by the effect of electrochemical activity in the human body. Examples of biopotential measurement include electrocardiogram (ECG) and electroencephalogram. They check extremely low amplitude signals in frequency bands with multiple interferences. The measurable part in ganglion positioning measurement is extremely large. Therefore, when using biopotential measurement, in order to achieve the purpose of accurate positioning, the human body impedance data spectrum technology can be used to delineate the population group (population category) and the high and low starting points of the population group impedance value. At the same time, before processing the signal, it must be amplified and filtered, and the spontaneous discharge frequency of the organism needs to be obtained. After moving the positive terminal to the current point, the biopotential signal is collected and converted into a human body impedance value, and the human body impedance value is compared with the target human body impedance value reference range. If the human body impedance value of the current point belongs to the target human body impedance value reference range, the current point is determined to be the point of the target human ganglion; if the human body impedance value of the current point does not belong to the target human body impedance value reference range, the positive terminal is moved to find a new point for measurement.

[0065] Optionally, in the step of obtaining the points of each human ganglion of the person to be tested by measuring the points of the human reference ganglion as the negative extreme point based on the human body impedance value data map and taking the points of the human reference ganglion as the negative extreme point through the positive extreme point measurement, the target human body impedance value reference range between the human reference ganglion and the target human ganglion for the person to be tested can be determined based on the human body impedance value data map; the human body impedance value of the current point is determined by changing the AC excitation frequency between the negative extreme point and the positive extreme point; if the human body impedance value of the current point belongs to the target human body impedance value reference range, the current point is determined to be the point of the target human ganglion; if the human body impedance value of the current point does not belong to the target human body impedance value reference range, the positive extreme point is moved to find a new point for measurement.

[0066] In an embodiment of the present invention, the target human ganglion to be located can be input, and the target human impedance value reference range between the human reference ganglion and the target human ganglion can be found in the human impedance value data map. The target human impedance value reference range is used to indicate whether the human point where the positive end is located is the target ganglion.

[0067] Embodiments of the present invention may employ measurements based on bioimpedance, which is another measurement method that can provide useful information about the state of the body. Impedance measurements provide information about electrochemical activity, body composition, and hydration status. Different measurement techniques may be used to measure each physiological parameter. The number of electrodes required for each measurement technique, as well as the point in time at which the technique is applied, varies depending on the frequency range used.

[0068] In the bioimpedance measurement method provided in the embodiment of the present invention, a specific frequency (usually 50-60 kHz frequency) can be output between two electrodes (negative and positive terminals) at the same time when measuring the ganglion impedance, and the point adjustment based on the human body impedance data spectrum feedback can be achieved by changing the AC excitation frequency. The receiving bandwidth can be up to 50 kHz and the signal-to-noise ratio (SNR) is 100 dB, which can achieve accurate application in medical applications.

[0069] After moving the positive terminal to the current point, the human body impedance signal is collected and converted into a human body impedance value by converting the analog signal to a digital signal, and the human body impedance value is compared with the target human body impedance value reference range. If the human body impedance value at the current point belongs to the target human body impedance value reference range, the current point is determined to be the point of the target human ganglion; if the human body impedance value at the current point does not belong to the target human body impedance value reference range, the positive terminal is moved to find a new point for measurement.

[0070] Optionally, in the step of obtaining the positions of each human ganglion of the person to be tested by measuring the position of the human reference ganglion as the negative terminal based on the human impedance value data map and taking the position of the human reference ganglion as the negative terminal, the target human impedance value reference range between the human reference ganglion and the target human ganglion for the person to be tested can be determined based on the human impedance value data map; between the negative terminal and the positive terminal, an excitation signal is provided through the loop where the first voltage generator is located, and a common mode signal is provided through the loop where the second voltage generator is located; the real part and the imaginary part of the impedance between the negative terminal and the positive terminal are extracted to obtain the human impedance value of the current point; if the human impedance value of the current point belongs to the target human impedance value reference range, the current point is determined to be the point of the target human ganglion; if the human impedance value of the current point does not belong to the target human impedance value reference range, the positive terminal is moved to find a new point for measurement.

