Closed-loop vagus nerve stimulation system acting on depression

Abstract

The invention discloses a closed-loop vagus nerve stimulation system acting on depression, which comprises a data acquisition unit, a core analysis unit, a signal regulation and control unit and a nerve stimulation unit, and is characterized in that patient heart rate data and combined treatment data of a depression patient are acquired through the data acquisition unit; the core analysis unit is used for analyzing the influence function of the medicine and electrotherapy combined treatment on the physical signs of the patient so as to obtain an optimal collaborative treatment scheme and a corresponding electrotherapy design scheme, and the signal regulation and control unit is used for carrying out targeted parameter regulation and control on the electrotherapy signal and outputting an electrotherapy optimization signal; personalized electrotherapy is carried out on the depression patient through the nerve stimulation unit, targeted parameter regulation and control are carried out on the closed-loop vagus nerve stimulation system according to the personalized illness state of the patient, and the actual application accuracy of the closed-loop vagus nerve stimulation system is improved by analyzing the combined action mechanism of electrical stimulation and drug therapy. More comprehensive and effective depression auxiliary monitoring and diagnosis and treatment effects are realized.

Description

Technical Field

[0001] The present invention relates to the field of nerve stimulation technology, and in particular to a closed-loop vagus nerve stimulation system for treating depression. Background Art

[0002] The closed-loop vagus nerve stimulation system can adjust the treatment state according to physiological changes, for example, by sensing the patient's heart rate changes to automatically adjust the stimulation time and intensity, thereby selectively triggering stimulation based on the patient's own physiological activities;

[0003] The existing closed-loop vagus nerve stimulation system interacts and influences other drug treatments when used on patients with depression, resulting in poor accuracy in the actual application of the system. It is difficult to achieve personalized electrical stimulation parameter regulation for patients with depression during the process of coordinated neurostimulation and drug treatment, resulting in poor auxiliary monitoring and diagnosis and treatment effects for depression.

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to solve the defects of the prior art in the poor accuracy, targeting and personalization of neural stimulation caused by the synergistic treatment of neural stimulation and other drugs, and to explore the comprehensive impact of neural stimulation and drug effects on patients, so as to carry out targeted parameter regulation of the closed-loop vagus nerve stimulation system according to the patient's personalized condition, realize adaptive adjustment of the system application process, and improve the actual application accuracy of the closed-loop vagus nerve stimulation system by analyzing the combined action mechanism of electrical stimulation and drug therapy, so as to realize more comprehensive and effective auxiliary monitoring and diagnosis and treatment effects of depression.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A closed-loop vagus nerve stimulation system for depression, comprising a data acquisition unit, a core analysis unit, a signal control unit and a nerve stimulation unit, wherein the data acquisition unit, the core analysis unit, the signal control unit and the nerve stimulation unit are signal-connected;

[0008] The data acquisition unit is used to collect the patient's heart rate data and combined treatment data of the depression patient, and the combined treatment data includes drug parameters and electrotherapy parameters;

[0009] The core analysis unit is used to analyze the heart rate data and combined treatment data of patients with depression: first analyze the influence relationship between the patient's heart rate data and drug parameters and the influence relationship between the patient's heart rate data and electrotherapy parameters, and then analyze the change relationship between the patient's heart rate data and the combined treatment data, so as to obtain the linkage influence relationship of the combination of drug parameters and electrotherapy parameters on the patient's heart rate data, and generate an electrotherapy design plan to send to the signal control unit;

[0010] The signal control unit is used to receive the electrotherapy design plan to perform parameter control on the electrotherapy signal, mark the electrotherapy signal after parameter control as an electrotherapy optimization signal, and then output the electrotherapy optimization signal to the nerve stimulation unit;

[0011] The neurostimulation unit is used to receive the electrotherapy optimization signal and act on the patient to stimulate the patient's nerves. At the same time, it generates a management signal to feed back to the data acquisition unit for re-data acquisition, so as to realize the cyclic refresh of the electrotherapy signal. Among them, the neurostimulation unit is provided with a vagus nerve stimulation electrode, through which the electrotherapy optimization signal is output and acts on the human body.

[0012] Furthermore, the specific operation process of the core analysis unit is as follows:

[0013] A1: Construct a curve analysis model and pre-process the patient's heart rate data, drug parameters, and electrotherapy parameters in sequence;

[0014] A101: Preprocessing patient heart rate data: obtaining a physical sign evaluation coefficient by analyzing the patient heart rate data of patients with depression, thereby evaluating the physical sign status of patient i;

[0015] A102: Pretreatment drug parameters:

[0016] A102-1: Obtain drug intake coefficient by analyzing drug parameters to evaluate drug intake effect;

[0017] A102-2: By combining the physical sign evaluation coefficient of patient i in the drug treatment mode with the drug intake coefficient, an influence function F1 is constructed to analyze the influence relationship between the patient's heart rate data and the drug parameters, and a drug effect evaluation index is obtained to evaluate the drug effect efficacy of patient i;

[0018] A103: Pre-treatment electrotherapy parameters:

[0019] A103-1: Obtain the electrotherapy stimulation coefficient by analyzing the electrotherapy parameters, thereby evaluating the electrotherapy stimulation efficacy;

