Transcutaneous auricular vagus nerve electrical stimulation control method for promoting recovery of intestinal function

Abstract

This invention discloses a percutaneous vagus nerve electrical stimulation control method for promoting intestinal function recovery. The method involves using electrodes to perform polling electrical stimulation on different locations on the ear, acquiring the current response stability, impedance fluctuation amplitude, and load change characteristics at each point, constructing a stimulation response feature vector, and determining the dominant stimulation points through similarity analysis. The method collects intestinal smooth muscle electroencephalogram (EEG) entropy values ​​after stimulation of the dominant points in scenarios including postprandial intestinal peristalsis activity, fasting resting period, and sleep period from multiple users, constructing a multi-scenario intestinal response feature matrix, extracting the principal component loading coefficients for each scenario through principal component analysis, determining the recovery effect data and stimulation control strategies under different scenarios, and generating an electrical stimulation control scheme. After implementation, the scheme parameters are adjusted based on the intestinal function recovery assessment results to obtain a personalized electrical stimulation management strategy. This invention achieves adaptive optimization of stimulation parameters, improving the targeting and effectiveness of intestinal function recovery.

Description

Technical Field

[0001] This invention relates to the field of electrical stimulation control technology, and in particular to a transcutaneous vagus nerve electrical stimulation control method for promoting intestinal function recovery. Background Technology

[0002] Postoperative paralysis of the intestines, prolonged bed rest, and neurological dysfunction often lead to weakened intestinal motility, causing abdominal distension, constipation, and even intestinal obstruction, severely impacting patient recovery. Vagus nerve stimulation (VNS) promotes gastrointestinal motility by activating the parasympathetic nervous system, with percutaneous auricular electrical vagus nerve stimulation (taVNS) attracting considerable attention due to its non-invasive nature and ease of operation. However, the distribution of the vagus nerve in the ear exhibits significant individual differences. Traditional taVNS often uses fixed acupoints and uniform parameters, failing to consider the different ear impedance characteristics, current response stability, and stimulation load variations of individual users. This results in indiscriminate selection of stimulation points, leading to poor therapeutic effects in some users due to poor contact or insufficient response.

[0003] Furthermore, intestinal function exhibits a distinct diurnal rhythm and food dependence. The electrophysiological state of intestinal smooth muscle and the vagus nerve's regulatory needs vary across different scenarios, including the active period of intestinal peristalsis after eating, the fasting resting period, and sleep. Existing taVNS protocols typically use a single stimulation parameter throughout the day, lacking adaptive strategies for different physiological scenarios. This makes it difficult to provide sufficient regulation during periods of high intestinal demand and to avoid overstimulation during resting periods. Simultaneously, the lack of objective quantitative assessment methods based on intestinal smooth muscle electrical signals after stimulation prevents dynamic adjustment of stimulation parameters based on actual recovery effects, leading to long-term rigidity of the regulation protocol and low recovery efficiency. Therefore, there is an urgent need for a taVNS control method that can individually locate advantageous stimulation points, adaptively match the needs of multiple scenarios, and dynamically optimize based on recovery effects. Summary of the Invention

[0004] To address at least one of the aforementioned technical problems, this invention proposes a percutaneous vagus nerve electrical stimulation control method for promoting intestinal function recovery.

[0005] The first aspect of this invention provides a method for controlling transcutaneous vagus nerve electrical stimulation for promoting intestinal function recovery, comprising: By using transcutaneous vagus nerve stimulation electrodes to perform electrical stimulation on different locations of the target user's ear, the stability of the current response, the amplitude of impedance fluctuation, and the characteristics of stimulation load change of each stimulation point within the effective range of electrical stimulation are obtained, and a stimulation response feature vector of the stimulation point is constructed. Based on the stimulus response feature vector, a similarity analysis is performed on each stimulus point to determine the response discrimination between each stimulus point, and the dominant stimulus points for the target user are determined based on the response discrimination. The entropy values ​​of intestinal smooth muscle electro-signal after electrical stimulation at the dominant stimulation point were obtained for multiple users in scenarios including the active period of intestinal peristalsis after eating, the fasting resting period, and the sleep period. Based on the entropy values ​​of intestinal smooth muscle electro-signal, a multi-scenario intestinal response feature matrix was constructed. Principal component analysis was performed on the multi-scenario intestinal response feature matrix to extract the principal component loading coefficients corresponding to each scenario. Based on the principal component loading coefficients, the data on the recovery effect of percutaneous ear vagus nerve electrical stimulation on intestinal function under different scenarios were determined. Based on the recovery effect data, stimulation control strategies for different scenarios were determined, resulting in a percutaneous ear vagus nerve electrical stimulation control scheme. Intestinal function recovery was assessed in target users after implementing the percutaneous vagus nerve stimulation control program. Based on the intestinal function recovery assessment results, the parameters of the percutaneous vagus nerve stimulation control program were modified to obtain a percutaneous vagus nerve stimulation management strategy for promoting intestinal function recovery.

[0006] In this scheme, the method involves using transcutaneous vagus nerve stimulation electrodes to perform electrical stimulation at different locations on the target user's ear, obtaining the current response stability, impedance fluctuation amplitude, and stimulation load variation characteristics of each stimulation point within the effective range of electrical stimulation, and constructing a stimulation response feature vector for each stimulation point. Specifically: Acquire the electrical stimulation output point information of the percutaneous ear vagus nerve stimulation electrode, and establish electrical contact sequentially at each stimulation point of the percutaneous ear vagus nerve stimulation electrode attached to the ear of the target user according to the electrical stimulation output point information. Apply electrical stimulation pulses with fixed pulse width and fixed repetition frequency to each stimulation point and perform a polling operation to acquire the stimulation voltage, stimulation current and electrode contact impedance change data of each point. Calculate the ratio sequence of stimulation current value to stimulation voltage value at multiple consecutive sampling times within the effective range of electrical stimulation sensing for each stimulation point, calculate the coefficient of variation of the ratio sequence, and use the coefficient of variation as the current response stability of that point. Based on the electrode contact impedance change data, the impedance difference between two adjacent sampling times is calculated, and the average value of the absolute values ​​of all impedance differences is taken as the impedance fluctuation amplitude of the stimulation point. Based on the stimulation voltage and stimulation current data of each stimulation point during the application of the electrical stimulation pulse, the product of stimulation voltage and stimulation current is calculated at each sampling time to obtain the instantaneous stimulation power. The first-order difference operation is performed on the instantaneous stimulation power sequence to obtain the stimulation load change rate sequence. Extract the duration and amplitude range of continuous non-zero change segments in the stimulus load change rate sequence, and use the combination of duration and amplitude range as the stimulus load change feature of the stimulus point. The current response stability, impedance fluctuation amplitude, and stimulus load change characteristics corresponding to each stimulus point are arranged in order of point number to form a set of values ​​with the same dimension, thus obtaining the stimulus response feature vector of each stimulus point.

[0007] In this scheme, the step of performing similarity analysis on each stimulus point based on the stimulus response feature vector to determine the response discrimination between each stimulus point, and determining the target user's dominant stimulus points based on the response discrimination, specifically involves: Calculate the absolute value of the difference between the current response stability and the preset stability benchmark value in the stimulus response feature vector of each stimulus point to obtain the stability deviation of each stimulus point. The impedance fluctuation amplitude and the duration in the stimulus load change characteristics of each stimulus point are normalized, and the Pearson correlation coefficient between the normalized impedance fluctuation amplitude and the normalized duration is calculated to obtain the consistency coefficient between the impedance fluctuation and the stimulus load change of each stimulus point. Determine whether the stability deviation of each stimulus point is less than the average stability deviation of all stimulus points, and whether the corresponding consistency coefficient is greater than the average consistency coefficient of all stimulus points. Stimulus points that simultaneously satisfy the condition that the stability deviation is less than the average stability deviation of all stimulus points and the consistency coefficient is greater than the average consistency coefficient of all stimulus points are classified as stable stimulus points. Extract the stimulus response feature vectors of each stable stimulus point, calculate the Euclidean distance between the stimulus response feature vectors of the stable stimulus points and the stimulus response feature vectors of all other unstable stimulus points on the target user's ear, and obtain the response difference value of the stable stimulus point relative to each unstable stimulus point. Calculate the average response difference value for each stable stimulus point to obtain the point response discrimination of the stable stimulus point. Compare the point response discrimination of all stable stimulus points and determine the stable stimulus point with the highest point response discrimination as the advantageous stimulus point for the target user.