[0071] In an embodiment of the present invention, the target human ganglion to be located can be input, and the target human impedance value reference range between the human reference ganglion and the target human ganglion can be found in the human impedance value data map. The target human impedance value reference range is used to indicate whether the human point where the positive end is located is the target ganglion.

[0072] Embodiments of the present invention may employ measurements based on bioimpedance, which is another measurement method that can provide useful information about the state of the body. Impedance measurements provide information about electrochemical activity, body composition, and hydration status. Different measurement techniques may be used to measure each physiological parameter. The number of electrodes required for each measurement technique, as well as the point in time at which the technique is applied, varies depending on the frequency range used.

[0073] In the measurement method based on bioimpedance provided in the embodiment of the present invention, the ganglion impedance can be measured in a four-wire configuration at the same time. For this type of four-wire configuration measurement, a high-frequency loop is used to provide an excitation signal; a programmable AC voltage generator (first voltage generator) provides an excitation signal, and the excitation signal is received by a first signal receiver to form a first loop, and the first loop is the loop where the first voltage generator is located. The second voltage generator can provide a common-mode voltage, and the common-mode voltage signal is received by a second signal receiver to form a second loop, and the second loop is the loop where the second voltage generator is located. Through the excitation signal and the common-mode voltage signal, the excitation signal of the high-frequency method can penetrate the human tissue. Different tissues have different impedances at different frequencies. More abundant human impedance information can be obtained through high-frequency excitation; the common-mode voltage signal can eliminate interference factors, so that the measurement can more accurately reflect the true situation of the human body impedance, so as to achieve correct measurement.

[0074] In a possible embodiment, the first receiver and the second receiver are not provided, and the current generated by the human body impedance can be directly collected. Specifically, the current generated by the human body impedance can be measured by a transimpedance amplifier and converted by a 16-bit ADC. The system is capable of measuring at a frequency of up to 200 kHz and can provide a signal-to-noise ratio (SNR) of 100 dB at 50 kHz. The digital signal is sent to a hardware accelerator to extract the required values; that is, the real part and the imaginary part of the impedance. A specific frequency (usually 50-200 kHz frequency is used) is output between the (negative end and the positive end), and the point adjustment based on the feedback of the human body impedance data spectrum is achieved by changing the AC excitation frequency. The receiving bandwidth can be up to 50 kHz and the signal-to-noise ratio (SNR) is 100 dB, which can be used for precision in medical applications.

[0075] In a possible embodiment, the excitation signal can be adjusted to 100 kHz, a 100 kHz current waveform signal can be used for feedback, and a 100 kHz current waveform signal can be used for human body impedance value conversion, and the human body impedance value at 100 kHz can be used to measure and locate the ganglion of the person to be measured.

[0076] After moving the positive terminal to the current point, the human body impedance signal is collected and converted into a human body impedance value by converting the analog signal to a digital signal, and the human body impedance value is compared with the target human body impedance value reference range. If the human body impedance value at the current point belongs to the target human body impedance value reference range, the current point is determined to be the point of the target human ganglion; if the human body impedance value at the current point does not belong to the target human body impedance value reference range, the positive terminal is moved to find a new point for measurement.

[0077] In this specific embodiment, a human body impedance value data map corresponding to different population categories, an excitation signal and a complete impedance measurement chain are provided, which can generate different frequencies to meet the measurement requirements of various human groups, achieve comprehensive and accurate bio-impedance and bio-potential readings, and thus improve the measurement accuracy of neural node positions.

[0078] like Figure 5 As shown, an embodiment of the present invention provides a ganglion measuring device based on impedance data, and the ganglion measuring device based on impedance data includes: a measuring device, a negative terminal, and a positive terminal, the negative terminal is connected to the negative port of the measuring device, and the positive terminal is connected to the positive port of the measuring device, and the measuring device is used to perform the ganglion measuring method based on impedance data as described in any one of the embodiments of the present invention.

[0079] The above-mentioned negative terminal includes a negative wire, one end of which is electrically connected to the negative port of the measuring device, and a conductive sheet (conductive patch) is set at the other end. The positive terminal includes a positive wire, one end of which is electrically connected to the positive port of the measuring device, and a ganglion measuring pen is set at the other end. The measuring device, the positive wire, the ganglion measuring pen, the human body, the conductive sheet, the negative wire, and the human body constitute a measurement circuit, which is used to measure the human body impedance value between the two points where the conductive sheet and the ganglion measuring pen are located.