[0020] A103-2: By combining the physical sign evaluation coefficient of patient i in the nerve stimulation treatment mode with the electrotherapy stimulation coefficient, an influence function F2 is constructed to analyze the influence relationship between the patient's heart rate data and the electrotherapy parameters, and an electrotherapy effect evaluation index is obtained to evaluate the electrotherapy effect of patient i;

[0021] A2: Comprehensive analysis of synergistic treatment mechanisms:

[0022] A201: Obtain the physical sign evaluation coefficient of patient i in the neural stimulation and drug synergistic treatment mode by monitoring, and combine it with the drug intake coefficient and the electrotherapy stimulation coefficient to construct a change function F3 to analyze the change relationship between the patient's heart rate data and the combined treatment data;

[0023] A202: The linkage effect evaluation index is obtained through measurement, so as to obtain the linkage influence relationship between the combination of drug parameters and electrotherapy parameters on the patient's heart rate data, and generate the optimal synergistic treatment plan, where the optimal synergistic treatment plan includes a drug design plan and an electrotherapy design plan.

[0024] Furthermore, the specific process of constructing the curve analysis model is as follows:

[0025] Input the curve Sj to the curve analysis model. It is assumed that the curve Sj has N0 points. Any point of the curve Sj is marked as p, the coordinates of point p are marked as (Xp, Yp), and the point closest to point p and its coordinates are marked as q (Xq, Yq);

[0026] Obtain the slope Kp of point p through the coordinates of point p and point q, and then obtain the slopes corresponding to N0 points of curve Sj, and then obtain the average increase rate Ks of curve Sj by averaging the slopes corresponding to N0 points;

[0027] By calculating the standard deviation of the vertical coordinates of the N0 points of the curve Sj, the fluctuation coefficient σs and the overall value of the curve Sj are obtained.

[0028] The ordinate of the end point of the curve Sj is marked as Ym, and the average increase rate of the curve Sj is Fluctuation coefficient σs, overall value And the vertical coordinate Ym of the end point are combined to generate the two-dimensional characteristic coefficient XER of the curve and output it.

[0029] Furthermore, the specific process of preprocessing the patient's heart rate data is as follows:

[0030] The patient's heart rate data includes the patient's heart rate value and heart rate collection time. Any depression patient is marked as i, the heart rate value of patient i is marked as Li, and the heart rate collection time is marked as Tl. A curve change diagram S0 of the heart rate value Li of patient i-heart rate collection time Tl is constructed;

[0031] Substitute the curve variation graph S0 into the curve analysis model, and output the curve two-dimensional characteristic coefficient of the curve S0 by analyzing the curve variation graph S0 and mark it as Xer0;

[0032] The standard interval of the two-dimensional characteristic coefficient Xer0 of the preset curve is [E1, E2]. When the two-dimensional characteristic coefficient Xer0 of the curve is in the standard interval [E1, E2], it is determined that the curve change of the heart rate value Li of the patient i is normal;

[0033] Then, the physical sign evaluation coefficient Xtz is obtained through the two-dimensional characteristic coefficient Xer0 of the curve S0 and its preset standard interval [E1, E2], and then the threshold of the physical sign evaluation coefficient Xtz is set, and the physical sign status of the patient i is evaluated through threshold comparison.

[0034] Furthermore, the specific process of preprocessing drug parameters is as follows:

[0035] Drug parameters include drug name, drug molecule concentration and medication time. The drug names are classified and marked, and any drug name is marked as X. The drug molecule concentration of drug name X in patient i is marked as Cx, and the medication time is marked as Tf. The curve change diagram S1 of drug molecule concentration Cx-medication time Tf is constructed simultaneously.

[0036] Substitute the curve change graph S1 into the curve analysis model, and output the curve two-dimensional characteristic coefficient of the curve S1 by analyzing the curve change graph S1 and mark it as the drug intake coefficient Xyw;

[0037] Then set the evaluation interval of the drug intake coefficient Xyw, and evaluate the drug intake effect through interval comparison;

[0038] By combining the physical sign evaluation coefficient of patient i in the drug-only treatment mode with the drug intake coefficient, the influence function F1 is constructed, and then the drug effect evaluation index Zyw is obtained to evaluate the drug effect efficacy of patient i.

[0039] Furthermore, the specific process of preprocessing the electrotherapy parameters is as follows:

[0040] The electrotherapy parameters include the pulse intensity, pulse frequency and electrotherapy time of the electrotherapy signal. The pulse intensity of the electrotherapy signal is marked as Ad, the pulse frequency of the electrotherapy signal is marked as Fd, and the electrotherapy time is marked as Td. A curve variation diagram S2 of the pulse intensity Ad-electrotherapy time Td of the electrotherapy signal is constructed, and a curve variation diagram S3 of the pulse frequency Fd-electrotherapy time Td of the electrotherapy signal is constructed synchronously.

