Human body self-adaptive micro-current stimulation method and system

Abstract

The invention relates to a human body self-adaptive micro-current stimulation method and system.The electrode points of the human body self-adaptive micro-current stimulation system are arranged in an array mode on a two-dimensional structure, the corresponding electrode points are controlled to output multi-frequency micro-current detection signals to all detected areas according to a preset point scanning mode, and cell response data are collected; performing feature extraction on the cell response data, and constructing a response state model of the detected area; acquiring a macroscopic model library and a microscopic model library, performing primary comparison on the response state model and the macroscopic model library, and determining personalized stimulation parameters according to a primary comparison result; performing secondary comparison on the response state model and the microscopic model library, and determining an optimal stimulation electrode combination according to a secondary comparison result; and generating an optimal treatment scheme according to the optimal stimulation electrode combination and the personalized stimulation parameters, and performing electrical stimulation on a target stimulation part of the treatment object through an electrode stimulation module.

Description

Technical Field

[0001] This application relates to the field of electrical stimulation technology, and in particular to a method and system for human body adaptive microcurrent stimulation. Background Technology

[0002] A human stimulation system is a medical device or technology that uses electricity, magnetism, light, sound, or other physical energy to act on human tissues or the nervous system to regulate physiological functions or treat diseases. Its core principle is to use external energy to stimulate the target area, triggering bioelectrical activity or physiological response, thereby achieving the purpose of treatment, rehabilitation, functional enhancement, or scientific research.

[0003] Current human electrical stimulation systems mostly rely on fixed parameters or manual intervention for adjustment, lacking dynamic adaptive capabilities. During use, doctors or operators must manually adjust stimulation parameters based on the user's subjective feedback. This adjustment method is not only inefficient but also makes it difficult to achieve precise treatment. Furthermore, existing electrical stimulation systems use static or semi-static adjustment modes, which cannot adapt to different individuals, different tissues, and dynamic changes during treatment. Current stimulation methods also do not consider multifaceted vital sign data, making it impossible for the system to comprehensively evaluate and optimize stimulation parameters. These limitations restrict the application of electrical stimulation systems in precision medicine, especially in scenarios requiring high-frequency dynamic adjustment (such as neurorehabilitation and pain management). Summary of the Invention

[0004] This application provides a human body adaptive microcurrent stimulation method and system to at least solve the problem that existing human body stimulation systems in related technologies cannot perform adaptive adjustment.

[0005] In a first aspect, embodiments of this application provide a human body adaptive microcurrent stimulation method, applied in a human body adaptive electrical stimulation system. The human body adaptive electrical stimulation system includes multiple electrode stimulation modules, which are fixed to different test areas of the treatment subject. The electrode points in the electrode stimulation modules are arranged in an array on a two-dimensional structure. The method includes: According to the preset point sweeping method, the corresponding electrode points are controlled to output multi-frequency microcurrent detection signals to each test area, and the cell response data of the test area are collected in real time. Feature extraction is performed on the cell response data to obtain a feature data sequence, and a response state model of the tested region is constructed based on the feature data sequence. Obtain a macroscopic model library and a microscopic model library; compare the response state model with the macroscopic model library once, and determine personalized stimulation parameters based on the comparison results; then compare the response state model with the microscopic model library a second time, and determine the optimal combination of stimulation electrodes based on the comparison results. The optimal treatment plan is generated based on the optimal combination of stimulation electrodes and the personalized stimulation parameters, and the target stimulation site of the treatment subject is electrically stimulated through the electrode stimulation module.

[0006] Specifically, the point scanning method includes a macroscopic scanning method for preliminary identification and a microscopic scanning method for precise positioning. The step of controlling the corresponding electrode points to output multi-frequency microcurrent detection signals to the treatment object according to the preset point scanning method includes: A first microcurrent detection signal modulated by the fundamental frequency is acquired. The electrode points are activated in a row or column as a unit, and all electrode points are quickly scanned according to the macroscopic scanning method to output the first microcurrent detection signal to the treatment object. Based on the results of macroscopic scanning, candidate electrode sites with strong stimulated responses in multiple rows or columns are obtained. A second microcurrent detection signal modulated by the modulation envelope frequency is acquired, and a preset number of adjacent candidate electrode points are activated sequentially according to a time sequence. All candidate electrode points are then rapidly scanned according to the microscopic scanning method to output the second microcurrent detection signal to the treatment object.

[0007] Specifically, the feature data sequence includes time and cellular response values; constructing the response state model of the treatment subject based on the feature data sequence includes: The response state model is obtained by performing linear fitting with time as the horizontal axis and cell response value as the vertical axis.

[0008] Specifically, the macroscopic model library contains standard tissue models of various types of human tissue structures. The step of comparing the response state model with the macroscopic model library and determining personalized stimulus parameters based on the comparison result includes: The similarity between the response state model and each tissue standard model in the macroscopic model library is calculated, and the tissue structure type of the treatment object is determined based on the tissue standard model with the highest similarity. Obtain the medical record information of the treatment subject, select the optimal stimulation current and optimal stimulation frequency based on the tissue structure type and the medical record information, and generate the personalized stimulation parameters.

[0009] Specifically, the microscopic model library contains standard models of various subdivided parts of tissue structures. The step of performing a secondary comparison between the response state model and the microscopic model library, and determining the optimal combination of stimulation electrodes based on the secondary comparison results, includes: The similarity between the response state model and the standard models of each part in the macroscopic model library is calculated, and the effective range of cell response values ​​is determined based on the standard model of the part with the highest similarity. By traversing all data in the response state model, the time periods falling within the range of the cell response values ​​are selected. The activated electrode sites and activation order within the time periods are recorded as the optimal stimulation electrode and the optimal stimulation path, respectively, to obtain the optimal stimulation electrode combination.

