Human skin and subcutaneous tissue impedance measurement method and device and electronic equipment

Abstract

The invention belongs to the technical field of human body impedance measurement, and particularly discloses a human body skin and subcutaneous tissue impedance measurement method and device and electronic equipment. The method comprises the following steps: step S101, acquiring impedance data of to-be-measured human body impedance under different excitation frequencies; step S102, based on the impedance data under different excitation frequencies, generating target curve data of the impedance data of the to-be-measured human body impedance along with the change of the excitation frequencies; step S103, fitting the target curve data by using a human body impedance model, and determining human body skin impedance and human body subcutaneous tissue impedance of the human body impedance to be measured; the human body impedance model is determined based on human body skin impedance and human body subcutaneous tissue impedance. According to the invention, precise measurement of impedance of human skin and subcutaneous tissue can be realized, the measurement precision and reliability are improved, and the richness and diversity of measurement data are increased.

Description

Technical Field

[0001] The present application belongs to the technical field of human body impedance measurement, and more specifically, to a method, device and electronic equipment for measuring the impedance of human skin and subcutaneous tissue. Background Art

[0002] Human body impedance measurement technology is an important non-invasive detection method with wide applications in the biomedical field, especially in clinical medicine, health monitoring and disease prevention. This technology applies a weak current to human biological tissue and measures the corresponding voltage changes to infer the electrical impedance characteristics of the tissue, thereby extracting information related to the physiological and pathological state of the human body.

[0003] At present, the research on human body impedance detection methods is still at a relatively superficial level. Many measurement methods lack the ability to measure biological tissues at different levels of the human body, which limits their application in clinical medicine and health monitoring. For example, the patent documents with patent numbers WO2020095298A3, WO2022015081A1 and CN110584667A, etc., the bioimpedance detection methods disclosed by them mainly focus on the measurement of the overall impedance and capacitive reactance information of the human body, lack the ability to independently measure the electrical characteristics of different levels such as skin and subcutaneous tissue, and cannot effectively distinguish and describe the electrical impedance characteristics of human skin and subcutaneous tissue.

[0004] At the same time, traditional human body impedance measurement data processing methods usually rely on simple linear or polynomial fitting, such as patent document No. US10470718B2 and patent document No. CN103230272B. These methods often cannot accurately fit the actual data when processing complex bioimpedance models, and the measurement results have large errors, making it impossible to achieve precise measurement of human body impedance.

[0005] Therefore, how to achieve precise measurement of the impedance of human skin and subcutaneous tissue has become a technical problem that needs to be solved urgently in the industry. Summary of the invention

[0006] In view of the defects of the prior art, the purpose of this application is to achieve precise measurement of the impedance of human skin and subcutaneous tissue, aiming to solve the problem of the lack of measurement capability of biological tissues at different levels of the human body in the prior art.

[0007] To achieve the above objectives, in a first aspect, the present application provides a method for measuring the impedance of human skin and subcutaneous tissue, comprising:

[0008] Step S101, obtaining impedance data of a human body impedance to be measured at different excitation frequencies;

[0009] Step S102, generating target curve data of the impedance data of the human body impedance to be measured changing with the excitation frequency based on the impedance data at different excitation frequencies;

[0010] Step S103, using a human body impedance model to fit the target curve data, to determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured; the human body impedance model is determined based on the human skin impedance and the human subcutaneous tissue impedance.

[0011] Optionally, the step S101 includes:

[0012] Acquire the values ​​of the first voltmeter, the adjustable resistance box and the second voltmeter at the different excitation frequencies measured by the data measurement module;

[0013] Determine the impedance data of the human body impedance to be measured at the different excitation frequencies according to the values ​​of the first voltmeter, the adjustable resistance box and the second voltmeter at the different excitation frequencies;

[0014] Among them, the data measurement module includes a sweep frequency signal source, a first voltmeter connected in parallel at both ends of the human body impedance to be measured, the adjustable resistance box and a second voltmeter connected in parallel at both ends of the adjustable resistance box; the sweep frequency signal source, the human body impedance to be measured and the adjustable resistance box are connected in series; the sweep frequency signal source is used to provide voltage signals with different excitation frequencies.