[0041] Substituting the curve change graph S2 and the curve change graph S3 into the curve analysis model in sequence, and obtaining the electrotherapy stimulation coefficient Xdl by combining the curve two-dimensional characteristic coefficients of the curve change graph S2 and the curve change graph S3;

[0042] Then set the evaluation interval of the electrotherapy stimulation coefficient Xdl, and evaluate the electrotherapy stimulation efficacy through interval comparison;

[0043] By combining the physical sign evaluation coefficient of patient i in the nerve stimulation treatment mode only with the electrotherapy stimulation coefficient, the influence function F2 is constructed, and then the electrotherapy effect evaluation index Zdl is obtained, so as to evaluate the electrotherapy effect of patient i.

[0044] Further, the specific process of comprehensive analysis of the synergistic treatment mechanism is as follows:

[0045] By combining the physical sign evaluation coefficient, drug intake coefficient and electrotherapy stimulation coefficient under the collaborative treatment mode, the change function F3 is constructed, and then the linkage effect evaluation index Zld is calculated and obtained;

[0046] Construct the curve change diagram S4 of the linkage effect evaluation index Zld, obtain the maximum value of the linkage effect evaluation index Zld by descending sorting, obtain the drug intake coefficient and the electrotherapy stimulation coefficient corresponding to the maximum value of the linkage effect evaluation index Zld, and then integrate them to generate the optimal synergistic treatment plan and output it;

[0047] Among them, the optimal synergistic treatment plan includes a drug design plan and an electrotherapy design plan. The drug design plan is sent to the attending physician for auxiliary reference for subsequent treatment, and the electrotherapy design plan is sent to the signal control unit to control the parameters of the electrotherapy signal.

[0048] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0049] The present invention collects the patient's heart rate data and combined treatment data of depression patients through a data acquisition unit, and then analyzes the influence function of the combined treatment of drugs and electrotherapy on the patient's physical signs through a core analysis unit, so as to obtain the optimal synergistic treatment plan and the corresponding electrotherapy design plan, and performs targeted parameter control on the electrotherapy signal through a signal control unit and outputs an electrotherapy optimization signal, and then performs personalized electrotherapy on depression patients based on vagus nerve stimulation electrodes through a nerve stimulation unit, thereby ensuring the flexibility and accuracy of system application;

[0050] The present invention explores the combined effects of neurostimulation and drug effects on patients, thereby performing targeted parameter regulation on the closed-loop vagus nerve stimulation system according to the patient's personalized condition, achieving adaptive adjustment of the system application process, and improving the accuracy of the actual application of the closed-loop vagus nerve stimulation system by analyzing the combined action mechanism of electrical stimulation and drug therapy, thereby achieving more comprehensive and effective auxiliary monitoring and diagnosis and treatment effects of depression. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1Shows a schematic diagram of the modules of the present invention;

[0052] Figure 2 A schematic diagram of the process of the present invention is shown. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] Embodiment 1:

[0055] like Figure 1-2 As shown, a closed-loop vagus nerve stimulation system for depression includes a data acquisition unit, a core analysis unit, a signal control unit and a nerve stimulation unit, wherein the data acquisition unit, the core analysis unit, the signal control unit and the nerve stimulation unit are signal-connected;

[0056] The working steps are as follows:

[0057] Sa, the data collection unit collects the patient heart rate data and joint treatment data of the depression patient:

[0058] Sa-1, the patient's heart rate data includes the patient's heart rate value and heart rate collection time; the patient's heart rate data is collected and obtained through the heart rate monitoring device;

[0059] Sa-2, combined therapy data including drug parameters and electrotherapy parameters:

[0060] Sa-201, drug parameters include drug name, drug molecule concentration and medication time; drug parameters are obtained by uploading the patient's blood test results to the patient's medical record and accessing the patient's medical record;

[0061] Sa-202, electrotherapy parameters include pulse intensity, pulse frequency and electrotherapy time of electrotherapy signal; electrotherapy parameters are obtained by collecting electrotherapy signal through oscilloscope;

[0062] Sb, the core analysis unit analyzes patient heart rate data and combined treatment data of patients with depression:

[0063] Sb-1, analyze the influence relationship between the patient's heart rate data and drug parameters and the influence relationship between the patient's heart rate data and electrotherapy parameters. The specific process is as follows:

[0064] A1: Construct a curve analysis model, pre-process the patient's heart rate data, drug parameters and electrotherapy parameters in sequence. The specific process of constructing the curve analysis model is as follows:

[0065] Input the curve Sj to the curve analysis model. It is assumed that the curve Sj has N0 points. Any point of the curve Sj is marked as p, the coordinates of point p are marked as (Xp, Yp), and the point closest to point p and its coordinates are marked as q (Xq, Yq);

[0066] Get the slope Kp of point p through the coordinates of point p and point q: Then, the slopes corresponding to the N0 points of the curve Sj are obtained, and then the average slopes corresponding to the N0 points are averaged to obtain the average increase rate of the curve Sj.

[0067] By calculating the standard deviation of the ordinates of the N0 points of the curve Sj, the fluctuation coefficient σs of the curve Sj is obtained: in, is the overall value of the curve Sj. The average value of the vertical coordinates of the N0 points of the curve Sj is obtained to obtain the overall value of the curve Sj.