[0008] In this solution, the acquisition of intestinal smooth muscle electromotive force (EMF) entropy values ​​after electrical stimulation at the dominant stimulation point for multiple users in scenarios including the active intestinal peristalsis period after eating, the fasting resting period, and the sleep period, and the construction of a multi-scenario intestinal response feature matrix based on the EMF entropy values, specifically involves: A pair of recording electrodes and a pair of reference electrodes are attached to the abdominal surface of multiple users, corresponding to the colon projection area and the ileocecal junction. The recording electrodes and the reference electrodes are connected to a bioelectric signal amplifier via lead wires. During the active period of intestinal peristalsis after eating, the fasting resting period, and the sleep period, percutaneous vagus nerve electrical stimulation pulses are applied to the dominant stimulation points of the target user's ear. The bioelectric signal amplifier collects the differential voltage signal between the two electrodes on the abdominal surface at a preset sampling frequency to obtain the original intestinal smooth muscle electrical signal. The original intestinal smooth muscle electromyography signal is sequentially passed through a bandpass filter with a lower cutoff frequency and an upper cutoff frequency to limit the frequency band, and then through a notch filter with a center frequency of power frequency to eliminate power frequency interference, so as to obtain a denoised intestinal smooth muscle electromyography signal. The denoised intestinal smooth muscle electromyography (EMG) signal is segmented according to a fixed time window. The sample entropy value is calculated for the signal within each time window to obtain the intestinal smooth muscle EMG signal entropy value corresponding to the dominant stimulation point for each user in each scenario. Multiple users are used as row elements of a matrix, and the active period of intestinal peristalsis after eating, the fasting resting period, and the sleep period are used as column elements of the matrix. The intestinal smooth muscle electroencephalogram entropy value of each user in each scenario is used to construct a multi-scenario intestinal response feature matrix.

[0009] In this scheme, the principal component analysis is performed on the multi-scenario intestinal response feature matrix to extract the principal component loading coefficients corresponding to each scenario. Based on the principal component loading coefficients, the data on the recovery effect of percutaneous vagus nerve stimulation on intestinal function under different scenarios are determined. Specifically: The columns of the multi-scenario intestinal response feature matrix are centered, and the covariance between the intestinal response features of each scenario is calculated to obtain the scenario response covariance matrix. The scene response covariance matrix is ​​decomposed into eigenvalues, the corresponding eigenvectors are sorted in descending order of eigenvalues, and the principal components are selected based on the cumulative variance contribution rate to obtain the principal component eigenvectors. The loading coefficients of each scenario on each principal component are calculated based on the product relationship between the principal component eigenvectors and the eigenvalues ​​of the scenario response covariance matrix. The loading coefficients of each principal component corresponding to the same scenario are then squared and normalized to obtain the feature weights of the intestinal response of each scenario. The entropy values ​​of the intestinal smooth muscle electroencephalogram (IEM) signals in the corresponding scenarios are weighted and summed according to the feature weights to obtain the comprehensive intestinal response characterization value for each scenario. The comprehensive intestinal response characterization value after multiple users receive electrical stimulation at the dominant stimulation points is calculated to compare it with the comprehensive intestinal response characterization value when no electrical stimulation is performed in the corresponding scenario, and the stimulation response gain for each scenario is obtained. Based on the ratio of the stimulus response gain to the comprehensive characterization value of the intestinal response in each scenario, the contribution of percutaneous vagus nerve electrical stimulation to the recovery of intestinal function in different scenarios is determined, and the contribution is used as the data on the recovery effect of percutaneous vagus nerve electrical stimulation on intestinal function in different scenarios.

[0010] In this scheme, the step of determining stimulation control strategies for different scenarios based on the recovery effect data to obtain a percutaneous vagus nerve electrical stimulation control scheme is as follows: Based on the ratio of the stimulation response gain to the comprehensive characterization value of the intestinal response in each scenario in the recovery effect data, the contribution of percutaneous vagus nerve electrical stimulation to the recovery of intestinal function in each scenario, including the active period of intestinal peristalsis after eating, the fasting resting period, and the sleep period, is determined. The contribution value is multiplied by the stimulus intensity benchmark value to obtain the stimulus intensity setting value corresponding to each scenario. The stimulus intensity benchmark value is the pre-calibrated minimum effective sensing current threshold of the vagus nerve in the ear. The ratio of the comprehensive gut response value of each scenario to the sum of the comprehensive gut response values ​​of all scenarios is calculated to obtain the response proportion coefficient of each scenario; the response proportion coefficient is multiplied by the total stimulation duration to obtain the stimulation duration setting value corresponding to each scenario, wherein the total stimulation duration is the cumulative action time of transcutaneous vagus nerve electrical stimulation in a single day; Based on the stimulation intensity and duration settings for each scenario, a set of stimulation control parameters for each scenario is constructed, and a transcutaneous vagus nerve electrical stimulation control scheme is formed from the set of stimulation control parameters.

[0011] In this scheme, the intestinal function recovery assessment is performed on the target users after implementing the percutaneous vagus nerve stimulation control scheme. Based on the intestinal function recovery assessment results, the parameters of the percutaneous vagus nerve stimulation control scheme are modified to obtain a percutaneous vagus nerve stimulation management strategy for promoting intestinal function recovery, specifically as follows: After implementing the percutaneous vagus nerve electrical stimulation control program, the intestinal smooth muscle electrical signals collected by recording electrodes and reference electrodes were obtained from the corresponding colon projection area and ileocecal region on the abdominal surface of the target user. The intestinal smooth muscle electrical signals were subjected to Hilbert transform to obtain analytical signals, and the instantaneous amplitude sequence and instantaneous frequency sequence of the analytical signals were calculated. The signal energy intensity is obtained by calculating the root mean square value of the instantaneous amplitude sequence, and the frequency fluctuation degree is obtained by calculating the mean value of the absolute values ​​of the frequency changes at adjacent sampling times of the instantaneous frequency sequence. The signal energy intensity and the frequency fluctuation degree are combined to form the intestinal electrical activity state characterization value of the target user. The intestinal electrical activity status characteristics of target users were obtained at each time point after implementing the percutaneous vagus nerve electrical stimulation control scheme in the scenarios of active intestinal peristalsis after eating, fasting rest period and sleep period. The intestinal electrical activity status characteristics of each time point in each scenario were linearly fitted according to the order of collection, and the slope of the fitted line was calculated as the intestinal electrical activity trend change rate in each scenario. The stimulation response gain of each scenario in the recovery effect data is extracted, and the rate of change of intestinal electrical activity trend in each scenario is multiplied by the stimulation response gain of the corresponding scenario to obtain the intestinal function recovery effect evaluation value of each scenario. Based on the ratio of the intestinal function recovery effect evaluation value to the comprehensive characterization value of intestinal response in each scenario in the recovery effect data, the actual recovery effect data of percutaneous vagus nerve electrical stimulation on intestinal function in different scenarios are determined. Determine whether the actual recovery effect data reaches the contribution value of the corresponding scenario in the recovery effect data. If not, extract the feature weight corresponding to the scenario response feature with the largest absolute value in the principal component loading coefficients under that scenario, and multiply the feature weight with the stimulus intensity benchmark value to obtain the corrected stimulus intensity. The total stimulation duration is redistributed according to the ratio of the feature weight to the sum of the feature weights of all scenarios to obtain the modified stimulation duration. The stimulation intensity setting value and stimulation duration setting value of the corresponding scenario in the transcutaneous vagus nerve electrical stimulation control scheme are replaced according to the modified stimulation intensity and modified stimulation duration to obtain the transcutaneous vagus nerve electrical stimulation management strategy for promoting intestinal function recovery.