[0010] Specifically, generating the optimal treatment plan based on the optimal combination of stimulation electrodes and the personalized stimulation parameters includes: The personalized stimulation parameters are modulated into a microcurrent stimulation waveform; The microcurrent stimulation waveform is applied to the target stimulation site according to the optimal combination of stimulation electrodes.

[0011] Specifically, during the process of electrically stimulating the target stimulation site of the treatment subject, the method further includes: Continuously monitor the cellular response at the target stimulation site and obtain the latest cellular response data; Based on the latest cell response data, the latest personalized stimulation parameters and optimal stimulation electrode combination are re-acquired; The optimal treatment plan is dynamically adjusted based on the latest personalized stimulation parameters and the best combination of stimulation electrodes until the electrical stimulation is stopped when the termination condition is triggered.

[0012] Secondly, this application provides a human adaptive microcurrent stimulation system for implementing the human adaptive microcurrent stimulation method as described in any of the preceding claims, the system comprising: The data acquisition system is used to control the corresponding electrode points to output multi-frequency microcurrent detection signals to each test area according to the preset point sweeping method, and to collect the cell response data of the test area in real time. The central processing unit is used to extract features from the cell response data to obtain feature data sequences, and construct a response state model of the tested region based on the feature data sequences; it also acquires a macroscopic model library and a microscopic model library, compares the response state model with the macroscopic model library once, and determines personalized stimulation parameters based on the comparison results; and compares the response state model with the microscopic model library a second time, and determines the optimal combination of stimulation electrodes based on the comparison results. A carrier generator, connected to the central processing unit and the data acquisition system, is used to generate an optimal treatment plan based on the optimal combination of stimulation electrodes output by the central processing unit and the personalized stimulation parameters, and to perform electrical stimulation on the target stimulation site of the treatment subject through the electrode stimulation module. The carrier generator generates a fundamental electrical signal of 100Hz-200kHz and a carrier electrical signal with a frequency range of 1Hz-200Hz. The magnitude of the stimulation current is controlled by dynamically modulating the current amplitude of the fundamental and carrier electrical signals. When the carrier electrical signal is an alternating current stimulation signal, the portion of the carrier electrical signal waveform defining the positive polarity has a larger amplitude and a shorter duration than the portion defining the reverse polarity. By adjusting the duty cycle and current amplitude ratio of the carrier electrical signal, a difference in amplitude exists between the portions defining the positive and reverse polarities, and each corresponding integral pair of the current amplitude is equal between consecutive time instances of alternating polarities in the carrier electrical signal waveform.

[0013] Specifically, the data acquisition system includes: Multiple electrode stimulation modules include multiple electrode points arranged in an array in a two-dimensional structure to form an electrical connection with the measured area of ​​the treatment object. The electrode points are dynamically switched to form different measurement and stimulation circuits. The data measurement module, connected to the electrode stimulation module, is used to generate multi-frequency microcurrent detection signals and measure the cell response data of the tested area.

[0014] Specifically, the central processing unit includes: The macroscopic sampling module is used to iterate and calculate the similarity between the response state model and each tissue standard model in the macroscopic model library, and determine the tissue structure type of the treatment object based on the tissue standard model with the highest similarity; obtain the medical record information of the treatment object, select the optimal stimulation current and optimal stimulation frequency based on the tissue structure type and the medical record information, and generate the personalized stimulation parameters.

[0015] The microscopic sampling module is used to traverse and calculate the similarity between the response state model and the standard models of each part in the macroscopic model library, and determine the effective range of cell response values ​​based on the standard model of the part with the highest similarity; it traverses all data in the response state model, filters out the time period that falls within the range of cell response values, and records the activated electrode points and activation order within the time period as the optimal stimulation electrode and the optimal stimulation path, respectively, to obtain the optimal stimulation electrode combination.

[0016] The human body adaptive microcurrent stimulation method and system provided in this application have at least the following technical effects: This application utilizes a multi-electrode array combined with macroscopic and microscopic scanning modes to actively and accurately sense the electrophysiological characteristics of human tissues and dynamically construct personalized response state models based on this. Furthermore, by employing a dual comparison mechanism between macroscopic and microscopic models, the system can not only identify tissue types but also precisely locate the optimal stimulation target and assess safety in real time. Finally, stimulation parameters are dynamically generated and adjusted based on this intelligent decision-making result. This application can automatically adapt to changes in the physiological state of different users, different parts of the same user, and the same part at different times, completely changing the traditional model that relies on human experience to preset fixed parameters. It fundamentally solves the core defects of poor stimulation effect and difficulty in ensuring safety caused by individual differences and dynamic changes in tissue state, achieving an adaptive leap from "one parameter for a thousand people" to "one parameter for a thousand people, one parameter for a single moment."

[0017] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0018] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart of a human adaptive microcurrent stimulation method in one embodiment of this application; Figure 2 This is a schematic diagram of the electrode point arrangement of the electrode stimulation module in one embodiment of this application; Figure 3 yes Figure 2 A schematic diagram of the macroscopic scanning method of the electrode stimulation module; Figure 4 yes Figure 2 Schematic diagram of the microscopic scanning method of the electrode stimulation module; Figure 5 This is a flowchart illustrating the first and second comparison processes in one embodiment of this application; Figure 6 This is a structural block diagram of a human adaptive microcurrent stimulation system according to an embodiment of this application; Figure 7 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the application is described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.