[0068] The ordinate of the end point of the curve Sj is marked as Ym, and the average increase rate of the curve Sj is Fluctuation coefficient σs, overall value And the end point ordinate Ym is combined to generate the curve two-dimensional characteristic coefficient XER and output:

[0069] Among them, the ordinate Ym of the end point of the curve Sj is related to the average growth rate Combined with the curve to obtain the state coefficient of the curve, when the vertical coordinate Ym of the end point is equal to the average growth rate The higher the value, the higher the coefficient of the curve growth state, indicating that the curve growth trend is more obvious; through the fluctuation coefficient σs of the curve Sj and the overall value Combined to obtain the historical state coefficient of the curve, when the fluctuation coefficient σs and the overall value The higher it is, the higher the historical state coefficient of the curve is, indicating that the overall level of the curve is high and the degree of fluctuation is high during the historical period, indicating that the historical state of the curve has developed more violently;

[0070] λ1 and λ2 are weight coefficients of the curve growth state coefficient and the curve history state coefficient, respectively, and both λ1 and λ2 are greater than 0. The weight coefficients are preset and obtained after a large amount of data experimental measurement. When the curve growth state coefficient and the curve history state coefficient are higher, the curve two-dimensional characteristic coefficient XER is higher, indicating that the two-dimensional characteristic evaluation of the curve Sj is more significant.

[0071] A101: Preprocessing patient heart rate data: By analyzing the heart rate data of patients with depression, the physical sign evaluation coefficient is obtained, so as to evaluate the physical sign status of patient i. The specific process is as follows:

[0072] Mark any depression patient as i, mark the heart rate value of patient i as Li, mark the heart rate collection time as Tl, and construct a curve change graph S0 of the heart rate value Li of patient i-heart rate collection time Tl;

[0073] Substitute the curve variation graph S0 into the curve analysis model, and output the curve two-dimensional characteristic coefficient of the curve S0 by analyzing the curve variation graph S0 and mark it as Xer0;

[0074] The standard interval of the two-dimensional characteristic coefficient Xer0 of the curve is preset to be [E1, E2]. When the two-dimensional characteristic coefficient Xer0 of the curve is in the standard interval [E1, E2], it is determined that the curve change of the heart rate value Li of the patient i is normal; conversely, when the two-dimensional characteristic coefficient Xer0 of the curve is higher or lower than the standard interval [E1, E2], it is determined that the curve change of the heart rate value Li of the patient i is abnormal.

[0075] Then, the physical sign evaluation coefficient Xtz is obtained through the curve two-dimensional characteristic coefficient Xer0 of curve S0 and its preset standard interval [E1, E2]: Xtz = (Xer0-E1)*(E2-Xer0)

[0076] Then, the threshold of the physical sign evaluation coefficient Xtz is set to 0, and the physical sign status of the patient i is evaluated by threshold comparison: when the physical sign evaluation coefficient Xtz is greater than 0, it means that the curve change of the heart rate value Li of the patient i is normal, and thus the physical sign status of the patient is normal; when the physical sign evaluation coefficient Xtz is less than 0, it means that the curve change of the heart rate value Li of the patient i is abnormal, and thus the physical sign status of the patient is abnormal;

[0077] A102: Pretreatment drug parameters:

[0078] A102-1: The drug intake coefficient is obtained by analyzing drug parameters to evaluate the drug intake effect. The specific process is as follows:

[0079] Applying the drug-only treatment mode to patient i, thereby acquiring the corresponding patient heart rate data and drug parameters under the current mode, so as to construct a curve change graph S1 under the drug treatment mode;

[0080] Classify and label the drug names, label any drug name as X, label the drug molecule concentration of drug name X in patient i as Cx, label the medication time as Tf, and simultaneously construct a curve change diagram S1 of drug molecule concentration Cx-medication time Tf;

[0081] Substitute the curve change graph S1 into the curve analysis model, and output the curve two-dimensional characteristic coefficient of the curve S1 by analyzing the curve change graph S1 and mark it as the drug intake coefficient Xyw;

[0082] Then set the evaluation interval of the drug intake coefficient Xyw, and evaluate the drug intake effect by comparing the intervals:

[0083] There are R evaluation intervals of the preset drug intake coefficient Xyw, and any evaluation interval of the drug intake coefficient Xyw is marked as Hr, wherein r is the serial number of the evaluation interval, 0<r≤R, and when the drug intake coefficient Xyw is in the evaluation interval Hr, the drug intake effect is determined to be level r; when the drug intake coefficient Xyw is higher, the level of the drug intake effect is higher, indicating that the drug intake dose of the evaluated patient is higher and the intake effect is better;

[0084] A102-2: By combining the physical sign evaluation coefficient of patient i in the drug treatment mode with the drug intake coefficient, an influence function F1 is constructed to analyze the influence relationship between the patient's heart rate data and the drug parameters, and a drug effect evaluation index is obtained to evaluate the drug effect efficacy of patient i. The specific process is as follows:

[0085] The physical sign evaluation coefficient and the drug intake coefficient of patient i in the drug treatment mode are marked as Xtz1 and Xyw1, respectively. Then, the physical sign evaluation coefficient Xtz1 of patient i in the drug treatment mode is combined with the drug intake coefficient Xyw1 to construct an influence function F1: Xtz1 = F1 (Xyw1). The drug intake coefficient Xyw1 is substituted into the influence function F1 to obtain the corresponding physical sign evaluation coefficient Xtz1.