[0012] A second aspect of the present invention provides a transcutaneous vagus nerve electrical stimulation control system for promoting intestinal function recovery. The system includes a memory and a processor. The memory includes a program for a transcutaneous vagus nerve electrical stimulation control method for promoting intestinal function recovery. When the processor executes the program for the transcutaneous vagus nerve electrical stimulation control method for promoting intestinal function recovery, it implements the steps of the transcutaneous vagus nerve electrical stimulation control method for promoting intestinal function recovery as described in any of the preceding claims.

[0013] This invention discloses a percutaneous vagus nerve electrical stimulation control method for promoting intestinal function recovery. The method involves using electrodes to perform polling electrical stimulation on different locations on the ear, acquiring the current response stability, impedance fluctuation amplitude, and load change characteristics at each point, constructing a stimulation response feature vector, and determining the dominant stimulation points through similarity analysis. The method collects intestinal smooth muscle electroencephalogram (EEG) entropy values ​​after stimulation of the dominant points in scenarios including postprandial intestinal peristalsis activity, fasting resting period, and sleep period from multiple users, constructing a multi-scenario intestinal response feature matrix, extracting the principal component loading coefficients for each scenario through principal component analysis, determining the recovery effect data and stimulation control strategies under different scenarios, and generating an electrical stimulation control scheme. After implementation, the scheme parameters are adjusted based on the intestinal function recovery assessment results to obtain a personalized electrical stimulation management strategy. This invention achieves adaptive optimization of stimulation parameters, improving the targeting and effectiveness of intestinal function recovery. Attached Figure Description

[0014] Figure 1 A flowchart of a percutaneous ear vagus nerve electrical stimulation control method for promoting intestinal function recovery according to the present invention is shown; Figure 2 The flowchart illustrating the construction of stimulus response feature vectors for stimulus sites according to the present invention is shown. Figure 3 The flowchart illustrating the present invention for determining the dominant stimulation points of a target user is shown. Figure 4 A block diagram of a transcutaneous vagus nerve electrical stimulation control system for promoting intestinal function recovery according to the present invention is shown. Detailed Implementation

[0015] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0016] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0017] Figure 1 A flowchart of a percutaneous ear vagus nerve electrical stimulation control method for promoting intestinal function recovery according to the present invention is shown.

[0018] like Figure 1 As shown, the first aspect of the present invention provides a transcutaneous vagus nerve electrical stimulation control method for promoting intestinal function recovery, comprising: By using transcutaneous vagus nerve stimulation electrodes to perform electrical stimulation on different locations of the target user's ear, the stability of the current response, the amplitude of impedance fluctuation, and the characteristics of stimulation load change of each stimulation point within the effective range of electrical stimulation are obtained, and a stimulation response feature vector of the stimulation point is constructed. Based on the stimulus response feature vector, a similarity analysis is performed on each stimulus point to determine the response discrimination between each stimulus point, and the dominant stimulus points for the target user are determined based on the response discrimination. The entropy values ​​of intestinal smooth muscle electro-signal after electrical stimulation at the dominant stimulation point were obtained for multiple users in scenarios including the active period of intestinal peristalsis after eating, the fasting resting period, and the sleep period. Based on the entropy values ​​of intestinal smooth muscle electro-signal, a multi-scenario intestinal response feature matrix was constructed. Principal component analysis was performed on the multi-scenario intestinal response feature matrix to extract the principal component loading coefficients corresponding to each scenario. Based on the principal component loading coefficients, the data on the recovery effect of percutaneous ear vagus nerve electrical stimulation on intestinal function under different scenarios were determined. Based on the recovery effect data, stimulation control strategies for different scenarios were determined, resulting in a percutaneous ear vagus nerve electrical stimulation control scheme. Intestinal function recovery was assessed in target users after implementing the percutaneous vagus nerve stimulation control program. Based on the intestinal function recovery assessment results, the parameters of the percutaneous vagus nerve stimulation control program were modified to obtain a percutaneous vagus nerve stimulation management strategy for promoting intestinal function recovery.

[0019] It should be noted that by constructing a stimulus response feature vector through electrostimulation polling, a quantitative characterization of the stability of current response, impedance fluctuations, and load changes at various points in the ear was achieved. This provides an objective basis for accurately locating advantageous stimulation points and solves the problem of inaccurate stimulation point location. Based on the entropy values ​​of intestinal smooth muscle electroencephalograms in multiple scenarios, a response feature matrix was constructed and principal component analysis was performed. The principal component loading coefficients for each scenario were extracted to determine the recovery effect data. This scientifically distinguishes the actual contribution of vagal nerve regulation to intestinal function under different physiological states, overcoming the shortcomings of single-parameter stimulation throughout the day that does not match the needs of intestinal rhythm. Furthermore, based on the recovery effect data, scenario-specific stimulation control strategies were formulated. After implementation, the rate of change of intestinal electrical activity trends was quantified using Hilbert transform. The stimulation intensity and duration were dynamically adjusted based on the actual recovery effect, achieving adaptive closed-loop optimization of the stimulation program and significantly improving the targeting and effectiveness of intestinal function recovery.

[0020] Figure 2 The flowchart illustrating the construction of stimulus response feature vectors for stimulus sites according to the present invention is shown.

[0021] According to an embodiment of the present invention, the method of using percutaneous vagus nerve stimulation electrodes to perform electrical stimulation at different locations on the target user's ear, obtaining the current response stability, impedance fluctuation amplitude, and stimulation load change characteristics of each stimulation point within the effective range of electrical stimulation sensing, and constructing a stimulation response feature vector for the stimulation point, specifically involves: Acquire the electrical stimulation output point information of the percutaneous ear vagus nerve stimulation electrode, and establish electrical contact sequentially at each stimulation point of the percutaneous ear vagus nerve stimulation electrode attached to the ear of the target user according to the electrical stimulation output point information. Apply electrical stimulation pulses with fixed pulse width and fixed repetition frequency to each stimulation point and perform a polling operation to acquire the stimulation voltage, stimulation current and electrode contact impedance change data of each point. Calculate the ratio sequence of stimulation current value to stimulation voltage value at multiple consecutive sampling times within the effective range of electrical stimulation sensing for each stimulation point, calculate the coefficient of variation of the ratio sequence, and use the coefficient of variation as the current response stability of that point. Based on the electrode contact impedance change data, the impedance difference between two adjacent sampling times is calculated, and the average value of the absolute values ​​of all impedance differences is taken as the impedance fluctuation amplitude of the stimulation point. Based on the stimulation voltage and stimulation current data of each stimulation point during the application of the electrical stimulation pulse, the product of stimulation voltage and stimulation current is calculated at each sampling time to obtain the instantaneous stimulation power. The first-order difference operation is performed on the instantaneous stimulation power sequence to obtain the stimulation load change rate sequence. Extract the duration and amplitude range of continuous non-zero change segments in the stimulus load change rate sequence, and use the combination of duration and amplitude range as the stimulus load change feature of the stimulus point. The current response stability, impedance fluctuation amplitude, and stimulus load change characteristics corresponding to each stimulus point are arranged in order of point number to form a set of values ​​with the same dimension, thus obtaining the stimulus response feature vector of each stimulus point.