[0015] Optionally, the step S103 includes:

[0016] Using the Monte Carlo method, a plurality of impedance data samples are randomly generated; each of the impedance data samples includes human skin impedance and human subcutaneous tissue impedance; the human skin impedance includes skin resistance and skin capacitance, and the human subcutaneous tissue impedance includes subcutaneous tissue resistance;

[0017] Based on the human body impedance model, determining impedance prediction data of each impedance data sample at the different excitation frequencies;

[0018] The target curve data is fitted based on the impedance prediction data under the different excitation frequencies to determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured.

[0019] Optionally, fitting the target curve data based on the impedance prediction data at different excitation frequencies to determine the human skin impedance and human subcutaneous tissue impedance of the human body impedance to be measured includes:

[0020] Based on the impedance prediction data at the different excitation frequencies, generating impedance prediction curve data corresponding to each of the impedance data samples;

[0021] The impedance prediction curve data and the target curve data are fitted by using the least square method to determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured.

[0022] Optionally, the least square method is used to fit each of the impedance prediction curve data and the target curve data to determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured, including:

[0023] Taking the minimum sum of squares of errors between the impedance prediction data and the corresponding impedance data in the target curve data as the goal, determining the impedance prediction curve data with the highest matching degree with the target curve data from each of the impedance prediction curve data;

[0024] Based on the impedance prediction curve data with the highest matching degree, determining a corresponding target impedance data sample from each of the impedance data samples;

[0025] According to the target impedance data sample, the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured are obtained.

[0026] Optionally, after step S103, the method further includes:

[0027] Repeating steps S101 to S103 according to a preset number of measurements to obtain the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured for multiple times;

[0028] The human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured obtained by multiple measurements are averaged to obtain the target human skin impedance and the target human subcutaneous tissue impedance of the human body impedance to be measured.

[0029] In a second aspect, the present application provides a human skin and subcutaneous tissue impedance measurement device, comprising:

[0030] A data acquisition module, used to acquire impedance data of a human body impedance to be measured at different excitation frequencies;

[0031] A curve generating module, for generating target curve data of the impedance data of the human body impedance to be measured changing with the excitation frequency based on the impedance data at different excitation frequencies;

[0032] The data processing module is used to fit the target curve data using a human body impedance model to determine the human skin impedance and human subcutaneous tissue impedance of the human body impedance to be measured; the human body impedance model is determined based on the human skin impedance and human subcutaneous tissue impedance.

[0033] In a third aspect, the present application provides an electronic device comprising: at least one memory for storing programs; and at least one processor for executing the programs stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method described in the first aspect or any possible implementation of the first aspect.

[0034] In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method described in the first aspect or any possible implementation of the first aspect.

[0035] In a fifth aspect, the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the method described in the first aspect or any possible implementation of the first aspect.

[0036] In general, the above technical solutions conceived by this application have the following beneficial effects compared with the prior art:

[0037] The embodiments of the present application provide a method, device and electronic device for measuring the impedance of human skin and subcutaneous tissue. The method measures the impedance data of the human body impedance to be measured at different excitation frequencies by extending the frequency scanning range, and uses a large amount of measurement data to generate curve data of the human body impedance data changing with the excitation frequency. Then, a human body impedance model constructed by human skin impedance and human subcutaneous tissue impedance parameters is used to continuously fit the above curve data. The parameter iterative optimization capability of the data fitting algorithm is used to obtain the impedance data with the highest fitting degree, thereby obtaining the human skin impedance and human subcutaneous tissue impedance of the human body impedance to be measured. The precise measurement of the human skin and subcutaneous tissue impedance can be realized, which not only improves the accuracy and reliability of the measurement, but also increases the richness and diversity of the measurement data, and provides more accurate technical means for clinical medicine and health monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a flow chart of a method for measuring the impedance of human skin and subcutaneous tissue provided in an embodiment of the present application;

[0039] Figure 2 It is a schematic diagram of the principle of the human body impedance model used in the human skin and subcutaneous tissue impedance measurement method provided in the embodiment of the present application;

[0040] Figure 3 It is a structural schematic diagram of a data measurement module in a method for measuring impedance of human skin and subcutaneous tissue provided in an embodiment of the present application;

[0041] Figure 4 It is a schematic diagram of the results of data fitting in the human skin and subcutaneous tissue impedance measurement method provided in the embodiment of the present application;

[0042] Figure 5 is a schematic diagram of the structure of a human skin and subcutaneous tissue impedance measuring device provided in an embodiment of the present application;

[0043] Figure 6 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0045] The terms "first", "second", etc. in the specification and claims herein are used to distinguish different objects rather than to describe a specific order of the objects. For example, a first voltmeter and a second voltmeter are used to distinguish different voltmeters rather than to describe a specific order of the voltmeters.