[0086] Then obtain the drug effect evaluation index Zyw: Thus, the efficacy of the drug effect on patient i can be evaluated;

[0087] When the physical sign evaluation coefficient Xtz1 of patient i in the drug treatment mode is higher and the drug intake coefficient Xyw1 is lower, the drug effect evaluation index Zyw is higher, indicating that under the condition of lower drug intake dose level, the physical sign state of the patient after treatment is better, so the drug effect efficacy of patient i is higher, indicating that the drug treatment effect of patient i is better, conversely, when the drug effect evaluation index Zyw is lower, it means that the drug treatment effect of patient i is worse;

[0088] A103: Pre-treatment electrotherapy parameters:

[0089] A103-1: The electrotherapy stimulation coefficient is obtained by analyzing the electrotherapy parameters, thereby evaluating the electrotherapy stimulation efficacy. The specific process is as follows:

[0090] Applying only the nerve stimulation treatment mode to the patient i to collect and obtain the corresponding patient heart rate data and electrotherapy parameters under the current mode, so as to construct the curve change graph S2 and the curve change graph S3 under the nerve stimulation treatment mode;

[0091] The pulse intensity of the electrotherapy signal is marked as Ad, the pulse frequency of the electrotherapy signal is marked as Fd, and the electrotherapy time is marked as Td, and a curve variation diagram S2 of the pulse intensity Ad-electrotherapy time Td of the electrotherapy signal is constructed, and a curve variation diagram S3 of the pulse frequency Fd-electrotherapy time Td of the electrotherapy signal is constructed synchronously;

[0092] Substitute the curve change graph S2 and the curve change graph S3 into the curve analysis model in sequence, output the curve two-dimensional characteristic coefficient of the curve S2 by analyzing the curve change graph S2 and mark it as Xera, and output the curve two-dimensional characteristic coefficient of the curve S3 by analyzing the curve change graph S3 and mark it as Xerf;

[0093] By combining the two-dimensional characteristic coefficients Xera and Xerf of the curve, the electrotherapy stimulation coefficient Xdl is obtained: Xdl = ω1*Xera+ω2*Xerf;

[0094] Among them, ω1 and ω2 are weight coefficients of the two-dimensional characteristic coefficients Xera and Xerf of the curve, respectively, and ω1 and ω2 are both greater than 0; when the two-dimensional characteristic coefficients Xera and Xerf of the curve are higher, the electrotherapy stimulation coefficient Xdl is higher, indicating that the pulse intensity Ad and pulse frequency Fd of the electrotherapy signal are higher and more intense, and thus the comprehensive electrotherapy stimulation degree is higher;

[0095] Then set the evaluation interval of the electrotherapy stimulation coefficient Xdl, and evaluate the electrotherapy stimulation efficacy by comparing the intervals:

[0096] There are G evaluation intervals of the preset electrotherapy stimulation coefficient Xdl, and any evaluation interval of the electrotherapy stimulation coefficient Xdl is marked as Hg, wherein g is the serial number of the evaluation interval, 0<g≤G, and when the electrotherapy stimulation coefficient Xdl is in the evaluation interval Hg, the electrotherapy stimulation efficacy is determined to be level g; when the electrotherapy stimulation coefficient Xdl is higher, the level of the electrotherapy stimulation efficacy is higher, indicating that the degree of electrotherapy stimulation effect on the patient is higher and the stimulation efficacy is higher;

[0097] A103-2: By combining the physical sign evaluation coefficient of patient i in the nerve stimulation treatment mode with the electrotherapy stimulation coefficient, an influence function F2 is constructed to analyze the influence relationship between the patient's heart rate data and the electrotherapy parameters, and the electrotherapy effect evaluation index is obtained to evaluate the electrotherapy effect of patient i. The specific process is as follows:

[0098] The physical sign evaluation coefficient and the electrotherapy stimulation coefficient of patient i in the nerve stimulation treatment mode are marked as Xtz2 and Xdl2, respectively. Then, the physical sign evaluation coefficient Xtz2 of patient i in the nerve stimulation treatment mode is combined with the electrotherapy stimulation coefficient Xdl2 to construct an influence function F2: Xtz2=F2(Xdl2). The electrotherapy stimulation coefficient Xdl2 is substituted into the influence function F2 to obtain the corresponding physical sign evaluation coefficient Xtz2.

[0099] Then the electrotherapy effect evaluation index Zdl is obtained: Thus, the effect of electrotherapy on patient i can be evaluated;

[0100] When the physical sign evaluation coefficient Xtz2 of patient i in the nerve stimulation treatment mode is higher and the electrotherapy stimulation coefficient Xdl2 is lower, the electrotherapy effect evaluation index Zdl is higher, indicating that under the condition of lower electrotherapy stimulation effect, the physical sign state of the patient after treatment is better. Therefore, the higher the electrotherapy effect of patient i, the better the nerve electrical stimulation treatment effect of patient i. Conversely, when the electrotherapy effect evaluation index Zdl is lower, the electrotherapy effect of patient i is worse.

