Intermediate frequency carrier and low frequency modulation wave composite output control method

Abstract

The invention provides an intermediate-frequency carrier and low-frequency modulated wave composite output control method, which comprises the following steps of: acquiring spatial intensity change distribution of a composite waveform in optic nerve tissue, and acquiring an actual measurement value of a carrier intensity distribution field by combining a microtube skeleton polymerization rate and an extension orientation angle of growth cone propulsion, forming basic data of an initial distribution field; extracting candidate output of an optimal waveform modulation combination from the adjusted envelope gradual change speed control combination, comparing an actual path of directional extension with an expected damage repair track through track overlapping degree measurement, and determining a quantization result of the deviation degree of the extension path; and performing deviation degree classification processing on the extension path deviation degree quantification result, obtaining a high deviation subset in a classification result, generating a compensation signal in combination with an aggregation rate change development trend, and obtaining a compensated composite waveform output combination.

Description

Technical Field

[0001] This invention relates to the field of information technology, and in particular to a method for controlling the composite output of a medium-frequency carrier wave and a low-frequency modulated wave. Background Technology

[0002] Optic nerve injury repair is crucial for restoring optic nerve function caused by disease or trauma and significantly improves patients' quality of life. Regeneration of optic nerve axons requires precise guidance of their growth direction to ensure effective connection to the target area. However, current research and applications face significant challenges in achieving this goal, necessitating breakthroughs to advance clinical treatment. Existing methods for guiding optic nerve axon regeneration rely on biological or physical stimulation, such as chemical inducing factors or static electric fields. While these methods can promote axon growth to some extent, they often struggle to adapt to complex tissue environments. They are insufficient in dynamically regulating the spatial orientation of axonal growth cones and the aggregation rate of the microtubule skeleton, especially in the complex three-dimensional environment of the fundus tissue. The lack of real-time, precise control over the growth process leads to axonal extension paths deviating from the expected target, resulting in poor repair outcomes. The root cause of this path deviation lies in the spatial orientation error of the axonal growth cone when sensing external guiding signals. Specifically, the filamentous pseudopodia of the growth cone cannot accurately identify directional changes in the carrier intensity gradient, causing the spatial distribution of microtubule skeleton aggregation to lose its correct orientation. Simultaneously, the mismatch between the microtubule skeleton aggregation rate and the spatial orientation requirements of the growth cone inevitably exists during the dynamic adjustment process. The spatial orientation of the axonal growth cone directly determines the direction of the regeneration path, while the aggregation rate of the microtubule skeleton affects the speed and stability of axonal extension. These two are interdependent: the spatial orientation of the growth cone provides directional guidance for microtubule skeleton aggregation, determining the spatial distribution pattern of microtubule aggregation; while the aggregation rate of the microtubule skeleton provides structural support for the spatial orientation of the growth cone. An excessively slow aggregation rate limits the growth cone's sensing ability and orientation accuracy, while an excessively fast aggregation rate causes the growth cone to lose sensitivity to external signals. When the carrier intensity exceeds the tissue tolerance threshold, the excessively rapid aggregation speed of the microtubule skeleton leads to disordered expansion of the filamentous pseudopodia of the growth cone, causing axonal extension to lose directional control and deviate from the predetermined regeneration path. Carrier intensity creates a specific distribution field within the fundus tissue, providing spatial orientation signals to axonal growth cones through gradient distribution differences. Growth cone sensors identify directional changes in the intensity gradient and convert them into directional commands for microtubule aggregation, guiding the axonal growth cones towards the damaged area. However, when the carrier intensity exceeds a threshold, the excessively rapid microtubule aggregation leads to disordered expansion of the growth cone's filamentous pseudopodia, causing axonal extension to lose directional control and making it difficult to guide the axonal growth cones towards the damaged area. For example, in optic nerve injury repair, if the growth cone deviates from its direction due to insufficient external signals, or if microtubule aggregation is too slow, causing extension to stagnate, the axon may not accurately reach the damaged area, thus affecting the recovery of nerve function. This becomes a key issue in the precise control of the optic nerve injury repair pathway. Summary of the Invention

[0003] This invention provides a method for controlling the composite output of an intermediate frequency carrier wave and a low-frequency modulated wave, mainly comprising: Acquire the spatial intensity variation distribution of the composite waveform within the optic nerve tissue to generate basic data for the initial distribution field; Based on the initial distribution field data, the variation range of the microtubule skeleton polymerization rate is identified, the correlation strength between the microtubule skeleton polymerization rate and the directional extension of the growth cone is calculated, and the development trend of the microtubule skeleton polymerization rate variation is determined. Analyze the relationship between the development trend of the microtubule skeleton polymerization rate and the preset critical value, and adjust the modulation wave envelope gradient speed to generate an envelope gradient speed control combination; Candidate waveform modulation combinations are extracted from the envelope gradient speed control combination, and the actual extension path of the growth cone is compared with the expected damage repair trajectory to determine the quantitative result of the deviation of the extension path. The deviation of the extended path is classified according to the quantitative results, and a high deviation subset is extracted and combined with the development trend of the microtubule skeleton polymerization rate to generate a compensated composite waveform output combination. The measured values ​​of spatial intensity variation distribution field are updated by combining the compensated composite waveform outputs, and the optimal waveform modulation combination is locked.

[0004] Furthermore, the step of acquiring the spatial intensity variation distribution of the composite waveform within the optic nerve tissue to generate initial distribution field basic data includes: Carrier intensity values ​​at different depths of optic nerve tissue are collected. Acquisition points are set according to preset intervals, and a three-dimensional coordinate system is established to record the carrier intensity values ​​and corresponding spatial coordinates, generating carrier intensity spatial distribution data. Fluorescence intensity changes at corresponding positions of each acquisition point in the carrier intensity spatial distribution data are monitored. The microtubule skeleton polymerization rate is calculated based on the fluorescence intensity increment, and the extension orientation angle of the growth cone tip relative to the axonal main axis is measured. Spatial mapping is performed based on the carrier intensity spatial distribution data, the microtubule skeleton polymerization rate, and the extension orientation angle to construct an initial distribution field basic data matrix.

[0005] Furthermore, the step of identifying the variation range of the microtubule skeleton polymerization rate, calculating the correlation strength between the microtubule skeleton polymerization rate and the directional extension of the growth cone, and determining the development trend of the microtubule skeleton polymerization rate variation includes: The microtubule skeleton polymerization rate values ​​at each spatial location are extracted, and the ratio of the rate difference between adjacent time points to the time interval is calculated to generate a rate change amplitude sequence data. Based on the rate change amplitude sequence data and the growth cone extension orientation angle value at the corresponding time point, the correlation coefficient value between the two is calculated, and spatial locations where the absolute value of the correlation coefficient exceeds a preset threshold are marked as strongly correlated regions, generating a correlation intensity distribution. After smoothing the rate change amplitude sequence of the strongly correlated regions in the correlation intensity distribution, linear fitting is performed based on the rate data at the turning point characteristic moment to determine the development trend of the microtubule skeleton polymerization rate change.