[0020] Obviously, the accompanying drawings described below are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar scenarios based on these drawings without any inventive effort. Furthermore, it is understood that although the efforts made in this development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, any changes to design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as insufficient disclosure of the content of this application.

[0021] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that is mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0022] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following objects are in an "or" relationship. The terms "first," "second," and "third" used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0023] Most existing technologies rely on manual intervention, which involves doctors or operators asking about the user's experience and then adjusting parameters. Since dynamic parameter adjustment is not possible, self-testing and self-correction cannot be achieved, thus preventing precise adaptive treatment based on different subjects, tissues, and treatment processes.

[0024] Based on the above, embodiments of this application provide a human body adaptive microcurrent stimulation method and system.

[0025] In a first aspect, embodiments of this application provide a human body adaptive microcurrent stimulation method, which is applied in a human body adaptive electrical stimulation system. The human body adaptive electrical stimulation system includes multiple electrode stimulation modules, which are fixed in different test areas of the treatment object. The electrode points in the electrode stimulation modules are arranged in an array on a two-dimensional structure. Figure 1 This is a flowchart of the stimulation method, such as... Figure 1 As shown, the human body adaptive microcurrent stimulation method of this application is implemented by the following steps.

[0026] Step S1: Control the corresponding electrode points to output multi-frequency microcurrent detection signals to each test area according to the preset point sweeping mode, and collect the cell response data of the test area in real time. In this embodiment, the point sweeping mode includes a macroscopic scanning mode for preliminary identification and a microscopic scanning mode for precise positioning.

[0027] Specifically, a first microcurrent detection signal modulated by the fundamental frequency is acquired. The electrode points are activated in rows or columns as a unit, and all electrode points are rapidly scanned according to the macroscopic scanning method to output the first microcurrent detection signal to the treatment subject. Based on the macroscopic scanning results, multiple rows or columns of candidate electrode points with strong stimulation responses are acquired. A second microcurrent detection signal modulated by the modulation envelope frequency is acquired, and a preset number of adjacent candidate electrode points are activated sequentially according to the time sequence. All candidate electrode points are rapidly scanned according to the microscopic scanning method to output the second microcurrent detection signal to the treatment subject.

[0028] In a preferred embodiment, the arrangement of the electrode points is referenced. Figure 2 In this embodiment, after the arrangement of the electrodes attached to human tissue is topologically classified into a two-dimensional structure, it is assumed that there are A electrodes in the X direction and B electrodes in the Y direction.

[0029] In this embodiment, the macroscopic scanning method is a rapid array sweeping of electrodes, referencing... Figure 3 At time t0, electrodes Y1-Y3 are activated as the first set of sampling electrodes, and at time t1, electrodes Y2-Y4 are activated as the second set of sampling electrodes. The advantage of this scheme is its high sampling efficiency, facilitating analysis and judgment of the tested tissue's response to stimulation currents of different frequencies from a macroscopic model perspective. It also facilitates the analysis of macroscopic physiological states, body fat percentage, muscle density, water content, and neural response speed. The disadvantage is the low pixel count of the sampling results, which is not conducive to targeted stimulation at specific points (N-choose-2 or N-choose-3).

[0030] The microscopic scanning method involves sequentially scanning a small number of electrodes, i.e., pre-setting a sliding window and moving forward one window at a time, as shown in the reference. Figure 4 A horizontal sweep is performed from Y0 to YB, and at any given moment, only three horizontal electrodes are selected as a group to sequentially activate and form a current loop for sampling. For example... Figure 4 As shown, at time t0, the first group of 3 electrodes in row Y0 is activated for sampling, and at time t1, the sampling is switched to the second group of 3 electrodes in row Y0. Since all electrodes in row Y0 have been sampled, the sampling is switched to the electrodes in row Y1. Figure 4 The timing method used is only one embodiment of this patent and is not limited to this method. The number of electrodes selected can be adjusted according to needs. The advantage of the microscopic scanning method is that the sampling is highly targeted and the data points are abundant, which is more conducive to in-depth analysis, but the efficiency is low and it is more time-consuming.

[0031] Step S2 involves extracting features from the cell response data to obtain a feature data sequence, and then constructing a response state model of the tested region based on the feature data sequence. In this embodiment, a linear fit is performed with time as the horizontal axis and the cell response value as the vertical axis to obtain the response state model. Specifically, taking the frequency response model in the macroscopic model as an example, a response state model of the tested tissue to different frequencies is established. The horizontal input variables are the fundamental frequency of different stimulation currents or the modulation envelope frequency of the stimulation current, and the vertical output results are the cell response status (such as changes in electrical properties (impedance), ion channel activation, changes in metabolic activity, etc.).

[0032] Step S3: Obtain the macroscopic model library and the microscopic model library; compare the response state model with the macroscopic model library once, and determine the personalized stimulation parameters based on the comparison results; and compare the response state model with the microscopic model library a second time, and determine the optimal stimulation electrode combination based on the comparison results.

[0033] Specifically, the macroscopic model library contains standard tissue models of various types of human tissue structures. During the macroscopic comparison process, the similarity between the response state model and each standard tissue model in the macroscopic model library is calculated. The tissue structure type of the treatment object is determined based on the standard tissue model with the highest similarity. The medical record information of the treatment object is obtained. The optimal stimulation current and optimal stimulation frequency are selected based on the tissue structure type and the medical record information to generate the personalized stimulation parameters.