[0101] Sb-2, analyze the change relationship between the patient's heart rate data and the combined treatment data, so as to obtain the linkage influence relationship between the drug parameters and the electrotherapy parameters on the patient's heart rate data, and generate an electrotherapy design plan to send to the signal control unit. The specific process is as follows:

[0102] A2: Comprehensive analysis of synergistic treatment mechanisms:

[0103] A201: The physical sign evaluation coefficient of patient i in the neural stimulation and drug synergistic treatment mode is obtained by monitoring, and combined with the drug intake coefficient and the electrotherapy stimulation coefficient, and the change function F3 is constructed to analyze the change relationship between the patient's heart rate data and the combined treatment data. The specific process is as follows:

[0104] Applying the neural electrical stimulation and drug synergistic treatment mode to patient i, so as to monitor and obtain the physical sign evaluation coefficient of patient i in the neural electrical stimulation and drug synergistic treatment mode and mark it as Xtz3, and mark the drug intake coefficient and the electrical therapy stimulation coefficient in the synergistic treatment mode as Xyw3 and Xdl3 respectively;

[0105] By combining the physical sign evaluation coefficient Xtz3, the drug intake coefficient Xyw3 and the electrotherapy stimulation coefficient Xdl3 in the collaborative treatment mode, a change function F3 is constructed: Xtz3=F3(Xyw3,Xdl3), and the drug intake coefficient Xyw3 and the electrotherapy stimulation coefficient Xdl3 are substituted into the change function F3 to obtain the corresponding physical sign evaluation coefficient Xtz3;

[0106] A202: The linkage effect evaluation index is obtained by calculation, so as to obtain the linkage effect relationship between the drug parameters and the electrotherapy parameters on the patient's heart rate data, and generate the optimal synergistic treatment plan, where the optimal synergistic treatment plan includes the drug design plan and the electrotherapy design plan. The specific process is as follows:

[0107] Calculate and obtain the linkage effect evaluation index Zld:

[0108]

[0109] Among them, μ1 and μ2 are weight coefficients of the drug intake coefficient Xyw3 and the electrotherapy stimulation coefficient Xdl3, respectively, and both μ1 and μ2 are greater than 0; when the physical sign evaluation coefficient Xtz3 is higher, and the drug intake coefficient Xyw3 and the electrotherapy stimulation coefficient Xdl3 are lower, the linkage effect evaluation index Zld is higher, indicating that when the drug intake dose level and the electrotherapy stimulation effect are lower, the physical sign state of the patient after the synergistic treatment is better, therefore, the linkage effect of the synergistic treatment of the nerve electrical stimulation and the drug for the patient i is better;

[0110] Construct a curve variation diagram S4 of the linkage effect evaluation index Zld, obtain the maximum value of the linkage effect evaluation index Zld by descending sorting and mark it as Zldm, obtain the drug intake coefficient Xyw3m and the electrotherapy stimulation coefficient Xdl3m corresponding to the maximum value Zldm of the linkage effect evaluation index Zld, integrate the drug prescription and the neural electrical stimulation scheme corresponding to the drug intake coefficient Xyw3m and the electrotherapy stimulation coefficient Xdl3m into the optimal synergistic treatment scheme and output it;

[0111] Among them, the neural electrical stimulation scheme is the electrotherapy parameter design scheme corresponding to the electrotherapy stimulation coefficient Xdl3m, which is marked as the electrotherapy design scheme, and the drug prescription corresponding to the drug intake coefficient Xyw3m is marked as the drug design scheme. Therefore, the optimal synergistic treatment plan includes the drug design scheme and the electrotherapy design scheme. The drug design scheme is sent to the attending physician for auxiliary reference for subsequent treatment, and the electrotherapy design scheme is sent to the signal control unit, so as to perform parameter control on the electrotherapy signal;

[0112] It should be noted that the purpose of data monitoring and analysis of the drug treatment mode only and the neural stimulation treatment mode only is to obtain the corresponding physical sign assessment coefficient of the current depression patient i under the single treatment mode. The physical sign assessment coefficient obtained by the collaborative treatment mode should not be lower than the physical sign assessment coefficient under any single treatment mode, so as to obtain the optimal treatment plan under the collaborative treatment mode. If the physical sign assessment coefficient obtained by the collaborative treatment mode is lower than the physical sign assessment coefficient under any single treatment mode, the system will send an abnormal warning signal in time and display an abnormal text, so as to feedback the treatment opinions presented in the abnormal text to the attending physician for reference, so as to adaptively adjust the current patient's diagnosis and treatment methods;

[0113] Sc, the signal control unit receives the electrotherapy design scheme and controls the parameters of the electrotherapy signal:

[0114] The electrotherapy signal refers to a signal that outputs the power supply energy in the form of electric pulses, and the parameter control refers to the control of the electrotherapy parameters, such as the parameter control of the pulse intensity and pulse frequency of the electrotherapy signal, marking the electrotherapy signal after the parameter control as an electrotherapy optimization signal, and then outputting the electrotherapy optimization signal to the nerve stimulation unit;

[0115] Sd, the neurostimulation unit receives the electrotherapy optimization signal and acts on the patient's body to stimulate the patient's nerves, and at the same time generates a management signal to feed back to the data acquisition unit for re-data acquisition, so as to realize the cyclic refresh of the electrotherapy signal, wherein the neurostimulation unit is provided with a vagus nerve stimulation electrode, through which the electrotherapy optimization signal is output and acts on the human body.