[0046] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0047] In the description of the embodiments of the present application, unless otherwise specified, “plurality” means two or more than two. For example, a plurality of impedance data samples refers to two or more than two impedance data samples, etc.

[0048] The embodiments of the present application are described below in conjunction with the drawings in the embodiments of the present application.

[0049] Figure 1 is a flow chart of a method for measuring the impedance of human skin and subcutaneous tissue provided in an embodiment of the present application, such as Figure 1 As shown, including:

[0050] Step S101, obtaining impedance data of a human body impedance to be measured at different excitation frequencies;

[0051] Step S102, generating target curve data of impedance data of a human body impedance to be measured changing with the excitation frequency based on the impedance data at different excitation frequencies;

[0052] Step S103, using the human body impedance model to fit the target curve data, determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured; the human body impedance model is determined based on the human skin impedance and the human subcutaneous tissue impedance.

[0053] Specifically, the human body impedance to be measured described in the embodiment of the present application refers to the human body impedance formed by connecting the object to be measured through the signal probe of the measuring device, and its specific implementation process is that the measuring probe directly contacts the skin of the object to be measured.

[0054] The target curve data described in the embodiment of the present application refers to the curve data obtained when the impedance of the human body to be measured changes with the continuous change of the excitation frequency and the impedance measurement data thereof changes.

[0055] The human body impedance model described in the embodiment of the present application refers to a human body impedance model constructed based on human skin impedance and human subcutaneous tissue impedance.

[0056] In the embodiments of the present application, the human body impedance includes body surface impedance and body tissue impedance, wherein the body surface impedance is the human skin impedance, including the resistance and capacitance of the human skin epidermis; the body tissue impedance is the resistance of the human subcutaneous tissue.

[0057] Figure 2 Schematic diagram of the principle of the human body impedance model used in the human skin and subcutaneous tissue impedance measurement method provided in the embodiment of the present application, such as Figure 2 As shown in the figure, the subcutaneous tissue in the body has good conductivity and can be simulated as a pure resistor R1; the surface impedance mainly comes from the stratum corneum of the epidermis, which is equivalent to an insulating film similar to the dielectric in a capacitor, and can be regarded as a parallel connection of a pure capacitor C and a pure resistor R2. Therefore, the theoretical model of human body impedance can be approximately expressed as:

[0058]

[0059] Among them, Z represents the overall impedance of the human body; R1 represents the resistance of the human subcutaneous tissue; C and R2 represent the capacitance and resistance of the human skin epidermis respectively.

[0060] In an embodiment of the present application, in step S101, an AC voltammetry method can be used to design a circuit for measuring the overall impedance of the human body, and an AC signal source is used as an excitation voltage source. The human body impedance data is measured through a voltage divider relationship connected in series with a standard resistor, and the excitation frequency output by the signal source is continuously adjusted to expand the frequency scanning range and obtain the impedance data of the human body impedance to be measured at different excitation frequencies.

[0061] It should be noted that in the embodiments of the present application, the scanning range of the excitation frequency covers a wide band from near DC to above MHz, and the specific frequency range adopted can be 4 Hz to 0.1 MHz, including 4 Hz, 8 Hz, 16 Hz, 32 Hz, 64 Hz, 128 Hz, 256 Hz, 512 Hz, 1024 Hz, 2048 Hz, 4096 Hz, 8192 Hz, 16384 Hz, 32768 Hz, 65536 Hz, etc.

[0062] In an embodiment of the present application, in step S102, the impedance data at different excitation frequencies are used to draw a curve to generate target curve data of the impedance data of the human body impedance to be measured changing with the excitation frequency, that is, a human body impedance-frequency change curve is obtained.

[0063] Furthermore, in an embodiment of the present application, in step S103, the above-mentioned human body impedance model is used to continuously optimize and adjust the impedance parameter data in the model to fit the target curve data through a data fitting algorithm, such as a least squares method, a spline interpolation method, etc., until the curve data generated by the human body impedance model reaches the highest degree of fit with the target curve data. At this time, the optimal impedance parameter data of the model is obtained to determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured.

