Electrical stimulation dynamic regulation and control method and system based on biological impedance feedback

Abstract

The invention discloses an electrical stimulation dynamic regulation and control method and system based on biological impedance feedback, and relates to the technical field of biomedical electronics and intelligent control. The method comprises the steps that biological impedance spectrum data of a target area are collected in real time through a body surface electrode, and impedance characteristic parameters representing the physiological state of tissue are obtained through calculation based on a Cole-Cole model; comparing the parameter with a preset threshold value, and directly querying and determining an electrical stimulation output parameter from a pre-stored mapping table according to a result; and generating an electrical stimulation signal according to the parameter and applying the electrical stimulation signal to the target area. The state analysis-direct mapping mechanism is used for replacing traditional PID control, millisecond-level real-time regulation and control are achieved, the anti-adaptive disturbance and thermal-electric cooperative control are combined, the neural adaptability is effectively overcome, and the long-term effect and stability of the curative effect are improved.

Description

Technical Field

[0001] This invention relates to the field of biomedical electronics and intelligent control technology, and in particular to a method and system for dynamic regulation of electrical stimulation based on bioimpedance feedback. Background Technology

[0002] Electrostimulation therapy is a common physical therapy method that regulates physiological states by applying electrical stimulation signals to acupoints. It is widely used as an adjunct treatment for various diseases and for health maintenance. However, existing electrostimulation therapy equipment has many technical limitations: Fixed parameters: Treatment parameters are preset and cannot be adjusted in real time according to the dynamic changes in the patient's tissue state during treatment, resulting in unstable therapeutic effects.

[0003] Single feedback dimension: Some closed-loop control systems rely only on simple electrical parameters (such as output voltage / current) or single physiological signals (such as electromyography, electrocardiography), failing to reach the cellular level changes in the physiological state of tissues, resulting in insufficient regulatory precision.

[0004] Neurological adaptation deficit: A constant stimulation pattern can easily lead to adaptation in the nervous system, resulting in a significant decrease in the therapeutic effect over time, with the effect decreasing by ≥40% after 30 minutes of treatment.

[0005] System response delay: Systems that use complex algorithms (such as PID tuning) to fuse multi-sensor data have a large response delay (often >200ms), making it difficult to achieve truly real-time and precise control.

[0006] Among existing related technologies, patent CN118672192B uses an optimization algorithm for PID parameter tuning, but the control logic is essentially still based on error feedback rather than on direct analysis and mapping of tissue physiological states, resulting in response delays. Patent CN117797406A requires the integration of multiple physiological signals, making the system complex and costly, with poor clinical applicability. Furthermore, some technologies, due to limitations related to disease diagnosis or treatment methods, do not meet the requirements of Article 25, Paragraph 3 of the Patent Law and cannot obtain effective protection.

[0007] Therefore, the present invention aims to provide a dynamic control scheme for electrical stimulation that has a fast response speed, high control precision, can effectively overcome neural adaptation, and complies with the provisions of patent law. By replacing the traditional control logic with a direct state-action mapping mechanism based on bioimpedance feedback, it realizes dynamic adaptive control of electrical stimulation parameters, which is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0008] In view of this, the present invention provides a method and system for dynamic regulation of electrical stimulation based on bioimpedance feedback. It abandons the traditional control path based on error feedback and instead establishes a direct parameter mapping mechanism based on physiological state analysis. By monitoring the bioimpedance characteristic parameters that reflect the physiological state of cells in real time, it directly maps them to the optimal electrical stimulation parameters, thereby achieving precise and adaptive regulation with millisecond-level response.

[0009] To achieve the above objectives, the present invention adopts the following technical solution: A method for dynamic modulation of electrical stimulation based on bioimpedance feedback includes the following steps: S1 Real-time monitoring and analysis steps: Real-time acquisition of bioimpedance spectrum data of the target area collected by the body surface electrode, and calculation of at least one impedance characteristic parameter characterizing the physiological state of the tissue based on the Cole-Cole model; S2 Dynamic Mapping and Decision-Making Steps: Compare the impedance characteristic parameters obtained in S1 with the preset threshold. Based on the comparison results, query and determine the electrical stimulation output parameters corresponding to the current impedance characteristic parameters from the pre-stored stimulation parameter mapping table. S3 Parameter Output and Execution Steps: Based on the electrical stimulation output parameters determined in S2, generate the corresponding electrical stimulation signal.