[0034] The microscopic model library contains standard models of various subdivided parts of tissue structures. During the microscopic comparison process, the similarity between the response state model and the standard models of each part in the macroscopic model library is calculated, and the effective range of cell response values ​​is determined based on the standard model of the part with the highest similarity. All data in the response state model are traversed, and time periods falling within the range of cell response values ​​are selected. The activated electrode sites and activation order within the time period are recorded as the optimal stimulation electrode and the optimal stimulation path, respectively, to obtain the optimal combination of stimulation electrodes.

[0035] In this embodiment, the cell response model first compares the cell response in the fundamental frequency detection results to identify similar objects (a certain human tissue being tested), thereby determining the effective fundamental frequency range of the tested tissue. Then, it compares the cell response under different modulation envelope frequencies to more accurately determine and generate the stimulation waveform of the input current to be used during treatment.

[0036] In a preferred embodiment, a comparison reference is provided between the macroscopic model and the microscopic model. Figure 5First, a macroscopic model is compared to determine the physiological condition of the tissue being tested. Based on the macroscopic model, a microscopic model is then compared to determine the specific electrode combination and the optimal stimulation pathway.

[0037] For macroscopic models, the main parameter for comparison is the overall electrical impedance of the tested human tissue. For example, data in the model library shows that the electrode impedance of the brain is between 200-500 ohms and the rate of change decreases linearly with increasing frequency. If the macroscopic model we measure shows a significant similarity to this data, then the tested tissue is identified as a region of the human body. However, the patent is not limited to measuring impedance. Similarly, for microscopic models, because the electrode measurement scanning method involves a small number of sequential electrode scans, it is possible to determine what a specific region in the overall tissue is, such as whether it is the temple or the forehead, which are brain tissue regions.

[0038] In summary, this approach first uses macroscopic model comparison to determine whether the overall impedance and rate of change of the tested human tissue are similar to existing data in the model library. If the similarity reaches 95%, it is concluded that the tested tissue is a specific human tissue from the model library. Next, microscopic model comparison is performed to determine the positional relationship between the tested human tissue and specific electrodes; for example, the Y2-Y4 electrode row covers the forehead area, and the Y5-Y6 electrode row covers the temples. This allows for the determination of which specific electrode combination should be selected to release the stimulating current.

[0039] Continue to refer to Figure 5 This embodiment first analyzes basic macroscopic parameters such as body fat percentage, muscle density, and overall impedance. Then, it selects a macroscopic electrode array to output a uniform frequency to detect the cell excitation state (i.e., current intensity) in the measured area at different times, obtaining a primary optimal electrode combination for activating electrodes from time tA to tB. Next, a small number of electrodes from the primary optimal electrode combination are selected for microscopic electrode array detection, again obtaining a secondary optimal electrode combination based on the cell excitation state. This process is repeated, or the optimal electrode combination for outputting the stimulation current is finally determined according to treatment needs.

[0040] When cells in the tested tissue area are stimulated by a current of the same frequency, different areas of the cells will exhibit different current intensities, indicating different impedances. The rate of impedance change in the tested area can then be obtained by applying currents of different frequencies. Based on treatment needs, areas with impedance and rate of change similar to the control model, and covered by a small number of electrodes, are selected for testing.

[0041] Step S4: Generate an optimal treatment plan based on the optimal stimulation electrode combination and the personalized stimulation parameters, and apply electrical stimulation to the target stimulation site of the treatment subject through the electrode stimulation module. Specifically, a microcurrent stimulation waveform is modulated according to the personalized stimulation parameters; the microcurrent stimulation waveform is applied to the target stimulation site according to the optimal stimulation electrode combination.

[0042] In one specific embodiment, taking the key parameter of stimulation current intensity as an example, to avoid discomfort to the human body, it is necessary to find a suitable stimulation current intensity. For example, after comparison with a macroscopic model, if the tissue being tested is determined to be a tendon, due to its dense connective tissue composition, its resistance is relatively high. Therefore, to achieve effective treatment in this area, a higher intensity stimulation current is required. If the tissue being tested is determined to be a blood vessel or nerve, since blood vessels contain water and ions and have good conductivity, while nerves contain a large amount of electrolytes and have the lowest resistance, microcurrent stimulation must be used. This dynamic adjustment is only one of the results obtained based on the feature comparison results. In general, the appropriate intensity of stimulation current is selected according to the different human tissues.

[0043] Preferably, a big data model can be built into the device itself. The macro model library in the big data model has recorded different tissue regions of the human body. This record can be compared with the data obtained from the currently measured region to form a judgment.

[0044] Taking the fundamental frequency of the stimulation current as an example, the system can dynamically evaluate the biocompatibility and stimulation effect of the current path, ensuring the accuracy of treatment and detection. The impedance spectrum, which measures the complex impedance at different frequencies as a function of frequency f, equates human tissue to a series-parallel resistance-capacitance network model. Through curve fitting, parameters such as intracellular resistance, extracellular resistance, and membrane capacitance are obtained.

[0045] In this embodiment, the measurement range is selected according to the object being measured: extremely low frequency 1Hz-100Hz is used to measure nerve stimulation and reflective current response; low frequency 1KHz-10KHz is used to measure extracellular fluid response; and medium frequency 10KHz-200KHz is used to penetrate cells to induce nerve responses.