[0064] The human skin and subcutaneous tissue impedance measurement method of the embodiment of the present application expands the frequency scanning range, measures the impedance data of the human body impedance to be measured at different excitation frequencies, uses a large amount of measurement data to generate curve data of the human body impedance data changing with the excitation frequency, and then uses the human body impedance model constructed by the human skin impedance and human subcutaneous tissue impedance parameters to continuously fit the above curve data, and uses the parameter iterative optimization capability of the data fitting algorithm to obtain the impedance data with the highest fitting degree, thereby obtaining the human skin impedance and human subcutaneous tissue impedance of the human body impedance to be measured, and can realize the precise measurement of the human skin and subcutaneous tissue impedance, which not only improves the measurement accuracy and reliability, but also increases the richness and diversity of the measurement data, and provides more accurate technical means for clinical medicine and health monitoring.

[0065] Based on the content of the above embodiment, as an optional embodiment, step S101 includes:

[0066] Acquire the values ​​of the first voltmeter, the adjustable resistance box and the second voltmeter at different excitation frequencies measured by the data measurement module;

[0067] Determine the impedance data of the human body impedance to be measured at different excitation frequencies according to the values ​​of the first voltmeter, the adjustable resistance box and the second voltmeter at different excitation frequencies;

[0068] Among them, the data measurement module includes a sweep frequency signal source, a first voltmeter connected in parallel at both ends of the human body impedance to be measured, an adjustable resistance box and a second voltmeter connected in parallel at both ends of the adjustable resistance box; the sweep frequency signal source, the human body impedance to be measured and the adjustable resistance box are connected in series; the sweep frequency signal source is used to provide voltage signals with different excitation frequencies.

[0069] Specifically, the first voltmeter described in the embodiment of the present application refers to a precision voltmeter used to measure the voltage readings across the human body impedance to be measured.

[0070] The second voltmeter described in the embodiment of the present application refers to a precision voltmeter used to measure the voltage reading across an adjustable resistance box, wherein the adjustable resistance box can adopt a standard adjustable resistance box, which can provide precise and adjustable resistance values, and the accuracy can generally reach 0.01% or higher.

[0071] Figure 3 is a structural schematic diagram of a data measurement module in a method for measuring impedance of human skin and subcutaneous tissue provided in an embodiment of the present application, such as Figure 3 As shown, the data measurement module includes a frequency sweeping signal source, a precision voltmeter 2 connected in parallel at both ends of the human body impedance to be measured, i.e., a first voltmeter, a standard adjustable resistance box, and a precision voltmeter 1 connected in parallel at both ends of the adjustable resistance box, i.e., a second voltmeter. Among them, the frequency sweeping signal source, the human body impedance to be measured, and the adjustable resistance box are connected in series; the frequency sweeping signal source can adopt an adjustable frequency AC voltage signal source, and the output frequency is continuously adjustable, which is used to provide voltage signals with different excitation frequencies.

[0072] In the embodiments of this application, refer to Figure 3 The AC voltammetry measurement circuit structure of the data measurement module and the measurement principle of human body impedance are as follows:

[0073] The overall impedance value of the human body is measured by using the voltage division relationship in series with the standard resistor provided by the standard adjustable resistance box. The human body impedance Z to be measured can be expressed as:

[0074]

[0075] Among them, U R , U Z They respectively represent the voltage difference between the two ends of the standard adjustable resistance box (precision voltmeter 1) and the two ends of the human body impedance to be measured (precision voltmeter 2), and R represents the resistance of the standard adjustable resistance box.

[0076] It should be noted that since the excitation power supply is an AC signal, the actual measurement is the modulus value. The above formula can be further expressed as:

[0077]

[0078] Therefore, by adjusting the output frequency of the swept signal source, changing the output frequency of the excitation signal source from close to DC to above MHz, and repeating the above measurement method, the values ​​of the first voltmeter, adjustable resistance box and second voltmeter at different excitation frequencies measured by the data measurement module can be obtained.

[0079] Furthermore, in an embodiment of the present application, by using the values ​​of the first voltmeter, the adjustable resistance box and the second voltmeter at different excitation frequencies and substituting them into the calculation formula of the human body impedance to be measured, the impedance data |Z| of the human body impedance Z to be measured at different excitation frequencies can be calculated.