[0010] Optionally, in the above method, the impedance characteristic parameters in S1 include extracellular fluid resistance R. e Intracellular fluid resistance R i and cell membrane capacitance C m At least one of them.

[0011] Optionally, in the above method, the S1 real-time monitoring and analysis step may employ an improved golf optimization algorithm to fit the parameters of the Cole-Cole model. The improvements include: The population is initialized using Sobol sequences; A cosine perturbation strategy based on the golden ratio is used for position updates during the exploration phase; A non-uniform elite mutation strategy is adopted to enhance the convergence of the development phase.

[0012] The above method, optionally, includes the following specific steps in the S2 dynamic mapping and decision-making process: calculating the rate of change ΔZ of the current total impedance value relative to the reference value. If ΔZ is less than or equal to the first negative threshold, then query the mapping table to determine the first electrical stimulation parameters with the strategy of increasing stimulation frequency and stimulation amplitude. If ΔZ is between the first negative threshold and the first positive threshold, then query the mapping table to determine the second electrical stimulation parameter with the strategy of maintaining the current parameter. If ΔZ is greater than the first positive threshold, the mapping table is queried to determine the third electrical stimulation parameter with the strategy of switching to mid-frequency stimulation and shortening the pulse width.

[0013] Optionally, the above method may also include the S4 thermotherapy synergistic control step: dynamically adjusting the thermotherapy temperature based on impedance characteristic parameters; The specific content is: Calculating the extracellular fluid resistance R. e With intracellular fluid resistance R i If the ratio is greater than the preset ratio threshold, the thermotherapy module is controlled to heat up to the first high temperature setting value.

[0014] Optionally, the above method also includes the S5 anti-adaptive perturbation step: during the treatment process, a random perturbation pulse sequence of a certain duration is automatically injected at fixed or non-fixed time intervals; The amplitude of the disturbance pulse fluctuates within ±15% of its amplitude value, and its frequency fluctuates within ±20% of its frequency value.

[0015] Optionally, the above method may also include the S6 multimodal collaborative control step: combining real-time monitoring of the hyperthermia temperature T and impedance phase angle. θ Calculate the co-regulation factor and based on Different working modes can be selected based on the numerical values; when When the temperature is below the mode switching threshold, the first working mode is activated, which corresponds to the first thermotherapy temperature and the second electrical stimulation frequency. when When the threshold for mode switching is greater than or equal to the threshold, the second working mode is activated, which corresponds to the second thermotherapy temperature and the third electrical stimulation frequency.

[0016] The above methods, optionally, include co-regulatory factors. The specific calculation formula is as follows: ; In the formula, in the formula, This represents the weighting coefficient for the temperature term. This is a factor for adjusting the temperature response. This is a reference value for the impedance phase angle. This is the reference value for the temperature center point.

[0017] A bioimpedance feedback-based dynamic modulation system for electrical stimulation, used to execute any one of the above-described bioimpedance feedback-based dynamic modulation methods for electrical stimulation, comprising: The main control module is used to execute algorithm logic and numerical calculations; The bioimpedance measurement module, connected to the main control module, is used to acquire bioimpedance spectrum data. The electrical stimulation output module, connected to the main control module, is used to generate and output electrical stimulation signals; The body surface electrodes, connected to the bioimpedance measurement module and the electrical stimulation output module, are used to attach to the target area.

[0018] Optionally, the system described above may also include a thermotherapy control module connected to the main control module, used to control the heating element to heat the target area according to the instructions of the main control module.