[0116] In summary, the present invention collects the patient heart rate data and combined treatment data of depression patients through the data acquisition unit, and then analyzes the influence function of the combined treatment of drugs and electrotherapy on the patient's physical signs through the core analysis unit, so as to obtain the optimal synergistic treatment plan and the corresponding electrotherapy design plan, and the signal control unit performs targeted parameter control on the electrotherapy signal and outputs the electrotherapy optimization signal, and then the neurostimulation unit performs personalized electrotherapy on the depression patient based on the vagus nerve stimulation electrode, thereby ensuring the flexibility and accuracy of the system application;

[0117] The present invention explores the combined effects of neurostimulation and drug effects on patients, thereby performing targeted parameter regulation on the closed-loop vagus nerve stimulation system according to the patient's personalized condition, achieving adaptive adjustment of the system application process, and improving the accuracy of the actual application of the closed-loop vagus nerve stimulation system by analyzing the combined action mechanism of electrical stimulation and drug therapy, thereby achieving more comprehensive and effective auxiliary monitoring and diagnosis and treatment effects of depression.

[0118] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technical personnel in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0119] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0120] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A closed-loop vagus nerve stimulation system for depression, characterized in that: It includes a data acquisition unit, a core analysis unit, a signal control unit and a neural stimulation unit, wherein the data acquisition unit, the core analysis unit, the signal control unit and the neural stimulation unit are signal-connected; The data acquisition unit is used to collect the patient's heart rate data and combined treatment data of the depression patient, and the combined treatment data includes drug parameters and electrotherapy parameters; The core analysis unit is used to analyze the heart rate data and combined treatment data of patients with depression: first analyze the influence relationship between the patient's heart rate data and drug parameters and the influence relationship between the patient's heart rate data and electrotherapy parameters, and then analyze the change relationship between the patient's heart rate data and the combined treatment data, so as to obtain the linkage influence relationship of the combination of drug parameters and electrotherapy parameters on the patient's heart rate data, and generate an electrotherapy design plan to send to the signal control unit; The signal control unit is used to receive the electrotherapy design plan to perform parameter control on the electrotherapy signal, mark the electrotherapy signal after parameter control as an electrotherapy optimization signal, and then output the electrotherapy optimization signal to the nerve stimulation unit; The neurostimulation unit is used to receive the electrotherapy optimization signal and act on the patient to stimulate the patient's nerves. At the same time, it generates a management signal to feed back to the data acquisition unit for re-data acquisition, so as to realize the cyclic refresh of the electrotherapy signal. Among them, the neurostimulation unit is provided with a vagus nerve stimulation electrode, through which the electrotherapy optimization signal is output and acts on the human body.

2. A closed-loop vagus nerve stimulation system for depression according to claim 1, characterized in that: The specific operation process of the core analysis unit is as follows: A1: Construct a curve analysis model and pre-process the patient's heart rate data, drug parameters, and electrotherapy parameters in sequence; A101: Preprocessing patient heart rate data: obtaining a physical sign evaluation coefficient by analyzing the patient heart rate data of patients with depression, thereby evaluating the physical sign status of patient i; A102: Pretreatment drug parameters: A102-1: Obtain drug intake coefficient by analyzing drug parameters to evaluate drug intake effect; A102-2: By combining the physical sign evaluation coefficient of patient i in the drug treatment mode with the drug intake coefficient, an influence function F1 is constructed to analyze the influence relationship between the patient's heart rate data and the drug parameters, and a drug effect evaluation index is obtained to evaluate the drug effect efficacy of patient i; A103: Pre-treatment electrotherapy parameters: A103-1: Obtain the electrotherapy stimulation coefficient by analyzing the electrotherapy parameters, thereby evaluating the electrotherapy stimulation efficacy; A103-2: By combining the physical sign evaluation coefficient of patient i in the nerve stimulation treatment mode with the electrotherapy stimulation coefficient, an influence function F2 is constructed to analyze the influence relationship between the patient's heart rate data and the electrotherapy parameters, and an electrotherapy effect evaluation index is obtained to evaluate the electrotherapy effect of patient i; A2: Comprehensive analysis of synergistic treatment mechanisms: A201: Obtain the physical sign evaluation coefficient of patient i in the neural stimulation and drug synergistic treatment mode by monitoring, and combine it with the drug intake coefficient and the electrotherapy stimulation coefficient to construct a change function F3 to analyze the change relationship between the patient's heart rate data and the combined treatment data; A202: The linkage effect evaluation index is obtained through measurement, so as to obtain the linkage influence relationship between the combination of drug parameters and electrotherapy parameters on the patient's heart rate data, and generate the optimal synergistic treatment plan, where the optimal synergistic treatment plan includes a drug design plan and an electrotherapy design plan.