[0080] The method of the embodiment of the present application, by designing the aforementioned AC voltammetry measurement circuit to construct a data measurement module, can effectively improve the accuracy of impedance data measurement under different excitation frequencies, has the advantages of simple structure, easy operation, high data accuracy, etc., and is beneficial to improving the accuracy of subsequent human skin impedance and human subcutaneous tissue impedance measurements.

[0081] Based on the content of the above embodiment, as an optional embodiment, step S103 includes:

[0082] Using the Monte Carlo method, a plurality of impedance data samples are randomly generated; each impedance data sample includes human skin impedance and human subcutaneous tissue impedance; human skin impedance includes skin resistance and skin capacitance, and human subcutaneous tissue impedance includes subcutaneous tissue resistance;

[0083] Based on the human body impedance model, determining the impedance prediction data of each impedance data sample at different excitation frequencies;

[0084] The target curve data is fitted based on the impedance prediction data under different excitation frequencies to determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured.

[0085] Specifically, the impedance prediction data described in the embodiment of the present application refers to the impedance data obtained by substituting the data of the impedance data sample into the human body impedance model, which is the prediction data given by the theoretical model.

[0086] In an embodiment of the present application, based on the unique advantages in dealing with complex systems, multidimensional problems and continuity problems, the Monte Carlo method is used to randomly generate multiple impedance data samples, wherein each impedance data sample includes three parameters: skin resistance, skin capacitance and subcutaneous tissue resistance.

[0087] Further, in the embodiment of the present application, by substituting the three types of parameter data in each impedance data sample into the aforementioned human body impedance model, the impedance prediction data of each impedance data sample at different excitation frequencies can be obtained. Then, according to the impedance prediction data of each impedance data sample at different excitation frequencies, the corresponding impedance data in the target curve data can be fitted one by one, and then through iterative calculation, a group of impedance data samples with the highest fitting degree can be determined, and the human skin resistance, skin capacitance and subcutaneous tissue resistance of the human body impedance to be measured can be obtained therefrom.

[0088] The method of the embodiment of the present application, by utilizing the Monte Carlo method to optimize sample parameters, and optimizing and selecting human body impedance parameters through a data fitting algorithm, enables the measured data to be fitted with the theoretical model data, thereby effectively improving the accuracy of the measurement results of human skin impedance and human subcutaneous tissue impedance, and improving the accuracy of human body impedance measurement.

[0089] Based on the content of the above embodiment, as an optional embodiment, the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured are determined based on the impedance prediction data at different excitation frequencies to fit the target curve data, including:

[0090] Based on the impedance prediction data at different excitation frequencies, generate impedance prediction curve data corresponding to each impedance data sample;

[0091] The least square method is used to fit each impedance prediction curve data and the target curve data to determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured.

[0092] It should be noted that traditional impedance measurement data processing methods usually rely on simple linear or polynomial fitting, which often cannot accurately fit the actual data when processing complex bioimpedance models. Since the electrical characteristics of human biological tissues are highly nonlinear and complex, simple fitting methods are difficult to accurately reflect their changing patterns, resulting in large errors in measurement results, affecting the accuracy of diagnosis and monitoring.

[0093] It should also be noted that the least squares method can provide a relatively stable and reliable fitting result for most data sets, especially when the number of data points is large enough. It finds the best function matching the data by minimizing the sum of squared errors. In curve fitting, the least squares method is widely used to determine the best function model for a set of data points, and can be easily extended to multidimensional data fitting and multi-parameter models, which is very useful for complex data structures and high-dimensional data analysis.

[0094] Specifically, in an embodiment of the present application, a curve is first drawn according to the impedance prediction data at different excitation frequencies, thereby generating impedance prediction curve data corresponding to each impedance data sample in a coordinate system with impedance data and excitation frequency as coordinate axes.

[0095] Furthermore, in an embodiment of the present application, the impedance prediction curve data and the target curve data corresponding to each impedance data sample are fitted using the least squares method to determine the human body impedance data at which the curve data reaches the highest degree of fit, and then the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured can be obtained.