[0022] It should be noted that due to differences in ear anatomy among different users, the distribution density and depth of the vagus nerve in areas such as the cymba conchae and cavum conchae vary, resulting in naturally different physiological response intensities at different points to the same electrical stimulation. Simultaneously, individual differences in ear skin thickness, sweat gland secretion, and subcutaneous tissue water content directly affect the contact impedance between the electrode and the skin, causing different impedance fluctuation amplitudes at different points during electrical stimulation. Furthermore, the different orientations of nerve bundles beneath each point and the varying proportions of surrounding fat and muscle tissue result in differences in the conduction path and dissipation mode of electrical stimulation energy within the nerve tissue, leading to different durations and amplitude ranges of continuous non-zero change segments in the instantaneous stimulation power rate sequence. It is precisely this combined difference in nerve distribution density, skin contact conditions, and tissue energy conduction characteristics that causes variations in the current response stability, impedance fluctuation amplitude, and stimulation load change characteristics at different stimulation points. Therefore, it is necessary to obtain actual response data for each point through electrical stimulation polling and construct a stimulation response feature vector to objectively reflect the true stimulation characteristics of each point and select the optimal stimulation points.

[0023] Figure 3 The flowchart illustrating the present invention for determining the dominant stimulation points of a target user is shown.

[0024] According to an embodiment of the present invention, the step of performing similarity analysis on each stimulus point based on the stimulus response feature vector to determine the response discrimination between each stimulus point, and determining the dominant stimulus points of the target user based on the response discrimination, specifically involves: Calculate the absolute value of the difference between the current response stability and the preset stability benchmark value in the stimulus response feature vector of each stimulus point to obtain the stability deviation of each stimulus point. The impedance fluctuation amplitude and the duration in the stimulus load change characteristics of each stimulus point are normalized, and the Pearson correlation coefficient between the normalized impedance fluctuation amplitude and the normalized duration is calculated to obtain the consistency coefficient between the impedance fluctuation and the stimulus load change of each stimulus point. Determine whether the stability deviation of each stimulus point is less than the average stability deviation of all stimulus points, and whether the corresponding consistency coefficient is greater than the average consistency coefficient of all stimulus points. Stimulus points that simultaneously satisfy the condition that the stability deviation is less than the average stability deviation of all stimulus points and the consistency coefficient is greater than the average consistency coefficient of all stimulus points are classified as stable stimulus points. Extract the stimulus response feature vectors of each stable stimulus point, calculate the Euclidean distance between the stimulus response feature vectors of the stable stimulus points and the stimulus response feature vectors of all other unstable stimulus points on the target user's ear, and obtain the response difference value of the stable stimulus point relative to each unstable stimulus point. Calculate the average response difference value for each stable stimulus point to obtain the point response discrimination of the stable stimulus point. Compare the point response discrimination of all stable stimulus points and determine the stable stimulus point with the highest point response discrimination as the advantageous stimulus point for the target user.

[0025] It should be noted that the principle of using similarity analysis based on stimulus response feature vectors to determine the optimal stimulation points for target users lies in the fact that the current response stability, impedance fluctuation amplitude, and stimulation load variation characteristics in the stimulus response feature vectors respectively characterize the comprehensive physiological and electrical profile of each point on the ear to electrical stimulation from two dimensions: stimulation transmission quality and neural dynamic response. Specifically, current response stability reflects the degree of fluctuation in the conductivity of the skin-electrode interface over time; impedance fluctuation amplitude reflects the drift of electrode contact impedance during stimulation; and stimulation load variation characteristics are extracted from the differential sequence of instantaneous stimulation power, showing the duration and amplitude range of continuous non-zero variation segments, carrying nonlinear load dynamic information of the excitatory response of neural tissue to electrical stimulation. These three features, after normalization, have unified dimensions, ensuring that the vector distance between different points is consistent. The comparison has physical significance. Based on this, since there are natural physiological differences in impedance characteristics and neural load response patterns between densely distributed vagal nerve areas such as the conchae and cavum and non-nervous areas, the feature vectors of similar areas tend to cluster in vector space while those of different areas tend to separate. Therefore, by calculating the Euclidean distance between stable and unstable stimulation points and taking the average, the point response discrimination degree can be obtained. The larger the discrimination degree value, the more significant the difference in response between the point and the ineffective or inefficient stimulation area, that is, the more accurately the point is located in the core position of the vagal nerve-rich area. Thus, the point with the highest discrimination degree can be selected from all stable stimulation points with reliable physical contact and real neural response as the preferred stimulation point, so as to achieve accurate target area localization based on the actual electrophysiological response data of the individual without relying on prior anatomical atlases.

[0026] According to an embodiment of the present invention, the step of obtaining the entropy values ​​of intestinal smooth muscle electromotive force (EMF) after electrical stimulation at the dominant stimulation point in multiple scenarios including the active period of intestinal peristalsis after eating, the fasting resting period, and the sleep period, and constructing a multi-scenario intestinal response feature matrix based on the EMF entropy values, specifically involves: A pair of recording electrodes and a pair of reference electrodes are attached to the abdominal surface of multiple users, corresponding to the colon projection area and the ileocecal junction. The recording electrodes and the reference electrodes are connected to a bioelectric signal amplifier via lead wires. During the active period of intestinal peristalsis after eating, the fasting resting period, and the sleep period, percutaneous vagus nerve electrical stimulation pulses are applied to the dominant stimulation points of the target user's ear. The bioelectric signal amplifier collects the differential voltage signal between the two electrodes on the abdominal surface at a preset sampling frequency to obtain the original intestinal smooth muscle electrical signal. The original intestinal smooth muscle electromyography signal is sequentially passed through a bandpass filter with a lower cutoff frequency and an upper cutoff frequency to limit the frequency band, and then through a notch filter with a center frequency of power frequency to eliminate power frequency interference, so as to obtain a denoised intestinal smooth muscle electromyography signal. The denoised intestinal smooth muscle electromyography (EMG) signal is segmented according to a fixed time window. The sample entropy value is calculated for the signal within each time window to obtain the intestinal smooth muscle EMG signal entropy value corresponding to the dominant stimulation point for each user in each scenario. Multiple users are used as row elements of a matrix, and the active period of intestinal peristalsis after eating, the fasting resting period, and the sleep period are used as column elements of the matrix. The intestinal smooth muscle electroencephalogram entropy value of each user in each scenario is used to construct a multi-scenario intestinal response feature matrix.

[0027] It is important to note that the electrophysiological activity of intestinal smooth muscle is dually regulated by the autonomic nervous system, exhibiting a distinct diurnal rhythm and food dependence. During the active period of intestinal peristalsis after eating, vagal tone is already elevated, and gastrointestinal migratory complex movements are enhanced. During the fasting resting period, the intestinal state is at a low amplitude and low frequency baseline. During sleep, the parasympathetic nervous system dominates, but body movement decreases, and both intestinal blood flow and nerve sensitivity change. The baseline response, plasticity window, and energy metabolism requirements of the intestine to vagal nerve electrical stimulation differ significantly in these three scenarios. If these scenario differences are ignored and fixed stimulation parameters are used uniformly, insufficient stimulation intensity during the active period may fail to further amplify the peristaltic effect, while overstimulation during resting or sleep may trigger vagal reflex inhibition or disrupt normal sleep rhythms. Therefore, it is necessary to collect intestinal smooth muscle electromuscular signals after electrical stimulation at the dominant stimulation sites under the three typical physiological scenarios mentioned above. After denoising and calculating the sample entropy, the entropy values ​​reflecting the complexity and regularity of the signals are extracted. In order to construct a multi-scenario intestinal response feature matrix with multiple users as rows and multiple scenarios as columns, the differences in intestinal electrical response under different physiological states can be quantified and structured. This provides an objective data basis for subsequent principal component analysis to extract feature weights for each scenario and formulate scenario-specific adaptive stimulation strategies, ensuring that the electrical stimulation scheme is accurately matched with the real-time physiological needs of the intestine.