3. A closed-loop vagus nerve stimulation system for depression according to claim 2, characterized in that: The specific process of constructing the curve analysis model is as follows: Input the curve Sj to the curve analysis model. It is assumed that the curve Sj has N0 points. Any point of the curve Sj is marked as p, the coordinates of point p are marked as (Xp, Yp), and the point closest to point p and its coordinates are marked as q (Xq, Yq); The slope Kp of point p is obtained through the coordinates of point p and point q, and then the slopes corresponding to the N0 points of the curve Sj are obtained. Then, the average slope corresponding to the N0 points is calculated to obtain the average increase rate of the curve Sj. By calculating the standard deviation of the vertical coordinates of the N0 points of the curve Sj, the fluctuation coefficient σs and the overall value of the curve Sj are obtained. The ordinate of the end point of the curve Sj is marked as Ym, and the average increase rate of the curve Sj is Fluctuation coefficient σs, overall value And the vertical coordinate Ym of the end point are combined to generate the two-dimensional characteristic coefficient XER of the curve and output it.

4. A closed-loop vagus nerve stimulation system for depression according to claim 3, characterized in that: The specific process of preprocessing patient heart rate data is as follows: The patient's heart rate data includes the patient's heart rate value and heart rate collection time. Any depression patient is marked as i, the heart rate value of patient i is marked as Li, and the heart rate collection time is marked as Tl. A curve change diagram S0 of the heart rate value Li of patient i-heart rate collection time Tl is constructed; Substitute the curve variation graph S0 into the curve analysis model, and output the curve two-dimensional characteristic coefficient of the curve S0 by analyzing the curve variation graph S0 and mark it as Xer0; The standard interval of the two-dimensional characteristic coefficient Xer0 of the preset curve is [E1, E2]. When the two-dimensional characteristic coefficient Xer0 of the curve is in the standard interval [E1, E2], it is determined that the curve change of the heart rate value Li of the patient i is normal; Then, the physical sign evaluation coefficient Xtz is obtained through the two-dimensional characteristic coefficient Xer0 of the curve S0 and its preset standard interval [E1, E2], and then the threshold of the physical sign evaluation coefficient Xtz is set, and the physical sign status of the patient i is evaluated through threshold comparison.

5. A closed-loop vagus nerve stimulation system for depression according to claim 4, characterized in that: The specific process of preprocessing drug parameters is: Drug parameters include drug name, drug molecule concentration and medication time. The drug names are classified and marked, and any drug name is marked as X. The drug molecule concentration of drug name X in patient i is marked as Cx, and the medication time is marked as Tf. The curve change diagram S1 of drug molecule concentration Cx-medication time Tf is constructed simultaneously. Substitute the curve change graph S1 into the curve analysis model, and output the curve two-dimensional characteristic coefficient of the curve S1 by analyzing the curve change graph S1 and mark it as the drug intake coefficient Xyw; Then set the evaluation interval of the drug intake coefficient Xyw, and evaluate the drug intake effect through interval comparison; By combining the physical sign evaluation coefficient of patient i in the drug-only treatment mode with the drug intake coefficient, the influence function F1 is constructed, and then the drug effect evaluation index Zyw is obtained to evaluate the drug effect efficacy of patient i.

6. A closed-loop vagus nerve stimulation system for depression according to claim 5, characterized in that: The specific process of preprocessing electrotherapy parameters is as follows: The electrotherapy parameters include the pulse intensity, pulse frequency and electrotherapy time of the electrotherapy signal. The pulse intensity of the electrotherapy signal is marked as Ad, the pulse frequency of the electrotherapy signal is marked as Fd, and the electrotherapy time is marked as Td. A curve variation diagram S2 of the pulse intensity Ad-electrotherapy time Td of the electrotherapy signal is constructed, and a curve variation diagram S3 of the pulse frequency Fd-electrotherapy time Td of the electrotherapy signal is constructed synchronously. Substituting the curve change graph S2 and the curve change graph S3 into the curve analysis model in sequence, and obtaining the electrotherapy stimulation coefficient Xdl by combining the curve two-dimensional characteristic coefficients of the curve change graph S2 and the curve change graph S3; Then set the evaluation interval of the electrotherapy stimulation coefficient Xdl, and evaluate the electrotherapy stimulation efficacy through interval comparison; By combining the physical sign evaluation coefficient of patient i in the nerve stimulation treatment mode only with the electrotherapy stimulation coefficient, the influence function F2 is constructed, and then the electrotherapy effect evaluation index Zdl is obtained, so as to evaluate the electrotherapy effect of patient i.

7. A closed-loop vagus nerve stimulation system for depression according to claim 6, characterized in that: The specific process of comprehensive analysis of the synergistic treatment mechanism is as follows: By combining the physical sign evaluation coefficient, drug intake coefficient and electrotherapy stimulation coefficient under the collaborative treatment mode, the change function F3 is constructed, and then the linkage effect evaluation index Zld is calculated and obtained; Construct the curve change diagram S4 of the linkage effect evaluation index Zld, obtain the maximum value of the linkage effect evaluation index Zld by descending sorting, obtain the drug intake coefficient and the electrotherapy stimulation coefficient corresponding to the maximum value of the linkage effect evaluation index Zld, and then integrate them to generate the optimal synergistic treatment plan and output it; Among them, the optimal synergistic treatment plan includes a drug design plan and an electrotherapy design plan. The drug design plan is sent to the attending physician for auxiliary reference for subsequent treatment, and the electrotherapy design plan is sent to the signal control unit to control the parameters of the electrotherapy signal.

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