[0006] Furthermore, the analysis of the relationship between the development trend of the microtubule skeleton polymerization rate change and the preset critical value, and the adjustment of the modulation wave envelope gradient velocity to generate an envelope gradient velocity control combination, includes: The development trend value of the microtubule skeleton polymerization rate is compared with a preset critical value. The product of the absolute value of the rate and the acceleration at the time of exceeding the limit is calculated as a risk index. The risk level is divided according to the risk index, and the modulation wave envelope gradient adjustment amplification coefficient is determined. The envelope gradient adjustment control quantity is determined according to the offset change rate of the growth cone orientation angle and the amplification coefficient. The compensation adjustment quantity is calculated according to the difference between the actual extension speed of the growth cone and the speed of the target repair path, and superimposed on the control quantity to generate a comprehensive adjustment command. The modulation wave envelope gradient speed value is updated according to the comprehensive adjustment command to generate the envelope gradient speed control combination.

[0007] Furthermore, the step of extracting candidate waveform modulation combinations from the envelope gradient speed control combination, comparing the actual extension path of the growth cone with the expected damage repair trajectory, and determining the quantification result of the deviation degree of the extension path includes: The carrier intensity fluctuation amplitude, envelope value difference accumulation smoothness, and modulation frequency deviation are evaluated from the envelope gradual velocity control combination. After normalization, the weighted sum is used to generate a comprehensive score. Schemes with scores exceeding a preset threshold are selected as candidate waveform modulation combinations. The coordinate sequence corresponding to the expected damage repair trajectory is extracted. The maximum Hausdorff distance between the corresponding points of the two trajectories is calculated to generate the quantitative result of the deviation of the extended path.

[0008] Furthermore, the step of classifying the data based on the quantification results of the deviation degree of the extended path, extracting a high-deviation subset, and combining it with the development trend of the microtubule skeleton polymerization rate change to generate a compensated composite waveform output combination includes: Based on the magnitude of the quantification result of the deviation degree of the extended path, the data points are classified into low, medium, and high deviation categories according to preset low and high deviation thresholds. Data points of the high deviation category are extracted to form a high deviation subset. The development trend of the microtubule skeleton aggregation rate at the corresponding time of each data point in the high deviation subset is extracted, and the product of the trend slope and the quantification value of the deviation degree is calculated to determine the amplitude and phase parameters of the compensation signal. The amplitude of the compensation signal is used to modulate the carrier amplitude and offset the phase of the modulated wave envelope to generate the compensated composite waveform output combination.

[0009] Furthermore, the locking of the optimal waveform modulation combination includes: The compensated composite waveform output is applied to the optic nerve tissue to collect carrier intensity response values ​​at monitoring points. The intensity distribution field is reconstructed using Kriging spatial interpolation to generate updated spatial intensity change distribution field measurements. The point-by-point difference between the updated distribution field measurements and the ideal distribution field values ​​is calculated, and the root mean square value is obtained as the overall deviation index to determine if it meets the precision control standard. The carrier frequency, amplitude, phase, and modulation envelope parameters are extracted and locked as the optimal waveform modulation combination.

[0010] Furthermore, the method also includes: deploying an envelope gradient adjustment control strategy based on the optimal waveform modulation combination, integrating the microtubule skeleton polymerization rate response time and growth cone propulsion orientation angle data, and generating a damage repair path control scheme.

[0011] Furthermore, the step of deploying an envelope gradient adjustment control strategy based on the optimal waveform modulation combination, integrating the microtubule skeleton polymerization rate response time and growth cone propulsion orientation angle data, to generate a damage repair path control scheme includes: The carrier frequency and amplitude range in the optimal waveform modulation combination are extracted to determine the frequency modulation boundary and amplitude adjustment step interval, and encoded into an envelope gradient adjustment execution parameter set. An amplitude-sudden change carrier stimulation signal is applied, and the steady-state response time of the microtubule skeleton aggregation rate is recorded. The growth cone orientation angle sequence within the response time is collected, the angle change rate is calculated, and the execution parameter set is associated and stored. The response time is divided into initial, transition, and stable segments, and the average and standard deviation of the aggregation rate of each segment are calculated to determine the response characteristic type. Based on the response characteristic type and the angle change rate, the damage repair path control scheme is generated.

[0012] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects: This invention discloses a composite output control method for intermediate frequency carrier waves and low frequency modulated waves. Addressing the issues of insufficient correlation between the microtubule skeleton aggregation rate and the directional extension of the growth cone in optic nerve injury repair, as well as path deviation and erroneous connections, this method collects initial data on the spatial intensity distribution of the composite waveform, the microtubule aggregation rate, and the growth cone orientation angle. It establishes a distribution field and analyzes the aggregation rate variation trend to assess its correlation strength with growth cone extension. When the rate change exceeds a preset critical value, this invention generates an optimal waveform modulation combination by adjusting the gradual change speed of the modulation wave envelope in real time, combined with the growth cone extension speed and target path matching principle. It also quantifies the path deviation by measuring trajectory overlap, classifies high-deviation subsets, generates compensation signals, and updates the distribution field measurements. If the deviation is below the critical value, the optimal waveform modulation combination is locked, and a control strategy including amplitude and frequency modulation is deployed. This integrates the aggregation rate response and orientation angle data to ultimately form a precise injury repair path control scheme. This invention significantly improves the accuracy and stability of the optic nerve repair path, effectively avoids erroneous connections, and optimizes the repair effect. Attached Figure Description

[0013] Fig. 1 This is a flowchart of a composite output control method for intermediate frequency carrier and low frequency modulation wave according to the present invention.

[0014] Fig. 2 This is a schematic diagram of a composite output control method for intermediate frequency carrier and low frequency modulation wave according to the present invention. Detailed Implementation

[0015] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. 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.

[0016] like Figs. 1-2 The method for controlling the composite output of an intermediate frequency carrier and a low frequency modulated wave in this embodiment may specifically include: Step S101: Obtain the spatial intensity variation distribution of the composite waveform within the optic nerve tissue. By acquiring the actual measured values ​​of the carrier intensity distribution field and combining them with the microtubule skeleton polymerization rate and the extension orientation angle of the growth cone propulsion, the basic data of the initial distribution field are formed.

[0017] Real-time carrier intensity values ​​were acquired at different depths of optic nerve tissue using an optical coherence tomography (OCT) scanner. Acquisition points were set at preset intervals according to tissue depth. A three-dimensional coordinate system was established from the origin of the optic nerve to the edge of the lesion area. The carrier intensity value and corresponding spatial coordinates of each acquisition point were recorded to obtain spatial distribution data of carrier intensity. Tubulin in the microtubule skeleton was labeled using fluorescence labeling. The fluorescence intensity changes at corresponding locations of the acquisition points in the spatial distribution data of carrier intensity were monitored using confocal microscopy. The microtubule skeleton polymerization rate was calculated based on the linear relationship between the fluorescence intensity increment per unit time and the microtubule concentration. Simultaneously, the extension orientation angle of the growth cone tip relative to the axonal main axis was measured. Spatial mapping was performed between the spatial distribution data of carrier intensity and the corresponding microtubule skeleton polymerization rate and growth cone extension orientation angle. Intensity estimation of unacquired areas was performed using Kriging interpolation based on the known carrier intensity values ​​of acquisition points and their spatial correlation, constructing an initial distribution field basic data matrix containing three dimensions: carrier intensity, polymerization rate, and extension orientation angle.

[0018] Specifically, in one implementation, an optical coherence tomography scanner emits a near-infrared beam that penetrates the optic nerve tissue and uses the principle of interference to obtain carrier intensity reflection signals at different depths.