[0028] According to an embodiment of the present invention, the step of performing principal component analysis on the multi-scenario intestinal response feature matrix, extracting the principal component loading coefficients corresponding to each scenario, and determining the data on the recovery effect of percutaneous vagus nerve electrical stimulation on intestinal function under different scenarios based on the principal component loading coefficients, specifically includes: The columns of the multi-scenario intestinal response feature matrix are centered, and the covariance between the intestinal response features of each scenario is calculated to obtain the scenario response covariance matrix. The scene response covariance matrix is ​​decomposed into eigenvalues, the corresponding eigenvectors are sorted in descending order of eigenvalues, and the principal components are selected based on the cumulative variance contribution rate to obtain the principal component eigenvectors. The loading coefficients of each scenario on each principal component are calculated based on the product relationship between the principal component eigenvectors and the eigenvalues ​​of the scenario response covariance matrix. The loading coefficients of each principal component corresponding to the same scenario are then squared and normalized to obtain the feature weights of the intestinal response of each scenario. The entropy values ​​of the intestinal smooth muscle electroencephalogram (IEM) signals in the corresponding scenarios are weighted and summed according to the feature weights to obtain the comprehensive intestinal response characterization value for each scenario. The comprehensive intestinal response characterization value after multiple users receive electrical stimulation at the dominant stimulation points is calculated to compare it with the comprehensive intestinal response characterization value when no electrical stimulation is performed in the corresponding scenario, and the stimulation response gain for each scenario is obtained. Based on the ratio of the stimulus response gain to the comprehensive characterization value of the intestinal response in each scenario, the contribution of percutaneous vagus nerve electrical stimulation to the recovery of intestinal function in different scenarios is determined, and the contribution is used as the data on the recovery effect of percutaneous vagus nerve electrical stimulation on intestinal function in different scenarios.

[0029] It should be noted that by performing principal component analysis on the intestinal response feature matrix of multiple scenarios, the multidimensional high-dimensional data of intestinal smooth muscle electroencephalogram (EMG) entropy values ​​of multiple users during the active intestinal peristalsis period after eating, the fasting resting period, and the sleep period are mapped to a few uncorrelated principal components. This effectively eliminates the interference of individual differences among different users and redundant information between scenarios, highlighting the intrinsic structural characteristics of intestinal responses in each scenario. The loading coefficients of each scenario on each principal component are calculated based on the product relationship between the principal component eigenvectors and the eigenvalues ​​of the covariance matrix. After square normalization, the feature weights of intestinal responses in each scenario are obtained. These weights accurately quantify the contribution ratio of intestinal electrical activity to the overall response in each scenario, providing a scientific weighting basis for subsequent comprehensive evaluation. The intestinal smooth muscle EMG entropy values ​​are weighted and summed using the feature weights to obtain a comprehensive intestinal response characterization value that comprehensively reflects the intensity of intestinal responses in multiple user groups under each scenario. This value is then compared with the baseline state without electrical stimulation to obtain the stimulation response gain for each scenario. Finally, the contribution of electrical stimulation to the recovery of intestinal function is determined by the ratio of the gain to the comprehensive characterization value. This contribution objectively characterizes the actual recovery efficacy of percutaneous vagus nerve electrical stimulation in different physiological scenarios in a dimensionless numerical form. It can not only compare the differences in stimulation effects between different scenarios, but also avoid the evaluation bias caused by individual baseline differences due to the single entropy value index. It provides reliable data support for the subsequent formulation of differentiated stimulation intensity and stimulation duration settings for different scenarios, thereby ensuring that the electrical stimulation control scheme can accurately match the real recovery needs of the intestine under different physiological states, and maximize the pertinence and effectiveness of intestinal function recovery.

[0030] According to an embodiment of the present invention, the step of determining stimulation control strategies for different scenarios based on the recovery effect data to obtain a percutaneous vagus nerve electrical stimulation control scheme specifically includes: Based on the ratio of the stimulation response gain to the comprehensive characterization value of the intestinal response in each scenario in the recovery effect data, the contribution of percutaneous vagus nerve electrical stimulation to the recovery of intestinal function in each scenario, including the active period of intestinal peristalsis after eating, the fasting resting period, and the sleep period, is determined. The contribution value is multiplied by the stimulus intensity benchmark value to obtain the stimulus intensity setting value corresponding to each scenario. The stimulus intensity benchmark value is the pre-calibrated minimum effective sensing current threshold of the vagus nerve in the ear. The ratio of the comprehensive gut response value of each scenario to the sum of the comprehensive gut response values ​​of all scenarios is calculated to obtain the response proportion coefficient of each scenario; the response proportion coefficient is multiplied by the total stimulation duration to obtain the stimulation duration setting value corresponding to each scenario, wherein the total stimulation duration is the cumulative action time of transcutaneous vagus nerve electrical stimulation in a single day; Based on the stimulation intensity and duration settings for each scenario, a set of stimulation control parameters for each scenario is constructed, and a transcutaneous vagus nerve electrical stimulation control scheme is formed from the set of stimulation control parameters.

[0031] It should be noted that the contribution value is determined based on the ratio of the stimulation response gain to the comprehensive intestinal response value in each scenario from the recovery effect data. This value is then multiplied by the pre-calibrated minimum effective sensing current threshold of the vagus nerve in the ear to obtain the stimulation intensity setting value for each scenario. This ensures that the stimulation intensity is strictly proportional to the actual contribution of electrical stimulation to intestinal function recovery in that scenario. Scenarios with higher contribution values ​​are automatically matched with stronger stimulation intensities. This avoids limited regulatory effects due to insufficient stimulation during active periods when intestinal responses are already strong, while also preventing excessive stimulation during rest or sleep periods from causing vagal nerve reflex inhibition or interfering with normal physiological rhythms. Simultaneously, by calculating the response ratio coefficient of the comprehensive intestinal response value of each scenario to the sum of all scenarios, and multiplying this by the total daily stimulation duration, the stimulation duration setting value for each scenario is obtained. This enables the dynamic allocation of total stimulation time across multiple scenarios on demand. Scenarios with higher comprehensive response values ​​receive longer stimulation durations, ensuring that stimulation resources are tilted towards the periods when the need for intestinal recovery is most urgent. Ultimately, the stimulation intensity and duration settings for each scenario are combined to construct a set of stimulation control parameters for each scenario, forming a complete transcutaneous vagus nerve electrical stimulation control scheme. This scheme can automatically adjust the stimulation dose according to the actual needs of the intestine for vagus nerve regulation under different physiological states. Under the premise of ensuring that the total stimulation amount throughout the day is reasonable and controllable, it achieves precise delivery of stimulation energy in both time and intensity dimensions, significantly improving the efficiency and safety of intestinal function recovery.

[0032] According to an embodiment of the present invention, the step of assessing the intestinal function recovery of the target user after implementing the percutaneous vagus nerve stimulation control scheme, and adjusting the parameters of the percutaneous vagus nerve stimulation control scheme based on the intestinal function recovery assessment results, to obtain a percutaneous vagus nerve stimulation management strategy for promoting intestinal function recovery, specifically includes: After implementing the percutaneous vagus nerve electrical stimulation control program, the intestinal smooth muscle electrical signals collected by recording electrodes and reference electrodes were obtained from the corresponding colon projection area and ileocecal region on the abdominal surface of the target user. The intestinal smooth muscle electrical signals were subjected to Hilbert transform to obtain analytical signals, and the instantaneous amplitude sequence and instantaneous frequency sequence of the analytical signals were calculated. The signal energy intensity is obtained by calculating the root mean square value of the instantaneous amplitude sequence, and the frequency fluctuation degree is obtained by calculating the mean value of the absolute values ​​of the frequency changes at adjacent sampling times of the instantaneous frequency sequence. The signal energy intensity and the frequency fluctuation degree are combined to form the intestinal electrical activity state characterization value of the target user. The intestinal electrical activity status characteristics of target users were obtained at each time point after implementing the percutaneous vagus nerve electrical stimulation control scheme in the scenarios of active intestinal peristalsis after eating, fasting rest period and sleep period. The intestinal electrical activity status characteristics of each time point in each scenario were linearly fitted according to the order of collection, and the slope of the fitted line was calculated as the intestinal electrical activity trend change rate in each scenario. The stimulation response gain of each scenario in the recovery effect data is extracted, and the rate of change of intestinal electrical activity trend in each scenario is multiplied by the stimulation response gain of the corresponding scenario to obtain the intestinal function recovery effect evaluation value of each scenario. Based on the ratio of the intestinal function recovery effect evaluation value to the comprehensive characterization value of intestinal response in each scenario in the recovery effect data, the actual recovery effect data of percutaneous vagus nerve electrical stimulation on intestinal function in different scenarios are determined. Determine whether the actual recovery effect data reaches the contribution value of the corresponding scenario in the recovery effect data. If not, extract the feature weight corresponding to the scenario response feature with the largest absolute value in the principal component loading coefficients under that scenario, and multiply the feature weight with the stimulus intensity benchmark value to obtain the corrected stimulus intensity. The total stimulation duration is redistributed according to the ratio of the feature weight to the sum of the feature weights of all scenarios to obtain the modified stimulation duration. The stimulation intensity setting value and stimulation duration setting value of the corresponding scenario in the transcutaneous vagus nerve electrical stimulation control scheme are replaced according to the modified stimulation intensity and modified stimulation duration to obtain the transcutaneous vagus nerve electrical stimulation management strategy for promoting intestinal function recovery.