[0080] The above-mentioned measuring device specifically includes a signal generator and a high-precision voltage-to-current conversion circuit. The voltage signal of the signal generator in the measuring device serves as the input of the high-precision voltage-to-current conversion circuit. The signal generator in the measuring device adopts a frequency division subcircuit. The frequency division subcircuit includes two frequency selection registers, a phase accumulator, two phase offset registers and a phase offset adder. The frequency selection register and the phase accumulator are both 28 bits, and the phase range of the continuous-time signal is 0 to 1.8π.

[0081] The measuring device provides a display interface for inputting the frequency of the excitation signal and the target human ganglion, and for displaying whether the point is the target human ganglion. When the current point is the target human ganglion, a confirmation signal is sent through the display interface, such as the indicator point turns green. When the current point is not the target ganglion, a negative signal is sent through the display interface, such as the indicator point turns red.

[0082] Furthermore, a four-wire configuration is used between the negative terminal and the positive terminal to form a loop where a first voltage generator is located and a loop where a second voltage generator is located. The loop where the first voltage generator is located is used to provide an excitation signal, and the loop where the second voltage generator is located is used to provide a common-mode signal.

[0083] Specifically, the measuring device in this embodiment includes a band-pass filter (BPF), a run length decoder (RLD), a low power transimpedance amplifier (LPTIA), a low power digital-to-analog converter (LPDAC), a high-speed digital-to-analog converter (HSDAC), a high-speed transimpedance amplifier (HSTIA), an analog-to-digital converter (ADC), a leads OFF detection, a waveform generator, a control logic, a digital processing, an excitation buffer, a switch matrix, a voltage control module (VCM), In-Amp is an instrument amplifier, and A2 and C are amplifier modules.

[0084] The current signal collected from the human-computer interface enters from the input end and is first filtered by the BPF. The filtered signal enters the In-Amp module for compression or transformation. The processed signal enters the RLD module for decoding and recovery. The decoded signal is amplified by the A2 module. The amplified signal enters the Leads Off Detection module to detect whether the wire is off. The detected signal enters the Excitation Buffer for buffering. The buffered signal interacts with the waveform signal generated by the WaveformGenerator. The signal is further processed and analyzed by the HSDAC, LPTIA, LPDAC, HSTIA and other modules. The processed analog signal is converted into a digital signal by the ADC. The digital signal enters the DigitalSignal Processing (DSP) module for various algorithm processing. The Control Logic module controls the coordinated work of the various modules of the system. Finally, the signal is switched and transmitted through the Switch Matrix.

[0085] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the computer-readable storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).

[0086] The above disclosure is only the preferred embodiment of the present invention, which certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A ganglion measurement method based on impedance data, characterized in that: The method comprises the following steps: Determine the population category to which the person to be tested belongs; Acquire a human body impedance value data spectrum corresponding to the population category to which the person to be tested belongs, different population categories correspond to different human body impedance value data spectrums, and the human body impedance value data spectrum includes a human body reference ganglion and a human body impedance value reference range between different human body ganglia; Based on the human body impedance value data map, the point of the human reference ganglion is taken as the negative terminal, and the point of each human ganglion of the person to be measured is obtained through the positive terminal measurement.

2. The method for measuring ganglia based on impedance data according to claim 1, characterized in that: Before the step of obtaining a human body impedance value data map corresponding to the population category to which the person to be tested belongs, the method further includes: By measuring the body resistance of different people, a resistance value table of different people is obtained; Based on the resistance value tables of different persons, a human body impedance data set is determined for constructing a human body impedance value data map, wherein the human body impedance data set includes human body impedance data of different persons; Based on the human body impedance data set, a human body impedance value data map corresponding to different population categories is constructed.

3. The ganglion measurement method based on impedance data according to claim 2, characterized in that: The step of constructing a human body impedance value data map corresponding to different population categories based on the human body impedance data set comprises: Preprocessing the human body impedance data set to construct a human body impedance data semantic network, wherein the human body impedance data semantic network includes the relationship between human body impedance value data and human body parts; Based on the human body impedance data semantic network, semantic extraction is performed on the human body impedance data in the human body impedance data set to obtain reference ranges of human body impedance values ​​for different groups of people for each body part; Based on the reference range of human body impedance values ​​for various parts of the human body for different population categories, a data map of human body impedance values ​​corresponding to different population categories is constructed.