[0019] As can be seen from the above technical solution, compared with the prior art, the present invention provides a method and system for dynamic regulation of electrical stimulation based on bioimpedance feedback, which has the following beneficial effects: (1) Extreme response speed: By directly querying the parameter mapping table instead of complex algorithm calculation, the system decision time is shortened to less than 50ms, realizing true real-time feedback; (2) Revolutionary improvement in regulatory precision: Analysis of cell physiological parameters (R) based on the Cole-Cole model e R i C m This allows regulation to act directly on the physiological root cause, rather than on apparent signals; (3) Long-term protection: The original anti-adaptive perturbation strategy effectively breaks the neural adaptation. Clinical data shows that it can extend the effective treatment period to more than 24 hours and reduce the recurrence rate by 73.4%; (4) Significant synergistic effect: through the thermo-electric synergistic factor By organically combining temperature and electrical stimulation, the system can intelligently switch modes for different pathological states (acute allergy vs. chronic hypertrophy), thus broadening the range of indications. (5) Extremely high safety: Built-in multiple safety monitoring (such as electrode detachment detection and tissue edema warning) to ensure the safety and reliability of the treatment process. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0021] Figure 1 This invention discloses a flowchart of a dynamic modulation method for electrical stimulation based on bioimpedance feedback; Figure 2 This is a structural block diagram of an electrostimulation dynamic control system based on acupoint impedance feedback disclosed in this invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] In this application, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0024] See Figure 1 As shown, this invention discloses a method for dynamic modulation of electrical stimulation based on bioimpedance feedback, comprising the following steps: S1 Real-time monitoring and analysis steps: Real-time acquisition of bioimpedance spectrum data of the target area collected by the body surface electrode, and calculation of at least one impedance characteristic parameter characterizing the physiological state of the tissue based on the Cole-Cole model; S2 Dynamic Mapping and Decision-Making Steps: Compare the impedance characteristic parameters obtained in S1 with the preset threshold. Based on the comparison results, query and determine the electrical stimulation output parameters corresponding to the current impedance characteristic parameters from the pre-stored stimulation parameter mapping table. S3 Parameter Output and Execution Steps: Based on the electrical stimulation output parameters determined in S2, generate the corresponding electrical stimulation signal.

[0025] Furthermore, the impedance characteristic parameters in S1 include extracellular fluid resistance R. e Intracellular fluid resistance R i and cell membrane capacitance C m At least one of them.

[0026] Furthermore, in the S1 real-time monitoring and analysis step, an improved golf optimization algorithm is used to fit the parameters of the Cole-Cole model. The improvements include: The population is initialized using Sobol sequences; A cosine perturbation strategy based on the golden ratio is used for position updates during the exploration phase; A non-uniform elite mutation strategy is adopted to enhance the convergence of the development phase.

[0027] Furthermore, the specific content of the S2 dynamic mapping and decision-making steps is as follows: calculate the rate of change ΔZ of the current total impedance value relative to the reference value. If ΔZ is less than or equal to the first negative threshold, then query the mapping table to determine the first electrical stimulation parameters with the strategy of increasing stimulation frequency and stimulation amplitude. If ΔZ is between the first negative threshold and the first positive threshold, then query the mapping table to determine the second electrical stimulation parameter with the strategy of maintaining the current parameter. If ΔZ is greater than the first positive threshold, the mapping table is queried to determine the third electrical stimulation parameter with the strategy of switching to mid-frequency stimulation and shortening the pulse width.

[0028] In one specific embodiment, the first negative threshold is -10%, and the first positive threshold is 5%; If ΔZ≤-10%, then consult the mapping table to increase the electrical stimulation frequency to 10Hz and increase the amplitude by 0.3mA; If -10% < ΔZ ≤ 5%, then maintain the current electrical stimulation parameters; If ΔZ > 5%, then query the mapping table to switch the electrical stimulation frequency to 1 kHz and the pulse width to 50 μs.

[0029] The first electrical stimulation parameters were a frequency of 10 Hz and an amplitude increase of 0.3 mA. The second electrical stimulation parameter is the frequency, amplitude, and pulse width parameters that maintain the current output. The third electrical stimulation parameters are a frequency of 1 kHz and a pulse width of 50 µs.

[0030] Furthermore, it also includes the S4 thermotherapy synergistic control step: dynamically adjusting the thermotherapy temperature based on impedance characteristic parameters; The specific content is: Calculating the extracellular fluid resistance R. e With intracellular fluid resistance R i If the ratio is greater than the preset ratio threshold, the thermotherapy module is controlled to heat up to the first high temperature setting value.

[0031] In one specific embodiment, the preset ratio threshold is 1.5, and the first high temperature setting is 45°C.

[0032] Furthermore, it also includes the S5 anti-adaptive perturbation step: during treatment, a sequence of random perturbation pulses of a certain duration is automatically injected at fixed or non-fixed time intervals; The amplitude of the disturbance pulse fluctuates within ±15% of its amplitude value, and its frequency fluctuates within ±20% of its frequency value.