[0046] This application supports multi-frequency impedance measurement at multiple frequency points within the range of 1 kHz to 200 kHz. Default frequency points include 5 kHz, 10 kHz, 50 kHz, 100 kHz, and 200 kHz to extract tissue impedance characteristics at different depths and cellular response levels. 100 kHz is generally suitable for transmitting current signals that stimulate brain nerves. During the screening of stimulation currents at different frequencies, if, after comparison with a model library, it is determined that the tissue region responds significantly to a 100 kHz stimulation current at the same voltage, then the preferred modulation signal is based on the 100 kHz fundamental frequency.

[0047] In one specific embodiment, a fundamental electrical signal of 100Hz-200kHz and a carrier electrical signal with a frequency range of 1Hz-200Hz are generated by a carrier generator. The magnitude of the stimulation current is controlled by dynamically modulating the current amplitude of the fundamental electrical signal and the carrier electrical signal. When the carrier electrical signal is an alternating current stimulation signal, the portion of the carrier electrical signal waveform that defines the positive polarity has a larger amplitude and a shorter duration than the portion that defines the reverse polarity. By adjusting the duty cycle and current amplitude ratio of the carrier electrical signal, a difference in amplitude exists between the portion defining the positive polarity and the portion defining the reverse polarity. Each corresponding integral pair of the current amplitude is equal between consecutive time instances of alternating polarities in the carrier electrical signal waveform.

[0048] In a preferred embodiment, during the electrical stimulation of the target stimulation site of the treatment subject, the method of this embodiment further includes: continuously monitoring the cellular response of the target stimulation site and obtaining the latest cellular response data; re-obtaining the latest personalized stimulation parameters and the optimal stimulation electrode combination based on the latest cellular response data; dynamically adjusting the optimal treatment plan based on the latest personalized stimulation parameters and the optimal stimulation electrode combination until the electrical stimulation is stopped when the termination condition is triggered.

[0049] In summary, this application achieves a revolutionary breakthrough in human body current stimulation technology by introducing multi-mode scanning with multi-electrode arrays, dual comparison of macroscopic and microscopic models, and dynamic parameter adjustment based on real-time feedback. Specifically, firstly, a multi-frequency impedance measurement module is used to perform rapid macroscopic scanning and fine microscopic scanning of tissues to obtain rich impedance spectrum data, thereby comprehensively perceiving tissue type, structural level, and physiological state. Secondly, by intelligently comparing the extracted feature parameters with preset macroscopic physiological models and microscopic tissue models, the target stimulation site is automatically identified, the optimal stimulation electrode combination is accurately selected, and contact safety and stimulation effectiveness are evaluated in real time. Finally, personalized stimulation waveforms are dynamically generated based on the comparison results, and impedance changes are continuously monitored during treatment. The current parameters are finely adjusted in real time through a closed-loop control algorithm, or the treatment is immediately stopped in case of abnormalities. This complete technical closed loop completely overcomes the shortcomings of existing technologies that rely on fixed parameters and cannot adapt to individual differences and dynamic changes in tissues, achieving a leap from "artificial pre-setting" to "autonomous adaptation," significantly improving the safety, accuracy, and effectiveness of treatment.

[0050] Secondly, this application provides a human adaptive microcurrent stimulation system capable of implementing the human adaptive microcurrent stimulation method described in any of the above embodiments. The system in this embodiment includes: The data acquisition system is used to control the corresponding electrode points to output multi-frequency microcurrent detection signals to each test area according to the preset point sweeping method, and to collect the cell response data of the test area in real time. The central processing unit is used to extract features from the cell response data to obtain feature data sequences, and construct a response state model of the tested region based on the feature data sequences; it also acquires a macroscopic model library and a microscopic model library, compares the response state model with the macroscopic model library once, and determines personalized stimulation parameters based on the comparison results; and compares the response state model with the microscopic model library a second time, and determines the optimal combination of stimulation electrodes based on the comparison results. A carrier generator, connected to the central processing unit and the data acquisition system, is used to generate an optimal treatment plan based on the optimal combination of stimulation electrodes output by the central processing unit and the personalized stimulation parameters, and to perform electrical stimulation on the target stimulation site of the treatment subject through the electrode stimulation module. Specifically, the carrier generator is used to generate a fundamental electrical signal of 100Hz-200kHz and a carrier electrical signal with a frequency range of 1Hz-200Hz, and controls the magnitude of the stimulation current by dynamically modulating the amplitude of the fundamental wave and the carrier. When the generated carrier is an alternating current stimulation signal, the portion of the carrier waveform defining the positive polarity has a larger amplitude and a shorter duration than the portion defining the reverse polarity. The duty cycle and the current amplitude ratio are selected such that even if there is a difference in amplitude between the portion of the carrier waveform defining the positive polarity and the portion defining the reverse polarity, each corresponding integral pair of the current amplitude between consecutive time instances of the alternating polarity of the carrier waveform is substantially equal.

[0051] In a preferred embodiment, the data acquisition system includes: Multiple electrode stimulation modules include multiple electrode points arranged in an array in a two-dimensional structure to form an electrical connection with the measured area of ​​the treatment object. The electrode points are dynamically switched to form different measurement and stimulation circuits. The data measurement module, connected to the electrode stimulation module, is used to generate multi-frequency microcurrent detection signals and measure the cell response data of the tested area.

[0052] In a preferred embodiment, the central processing unit includes: The macroscopic sampling module is used to iterate and calculate the similarity between the response state model and each tissue standard model in the macroscopic model library, and determine the tissue structure type of the treatment object based on the tissue standard model with the highest similarity; obtain the medical record information of the treatment object, select the optimal stimulation current and optimal stimulation frequency based on the tissue structure type and the medical record information, and generate the personalized stimulation parameters.