[0019] Specifically, the scanner performs continuous scanning along the longitudinal axis of the optic nerve, recording the three-dimensional coordinates and corresponding carrier intensity value at each scanning point. The carrier intensity value reflects the degree of response of the tissue at that location to the composite waveform. The three-dimensional coordinate system has the origin at the beginning of the optic nerve, with the Z-axis extending along the nerve fiber to the edge of the lesion area, and the X-axis and Y-axis perpendicular to the nerve's main axis to form a cross-sectional positioning.

[0020] It should be noted that the fluorescent labeling method specifically binds fluorescent dyes to tubulin, causing the microtubule skeleton to emit fluorescence under excitation at a specific wavelength. Confocal microscopy captures real-time fluorescence image sequences at each acquisition point in the spatial distribution data of the carrier intensity, and the fluorescence intensity values ​​are extracted using image processing algorithms.

[0021] Preferably, the fluorescence intensity increment ΔF is linearly related to the concentration C of newly polymerized tubulin, i.e., ΔF = k × C, where k is the fluorescence conversion coefficient. The microtubule skeleton polymerization rate is obtained by dividing the fluorescence intensity increment per unit time by the conversion coefficient. The growth cone extension orientation angle is determined by identifying the offset angle of the brightest fluorescent spot at the tip of the growth cone relative to the axonal main axis, and the offset angle includes two components in three-dimensional space: a horizontal offset angle and a vertical offset angle.

[0022] In one possible implementation, Kriging interpolation estimates the intensity of uncollected areas based on the principle of spatial autocorrelation.

[0023] For example, for any uncollected point P, its estimated carrier intensity is determined by a weighted average of surrounding known collection points, with the weighting coefficients calculated based on spatial distance and a variogram. The variogram describes the correlation decay law of carrier intensity in space. Through the above spatial mapping process, each spatial location point contains three key data dimensions: the carrier intensity value characterizes the spatial distribution characteristics of external stimuli, the microtubule skeleton aggregation rate reflects the dynamic response capability of axonal growth, and the growth cone extension orientation angle determines the axonal growth direction. The initial distribution field basic data matrix organizes and stores the data of these three dimensions according to spatial location, forming a complete initial state description of the optic nerve injury repair process.

[0024] Step S102: Identify the variation range of the microtubule skeleton polymerization rate based on the initial distribution field basic data, evaluate the correlation strength between the microtubule skeleton polymerization rate and the directional extension of the growth cone, and analyze the development trend of the microtubule skeleton polymerization rate by continuously monitoring the rate change records at different time points during the extension of the growth cone.

[0025] The microtubule skeleton aggregation rate values ​​of each spatial location point in the continuous time series are extracted from the initial distribution field basic data matrix. The ratio of the rate difference between adjacent sampling time points to the time interval is calculated. Based on the physiological characteristics of optic nerve axon growth, the sampling interval is set to a preset duration to obtain the rate change amplitude sequence data for each spatial location. Based on the rate change amplitude sequence data and the growth cone extension orientation angle value recorded at the corresponding time point, the Pearson correlation coefficient calculation method is used, with the rate change amplitude as the first variable and the change in extension orientation angle as the second variable, to calculate the correlation coefficient value between the two. If the absolute value of the correlation coefficient exceeds a preset threshold, the spatial location is marked as a strongly correlated region, forming a correlation strength distribution between aggregation rate and directional extension. By performing time series analysis on the rate change amplitude sequence of the strongly correlated region in the correlation strength distribution, the moving average method is used to calculate the average value of each data point in the sequence and the preset number of data points before and after it to replace the original value. The difference value between adjacent points in the smoothed sequence is calculated to identify the acceleration, deceleration, and turning point characteristics of rate change, and to determine the rate change characteristic pattern of each time period. Based on the turning point and the rate values ​​before and after it identified in the rate change feature pattern, the rate data points within each preset time period before and after the turning point are linearly fitted using the least squares method. The slope of the fitted line is calculated as a local trend value. The overall development trend of the microtubule skeleton polymerization rate change is judged based on the positive and negative signs and magnitude of multiple local trend values.

[0026] Specifically, in one implementation, when extracting the rate change amplitude sequence from the initial distribution field basic data matrix, the sampling interval is set according to the physiological cycle characteristics of optic nerve axon growth.

[0027] Specifically, the growth cones of optic nerve axons exhibit a periodic response to compound waveform stimulation. The response period is typically related to microtubule polymerization kinetics, and the sampling interval is set to one-tenth of this response period to ensure the capture of detailed features of rate changes. The calculation of the rate change amplitude involves differential operations on rate values ​​at adjacent time points.

[0028] For example, if the polymerization rate at time t1 is v1 and the polymerization rate at time t2 is v2, then the rate change amplitude is (v2-v1) / (t2-t1), which reflects the degree of acceleration or deceleration of microtubule skeleton polymerization. By continuously sampling each spatial location point, a time series of rate change amplitudes reflecting the dynamic response characteristics of that location is formed. The sequence length is determined according to the monitoring duration and sampling frequency.

[0029] Preferably, in the calculation of the Pearson correlation coefficient, the rate change amplitude sequence is used as the first variable X, and the change in the growth cone extension orientation angle sequence is used as the second variable Y. The formula for calculating the correlation coefficient r is: r represents the correlation coefficient, X i Y represents the i-th observation of the first variable. i This represents the i-th observation of the second variable. This represents the average of the first variable. The coefficient represents the mean of the second variable, and n represents the number of samples in the observed data, i.e., the total number of data pairs. This formula is used to calculate the degree of linear correlation between the two variables. The absolute value of the correlation coefficient reflects the degree of linear association between the two variables, ranging from 0 to 1. When |r| is greater than 0.7, a strong correlation is considered to exist, and this spatial location is marked as a strongly correlated region. This strong correlation indicates that the change in the microtubule skeleton aggregation rate at this location is highly synchronized with the directional extension behavior of the growth cone, making it a key location for axonal regeneration pathway control. By calculating the correlation degree for all spatial locations, a complete correlation strength distribution map is constructed, which visually demonstrates the differences in the response sensitivity of different regions in the optic nerve tissue to composite waveform stimulation.

[0030] In one possible implementation, the choice of window width for the moving average method directly affects the smoothing effect. If the window is too small, the smoothing is insufficient, retaining too much noise; if the window is too large, the smoothing is over-smoothed, losing important information about rate changes.

[0031] For example, for data sampled at a frequency of 10 times per second, the moving average window is set to 5 data points, or a time span of 0.5 seconds.

[0032] Specifically, the moving average calculation process is as follows: for the i-th data point in the sequence, take the n data points before and after it, for a total of 2n+1 data points, and calculate the arithmetic mean as the smoothed value. The smoothed sequence retains the overall trend of the original data while filtering out high-frequency noise interference. Difference calculation identifies the direction and magnitude of rate changes through the difference between adjacent smoothed values; positive differences indicate acceleration, negative differences indicate deceleration, and a difference value close to zero indicates a stable state. Furthermore, the identification of inflection points is based on the sign change of the difference values. When consecutive positive differences turn into negative differences, or consecutive negative differences turn into positive differences, it is marked as an inflection point. The time corresponding to the inflection point reflects the key turning points in the microtubule skeleton aggregation behavior, which are closely related to the growth cone encountering the tissue barrier or changes in the guiding signal.