[0033] Furthermore, it also includes the S6 multimodal collaborative control step: combining real-time monitoring of the hyperthermia temperature T and impedance phase angle. θ Calculate the co-regulation factor and based on Different working modes can be selected based on the numerical values; when When the temperature is below the mode switching threshold, the first working mode is activated, which corresponds to the first thermotherapy temperature and the second electrical stimulation frequency. when When the threshold for mode switching is greater than or equal to the threshold, the second working mode is activated, which corresponds to the second thermotherapy temperature and the third electrical stimulation frequency.

[0034] Furthermore, co-regulatory factors The specific calculation formula is as follows: ; In the formula, in the formula, This represents the weighting coefficient for the temperature term. This is a factor for adjusting the temperature response. This is a reference value for the impedance phase angle. This is the reference value for the temperature center point.

[0035] In one specific embodiment, =0.7, =0.5, =40, =π / 4; The mode switching threshold is 0.4; The first working mode is a combination of a thermotherapy temperature of 42℃ and an electrical stimulation frequency of 2Hz. The second working mode is a combination of a thermotherapy temperature of 45℃ and an electrical stimulation frequency of 1kHz.

[0036] Furthermore, S2 also includes a safety monitoring sub-step: if extracellular fluid resistance (R) is detected... e） If the rate of decrease per unit time exceeds 8%min, a risk of tissue edema is identified, and a safety strategy is automatically triggered, reducing the electrical stimulation amplitude to 0.5 mA while increasing the frequency to 5 kHz.

[0037] and Figure 1 Corresponding to the method shown, this invention also discloses a dynamic modulation system for electrical stimulation based on bioimpedance feedback, used for... Figure 1 For the implementation and structure diagram of the method shown, please refer to [link / reference]. Figure 2 As shown, it includes: The main control module is used to execute algorithm logic and numerical calculations; The bioimpedance measurement module, connected to the main control module, is used to acquire bioimpedance spectrum data. The electrical stimulation output module, connected to the main control module, is used to generate and output electrical stimulation signals; The body surface electrodes, connected to the bioimpedance measurement module and the electrical stimulation output module, are used to attach to the target area.

[0038] Furthermore, it also includes a thermotherapy control module, which is connected to the main control module and is used to control the heating element to heat the target area according to the instructions of the main control module.

[0039] In one specific embodiment, the present invention is implemented as follows: I. Hardware System Architecture 1. Main control module: Core chip: STMicroelectronics' 32-bit ARM Cortex-M7 core microcontroller STM32H743VIT6.

[0040] Computing power support: Built-in double-precision floating-point unit (FPU) and DSP instruction set, enabling real-time Cole-Cole model fitting, complex number operations, and cofactor calculations. K s It provides powerful computing power for calculations.

[0041] Peripheral circuits include crystal oscillator circuit, reset circuit, power management circuit, and SWD debugging interface.

[0042] 2. Bioimpedance Measurement Module: Core chip: The AD5933 impedance converter chip from Analog Devices is used. This chip integrates an on-chip frequency generator and a 12-bit, 1MSPS ADC, which can perform impedance spectrum scanning with high accuracy (typical accuracy ±1%) in the frequency range of 0.1kHz to 10kHz.

[0043] Interface circuit: The AD5933 communicates with the main control chip STM32H743 via the I2C bus. The electrodes and the AD5933 are connected to the drive circuit through a voltage follower based on the ADA4528 operational amplifier to reduce the output impedance of the measurement channel and improve measurement stability and anti-interference capability.

[0044] 3. Electrical stimulation output module: Core circuit: Employs a voltage-controlled constant current source circuit based on the Howland current pump architecture. Uses a high-precision operational amplifier OPA2171.

[0045] Control method: The stimulation waveform is generated by the STM32H743's built-in 12-bit DAC.

[0046] Output specifications: Stimulation current amplitude 0.1~2.0mA (0.1mA steps), frequency range 2Hz~5kHz. Pulse width 50µs~500µs.

[0047] 4. Hyperthermia Control Module: Actuating element: A miniature thin-film resistance heating element is integrated inside the electrode, with a surface area ≥1cm². 2 .

[0048] Control method: Heating power is controlled using PWM. Temperature is monitored in real time via an NTC thermistor.

[0049] Control range: 38~45℃, accuracy: ±0.5℃.

[0050] 5. Electrode System: Materials and Structure: A graphene / silver paste composite flexible electrode is used, which combines biocompatibility, flexibility and high conductivity.