[0053] The microscopic sampling module is used to traverse and calculate the similarity between the response state model and the standard models of each part in the macroscopic model library, and determine the effective range of cell response values ​​based on the standard model of the part with the highest similarity; it traverses all data in the response state model, filters out the time period that falls within the range of cell response values, and records the activated electrode points and activation order within the time period as the optimal stimulation electrode and the optimal stimulation path, respectively, to obtain the optimal stimulation electrode combination.

[0054] In one specific embodiment, reference Figure 6This embodiment of the human body adaptive microcurrent stimulation system includes at least one multi-frequency impedance measurement module. By applying microcurrent signals of different frequencies, it measures the impedance spectrum between the electrodes and human tissue. Different frequencies can reflect information about different levels of tissue structure, such as skin, skull, and brain tissue. By analyzing the impedance spectrum, the contact state and position of the electrodes can be determined more accurately.

[0055] The human electrode connection module includes a dynamic electrode array of at least three electrodes, used to transmit the multi-frequency microcurrent signal to human tissue and interact with a multi-frequency impedance measurement module to form a data acquisition system. The at least three electrodes are distributed differently depending on the human tissue, and one electrode forms a loop with at least two other electrodes. The electrode connection module is not only used for traditional impedance measurement but also supports the measurement of physiological electrical signals such as capacitance characteristics, phase angle, and directional impedance changes. It can achieve multi-path signal acquisition through time-series electrode switching, thus more accurately reflecting the electrophysiological state of the target tissue, unlike existing technologies that are limited to single-point or static impedance measurement. Capacitance characteristics are assessed by treating the cell membrane as a capacitor, and capacitance responses can describe the health status of cells. Tissue anisotropy is analyzed by automatically switching electrode directions for sampling, based on differences in conductivity, to examine the electrical conductivity of tissues such as muscles and nerves in different directions. Phase angle is determined by comparing the phase angles of electrodes arranged in multiple directions and regions to determine the phase difference between resistance and reactance. Furthermore, the dynamic electrode array selects N-to-2 or N-to-3 to measure local tissue responses, thereby determining whether the stimulation parameters are effective and dynamically adjusting the stimulation parameters.

[0056] The data acquisition system is also used to synchronize the current and voltage signals output by the human body electrode connection module and the multi-frequency impedance measurement module, and to calculate the impedance value at ordinary frequencies.

[0057] The central processing unit is used to analyze and model the impedance spectrum, extract feature parameters and compare them with microscopic or macroscopic models. Macroscopic model comparison is used to analyze parameters such as the macroscopic physiological state of the human body, body fat percentage, muscle density, water content, and nerve reaction speed. Microscopic model is used to analyze specific human tissue information at the stimulation site, the effectiveness of current stimulation, electrode connection status, and whether the input and output current magnitude and position are correct. At the same time, based on the above information, it calculates the threshold of multi-frequency impedance and alerts the user or operator to intervene.

[0058] This application extracts electrophysiological characteristic parameters by performing equivalent circuit modeling, frequency domain feature extraction, and machine learning analysis on multi-frequency impedance spectra. These parameters are then compared with pre-built macroscopic physiological models of the human body (including body fat percentage, muscle density, and water content) and microscopic tissue models (electrode connection status, local tissue type, and electrical stimulation response) to form individualized analysis results and a safety reminder mechanism.

[0059] Specifically, the central processing unit includes a macroscopic model library and a microscopic model library. The central processing unit constructs response state models (macroscopic sampling models and microscopic sampling models) based on cell response data (such as impedance spectra). Then, it performs large-scale comparisons of the macroscopic and microscopic sampling models with the macroscopic and microscopic model libraries, respectively. Based on the comparison results, it adaptively outputs stimulation current and electrode combinations (i.e., a dynamic electrode array strategy). Finally, the output results are fed back to the operation interaction system and the carrier generator. The carrier generator modulates the corresponding waveform according to the output stimulation current, and operators can also control the equipment based on the feedback results. In this embodiment, the microscopic sampling module can be obtained from the macroscopic comparison results or generated from the sampled cell response data.

[0060] The system can dynamically evaluate the biocompatibility and stimulation effect of the current path, ensuring the accuracy of treatment and detection. The complex impedance measured at different frequencies by impedance spectroscopy represents human tissue as a series-parallel resistance-capacitance network model. Through curve fitting, parameters such as intracellular resistance, extracellular resistance, and membrane capacitance are obtained. The measurement range is selected according to the object being measured: extremely low frequency 1Hz-100Hz is used to measure nerve stimulation and reflective current response; low frequency 1KHz-10KHz is used to measure extracellular fluid response; medium frequency 10KHz-200KHz is used to penetrate cells to induce nerve response.

[0061] This system supports multi-frequency impedance measurement by selecting multiple frequency points in the range of 1 kHz to 200 kHz. The default frequency points include 5 kHz, 10 kHz, 50 kHz, 100 kHz, and 200 kHz to extract tissue impedance characteristics at different depths and cellular response levels.

[0062] In this embodiment, the macroscopic model is analyzed by comparing the fitted intracellular resistance and extracellular resistance ratio. Since muscle tissue, nerve tissue, and fat have different response characteristics to different frequencies, the properties of the tested area are accurately obtained by comparing with the population impedance spectrum database. At the same time, the personalized treatment plan of this current stimulation system is determined based on the response delay, phase change rate, and frequency resonance point of the tested tissue.