[0033] In one embodiment, the least squares linear fitting process includes: selecting rate data for 30 seconds before and after the inflection point to construct a set of time and rate data points. The slope k and intercept b of the fitted line are solved by minimizing the sum of squared distances from the data points to the fitted line. The slope k physically represents the average rate of change; a positive slope indicates an overall upward trend in rate, a negative slope indicates a downward trend, and the absolute value of the slope reflects the degree of drastic change.

[0034] Understandably, by locally fitting multiple inflection point intervals, a series of local trend values ​​are obtained. The statistical characteristics of these local trend values, such as the mean, standard deviation, and variation pattern, together constitute a comprehensive basis for judging the overall development trend of the microtubule skeleton polymerization rate. When most local trend values ​​are positive and large, it is judged as an upward trend; when the trend values ​​fluctuate around zero, it is judged as a stable trend; when most trend values ​​are negative, it is judged as a downward trend.

[0035] For example, in the early stages of optic nerve injury repair, the microtubule skeleton aggregation rate usually shows an upward trend, reflecting the positive response of axons to repair signals; in the intermediate stage, the rate tends to stabilize, indicating that axonal extension has entered a stable growth period; if a downward trend occurs, it suggests that growth obstacles or inhibition signals have been encountered, and it is necessary to adjust the composite waveform parameters to maintain an effective repair process.

[0036] Step S103: Analyze the situation where the development trend of the microtubule skeleton polymerization rate exceeds the preset critical value, evaluate the amplitude of increasing the modulation wave envelope gradient adjustment when the development trend of polymerization rate changes upward, and obtain the envelope gradient speed control combination by adjusting the control amount of gradient adjustment through the orientation angle of the growth cone.

[0037] The trend value of the microtubule skeleton polymerization rate is compared with a preset critical value. If the trend value exceeds the upper limit of the critical value, the absolute value of the rate and the acceleration at the time of exceeding the limit are extracted. The product of the absolute value of the rate and the acceleration is calculated as a risk index. Based on the magnitude of the risk index, three risk levels—low, medium, and high—are defined, each corresponding to a preset initial amplification coefficient for the modulation wave envelope gradient adjustment. The orientation angle offset data of the growth cone tip relative to the axon main axis is collected in real time, and the rate of change of the orientation angle offset is calculated. The basic control quantity for envelope gradient adjustment is determined based on the product of the offset rate and the initial amplification coefficient. If the orientation angle offset exceeds a preset safety range, the basic control quantity is multiplied by a preset amplification coefficient to obtain the envelope adjustment parameters for the angle response. The envelope gradient speed of the carrier wave is adjusted using the envelope adjustment parameters for the angle response. Simultaneously, the difference between the actual extension speed of the growth cone and the ideal extension speed required by the target repair path is monitored. A proportional-integral control algorithm is used to calculate a compensation adjustment amount based on the speed difference and a preset proportional coefficient and integral time constant. The compensation adjustment amount is then superimposed on the envelope adjustment parameters to form a comprehensive adjustment command. The gradual velocity value of the modulation wave envelope is updated in real time according to the comprehensive adjustment command. The updated carrier strength is monitored to see if it is close to the tissue tolerance threshold. If the carrier strength reaches the preset ratio of the threshold, the envelope gradual velocity is reduced by a predetermined step size. The adjustment is repeated until the carrier strength is lower than the safety threshold and the extension speed meets the requirements, thus obtaining the envelope gradual velocity control combination.

[0038] Specifically, in one implementation, the monitoring of the microtubule skeleton polymerization rate change trend is based on the aforementioned overall development trend value. When this value exceeds a preset critical upper limit, it indicates that axon growth has entered a rapid response period. The absolute value of the rate reflects the polymerization intensity at the current moment, while the acceleration reflects the dynamic characteristics of the polymerization process. The risk index formed by the product of the two comprehensively assesses the stability of axon growth. The risk level is divided into three levels: low risk corresponds to a risk index less than a preset lower limit, medium risk corresponds to a risk index between the upper and lower limits, and high risk corresponds to a risk index exceeding the upper limit, which are mapped to initial amplification coefficients of 1.2, 1.5, and 1.8, respectively. The real-time acquisition frequency of the growth cone orientation angle offset is synchronized with the sampling frequency of the microtubule skeleton polymerization rate to ensure the correspondence between the two in the time dimension. The orientation angle offset refers to the angle between the growth direction of the growth cone tip and the axon main axis, which includes both horizontal and vertical components in three-dimensional space. The offset change rate is calculated by dividing the angle difference between adjacent sampling times by the time interval. The basic control value is equal to the product of the offset change rate and the initial increase coefficient. This value directly reflects the degree of influence of the angular offset on the envelope adjustment.

[0039] Preferably, the preset safety range is set to ±15 degrees. When the orientation angle deviates beyond this range, it indicates that the growth cone may have deviated from the predetermined path. At this point, an amplification factor mechanism is introduced, which is dynamically determined based on the degree of deviation: 1.3 for deviations between 15 and 20 degrees; 1.6 for deviations between 20 and 25 degrees; and 2.0 for deviations exceeding 25 degrees. The angle response envelope adjustment parameter is obtained by multiplying the basic control value by the amplification factor. This graded amplification mechanism can take corresponding corrective measures based on the degree of deviation, ensuring the repair effect while avoiding tissue damage caused by over-adjustment.

[0040] In one possible implementation, the application of a proportional-integral (PI) controller involves setting two key parameters. The proportional gain determines the controller's response strength to the current speed deviation, while the integral time constant affects the handling of accumulated historical deviations.

[0041] For example, the proportional gain is set to 0.8 to give the controller moderate sensitivity to speed deviations; the integral time constant is set to 2 seconds to ensure that the effects of historical deviations gradually decay without causing overcompensation.

[0042] Specifically, the calculation of the velocity difference involves comparing the actual extension velocity of the growth cone with the ideal extension velocity required by the target repair path. The actual extension velocity is obtained by dividing the change in growth cone position between two consecutive moments by the time interval, while the ideal extension velocity is determined based on the length of the damaged area and the expected repair time. The compensation adjustment consists of two parts: a proportional part equal to the velocity difference multiplied by a proportionality coefficient, and an integral part equal to the cumulative value of the velocity difference within the time window divided by the integral time constant. The two parts are added together to obtain the total compensation adjustment, which is superimposed on the envelope adjustment parameters of the angle response to form a comprehensive adjustment command. Furthermore, real-time monitoring of the carrier intensity is achieved through sensing points set at key locations in the optic nerve tissue. The tissue tolerance threshold is predetermined based on the electrophysiological characteristics of optic nerve cells, typically set as a critical intensity value to avoid causing abnormal cell membrane depolarization. The preset proportion is set to 0.85 of the threshold, and a safety protection mechanism is triggered when the carrier intensity reaches this proportion.

[0043] In one embodiment, the envelope gradient rate is adjusted using a step-down strategy. A predetermined step size is set to 5% of the current gradient rate, and the carrier strength and spread velocity are reassessed after each adjustment. If the carrier strength still exceeds the safety limit, the rate continues to decrease by the step size; if the spread velocity is below the required lower limit, the step size is reduced to 2.5% for fine-tuning. This iterative process continues until a balance is found that simultaneously satisfies the strength safety constraints and speed performance requirements. During the iterative adjustment process, the changing trends of two key indicators need to be monitored: the rate of decrease of the carrier strength and the degree to which the spread velocity is maintained. When the carrier strength stabilizes below the safety threshold and the fluctuation does not exceed 3% within three consecutive sampling periods, the strength control is considered to have reached a stable state; when the deviation of the spread velocity from the ideal velocity is less than 10% and remains stable, the speed control is considered to meet the requirements. Only when both conditions are met simultaneously is the final envelope gradient rate control combination determined.