[0051] Usage: For single use only, it couples with the skin via a medical conductive gel.

[0052] II. Software Implementation Process

[0053] 1. Step S201: System Initialization

[0054] Initialize all MCU peripherals (I2C, DAC, ADC, PWM, etc.)

[0055] Load the preset stimulus parameter mapping table, anti-disturbance strategy parameters (such as a disturbance interval of 5 minutes, a duration of 10 seconds, and a fluctuation amplitude of ±15%), and safety thresholds (such as the ΔZ threshold and the Re descent rate threshold of 8% / min).

[0056] 2. Step S202: Impedance spectrum acquisition and real-time analysis

[0057] The MCU configures the AD5933 via the I2C bus, starts a frequency scan (from 0.1kHz to 10kHz), and selects 5-10 characteristic frequency points.

[0058] After the AD5933 completes the scan, the measured real part ( ) and imaginary part ( The data is returned to the MCU via I2C.

[0059] Cole-Cole model fitting: Objective function: Establish a complex nonlinear least squares fitting objective function based on the Cole-Cole model.

[0060] Optimization Algorithm: The improved golf optimization algorithm (IGOA) is used for fitting, and the specific steps are as follows: 1. Population initialization: Using Sobol sequences in a preset parameter space (R e R i C m The initial population is generated within a reasonable range to ensure that the initial solutions are uniformly distributed in space and to avoid getting trapped in local optima.

[0061] 2. Exploration Phase: The individual position is updated using the golden ratio cosine perturbation strategy, with the following formula: X new =X old +cos( π / 2) (X elite -X rand ) (in Golden ratio, X elit为 Elite individuals, X rand (as random individuals) to balance global exploration capabilities.

[0062] 3. Development Phase: Introduce a non-uniform elite mutation strategy, with the following formula: X new =X elite +δ (UB-LB) e -k (t / T)

[0063] (Where δ is the random perturbation vector, UB / LB are the upper and lower bounds of the parameters, t is the current iteration number, T is the total number of iterations, and k is the decay coefficient), the search range is gradually narrowed as the iteration proceeds, accelerating the convergence to the global optimal solution.

[0064] By fitting with IGOA, the final real-time output R is obtained. e R i C m Equal impedance characteristic parameters.

[0065] 3. Step S203: Dynamic Mapping and Decision Making

[0066] Calculate the rate of change of the current total impedance Z relative to the initial impedance Z0 at the start of treatment: ΔZ = (Z0 - Z0) / Z0 Z0) / Z0×100%

[0067] Query the mapping table: Compare ΔZ with the preset threshold and execute the corresponding strategy (see claims section).

[0068] Hyperthermia Decision: Simultaneously, calculate R e / R i If the ratio is greater than 1.5, then the 45℃ heat therapy mode will be activated.

[0069] Security monitoring: Real-time calculation of R e If the rate of change exceeds 8% / min within one minute, a safety strategy is immediately triggered (amplitude reduced to 0.5mA, frequency increased to 5kHz).

[0070] Step S204: Adaptive Disturbance Execution

[0071] The system has a built-in 5-minute timer. When the timer is triggered, a random pulse sequence lasting 10 seconds is superimposed on the current stimulus waveform.

[0072] The amplitude A of the random pulse r =A0×[1+U(-0.15,0.15)], frequency f r =f0×[1+U(-0.20,0.20)], where U(a,b) represents a uniform random distribution on the interval [a,b].

[0073] Step S205: Multimodal cooperative control

[0074] Real-time reading of the hyperthermia temperature T and the impedance phase angle θ at the current dominant frequency.

[0075] Substitute into the formula to calculate the co-regulation factor K s :

[0076] according to The value (threshold 0.4) selects the final working mode combination (thermotherapy temperature + electrical stimulation frequency).

[0077] Step S206: Stimulus parameter output and closed-loop feedback

[0078] The finalized stimulation parameters (amplitude, frequency, pulse width) and thermotherapy temperature settings are output to the electrical stimulation module and the thermotherapy control module, respectively.

[0079] The system repeatedly executes S202~S206 with a period of ≤100ms, forming a high-speed closed-loop control.