[0096] Figure 4 is a schematic diagram of the result of data fitting in the human skin and subcutaneous tissue impedance measurement method provided in the embodiment of the present application, such as Figure 4 As shown, it shows the impedance prediction curve data corresponding to a certain impedance data sample, that is, the theoretical fitting curve, which is fitted with the measured impedance data in the target curve data. Among them, by substituting the data of parameters R1, C and R2 in the impedance data sample and the data of different excitation frequencies into the human body impedance model, the corresponding impedance prediction curve data can be generated, that is, the corresponding theoretical fitting curve is obtained.

[0097] The method of the embodiment of the present application generates impedance prediction curve data corresponding to different impedance data samples by utilizing the human body impedance theoretical model, and uses the least squares algorithm to fit the impedance prediction curve data with the actually measured target curve data, thereby ensuring that the actually measured impedance curve data and the theoretical curve data are optimally matched, and can further improve the accuracy and reliability of the measurement results of human skin impedance and human subcutaneous tissue impedance.

[0098] Based on the content of the above embodiment, as an optional embodiment, the least square method is used to fit each impedance prediction curve data and the target curve data to determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured, including:

[0099] Taking the minimum sum of square errors between the impedance prediction data and the corresponding impedance data in the target curve data as the goal, the impedance prediction curve data with the highest matching degree with the target curve data is determined from each impedance prediction curve data;

[0100] Based on the impedance prediction curve data with the highest matching degree, determining the corresponding target impedance data sample from each impedance data sample;

[0101] According to the target impedance data sample, the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured are obtained.

[0102] Specifically, in the embodiment of the present application, based on the theoretical model of human body impedance, the measured data of human body impedance modulus and the human body impedance model are fitted by the least square method, specifically aiming at minimizing the sum of squares of errors between the impedance prediction data and the corresponding impedance data in the target curve data, so that the following value is minimized, which can be expressed as:

[0103]

[0104] Where i represents the sampling point number; N represents the total number of sampling points; f represents the excitation frequency corresponding to the sampling point; |Z(f) i | represents the measured human body impedance modulus, that is, the corresponding impedance data in the target curve data; |Z(f,R1,R2,C)| represents the theoretical impedance modulus under the parameters (R1,R2,C) of the impedance data sample, that is, the impedance prediction data.

[0105] Therefore, based on the above calculation target, the sum of square errors corresponding to each impedance prediction curve data can be calculated according to the impedance prediction data in each impedance prediction curve data and the impedance data in the target curve data under the same excitation frequency, and then the impedance prediction curve data corresponding to the minimum sum of square errors can be determined, that is, the impedance prediction curve data with the highest matching degree with the target curve data can be obtained.

[0106] Further, in an embodiment of the present application, based on the impedance prediction curve data with the highest matching degree, a target impedance data sample corresponding to the impedance prediction curve data can be determined from each impedance data sample. In other words, the impedance prediction curve data at different excitation frequencies obtained by substituting the target impedance data sample into the human body impedance model has the highest matching degree with the target curve data.

[0107] Furthermore, in an embodiment of the present application, human body impedance parameter data may be determined according to the target impedance data sample, thereby obtaining human skin resistance, skin capacitance and subcutaneous tissue resistance of the human body impedance to be measured.

[0108] The method of the embodiment of the present application, by using the least squares algorithm for fitting, takes the minimum sum of square errors between the impedance prediction data and the corresponding impedance data in the target curve data as the goal, calculates the matching degree between each impedance prediction curve data and the target curve data, finds the impedance prediction curve data with the highest matching degree, ensures that the measured impedance curve data and the theoretical curve data achieve the best match, and can further improve the measurement accuracy of human skin impedance and human subcutaneous tissue impedance.

[0109] Based on the content of the above embodiment, as an optional embodiment, after step S103, the method further includes:

[0110] Repeating steps S101 to S103 according to a preset number of measurements to obtain the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured for multiple times;

[0111] The human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured obtained by multiple measurements are averaged to obtain the target human skin impedance and the target human subcutaneous tissue impedance of the human body impedance to be measured.

[0112] Specifically, the preset number of measurements described in the embodiment of the present application refers to the preset number of repeated measurements for human body impedance measurement, which can be set according to the actual measurement accuracy requirements, such as repeated measurements 7 times, 8 times, etc., and the present application does not make specific restrictions on this.