[0044] For example, in the critical stage of optic nerve injury repair, when a sharp increase in the microtubule skeleton polymerization rate and a significant deviation in the growth cone are detected, the above-mentioned control mechanism can respond quickly: first, the modulation amplitude is increased according to the risk level, and then the control quantity is further adjusted according to the degree of angular deviation. The proportional-integral controller integrates the speed deviation to form a precise adjustment command, thereby realizing the dynamic optimization of the composite waveform envelope. This ensures that the axon extends along the correct path and avoids tissue damage or path deviation caused by excessive stimulation.

[0045] Step S104: Extract the candidate output of the optimal waveform modulation combination from the adjusted envelope gradual speed control combination, and determine the quantitative result of the deviation of the extension path by comparing the actual path of directional extension with the expected damage repair trajectory through trajectory overlap measurement.

[0046] Stability is assessed based on the carrier intensity fluctuation within a preset time window in the envelope gradient velocity control combination. Smoothness is assessed by accumulating the absolute differences between envelope values ​​at adjacent times. Consistency is assessed based on the deviation between the modulation frequency and the reference frequency. A comprehensive score is obtained by normalizing each indicator and then weighting the sum. Schemes with scores exceeding a preset threshold are selected as candidate waveform modulation combinations. The actual extension path of the growth cone under the action of the candidate waveform modulation combinations is continuously sampled to obtain the three-dimensional coordinate sequence at each sampling time. Simultaneously, the coordinate sequence at the corresponding time on the expected damage repair trajectory is extracted. The maximum Euclidean distance between each pair of corresponding points between the two trajectories is calculated using Hausdorff distance to obtain the trajectory overlap value. Based on the microtubule skeleton aggregation speed at the time corresponding to the trajectory overlap value being lower than a preset standard, combined with the deviation distance between the actual path and the expected trajectory at that time, the product of the deviation distance and the aggregation speed is divided by a preset normalization coefficient to obtain the quantitative result of the extension path deviation.

[0047] Specifically, in one implementation, the evaluation of the envelope gradient speed control combination involves quantitative indicators in three dimensions.

[0048] Specifically, carrier strength stability is measured by calculating the standard deviation of the carrier strength within a preset time window; a smaller standard deviation indicates higher stability. Envelope smoothness is represented by the sum of the absolute values ​​of the differences between envelope values ​​at adjacent times; a smaller sum indicates a smoother transition process. Modulation frequency consistency is evaluated by the percentage deviation between the actual modulation frequency and the reference frequency; a smaller deviation indicates better consistency. The normalization of the three indicators uses a linear mapping method, mapping each indicator value to the range of 0 to 1. The weighting coefficients for the weighted summation are set according to the actual needs of optic nerve repair: stability weight is 0.4, smoothness weight is 0.35, and consistency weight is 0.25. Schemes with a comprehensive score exceeding 0.7 are selected as candidate waveform modulation combinations. This multi-dimensional evaluation ensures that the selected candidate schemes meet the basic requirements in all performance indicators.

[0049] Preferably, the calculation process of Hausdorff distance includes obtaining the bidirectional distance.

[0050] For example, starting from each sampling point on the actual extended path, find the point closest to the expected repair trajectory, and record the maximum value among these minimum distances as the forward Hausdorff distance; then calculate the distance from the expected trajectory to the actual path in reverse, and take the larger value of the two distances as the final Hausdorff distance. This distance value directly reflects the degree of spatial deviation between the two trajectories; the smaller the distance, the higher the overlap between the trajectories, and the better the path control effect.

[0051] In one possible implementation, the quantification of deviation requires comprehensive consideration of spatial deviation and velocity factors. When the trajectory overlap value is below a preset standard of 0.8, the microtubule skeleton aggregation velocity value and the actual deviation distance at that moment are extracted. The normalization coefficient is predetermined based on the typical scale and growth rate range of optic nerve tissue, and is usually set to ensure that the quantification result falls within the range of 0 to 100. Furthermore, the physical meaning of the deviation quantification result lies in comprehensively reflecting the dynamic deviation characteristics of axonal growth. A large deviation distance but a slow aggregation speed indicates that the deviation is slow and controllable; a small deviation distance but a fast aggregation speed suggests a risk of rapid deviation. Through the product of deviation distance and aggregation speed, the quantification result simultaneously considers the spatial magnitude and temporal urgency of the deviation.

[0052] Step S105: Perform deviation classification processing on the quantification results of the deviation degree of the extended path, obtain the high deviation subset in the classification results, and generate a compensation signal by combining the development trend of the aggregation rate change, so as to obtain the compensation composite waveform output combination.

[0053] Based on the magnitude of the quantization results of the deviation degree of the extended path, data points are classified according to preset low and high deviation thresholds. Quantization results less than the low deviation threshold are classified as low deviation, those between the low and high deviation thresholds as medium deviation, and those exceeding the high deviation threshold as high deviation. All data points in the high deviation category are extracted to form a high deviation subset. The trend of microtubule skeleton aggregation rate change at each data point in the high deviation subset is extracted. A compensation intensity benchmark value is calculated based on the sign and absolute value of the trend slope. This benchmark value is multiplied by the corresponding deviation degree quantization value to obtain the compensation intensity. The amplitude and phase parameters of the compensation signal are determined based on the compensation intensity. The amplitude parameters of the compensation signal are used to modulate the carrier amplitude of the current composite waveform. The phase parameters of the compensation signal are used to shift the phase of the modulated wave envelope. The modulated carrier and the phase-shifted envelope are then superimposed to obtain the compensated composite waveform signal. The compensated composite waveform signal is fused with the aforementioned envelope gradient speed control combination. The frequency, amplitude, and envelope gradient rate parameters are weighted by preset fusion weight coefficients to form a compensated composite waveform output combination.

[0054] Specifically, in one implementation, the classification of the degree of deviation of the extended path is based on a threshold setting according to the numerical distribution characteristics of the quantization results.

[0055] Specifically, by statistically analyzing the degree of deviation in historical repair data, a probability distribution curve of the deviation is determined. The 33rd percentile of the distribution curve is set as the low deviation threshold, and the 67th percentile as the high deviation threshold. This threshold setting method based on statistical distribution can adapt to the differences in optic nerve tissue among different individuals, avoiding classification bias that may be caused by fixed thresholds. The extraction of the high deviation subset includes not only the numerical value of the deviation degree, but also the corresponding timestamps, spatial coordinates, and microtubule skeleton aggregation rate, among other related information. Each data point in the high deviation subset represents a key deviation event in the axon growth process, and the timing and location of these events are crucial for the accurate localization of subsequent compensation signals. By establishing a spatiotemporal index for the high deviation subset, the tissue regions requiring focused compensation can be quickly located.