[0033] It should be noted that by performing Hilbert transform on the intestinal smooth muscle electrical signals after the implementation of the electrical stimulation control scheme, the instantaneous amplitude and frequency sequences are extracted. The signal energy intensity is obtained by calculating the root mean square value, and the frequency fluctuation is obtained by calculating the mean of the absolute values ​​of frequency changes between adjacent time points. Combining these two values ​​yields a characterization value of intestinal electrical activity, enabling a comprehensive and real-time quantification of the electrophysiological activity and dynamic stability of the target user's intestinal smooth muscle. Furthermore, linear fitting is performed on the characterization values ​​at multiple time points under various scenarios. The slope of the fitted line is used as the trend change rate of intestinal electrical activity, which objectively characterizes the evolution direction and rate of intestinal function with stimulation intervention, providing a dynamic basis with a time dimension for evaluating the recovery effect. Multiplying the trend change rate by the stimulation response gain in the recovery effect data yields the recovery effect evaluation value. This value is then compared with the comprehensive characterization value of the intestinal response in the corresponding scenario to obtain the actual recovery effect data, achieving a closed-loop comparison between the expected contribution and the actual physiological feedback. When the actual recovery effect fails to reach the expected contribution, the feature weight corresponding to the scenario response feature with the largest absolute value among the principal component loading coefficients in that scenario is automatically extracted. This weight is then used to recalculate the corrected stimulation intensity and duration, and the corresponding parameters in the original control scheme are replaced. This results in a percutaneous vagus nerve electrical stimulation management strategy that can dynamically self-optimize based on the individual's actual recovery progress. By constructing a complete closed-loop feedback chain from signal acquisition, state assessment, effect comparison to parameter correction, the problem of fixed stimulation schemes being unable to adapt to changes in individual recovery progress is effectively solved, ensuring that the stimulation parameters always remain synchronized with the actual intestinal function recovery needs.

[0034] According to an embodiment of the present invention, it further includes: During the process of polling different locations on the target user's ear with electrical stimulation to obtain the current response stability, impedance fluctuation amplitude and stimulation load change characteristics of each stimulation point, the electrode contact impedance change data of each stimulation point at each sampling time are collected in real time. The impedance difference sequence between adjacent sampling times is calculated based on the electrode contact impedance change data. The change in sign of adjacent differences in the impedance difference sequence is statistically analyzed to obtain the impedance change direction switching frequency. The impedance change direction switching frequency is determined based on the ratio of the impedance change direction switching frequency to a preset switching frequency reference value. The impedance mutation detection coefficient is weighted and fused with the current response stability obtained by calculating the coefficient of variation based on the ratio sequence of stimulation voltage value to stimulation current value at the same stimulation point to obtain the corrected current response stability. The original current response stability is replaced by the corrected current response stability to update the stimulation response feature vector of the stimulation point.

[0035] It should be noted that by updating the stimulus response feature vector of the stimulus site, the calculation of response discrimination is no longer affected by the stability deviation distortion caused by impedance mutation when performing similarity analysis based on the stimulus response feature vector. This ensures the accuracy of the determination of the dominant stimulus site and provides a reliable site basis for constructing a multi-scenario intestinal response feature matrix and determining the recovery effect data.

[0036] According to an embodiment of the present invention, the step of statistically analyzing the sign changes of adjacent differences in the impedance difference sequence to obtain the impedance change direction switching frequency specifically involves: The sign of the product of every two adjacent impedance differences in the impedance difference sequence is traversed bit by bit. When the product is negative, it is determined that an impedance change direction switch has occurred between the corresponding adjacent sampling times. The number of all direction switches that occur within the unit polling time window is counted as the original number of switches. The normalized switching frequency is obtained by the ratio of the original number of switching times to the total number of sampling points within the unit polling time window. The normalized switching frequency is used as the switching frequency for impedance change direction. The impedance change direction switching frequency is used as the ratio of the switching frequency for impedance change direction to the preset switching frequency reference value to determine the impedance change detection coefficient. The preset switching frequency reference value is the normalized switching frequency average of all stimulation points within a unit polling time window. When the impedance mutation detection coefficient is greater than 1, it indicates that the stimulation point has abnormally frequent impedance fluctuations and repeated reversals during the polling period. Correspondingly, the impedance mutation detection coefficient is used as a weighting factor to perform reverse attenuation correction on the current response stability to obtain the corrected current response stability.

[0037] It should be noted that during the process of obtaining the current response stability, impedance fluctuation amplitude, and stimulation load change characteristics of different stimulation points by polling different locations on the ear, the electrode-skin contact state will change unpredictably at the sampling time due to skin oil secretion, sweat wetting, or slight head rotation of the user. This will cause non-physiological abrupt changes or frequent directional fluctuations in electrode contact impedance, directly contaminating the coefficient of variation obtained based on the stimulation voltage to current ratio sequence. This will cause the current response stability to deviate significantly from the true neurophysiological response level of that point, and in subsequent similarity analysis, it will cause the stability deviation to be erroneously amplified or reduced, ultimately misleading the determination of the dominant stimulation point and making the entire electrical stimulation control scheme based on the wrong point. To this end, this invention collects real-time data on the change in electrode contact impedance at each stimulation point at each sampling time, calculates the impedance difference sequence between adjacent sampling times, iterates through the product sign of adjacent differences in the sequence, and determines an impedance change direction switch when the product is negative. It counts the original number of switches within a unit polling time window and calculates the normalized switching frequency. This normalized switching frequency is then compared with a preset switching frequency benchmark value formed by the average normalized switching frequency of all stimulation points to quantify the impedance abrupt change detection coefficient, which reflects the severity of the impedance fluctuation direction reversal. When this coefficient is greater than 1, it indicates that there are abnormally frequent impedance fluctuation direction reversals at that point. In this case, it is used as a weighting factor to perform a reverse attenuation correction on the current response stability calculated based on the ratio sequence of stimulation voltage and stimulation current at the same stimulation point, obtaining a corrected current response stability and replacing the original value to update the stimulation response feature vector of that stimulation point. Through the above processing, the stability value distorted by impedance mutation is adaptively suppressed, and the updated stimulus response feature vector more realistically reflects the electrical stimulation response characteristics of the site itself. When calculating the stability deviation and performing similarity analysis, the calculation results of the response discrimination are no longer affected by the spurious fluctuations caused by the contact impedance mutation. The determination of the dominant stimulation site can be accurately locked, thus providing a solid site foundation for the reliable construction of the intestinal response feature matrix in multiple scenarios and the accurate determination of recovery effect data. This ensures that the final percutaneous ear vagus nerve electrical stimulation management strategy truly acts on the ear stimulation site with the most physiological response value.

[0038] Figure 4 A block diagram of a transcutaneous vagus nerve electrical stimulation control system for promoting intestinal function recovery according to the present invention is shown.