[0113] In the embodiment of the application, the process of the aforementioned steps S101 to S103 is repeatedly executed, and a measurement result can be obtained each time a repeated measurement is performed. Therefore, after repeated measurements are performed according to a preset number of measurements, the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured can be obtained for multiple measurements.

[0114] In the embodiment of the application, the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured obtained by multiple measurements are averaged, that is, the human skin impedance data obtained by multiple measurements are averaged to obtain the target human skin impedance of the human body impedance to be measured; and the human subcutaneous tissue impedance data obtained by multiple measurements are averaged to obtain the target human subcutaneous tissue impedance.

[0115] The method of the embodiment of the present application, by adopting a repeated measurement method, averages multiple measurement results as the final measurement result of human body impedance, which can further improve the accuracy and reliability of the measurement results of human skin impedance and human subcutaneous tissue impedance.

[0116] Compared with the prior art, this application has been improved in many aspects. For example, through a wider frequency scan and more accurate data fitting, the problems of insufficient measurement accuracy and lack of data diversity in traditional technologies are solved. In particular, this application can independently measure the impedance characteristics of different biological tissue layers, such as skin impedance and subcutaneous tissue impedance. These improvements make the application prospects of impedance measurement technology in clinical medicine broader and can better serve precision medicine and personalized health management.

[0117] The human skin and subcutaneous tissue impedance measuring device provided by the present invention is described below. The human skin and subcutaneous tissue impedance measuring device described below and the human skin and subcutaneous tissue impedance measuring method described above can be referenced to each other.

[0118] Figure 5is a schematic diagram of the structure of a human skin and subcutaneous tissue impedance measuring device provided in an embodiment of the present application, such as Figure 5 As shown, including:

[0119] A data acquisition module 510 is used to acquire impedance data of a human body impedance to be measured at different excitation frequencies;

[0120] The curve generating module 520 is used to generate target curve data of the impedance data of the human body impedance to be measured changing with the excitation frequency based on the impedance data at different excitation frequencies;

[0121] The data processing module 530 is used to fit the target curve data using the human body impedance model to determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured; the human body impedance model is determined based on the human skin impedance and the human subcutaneous tissue impedance.

[0122] It is understandable that the detailed functional implementation of each of the above modules can be found in the introduction of the aforementioned method embodiment, and will not be repeated here.

[0123] It should be understood that the above-mentioned device is used to execute the method in the above-mentioned embodiment. The implementation principle and technical effect of the corresponding program module in the device are similar to those described in the above-mentioned method. The working process of the device can refer to the corresponding process in the above-mentioned method, which will not be repeated here.

[0124] The human skin and subcutaneous tissue impedance measuring device of the embodiment of the present application measures the impedance data of the human body impedance to be measured at different excitation frequencies by extending the frequency scanning range, and uses a large amount of measurement data to generate curve data of the human body impedance data changing with the excitation frequency, and then uses the human body impedance model constructed by the human skin impedance and human subcutaneous tissue impedance parameters to continuously fit the above curve data, and obtains the impedance data with the highest fitting degree with the help of the parameter iterative optimization capability of the data fitting algorithm, thereby obtaining the human skin impedance and human subcutaneous tissue impedance of the human body impedance to be measured, and can realize independent and precise measurement of the human skin and subcutaneous tissue impedance, which not only improves the measurement accuracy and reliability, but also increases the richness and diversity of the measurement data, and provides more accurate technical means for clinical medicine and health monitoring.

[0125] Based on the method in the above embodiment, the embodiment of the present application provides an electronic device, such as Figure 6As shown, the electronic device may include: a processor (Processor) 610, a communication interface (CommunicationsInterface) 620, a memory (Memory) 630 and a communication bus 640, wherein the processor 610, the communication interface 620, and the memory 630 communicate with each other through the communication bus 640. The processor 610 may call the logic instructions in the memory 630 to execute the method in the above embodiment.

[0126] In addition, the logic instructions in the above-mentioned memory 630 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application.

[0127] Based on the method in the above embodiment, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method in the above embodiment.

[0128] Based on the method in the above embodiment, an embodiment of the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the method in the above embodiment.

[0129] It is understandable that the processor in the embodiment of the present application may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0130] The method steps in the embodiments of the present application can be implemented by hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, and the software modules can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, mobile hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC.