[0056] Preferably, the calculation of the compensation intensity benchmark value adopts a piecewise function approach, employing different calculation strategies based on different ranges of the trend slope. When the trend slope is positive and less than a preset upper limit, the compensation intensity benchmark value equals the slope value multiplied by a first coefficient; when the slope exceeds the upper limit, a logarithmic function is used for nonlinear mapping to avoid excessive compensation intensity leading to tissue damage; when the slope is negative, the compensation intensity benchmark value is taken as the square root of the absolute value of the slope. This approach provides appropriate compensation when the aggregation rate decreases, avoiding reverse deviation caused by overstimulation. The product operation of the compensation intensity benchmark value and the quantified value of the deviation ensures that the strength of the compensation signal considers both the current deviation state and the dynamic characteristics of the development trend, achieving comprehensive compensation for both static deviation and dynamic trend.

[0057] In one possible implementation, the amplitude parameter of the compensation signal directly affects the amplitude modulation process of the carrier wave. The amplitude modulation employs a multiplicative modulation method, multiplying the amplitude of the original carrier signal by a compensation factor, where the compensation factor equals 1 plus the normalized amplitude parameter. This modulation method ensures that the fundamental characteristics of the carrier wave are not destroyed, while simultaneously superimposing compensation information.

[0058] For example, phase shifting is achieved through Hilbert transform. The original modulated wave envelope is transformed by Hilbert to obtain an analytic signal. Phase shifting is achieved by rotating the phase angle of the analytic signal, where the shift angle is determined by the phase parameters of the compensation signal. The phase-shifted envelope is then superimposed with the amplitude-modulated carrier wave in the time domain to form a compensated composite waveform signal.

[0059] Specifically, the weighting coefficients in the parameter fusion process take into account the degree of influence of different parameters on the repair effect. The fusion weight for the frequency parameter is set to 0.3 because frequency changes have a relatively slow effect on neural responses; the fusion weight for the amplitude parameter is set to 0.5, reflecting the direct influence of amplitude on stimulus intensity; and the fusion weight for the envelope gradation rate is set to 0.2 to maintain the smoothness of the gradation process. Furthermore, the fusion calculation adopts a weighted sum form: the fused parameter equals the original parameter multiplied by the preservation weight plus the compensation parameter multiplied by the compensation weight.

[0060] For example, the fused frequency equals the original frequency multiplied by 0.7 plus the compensation frequency multiplied by 0.3. This fusion method retains the basic characteristics of the original control combination while introducing targeted compensation adjustments.

[0061] In one embodiment, the compensated composite waveform output combination also needs to undergo safety verification. By calculating the peak power, average power, and spectral distribution of the output waveform, it is confirmed that all indicators are within the safe tolerance range of optic nerve tissue. If any indicator exceeds the limit, all parameter values ​​are reduced proportionally until the safety requirements are met.

[0062] Step S106: Update the spatial intensity distribution field measurement value within the optic nerve tissue by combining the compensated composite waveform outputs, evaluate whether the updated distribution field measurement value meets the standard for precise control, and lock the optimal waveform modulation combination if the deviation of the distribution field measurement value is lower than the preset critical value; otherwise, loop back to the real-time acquisition stage to reacquire the intensity distribution measurement value and microtube extension rate.

[0063] The compensated composite waveform output is applied to optic nerve tissue. Carrier intensity response values ​​are collected at preset monitoring points. Based on the correspondence between the response values ​​and spatial coordinates, the intensity distribution field of the entire tissue region is reconstructed using the Kriging spatial interpolation method, resulting in updated spatial intensity variation distribution field measurements. The updated distribution field measurements are then compared point-by-point with the preset ideal distribution field values ​​to obtain the deviation values ​​at each spatial location. The overall deviation index is obtained by calculating the root mean square value of all deviation values. If the overall deviation index is lower than a preset critical value, the distribution field is deemed to meet the precision control standard. If the distribution field meets the precision control standard, the current carrier frequency, amplitude, phase parameters, and the gradient rate and shape parameters of the modulation wave envelope are extracted. These parameters are combined and stored according to a predetermined format to form a waveform modulation combination configuration. This configuration is locked as the optimal waveform modulation combination, where the carrier intensity and envelope adjustment parameters are fused with an intensity weight of 0.6 and an envelope weight of 0.4. If the overall deviation index exceeds the preset critical value, the system returns to the real-time acquisition stage to reacquire the carrier intensity distribution measurement values ​​of each monitoring point. At the same time, the microtubule skeleton extension rate at the corresponding location is extracted. Based on the newly acquired intensity distribution and extension rate data, the deviation is recalculated and a compensation signal is generated.

[0064] Specifically, in one implementation, the compensated composite waveform output combination is output to the optic nerve tissue through a multi-channel signal generator, and the monitoring points are arranged inside the tissue in a three-dimensional grid manner.

[0065] Specifically, a monitoring layer is set every 2 millimeters along the longitudinal axis of the optic nerve, with 16 monitoring points arranged in a 4×4 matrix on each layer, forming a three-dimensional monitoring network. Each monitoring point acquires carrier intensity response values ​​in real time via a microelectrode array; these response values ​​reflect the electrophysiological response intensity of the tissue at that location to the composite waveform. The Kriging spatial interpolation method, based on geostatistical principles, estimates the intensity distribution at unknown locations using the intensity values ​​of known monitoring points. The interpolation process first calculates the semi-variogram among the monitoring points, which describes the decrease in spatial correlation of intensity values ​​with increasing distance. Based on the spatial correlation structure determined by the semi-variogram, for each location to be interpolated, monitoring point data within its neighborhood are selected, and interpolation weight coefficients are obtained by solving the Kriging equations. The intensity value of each monitoring point is multiplied by its corresponding weight coefficient and summed to obtain the interpolated intensity value at that location. By performing point-by-point interpolation across the entire three-dimensional space, a continuous spatial intensity variation distribution field is reconstructed. This interpolation method not only provides intensity estimates but also the spatial distribution of estimation errors, providing a quantitative basis for uncertainty in subsequent precise control assessments.

[0066] Preferably, the ideal distribution field values ​​are set based on the physiological needs of optic nerve axon regeneration. At the axon initiation segment, the ideal intensity is set to a higher value to stimulate the initiation of the growth cone; in the intermediate extension segment, the intensity gradually decreases to guide directional growth; and near the target region, the intensity increases again to promote synaptic connection formation. This spatial distribution pattern conforms to the natural laws of axon growth.

[0067] In one possible implementation, point-by-point difference calculation is performed using three-dimensional matrix operations. The updated distribution field measurements and the ideal distribution field values ​​are stored as three-dimensional matrices, and the difference between corresponding elements yields the deviation matrix. The root mean square (RMS) value is calculated by first squaring all elements in the deviation matrix, then calculating the arithmetic mean of the squares, and finally taking the square root of the mean. This RMS value comprehensively reflects the degree of deviation throughout the entire space and is more sensitive to large deviations than a simple average deviation.

[0068] For example, the determination of the preset threshold value takes into account the balance between the physiological tolerance of optic nerve tissue and the repair effect. Setting the threshold value too low will lead to frequent cyclic adjustments, affecting the stability of the repair process; setting it too high may allow for excessive deviations, reducing the repair accuracy. Through preliminary experimental calibration, the threshold value is usually set at 15% of the average intensity of the ideal distribution field.