[0080] III. Key Parameter Calibration and Alternative Solutions

[0081] Determination of mapping table thresholds (-10%, 5%): These thresholds were derived based on statistical analysis of data from 60 clinical trial participants. By plotting the relationship between different ΔZ intervals and clinical symptom relief, -10% and 5% were found to be inflection points where significant changes in efficacy occurred. It should be clearly stated that these thresholds can be adjusted within a certain range (e.g., The basic effects of the invention can still be maintained even with ΔZ ≤ -8% to -12% and ΔZ > 3% to 7%, which provides flexibility for the interpretation of the claims.

[0082] Synergistic Factor Calculation formula: The weighting coefficients (0.7 and 0.3), temperature center point (40), and phase angle reference value (π / 4) in the formula are derived by fitting and optimizing multiple linear regression with clinical efficacy data. In alternatives, these coefficients can be fine-tuned (e.g., weights fluctuate within ±0.1, and the center point is adjusted between 39 and 41).

[0083] The key improvements of the IGOA algorithm are the Sobol sequence, the golden ratio cosine perturbation, and the non-uniform elite mutation. However, it should also be noted that other global optimization algorithms (such as the improved particle swarm optimization algorithm and the differential evolution algorithm) can also be used for Cole-Cole model fitting, provided that some convergence speed is sacrificed. This is an equivalent substitution of the present invention.

[0084] IV. Life safety guarantee mechanism

[0085] Current density safety: Electrode area ≥ 1 cm² 2 The maximum output current is 2.0mA, and the calculated maximum current density is 200µA / mm. 2 It is far below the safety limits specified in the IEC 60601-1-10 standard.

[0086] Electrode detachment detection: Real-time monitoring of impedance modulus |Z|. If |Z| drops sharply by more than 20% within a very short time (e.g., 50ms) and is accompanied by an abnormal phase angle, it is determined that the electrode has detached or has poor contact. The system immediately stops all electrical stimulation and thermotherapy outputs and issues an audible and visual alarm.

[0087] Hardware watchdog: The MCU is equipped with a hardware watchdog circuit to prevent the output from going out of control due to program crashes.

[0088] Experimental Example 1: Clinical Efficacy Trial

[0089] Methods: Sixty patients with chronic rhinitis were randomly divided into an experimental group (n=30) and a control group (n=30). The experimental group used the algorithm of this invention, while the control group had fixed electrical stimulation parameters. The stimulation was performed once a day for 20 minutes each time for 4 consecutive weeks.

[0090] The results are shown in Table 1. The algorithm of this invention is significantly better than the control group in terms of nasal congestion relief time, symptom recurrence rate, impedance stability and skin tolerance, and has significant clinical efficacy and safety.

[0091] Table 1 Experimental Results

[0092] Experiment Example 2: Technical Performance Test

[0093] Response time test: The system decision time is <50ms, which is significantly better than the >200ms of traditional PID control.

[0094] Verification of anti-interference effect: The nerve excitability of the perturbation group recovered to 92.3%, while that of the unperturbed group was only 78.1%.

[0095] Temperature control accuracy: The temperature control accuracy of hyperthermia is ±0.5℃, which meets the standards of medical equipment.

[0096] Compared with the prior art, the present invention: 1. A fundamental shift in technical thinking: from error feedback-based control (such as PID) to direct mapping based on state analysis. This is not simply optimization, but an innovation in technical approach.

[0097] 2. Deepening the feedback dimension: From feedback of circuit parameters / macrophysiological signals to feedback of cellular-level biophysical parameters, the essence of regulation has been grasped.

[0098] 3. Introduce proactive management mechanisms to resist disturbances: rather than passively adapting to the decline in efficacy, this is the key to maintaining long-term effectiveness.

[0099] 4. A thermo-electric synergistic factor was created. This new control variable, which unifies the decision-making of two physical factors through a quantitative model, enables intelligent multimodal therapy.

[0100] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for dynamic modulation of electrical stimulation based on bioimpedance feedback, characterized in that, Includes the following steps: S1 Real-time monitoring and analysis steps: Real-time acquisition of bioimpedance spectrum data of the target area collected by the body surface electrode, and calculation of at least one impedance characteristic parameter characterizing the physiological state of the tissue based on the Cole-Cole model; S2 Dynamic Mapping and Decision-Making Steps: Compare the impedance characteristic parameters obtained in S1 with the preset threshold. Based on the comparison results, query and determine the electrical stimulation output parameters corresponding to the current impedance characteristic parameters from the pre-stored stimulation parameter mapping table. S3 Parameter Output and Execution Steps: Based on the electrical stimulation output parameters determined in S2, generate the corresponding electrical stimulation signal.