[0063] The microscopic model includes: detecting the impedance values ​​between different electrode pairs at the same time; if the impedance is abnormally high, it indicates electrode detachment or abnormality; identifying whether the current path is correct through a dynamic electrode array; if the differences between different paths of multiple electrode combinations are abnormally large, the electrodes may be misplaced or cross different tissue types, making it impossible to initiate treatment; and analyzing the impedance change trend in real time within a certain time range by applying a small amount of stimulation current. If an abnormality occurs in a short period of time, such as a drop within a few seconds, it can be determined whether the tissue is abnormal due to stimulation, and the treatment should be interrupted in time. If the impedance does not change for a long time or rises abnormally, it can be determined that the treatment stimulation is ineffective or there is a local abnormality.

[0064] Thirdly, embodiments of this application provide an electronic device, Figure 7 This is a block diagram illustrating an electronic device according to an exemplary embodiment. (e.g.) Figure 7 As shown, the electronic device may include a processor 11 and a memory 12 storing computer program instructions.

[0065] Specifically, the processor 11 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0066] The memory 12 may include a large-capacity storage device for data or instructions. For example, and not limitingly, the memory 12 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), flash memory, an optical disk drive, a magneto-optical disk drive, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 12 may include removable or non-removable (or fixed) media. Where appropriate, the memory 12 may be internal or external to a data processing device. In a particular embodiment, the memory 12 is non-volatile memory. In a particular embodiment, the memory 12 includes read-only memory (ROM) and random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), an electrically alterable read-only memory (EAROM), or flash memory, or a combination of two or more of these. Where appropriate, the RAM can be Static Random-Access Memory (SRAM) or Dynamic Random-Access Memory (DRAM). DRAM can be Fast Page Mode Dynamic Random-Access Memory (FPMDRAM), Extended Data Out Dynamic Random-Access Memory (EDODRAM), Synchronous Dynamic Random-Access Memory (SDRAM), etc.

[0067] The memory 12 can be used to store or cache various data files that need to be processed and / or used for communication, as well as possible computer program instructions executed by the processor 11.

[0068] The processor 11 reads and executes computer program instructions stored in the memory 12 to implement any of the human body adaptive electrical stimulation methods in the above embodiments.

[0069] In one embodiment, the electronic device may further include a communication interface 13 and a bus 10. Wherein, as... Figure 6 As shown, the processor 11, memory 12, and communication interface 13 are connected through bus 10 and communicate with each other.

[0070] The communication interface 13 is used to enable communication between the various modules, devices, units, and / or equipment in the embodiments of this application. The communication port 13 can also enable data communication with other components such as external devices, image / data acquisition devices, databases, external storage, and image / data processing workstations.

[0071] Bus 10 includes hardware, software, or both, that couples components of an electronic device together. Bus 10 includes, but is not limited to, at least one of the following: data bus, address bus, control bus, expansion bus, and local bus. For example, and not as a limitation, bus 10 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 10 may include one or more buses. Although specific buses are described and illustrated in the embodiments of this application, this application considers any suitable bus or interconnection.

[0072] Fourthly, embodiments of this application provide a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the human adaptive electrical stimulation method provided in the first aspect.

[0073] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0074] In a possible implementation, this application may also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform steps implementing the human adaptive electrical stimulation method provided in the first aspect.

[0075] The program code for executing this application can be written in any combination of one or more programming languages. The program code can be executed entirely on the user device, partially on the user device, as a standalone software package, partially on the user device and partially on a remote device, or entirely on a remote device.

[0076] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0077] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method of human self-adapting micro-current stimulation, characterized in that, The application is applied to a human adaptive electric stimulation system, the human adaptive electric stimulation system comprises a plurality of electrode stimulation modules, the plurality of electrode stimulation modules are fixed in different measured areas of a treatment object, electrode points in the electrode stimulation modules are arranged in an array in a two-dimensional structure, and the method comprises the following steps: A preset point position sweeping mode is used to control corresponding electrode points to output multi-frequency micro-current detection signals to each measured area, and cell response data of the measured area is collected in real time; Feature extraction is performed on the cell response data to obtain a feature data sequence, and a response state model of the measured area is constructed according to the feature data sequence; A macroscopic model library and a microscopic model library are obtained, the response state model is compared with the macroscopic model library once, and individualized stimulation parameters are determined according to the comparison result; and the response state model is compared with the microscopic model library twice, and the best stimulation electrode combination is determined according to the comparison result; The best treatment scheme is generated according to the best stimulation electrode combination and the individualized stimulation parameters, and the electrode stimulation module is used to perform electric stimulation on a target stimulation site of the treatment object.

2. The method of claim 1, wherein, The point position sweeping mode comprises a macroscopic scanning mode for preliminary identification and a microscopic scanning mode for precise positioning, and the preset point position sweeping mode is used to control corresponding electrode points to output multi-frequency micro-current detection signals to the treatment object, which comprises the following steps: A first micro-current detection signal modulated by a fundamental frequency is obtained, the electrode points are activated in a whole row or a whole column as a unit, and all electrode points are rapidly swept according to the macroscopic scanning mode to output the first micro-current detection signal to the treatment object; Based on the result of macroscopic scanning, candidate electrode points with strong excited reaction in multiple rows or multiple columns are obtained; A second micro-current detection signal modulated by a modulated envelope frequency is obtained, a preset number of adjacent candidate electrode points are activated in a time-sequenced order, and all candidate electrode points are rapidly swept according to the microscopic scanning mode to output the second micro-current detection signal to the treatment object.