[0069] Specifically, the waveform modulation combination configuration is stored using a structured data format. Carrier parameters include center frequency, modulation depth, and initial phase; envelope parameters include rise time, plateau duration, fall time, and control point coordinates of the envelope shape function. Each parameter is organized according to a predetermined data structure to form a complete configuration file. The fusion weights reflect the different contributions of the carrier and envelope to the repair effect: the carrier primarily affects the excitability of nerve fibers, with a weight of 0.6; the envelope primarily controls the temporal characteristics of the stimulus, with a weight of 0.4. Furthermore, when the overall deviation index exceeds a critical value, the loop control mechanism is activated. The system returns to the initial stage of data acquisition but retains historical information from the previous loop. The new round of acquisition not only obtains the current intensity distribution but also records the differences from the previous acquisition, forming a dynamic trend. Re-acquisition of the microtubule skeleton extension rate focuses on areas with large deviations, obtaining more accurate local information by increasing the sampling density in these areas.

[0070] In one embodiment, an adaptive adjustment mechanism is introduced into the compensation signal calculation based on newly acquired data. The gain coefficient of the compensation intensity is dynamically adjusted according to the number of iterations and the deviation convergence trend. If the deviation shows a convergence trend, the current gain is maintained; if the deviation oscillates and does not converge, the gain is reduced to improve stability; if the deviation monotonically increases, the effectiveness of the entire control strategy needs to be reassessed.

[0071] Step S107: Deploy the envelope gradient adjustment control strategy according to the locked optimal waveform modulation combination, identify the response time of the microtubule skeleton polymerization rate and integrate the orientation angle data of the growth cone advancement, analyze the polymerization rate response characteristics and orientation angle change trend, and obtain the final damage repair path control scheme.

[0072] Based on the parameter configuration in the locked optimal waveform modulation combination, the carrier reference frequency and amplitude range are extracted. The upper and lower limits of frequency modulation are determined through the linear relationship between carrier frequency and modulation depth. The step interval of amplitude adjustment is set according to the tenths of the amplitude range. The boundary values ​​and interval values ​​are encoded to form the execution parameter set for envelope gradient adjustment control. A carrier stimulation signal with abrupt amplitude change is applied to the microtubule skeleton aggregation rate. The time interval required from the start of stimulation to the rate reaching 95% of the steady-state value is recorded as the response time. Simultaneously, the orientation angle sequence of the growth cone advancement is collected within the response time. The angle change rate data is obtained by calculating the difference between adjacent values ​​of the angle sequence. The execution parameter set is stored in association with the response time. The response time is divided into three intervals—initial segment, transition segment, and stable segment—at one-third and two-thirds of the time. The average value and standard deviation of the aggregation rate in each interval are calculated. The response characteristic type is determined based on the change of the average value. If the initial segment to the stable segment shows a monotonically increasing trend, it is classified as a positive response characteristic; otherwise, it is classified as an oscillating response characteristic. The response characteristic type and the angle change rate data are correlated and matched. If it is a positive response characteristic and the angle change rate is less than a preset threshold, the path control scheme is set to gradual control of continuous waveform output. If it is an oscillating response characteristic or the angle change rate exceeds the threshold, it is set to pulse control of intermittent waveform output, thus forming the final damage repair path control scheme.

[0073] Specifically, in one implementation, the parameter configuration of the optimal waveform modulation combination includes control parameters in multiple dimensions, which have been optimized in the early stage to reach a local optimum.

[0074] Specifically, the carrier reference frequency is typically set within the range of 1-10 kHz. This frequency range is determined based on the electrophysiological characteristics of optic nerve fibers, effectively stimulating neural responses without causing tissue fatigue. The amplitude range is set considering the balance between the tissue's safety threshold and the effective stimulation intensity, typically between 0.5-5 mA. The linear relationship between carrier frequency and modulation depth is obtained through experimental calibration. As the carrier frequency increases, the modulation depth needs to decrease accordingly to maintain a constant energy input. This linear relationship can be expressed as: modulation depth equals reference depth minus the frequency coefficient multiplied by the frequency offset. Based on this relationship, the allowable modulation depth range at different frequencies can be determined, thus obtaining the upper and lower limits of frequency modulation. The amplitude adjustment step interval uses a ten-position division method, dividing the entire amplitude range into ten equal intervals. The boundary value of each interval serves as an adjustment level. This discretization process ensures both adjustment accuracy and simplifies control complexity.

[0075] Preferably, the parameter set is encoded in a structured array format, comprising three parts: a frequency boundary array, an amplitude interval array, and a time control array. The frequency boundary array stores the upper and lower frequency limits; the amplitude interval array stores the amplitude values ​​for ten levels; and the time control array stores the time parameters for the gradual change process.

[0076] In one possible implementation, the carrier stimulus signal with abrupt amplitude changes is modulated using a step function. Initially, the carrier amplitude remains at the baseline level, then abruptly jumps to the target amplitude at a predetermined time. This abrupt change triggers a transient response in the microtubule skeleton's aggregation rate. The response time is measured in real-time, starting from the moment of stimulus application and continuously monitoring changes in the aggregation rate. The time interval at which the rate reaches and stabilizes at 95% of the final steady-state value is recorded as the response time. This 95% criterion is based on the concept of steady-state error bands in control theory, accurately reflecting the time it takes for the system to reach stability while avoiding the time delay caused by waiting for complete stability.

[0077] For example, the orientation angle of the growth cone advancement is obtained through image recognition methods. A high-speed camera system acquires a microscopic image of the growth cone every 100 milliseconds, identifies the contour of the growth cone using an edge detection algorithm, determines its principal axis direction, and calculates the angle between the principal axis and the reference coordinate system as the orientation angle. The difference calculation of the angle sequence uses a forward difference method, i.e., subtracting the angle from the previous moment's angle at the next moment and then dividing by the time interval to obtain the angle change rate.

[0078] Specifically, the response time intervals are divided based on the system's dynamic characteristics. The initial segment corresponds to the system's delay and rise phase, accounting for the first third of the total response time; the transition segment corresponds to the system's adjustment phase, from one-third to two-thirds of the time; and the steady segment corresponds to the stage where the system reaches steady state, which is the last third of the time. Within each interval, the arithmetic mean of all sampled aggregation rates is calculated to reflect the overall level of that interval, and the standard deviation is calculated to reflect the degree of fluctuation. Furthermore, the response characteristic type is determined using a trend analysis method. If the average values ​​of the three intervals show an increasing trend, and the growth rate gradually decreases, it indicates that the system response is stable and orderly, and is classified as a positive response characteristic; if the average values ​​show a pattern of first increasing and then decreasing or fluctuating back and forth, it indicates that the system has oscillating or unstable factors, and is classified as an oscillating response characteristic.

[0079] In one embodiment, the control scheme selection logic comprehensively considers response characteristics and angular stability. The progressive modulation mode employs a continuously output composite waveform, with waveform parameters changing slowly according to a preset time function, suitable for situations where the system response is stable and the direction is stable. The pulse modulation mode uses an intermittent output method, with each pulse lasting a fixed duration before stopping, and the next pulse being output after a certain interval. This method avoids oscillation accumulation and directional loss of control. The resulting damage repair path control scheme not only includes the selection of waveform output modes but also specific parameter configurations and timing control logic. This scheme can adaptively adjust stimulation parameters based on the real-time response characteristics of optic nerve tissue, achieving precise guidance of the axonal regeneration path.

[0080] The above-disclosed embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of the invention. Those skilled in the art will understand that implementing all or part of the above-described embodiments and making equivalent changes in accordance with the claims of the present invention are still within the scope of the invention.