4. The method for measuring ganglia based on impedance data according to claim 3, characterized in that: The step of constructing a human body impedance value data map corresponding to different population categories based on the human body impedance value reference range for each human body part for different population categories includes: Based on the reference range of human impedance values ​​for various human body parts for different population categories, typical feature values ​​of different population categories are learned under expert supervision; Based on the typical characteristic values ​​of different population categories and the pre-probability of the causal relationship between different population categories, crowdsourcing learning is carried out on different population categories. Through multiple one-to-one comparisons, the data maps of human body impedance values ​​corresponding to different population categories are obtained.

5. The ganglion measurement method based on impedance data according to any one of claims 1 to 4, characterized in that: The step of measuring the points of the human ganglia of the person to be tested based on the human impedance value data map and taking the points of the human reference ganglia as the negative terminal and obtaining the points of the human ganglia of the person to be tested through the positive terminal includes: Based on the human body impedance value data spectrum, determining a target human body impedance value reference range between a human body reference ganglion and a target human body ganglion for the person to be tested; The biopotential signal of the current point is obtained by measuring the positive terminal; Determine the human body impedance value at the current point based on the biopotential signal at the current point and the spontaneous biological discharge frequency of the person to be measured; If the human body impedance value of the current point belongs to the target human body impedance value reference range, then determining the current point as the point of the target human ganglion; If the human body impedance value at the current point does not belong to the target human body impedance value reference range, the positive terminal is moved to find a new point for measurement.

6. The ganglion measurement method based on impedance data according to any one of claims 1 to 4, characterized in that: The step of measuring the points of the human ganglia of the person to be tested based on the human impedance value data map and taking the points of the human reference ganglia as the negative terminal and obtaining the points of the human ganglia of the person to be tested through the positive terminal includes: Based on the human body impedance value data spectrum, determining a target human body impedance value reference range between a human body reference ganglion and a target human body ganglion for the person to be tested; By changing the AC excitation frequency between the negative terminal and the positive terminal, the human body impedance value at the current point is determined; If the human body impedance value of the current point belongs to the target human body impedance value reference range, then determining the current point as the point of the target human ganglion; If the human body impedance value at the current point does not belong to the target human body impedance value reference range, the positive terminal is moved to find a new point for measurement.

7. The ganglion measurement method based on impedance data according to any one of claims 1 to 4, characterized in that: The step of measuring the points of the human ganglia of the person to be tested based on the human impedance value data map and taking the points of the human reference ganglia as the negative terminal and obtaining the points of the human ganglia of the person to be tested through the positive terminal includes: Based on the human body impedance value data spectrum, determining a target human body impedance value reference range between a human body reference ganglion and a target human body ganglion for the person to be tested; Between the negative terminal and the positive terminal, an excitation signal is provided through a loop where a first voltage generator is located, and a common mode signal is provided through a loop where a second voltage generator is located; Extract the real part and imaginary part of the impedance between the negative terminal and the positive terminal to obtain the human body impedance value at the current point; If the human body impedance value of the current point belongs to the target human body impedance value reference range, then determining the current point as the point of the target human ganglion; If the human body impedance value at the current point does not belong to the target human body impedance value reference range, the positive terminal is moved to find a new point for measurement.

8. A ganglion measurement device based on impedance data, characterized in that: The ganglion measurement device based on impedance data includes: a measuring device, a negative terminal, and a positive terminal, wherein the negative terminal is connected to the negative port of the measuring device, and the positive terminal is connected to the positive port of the measuring device. The measuring device is used to perform the ganglion measurement method based on impedance data as described in any one of claims 1 to 7.

9. The ganglion measurement device based on impedance data according to claim 8, characterized in that: A four-wire configuration is used between the negative terminal and the positive terminal to form a loop where a first voltage generator is located and a loop where a second voltage generator is located. The loop where the first voltage generator is located is used to provide an excitation signal, and the loop where the second voltage generator is located is used to provide a common-mode signal.

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