3. The method of claim 1, wherein, The feature data sequence comprises time and cell response values; and the response state model of the treatment object is constructed according to the feature data sequence, which comprises the following steps: Linear fitting is performed with the time as the abscissa and the cell response values as the ordinate to obtain the response state model.

4. The method of claim 1, wherein, The macroscopic model library comprises tissue standard models of multiple types of human tissue structures, and the response state model is compared with the macroscopic model library once, and individualized stimulation parameters are determined according to the comparison result, which comprises the following steps: Similarity between the response state model and each tissue standard model in the macroscopic model library is calculated, and the tissue structure type to which the treatment object belongs is determined according to the tissue standard model with the highest similarity; Medical record information of the treatment object is obtained, the best stimulation current and the best stimulation frequency are selected according to the tissue structure type and the medical record information, and the individualized stimulation parameters are generated.

5. The method of claim 1, wherein, The micro-model library contains a plurality of sub-part standard models of sub-parts of tissue structures, the response state model is secondarily compared with the micro-model library, and an optimal stimulation electrode combination is determined according to a secondary comparison result, and the method comprises the following steps: Similarities of the response state model and each sub-part standard model in the macro-model library are calculated, and an effective cell response value range is determined according to a sub-part standard model with the highest similarity; All data in the response state model are traversed, a time period falling within the cell response value range is screened out, activated electrode points and an activation sequence in the time period are recorded as optimal stimulation electrodes and an optimal stimulation path respectively, and the optimal stimulation electrode combination is obtained.

6. The method of claim 1, wherein, The optimal treatment scheme is generated according to the optimal stimulation electrode combination and the individualized stimulation parameter, and the method comprises the following steps: A micro-current stimulation waveform is modulated according to the individualized stimulation parameter; The micro-current stimulation waveform is applied to the target stimulation part according to the optimal stimulation electrode combination.

7. The method of claim 1, wherein, In the process of electric stimulation on the target stimulation part of the treatment object, the method further comprises the following steps: Cell response conditions of the target stimulation part are continuously monitored, and latest cell response data are acquired; Latest individualized stimulation parameters and an optimal stimulation electrode combination are re-acquired according to the latest cell response data; The optimal treatment scheme is dynamically adjusted according to the latest individualized stimulation parameters and the optimal stimulation electrode combination, and the electric stimulation is stopped when a stop condition is triggered.

8. A human adaptive microcurrent stimulation system, characterized by, The system is used for implementing the human adaptive micro-current stimulation method in any one of claims 1-7, and the system comprises: A data acquisition system is used for controlling corresponding electrode points to output micro-current detection signals of multiple frequencies to each measured region according to a preset point sweeping mode, and cell response data of the measured region are acquired in real time; A central processing unit is used for extracting features of the cell response data to obtain a feature data sequence, constructing a response state model of the measured region according to the feature data sequence, acquiring a macro-model library and a micro-model library, performing primary comparison of the response state model and the macro-model library, determining individualized stimulation parameters according to a primary comparison result, performing secondary comparison of the response state model and the micro-model library, and determining an optimal stimulation electrode combination according to a secondary comparison result; and A carrier generator is connected with the central processing unit and the data acquisition system, and is configured to generate an optimal treatment scheme according to the optimal stimulation electrode combination and the individualized stimulation parameters output by the central processing unit, and to perform electrical stimulation on a target stimulation site of the treatment object through the electrode stimulation module; wherein the carrier generator is configured to generate a fundamental wave electrical signal with a frequency of 100 Hz-200 KHz, and a carrier wave electrical signal with a frequency range of 1 Hz-200 Hz, and to control the stimulation current size by dynamically modulating the current amplitude of the fundamental wave electrical signal and the carrier wave electrical signal; when the carrier wave electrical signal is an alternating current stimulation signal, the portion of the carrier wave electrical signal waveform defining the positive polarity has a greater amplitude and a shorter duration than the portion of the carrier wave electrical signal waveform defining the negative polarity, and by adjusting the duty cycle and the current amplitude ratio of the carrier wave electrical signal, a difference in amplitude between the portion defining the positive polarity and the portion defining the negative polarity is caused, and each corresponding integral of the current amplitude between successive time instances of alternating polarity of the carrier wave electrical signal waveform is equal.

9. The system of claim 8, wherein, The data acquisition system comprises: a plurality of electrode stimulation modules comprising a plurality of electrode points arranged in an array on a two-dimensional structure, configured to form an electrical connection with a measured region of the treatment object, and the electrode points are dynamically switched to form different measurement and stimulation loops; a data measurement module connected with the electrode stimulation module, configured to generate a micro-current detection signal of multiple frequencies, and to measure the cell response data of the measured region.

10. The system of claim 8, wherein, The central processing unit comprises: a macro sampling module configured to calculate the similarity between the response state model and each tissue standard model in the macro model library, and to determine the tissue structure type to which the treatment object belongs according to the tissue standard model with the highest similarity; to obtain the medical record information of the treatment object, to select the optimal stimulation current and the optimal stimulation frequency according to the tissue structure type and the medical record information, and to generate the individualized stimulation parameters; a micro sampling module configured to calculate the similarity between the response state model and each part standard model in the macro model library, and to determine the effective cell response value range according to the part standard model with the highest similarity; to traverse all data in the response state model, to filter out the time period within the cell response value range, and to record the electrode points and the activation sequence activated within the time period as the optimal stimulation electrode and the optimal stimulation path respectively, so as to obtain the optimal stimulation electrode combination.

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