Claims

1. A method for controlling the composite output of a medium-frequency carrier wave and a low-frequency modulated wave, characterized in that, include: Acquire the spatial intensity variation distribution of the composite waveform within the optic nerve tissue to generate basic data for the initial distribution field; Based on the initial distribution field data, the variation range of the microtubule skeleton polymerization rate is identified, the correlation strength between the microtubule skeleton polymerization rate and the directional extension of the growth cone is calculated, and the development trend of the microtubule skeleton polymerization rate variation is determined. Analyze the relationship between the development trend of the microtubule skeleton polymerization rate and the preset critical value, and adjust the modulation wave envelope gradient speed to generate an envelope gradient speed control combination; Candidate waveform modulation combinations are extracted from the envelope gradient speed control combination, and the actual extension path of the growth cone is compared with the expected damage repair trajectory to determine the quantitative result of the deviation of the extension path. The deviation of the extended path is classified according to the quantitative results, and a high deviation subset is extracted and combined with the development trend of the microtubule skeleton polymerization rate to generate a compensated composite waveform output combination. The measured values ​​of spatial intensity variation distribution field are updated by combining the compensated composite waveform outputs, and the optimal waveform modulation combination is locked.

2. The composite output control method of intermediate frequency carrier and low frequency modulated wave according to claim 1, characterized in that, The process of acquiring the spatial intensity variation distribution of the composite waveform within the optic nerve tissue to generate initial distribution field baseline data includes: Carrier intensity values ​​at different depths of optic nerve tissue are collected. Acquisition points are set according to preset intervals, and a three-dimensional coordinate system is established to record the carrier intensity values ​​and corresponding spatial coordinates, generating carrier intensity spatial distribution data. Fluorescence intensity changes at corresponding positions of each acquisition point in the carrier intensity spatial distribution data are monitored. The microtubule skeleton polymerization rate is calculated based on the fluorescence intensity increment, and the extension orientation angle of the growth cone tip relative to the axonal main axis is measured. Spatial mapping is performed based on the carrier intensity spatial distribution data, the microtubule skeleton polymerization rate, and the extension orientation angle to construct an initial distribution field basic data matrix.

3. The composite output control method of intermediate frequency carrier and low frequency modulated wave according to claim 1, characterized in that, The process of identifying the variation range of the microtubule skeleton polymerization rate, calculating the correlation strength between the microtubule skeleton polymerization rate and the directional elongation of the growth cone, and determining the development trend of the microtubule skeleton polymerization rate includes: Extract the microtubule skeleton polymerization rate values ​​at each spatial location point, calculate the ratio of the rate difference between adjacent time points to the time interval, and generate a rate change amplitude sequence data; calculate the correlation coefficient between the rate change amplitude sequence data and the growth cone extension orientation angle value at the corresponding time point, mark the spatial locations where the absolute value of the correlation coefficient exceeds a preset threshold as strongly correlated regions, generate a correlation intensity distribution, and determine the development trend of the microtubule skeleton polymerization rate change.

4. The composite output control method of intermediate frequency carrier and low frequency modulated wave according to claim 1, characterized in that, The analysis of the relationship between the development trend of the microtubule skeleton polymerization rate and the preset critical value, and the adjustment of the modulation wave envelope gradient velocity to generate an envelope gradient velocity control combination, includes: The development trend value of the microtubule skeleton polymerization rate is compared with a preset critical value. The product of the absolute value of the rate and the acceleration at the time of exceeding the limit is calculated as a risk index. The risk level is divided according to the risk index, and the modulation wave envelope gradient adjustment amplification coefficient is determined. The envelope gradient adjustment control quantity is determined according to the offset change rate of the growth cone orientation angle and the amplification coefficient. The compensation adjustment quantity is calculated according to the difference between the actual extension speed of the growth cone and the speed of the target repair path, and superimposed on the control quantity to generate a comprehensive adjustment command. The modulation wave envelope gradient speed value is updated according to the comprehensive adjustment command to generate the envelope gradient speed control combination.

5. The composite output control method of intermediate frequency carrier and low frequency modulated wave according to claim 1, characterized in that, The step of extracting candidate waveform modulation combinations from the envelope gradient velocity control combination, comparing the actual extension path of the growth cone with the expected damage repair trajectory, and determining the quantitative result of the deviation of the extension path includes: The carrier intensity fluctuation amplitude, envelope value difference accumulation smoothness, and modulation frequency deviation are evaluated from the envelope gradual velocity control combination. After normalization, the weighted sum is used to generate a comprehensive score. Schemes with scores exceeding a preset threshold are selected as candidate waveform modulation combinations. The coordinate sequence corresponding to the expected damage repair trajectory is extracted to generate the quantitative result of the deviation of the extended path.

6. The composite output control method of intermediate frequency carrier and low frequency modulated wave according to claim 1, characterized in that, The step of classifying the data based on the quantification results of the deviation of the extended path, extracting a high-deviation subset, and combining it with the trend of the microtubule skeleton polymerization rate change to generate a compensated composite waveform output combination includes: Based on the magnitude of the quantification result of the deviation degree of the extended path, the data points are classified into low, medium, and high deviation categories according to preset low and high deviation thresholds. Data points of the high deviation category are extracted to form a high deviation subset. The development trend of the microtubule skeleton aggregation rate at the corresponding time of each data point in the high deviation subset is extracted, and the product of the trend slope and the quantification value of the deviation degree is calculated to determine the amplitude and phase parameters of the compensation signal. The amplitude of the compensation signal is used to modulate the carrier amplitude and offset the phase of the modulated wave envelope to generate the compensated composite waveform output combination.

7. The composite output control method of intermediate frequency carrier and low frequency modulated wave according to claim 1, characterized in that, The locked optimal waveform modulation combination includes: The compensated composite waveform output is applied to the optic nerve tissue to collect carrier intensity response values ​​at monitoring points. The intensity distribution field is reconstructed using Kriging spatial interpolation to generate updated spatial intensity change distribution field measurements. The point-by-point difference between the updated distribution field measurements and the ideal distribution field values ​​is calculated, and the root mean square value is obtained as the overall deviation index to determine if it meets the precision control standard. The carrier frequency, amplitude, phase, and modulation envelope parameters are extracted and locked as the optimal waveform modulation combination.

8. The composite output control method of intermediate frequency carrier and low frequency modulated wave according to claim 1, characterized in that, The method further includes: deploying an envelope gradient adjustment control strategy based on the optimal waveform modulation combination, integrating the microtubule skeleton polymerization rate response time and growth cone propulsion orientation angle data, and generating a damage repair path control scheme.

9. The composite output control method of intermediate frequency carrier and low frequency modulated wave according to claim 8, characterized in that, The step of deploying an envelope gradient adjustment control strategy based on the optimal waveform modulation combination, integrating the microtubule skeleton polymerization rate response time and growth cone propulsion orientation angle data, to generate a damage repair path control scheme includes: Extract the carrier frequency and amplitude range from the optimal waveform modulation combination, determine the frequency modulation boundary and amplitude adjustment step interval, and encode them to form an envelope gradient adjustment execution parameter set; apply an amplitude abrupt carrier stimulation signal, record the steady-state response time of the microtubule skeleton aggregation rate, collect the growth cone orientation angle sequence within the response time, calculate the angle change rate, and associate and store the execution parameter set; divide the response time into initial, transition, and stable segments, calculate the average and standard deviation of the aggregation rate of each segment, and determine the response characteristic type; generate the damage repair path control scheme based on the response characteristic type and the angle change rate.

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