[0039] A second aspect of the present invention also provides a transcutaneous vagus nerve electrical stimulation control system for promoting intestinal function recovery. The system includes: a memory 401, a processor 402, and a communication interface 403. The memory includes a program for a transcutaneous vagus nerve electrical stimulation control method for promoting intestinal function recovery. The communication interface is used for data connection and communication between the memory and the processor. When the processor executes the program for the transcutaneous vagus nerve electrical stimulation control method for promoting intestinal function recovery, it implements the steps of the transcutaneous vagus nerve electrical stimulation control method for promoting intestinal function recovery as described in any of the above claims.

[0040] This invention discloses a percutaneous vagus nerve electrical stimulation control method for promoting intestinal function recovery. The method involves using electrodes to perform polling electrical stimulation on different locations on the ear, acquiring the current response stability, impedance fluctuation amplitude, and load change characteristics at each point, constructing a stimulation response feature vector, and determining the dominant stimulation points through similarity analysis. The method collects intestinal smooth muscle electroencephalogram (EEG) entropy values ​​after stimulation of the dominant points in scenarios including postprandial intestinal peristalsis activity, fasting resting period, and sleep period from multiple users, constructing a multi-scenario intestinal response feature matrix, extracting the principal component loading coefficients for each scenario through principal component analysis, determining the recovery effect data and stimulation control strategies under different scenarios, and generating an electrical stimulation control scheme. After implementation, the scheme parameters are adjusted based on the intestinal function recovery assessment results to obtain a personalized electrical stimulation management strategy. This invention achieves adaptive optimization of stimulation parameters, improving the targeting and effectiveness of intestinal function recovery.

[0041] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0042] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0043] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for controlling transcutaneous vagus nerve electrical stimulation for promoting intestinal function recovery, characterized in that, Includes the following steps: By using transcutaneous vagus nerve stimulation electrodes to perform electrical stimulation on different locations of the target user's ear, the stability of the current response, the amplitude of impedance fluctuation, and the characteristics of stimulation load change of each stimulation point within the effective range of electrical stimulation are obtained, and a stimulation response feature vector of the stimulation point is constructed. Based on the stimulus response feature vector, a similarity analysis is performed on each stimulus point to determine the response discrimination between each stimulus point, and the dominant stimulus points for the target user are determined based on the response discrimination. The entropy values ​​of intestinal smooth muscle electro-signal after electrical stimulation at the dominant stimulation point were obtained for multiple users in scenarios including the active period of intestinal peristalsis after eating, the fasting resting period, and the sleep period. Based on the entropy values ​​of intestinal smooth muscle electro-signal, a multi-scenario intestinal response feature matrix was constructed. Principal component analysis was performed on the multi-scenario intestinal response feature matrix to extract the principal component loading coefficients corresponding to each scenario. Based on the principal component loading coefficients, the data on the recovery effect of percutaneous ear vagus nerve electrical stimulation on intestinal function under different scenarios were determined. Based on the recovery effect data, stimulation control strategies for different scenarios were determined, resulting in a percutaneous vagus nerve electrical stimulation control scheme. Intestinal function recovery was assessed in target users after implementing the percutaneous vagus nerve stimulation control program. Based on the intestinal function recovery assessment results, the parameters of the percutaneous vagus nerve stimulation control program were modified to obtain a percutaneous vagus nerve stimulation management strategy for promoting intestinal function recovery.

2. The method for controlling transcutaneous vagus nerve electrical stimulation for promoting intestinal function recovery according to claim 1, characterized in that, The process involves using transcutaneous vagus nerve stimulation electrodes to perform electrical stimulation at different locations on the target user's ear, obtaining the current response stability, impedance fluctuation amplitude, and stimulation load variation characteristics of each stimulation point within the effective range of electrical stimulation, and constructing a stimulation response feature vector for each stimulation point. Specifically: Acquire the electrical stimulation output point information of the percutaneous ear vagus nerve stimulation electrode, and establish electrical contact sequentially at each stimulation point of the percutaneous ear vagus nerve stimulation electrode attached to the ear of the target user according to the electrical stimulation output point information. Apply electrical stimulation pulses with fixed pulse width and fixed repetition frequency to each stimulation point and perform a polling operation to acquire the stimulation voltage, stimulation current and electrode contact impedance change data of each point. Calculate the ratio sequence of stimulation current value to stimulation voltage value at multiple consecutive sampling times within the effective range of electrical stimulation sensing for each stimulation point, calculate the coefficient of variation of the ratio sequence, and use the coefficient of variation as the current response stability of that point. Based on the electrode contact impedance change data, the impedance difference between two adjacent sampling times is calculated, and the average value of the absolute values ​​of all impedance differences is taken as the impedance fluctuation amplitude of the stimulation point. Based on the stimulation voltage and stimulation current data of each stimulation point during the application of the electrical stimulation pulse, the product of stimulation voltage and stimulation current is calculated at each sampling time to obtain the instantaneous stimulation power. The first-order difference operation is performed on the instantaneous stimulation power sequence to obtain the stimulation load change rate sequence. Extract the duration and amplitude range of continuous non-zero change segments in the stimulus load change rate sequence, and use the combination of duration and amplitude range as the stimulus load change feature of the stimulus point. The current response stability, impedance fluctuation amplitude, and stimulus load change characteristics corresponding to each stimulus point are arranged in order of point number to form a set of values ​​with the same dimension, thus obtaining the stimulus response feature vector of each stimulus point.

3. The method for controlling transcutaneous vagus nerve electrical stimulation for promoting intestinal function recovery according to claim 1, characterized in that, The step of performing similarity analysis on each stimulus point based on the stimulus response feature vector to determine the response discrimination between each stimulus point, and determining the dominant stimulus points for the target user based on the response discrimination, specifically involves: Calculate the absolute value of the difference between the current response stability and the preset stability benchmark value in the stimulus response feature vector of each stimulus point to obtain the stability deviation of each stimulus point. The impedance fluctuation amplitude and the duration in the stimulus load change characteristics of each stimulus point are normalized, and the Pearson correlation coefficient between the normalized impedance fluctuation amplitude and the normalized duration is calculated to obtain the consistency coefficient between the impedance fluctuation and the stimulus load change of each stimulus point. Determine whether the stability deviation of each stimulus point is less than the average stability deviation of all stimulus points, and whether the corresponding consistency coefficient is greater than the average consistency coefficient of all stimulus points. Stimulus points that simultaneously satisfy the condition that the stability deviation is less than the average stability deviation of all stimulus points and the consistency coefficient is greater than the average consistency coefficient of all stimulus points are classified as stable stimulus points. Extract the stimulus response feature vectors of each stable stimulus point, calculate the Euclidean distance between the stimulus response feature vectors of the stable stimulus points and the stimulus response feature vectors of all other unstable stimulus points on the target user's ear, and obtain the response difference value of the stable stimulus point relative to each unstable stimulus point. Calculate the average response difference value for each stable stimulus point to obtain the point response discrimination of the stable stimulus point. Compare the point response discrimination of all stable stimulus points and determine the stable stimulus point with the highest point response discrimination as the advantageous stimulus point for the target user.