2. The method for dynamic regulation of electrical stimulation based on bioimpedance feedback according to claim 1, characterized in that, The impedance characteristic parameters in S1 include extracellular fluid resistance R. e Intracellular fluid resistance R i and cell membrane capacitance C m At least one of them.

3. The method for dynamic regulation of electrical stimulation based on bioimpedance feedback according to claim 2, characterized in that, In the S1 real-time monitoring and analysis step, an improved golf optimization algorithm is used to fit the parameters of the Cole-Cole model. The improvements include: The population is initialized using Sobol sequences; A cosine perturbation strategy based on the golden ratio is used for position updates during the exploration phase; A non-uniform elite mutation strategy is adopted to enhance the convergence of the development phase.

4. The method for dynamic regulation of electrical stimulation based on bioimpedance feedback according to claim 3, characterized in that, The specific steps of the S2 dynamic mapping and decision-making process are as follows: calculate the rate of change ΔZ of the current total impedance value relative to the reference value. If ΔZ is less than or equal to the first negative threshold, then query the mapping table to determine the first electrical stimulation parameters with the strategy of increasing stimulation frequency and stimulation amplitude. If ΔZ is between the first negative threshold and the first positive threshold, then query the mapping table to determine the second electrical stimulation parameter with the strategy of maintaining the current parameter. If ΔZ is greater than the first positive threshold, the mapping table is queried to determine the third electrical stimulation parameter with the strategy of switching to mid-frequency stimulation and shortening the pulse width.

5. The method for dynamic regulation of electrical stimulation based on bioimpedance feedback according to claim 4, characterized in that, It also includes the S4 thermotherapy co-control step: dynamically adjusting the thermotherapy temperature based on impedance characteristic parameters; The specific content is: Calculating the extracellular fluid resistance R. e With intracellular fluid resistance R i If the ratio is greater than the preset ratio threshold, the thermotherapy module is controlled to heat up to the first high temperature setting value.

6. The method for dynamic regulation of electrical stimulation based on bioimpedance feedback according to claim 5, characterized in that, It also includes the S5 anti-adaptive perturbation step: during treatment, a sequence of random perturbation pulses of a certain duration is automatically injected at fixed or non-fixed time intervals; The amplitude of the disturbance pulse fluctuates within ±15% of its amplitude value, and its frequency fluctuates within ±20% of its frequency value.

7. The method for dynamic modulation of electrical stimulation based on bioimpedance feedback according to claim 6, characterized in that, It also includes the S6 multimodal collaborative control step: combining real-time monitoring of the hyperthermia temperature T and impedance phase angle. θ Calculate the co-regulation factor and based on Different working modes can be selected based on the numerical values; when When the temperature is below the mode switching threshold, the first working mode is activated, which corresponds to the first thermotherapy temperature and the second electrical stimulation frequency. when When the threshold for mode switching is greater than or equal to the threshold, the second working mode is activated, which corresponds to the second thermotherapy temperature and the third electrical stimulation frequency.

8. The method for dynamic modulation of electrical stimulation based on bioimpedance feedback according to claim 7, characterized in that, Co-regulatory factors The specific calculation formula is as follows: ; In the formula, This represents the weighting coefficient for the temperature term. This is a factor for adjusting the temperature response. This is a reference value for the impedance phase angle. This is the reference value for the temperature center point.

9. A dynamic modulation system for electrical stimulation based on bioimpedance feedback, characterized in that, A method for performing dynamic modulation of electrical stimulation based on bioimpedance feedback as described in any one of claims 1-8, comprising: The main control module is used to execute algorithm logic and numerical calculations; The bioimpedance measurement module, connected to the main control module, is used to acquire bioimpedance spectrum data. The electrical stimulation output module, connected to the main control module, is used to generate and output electrical stimulation signals; The body surface electrodes, connected to the bioimpedance measurement module and the electrical stimulation output module, are used to attach to the target area.

10. The electrostimulation dynamic control system based on bioimpedance feedback according to claim 9, characterized in that, It also includes a thermotherapy control module, which is connected to the main control module and is used to control the heating element to heat the target area according to the instructions of the main control module.

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