[0131] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions may be transmitted from a website site, a computer, a server or a data center to another website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)), etc.

[0132] It should be understood that the various numerical numbers involved in the embodiments of the present application are only used for the convenience of description and are not used to limit the scope of the embodiments of the present application.

[0133] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for measuring the impedance of human skin and subcutaneous tissue, characterized in that: include: Step S101, obtaining impedance data of a human body impedance to be measured at different excitation frequencies; Step S102, generating target curve data of the impedance data of the human body impedance to be measured changing with the excitation frequency based on the impedance data at different excitation frequencies; Step S103, fitting the target curve data using a human body impedance model to determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured; The human body impedance model is determined based on human skin impedance and human subcutaneous tissue impedance.

2. The method for measuring human skin and subcutaneous tissue impedance according to claim 1, characterized in that: The step S101 includes: Acquire the values ​​of the first voltmeter, the adjustable resistance box and the second voltmeter at the different excitation frequencies measured by the data measurement module; Determine the impedance data of the human body impedance to be measured at the different excitation frequencies according to the values ​​of the first voltmeter, the adjustable resistance box and the second voltmeter at the different excitation frequencies; Among them, the data measurement module includes a sweep frequency signal source, a first voltmeter connected in parallel at both ends of the human body impedance to be measured, the adjustable resistance box and a second voltmeter connected in parallel at both ends of the adjustable resistance box; the sweep frequency signal source, the human body impedance to be measured and the adjustable resistance box are connected in series; the sweep frequency signal source is used to provide voltage signals with different excitation frequencies.

3. The method for measuring human skin and subcutaneous tissue impedance according to claim 1, characterized in that: The step S103 includes: Using the Monte Carlo method, a plurality of impedance data samples are randomly generated; each of the impedance data samples includes human skin impedance and human subcutaneous tissue impedance; the human skin impedance includes skin resistance and skin capacitance, and the human subcutaneous tissue impedance includes subcutaneous tissue resistance; Based on the human body impedance model, determining impedance prediction data of each impedance data sample at the different excitation frequencies; The target curve data is fitted based on the impedance prediction data under the different excitation frequencies to determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured.

4. The method for measuring human skin and subcutaneous tissue impedance according to claim 3, characterized in that: The step of fitting the target curve data based on the impedance prediction data at different excitation frequencies to determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured includes: Based on the impedance prediction data at the different excitation frequencies, generating impedance prediction curve data corresponding to each of the impedance data samples; The impedance prediction curve data and the target curve data are fitted by using the least square method to determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured.

5. The method for measuring human skin and subcutaneous tissue impedance according to claim 4, characterized in that: The method of fitting each of the impedance prediction curve data and the target curve data using the least square method to determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured includes: Taking the minimum sum of squares of errors between the impedance prediction data and the corresponding impedance data in the target curve data as the goal, determining the impedance prediction curve data with the highest matching degree with the target curve data from each of the impedance prediction curve data; Based on the impedance prediction curve data with the highest matching degree, determining a corresponding target impedance data sample from each of the impedance data samples; According to the target impedance data sample, the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured are obtained.

6. The method for measuring human skin and subcutaneous tissue impedance according to any one of claims 1 to 5, characterized in that: After step S103, the method further includes: Repeating steps S101 to S103 according to a preset number of measurements to obtain the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured for multiple times; The human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured obtained by multiple measurements are averaged to obtain the target human skin impedance and the target human subcutaneous tissue impedance of the human body impedance to be measured.

7. A human skin and subcutaneous tissue impedance measuring device, characterized in that: include: A data acquisition module, used to acquire impedance data of a human body impedance to be measured at different excitation frequencies; A curve generating module, for generating target curve data of the impedance data of the human body impedance to be measured changing with the excitation frequency based on the impedance data at different excitation frequencies; A data processing module, used for fitting the target curve data using a human body impedance model to determine the human skin impedance and the human subcutaneous tissue impedance of the human body impedance to be measured; The human body impedance model is determined based on human skin impedance and human subcutaneous tissue impedance.

8. An electronic device, characterized in that: include: at least one memory for storing a computer program; At least one processor is used to execute the program stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method according to any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program runs on a processor, the processor is caused to execute the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that When the computer program product runs on a processor, the processor is caused to execute the method according to any one of claims 1 to 6.

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