4. The method for controlling transcutaneous vagus nerve electrical stimulation for promoting intestinal function recovery according to claim 1, characterized in that, The process involves acquiring the entropy values ​​of intestinal smooth muscle electromyography (EMG) signals after electrical stimulation at the dominant stimulation point for multiple users during the active intestinal peristalsis period after eating, the fasting resting period, and the sleep period. Based on these EMG signal entropy values, a multi-scenario intestinal response feature matrix is ​​constructed. Specifically: A pair of recording electrodes and a pair of reference electrodes are attached to the abdominal surface of multiple users, corresponding to the colon projection area and the ileocecal junction. The recording electrodes and the reference electrodes are connected to a bioelectric signal amplifier via lead wires. During the active period of intestinal peristalsis after eating, the fasting resting period, and the sleep period, percutaneous vagus nerve electrical stimulation pulses are applied to the dominant stimulation points of the target user's ear. The bioelectric signal amplifier collects the differential voltage signal between the two electrodes on the abdominal surface at a preset sampling frequency to obtain the original intestinal smooth muscle electrical signal. The original intestinal smooth muscle electromyography signal is sequentially passed through a bandpass filter with a lower cutoff frequency and an upper cutoff frequency to limit the frequency band, and then through a notch filter with a center frequency of power frequency to eliminate power frequency interference, so as to obtain a denoised intestinal smooth muscle electromyography signal. The denoised intestinal smooth muscle electromyography (EMG) signal is segmented according to a fixed time window. The sample entropy value is calculated for the signal within each time window to obtain the intestinal smooth muscle EMG signal entropy value corresponding to the dominant stimulation point for each user in each scenario. Multiple users are used as row elements of a matrix, and the active period of intestinal peristalsis after eating, the fasting resting period, and the sleep period are used as column elements of the matrix. The intestinal smooth muscle electroencephalogram entropy value of each user in each scenario is used to construct a multi-scenario intestinal response feature matrix.

5. A method for controlling transcutaneous vagus nerve electrical stimulation for promoting intestinal function recovery according to claim 1, characterized in that, The process involves performing principal component analysis on the multi-scenario intestinal response feature matrix, extracting the principal component loading coefficients corresponding to each scenario, and determining the data on the recovery effect of percutaneous vagus nerve electrical stimulation on intestinal function under different scenarios based on the principal component loading coefficients. Specifically: The columns of the multi-scenario intestinal response feature matrix are centered, and the covariance between the intestinal response features of each scenario is calculated to obtain the scenario response covariance matrix. The scene response covariance matrix is ​​decomposed into eigenvalues, the corresponding eigenvectors are sorted in descending order of eigenvalues, and the principal components are selected based on the cumulative variance contribution rate to obtain the principal component eigenvectors. The loading coefficients of each scenario on each principal component are calculated based on the product relationship between the principal component eigenvectors and the eigenvalues ​​of the scenario response covariance matrix. The loading coefficients of each principal component corresponding to the same scenario are then squared and normalized to obtain the feature weights of the intestinal response of each scenario. The entropy values ​​of the intestinal smooth muscle electroencephalogram (IEM) signals in the corresponding scenarios are weighted and summed according to the feature weights to obtain the comprehensive intestinal response characterization value for each scenario. The comprehensive intestinal response characterization value after multiple users receive electrical stimulation at the dominant stimulation points is calculated to compare it with the comprehensive intestinal response characterization value when no electrical stimulation is performed in the corresponding scenario, and the stimulation response gain for each scenario is obtained. Based on the ratio of the stimulus response gain to the comprehensive characterization value of the intestinal response in each scenario, the contribution of percutaneous vagus nerve electrical stimulation to the recovery of intestinal function in different scenarios is determined, and the contribution is used as the data on the recovery effect of percutaneous vagus nerve electrical stimulation on intestinal function in different scenarios.

6. The method for controlling transcutaneous vagus nerve electrical stimulation for promoting intestinal function recovery according to claim 1, characterized in that, The step of determining stimulation control strategies for different scenarios based on the recovery effect data yields a transcutaneous vagus nerve electrical stimulation control scheme, specifically as follows: Based on the ratio of the stimulation response gain to the comprehensive characterization value of the intestinal response in each scenario in the recovery effect data, the contribution of percutaneous vagus nerve electrical stimulation to the recovery of intestinal function in each scenario, including the active period of intestinal peristalsis after eating, the fasting resting period, and the sleep period, is determined. The contribution value is multiplied by the stimulus intensity benchmark value to obtain the stimulus intensity setting value corresponding to each scenario. The stimulus intensity benchmark value is the pre-calibrated minimum effective sensing current threshold of the vagus nerve in the ear. The ratio of the comprehensive gut response value of each scenario to the sum of the comprehensive gut response values ​​of all scenarios is calculated to obtain the response proportion coefficient of each scenario; the response proportion coefficient is multiplied by the total stimulation duration to obtain the stimulation duration setting value corresponding to each scenario, wherein the total stimulation duration is the cumulative action time of transcutaneous vagus nerve electrical stimulation in a single day; Based on the stimulation intensity and duration settings for each scenario, a set of stimulation control parameters for each scenario is constructed, and a transcutaneous vagus nerve electrical stimulation control scheme is formed from the set of stimulation control parameters.

7. A method for controlling transcutaneous vagus nerve electrical stimulation for promoting intestinal function recovery according to claim 1, characterized in that, The process involves assessing the intestinal function recovery of target users after implementing the percutaneous vagus nerve stimulation control protocol. Based on the assessment results, the parameters of the percutaneous vagus nerve stimulation control protocol are adjusted to obtain a percutaneous vagus nerve stimulation management strategy for promoting intestinal function recovery. Specifically: After implementing the percutaneous vagus nerve electrical stimulation control program, the intestinal smooth muscle electrical signals collected by recording electrodes and reference electrodes were obtained from the corresponding colon projection area and ileocecal region on the abdominal surface of the target user. The intestinal smooth muscle electrical signals were subjected to Hilbert transform to obtain analytical signals, and the instantaneous amplitude sequence and instantaneous frequency sequence of the analytical signals were calculated. The signal energy intensity is obtained by calculating the root mean square value of the instantaneous amplitude sequence, and the frequency fluctuation degree is obtained by calculating the mean value of the absolute values ​​of the frequency changes at adjacent sampling times of the instantaneous frequency sequence. The signal energy intensity and the frequency fluctuation degree are combined to form the intestinal electrical activity state characterization value of the target user. The intestinal electrical activity status characteristics of target users were obtained at each time point after implementing the percutaneous vagus nerve electrical stimulation control scheme in the scenarios of active intestinal peristalsis after eating, fasting rest period and sleep period. The intestinal electrical activity status characteristics of each time point in each scenario were linearly fitted according to the order of collection, and the slope of the fitted line was calculated as the intestinal electrical activity trend change rate in each scenario. The stimulation response gain of each scenario in the recovery effect data is extracted, and the rate of change of intestinal electrical activity trend in each scenario is multiplied by the stimulation response gain of the corresponding scenario to obtain the intestinal function recovery effect evaluation value of each scenario. Based on the ratio of the intestinal function recovery effect evaluation value to the comprehensive characterization value of intestinal response in each scenario in the recovery effect data, the actual recovery effect data of percutaneous vagus nerve electrical stimulation on intestinal function in different scenarios are determined. Determine whether the actual recovery effect data reaches the contribution value of the corresponding scenario in the recovery effect data. If not, extract the feature weight corresponding to the scenario response feature with the largest absolute value in the principal component loading coefficients under that scenario, and multiply the feature weight with the stimulus intensity benchmark value to obtain the corrected stimulus intensity. The total stimulation duration is redistributed according to the ratio of the feature weight to the sum of the feature weights of all scenarios to obtain the modified stimulation duration. The stimulation intensity setting value and stimulation duration setting value of the corresponding scenario in the transcutaneous vagus nerve electrical stimulation control scheme are replaced according to the modified stimulation intensity and modified stimulation duration to obtain the transcutaneous vagus nerve electrical stimulation management strategy for promoting intestinal function recovery.

8. A transcutaneous vagus nerve electrical stimulation control system for promoting intestinal function recovery, characterized in that, The percutaneous vagus nerve electrical stimulation control system for promoting intestinal function recovery includes a memory and a processor. The memory includes a program for a percutaneous vagus nerve electrical stimulation control method for promoting intestinal function recovery. When the program for the percutaneous vagus nerve electrical stimulation control method for promoting intestinal function recovery is executed by the processor, it implements the steps of the percutaneous vagus nerve electrical stimulation control method for promoting intestinal function recovery as described in any one of claims 1 to 7.

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