Percutaneous ear vagus nerve electrical stimulation and disturbance of consciousness correlation qualitative analysis method and system

Abstract

The invention belongs to the technical field of diagnostic data processing, and particularly relates to a percutaneous ear vagus nerve electrical stimulation and disturbance of consciousness correlation qualitative analysis method and system. The consciousness state of the patient can be reflected more comprehensively by constructing the feature information of the standard consciousness evaluation index data distribution data, in addition, influence factors of drug therapy and diseases and lesions can be identified and eliminated more accurately through corresponding verification of the electrical stimulation signal abnormal fluctuation value, and the accuracy of the diagnosis result is improved. Therefore, the accuracy and effectiveness of pathogenesis analysis of the patient are improved, and medical resources can be reasonably distributed and used; the invention further provides a percutaneous ear vagus nerve electrical stimulation and disturbance of consciousness correlation qualitative analysis system and electronic equipment.

Description

Technical Field

[0001] The present invention belongs to the technical field of diagnostic data processing, and in particular relates to a method and system for qualitatively analyzing the correlation between transcutaneous auricular vagus nerve electrical stimulation and consciousness disorders. Background Art

[0002] The study of consciousness disorders and neural stimulation has attracted widespread attention in recent years. There are significant differences in the neural activity of patients with consciousness disorders and normal individuals. Studying these differences can help distinguish different types of consciousness disorders. At the same time, non-invasive brain nerve regulation technologies, such as mechanical stimulation, electrical stimulation, and magnetic stimulation, have been increasingly used. Specifically, electrical stimulation of the vagus nerve has achieved certain results in recent years. It has attracted much attention because it uses electrical stimulation to regulate the state of the body and has broad prospects for clinical application. However, in actual application, the correlation between neural electrical stimulation and consciousness disorders and its specific impact on the patient's state of consciousness still lacks clear qualitative analysis and correlation evaluation.

[0003] Therefore, how to conduct accurate qualitative analysis of the correlation through scientific methods and thus improve the clinical application effect of neural electrical stimulation has become a key issue in current research. Based on this, this program has conducted corresponding research and design. Summary of the invention

[0004] The purpose of the present invention is to provide a qualitative analysis method for the correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorder, which can accurately perform a qualitative analysis on the relationship between transcutaneous auricular vagus nerve stimulation and consciousness disorder.

[0005] The technical solution adopted by the present invention is as follows: A qualitative analysis method for the correlation between transcutaneous auricular vagus nerve electrical stimulation and consciousness disorders, comprising: Acquire the physiological data of the patient in a normal state of consciousness, and perform preprocessing to remove noise and abnormal values ​​to obtain the physiological parameters in a normal state of consciousness; Obtain the patient's physiological data in a state of impaired consciousness, and compare it with the physiological parameters in a state of normal consciousness to obtain consciousness assessment indicators; Obtaining an electrical stimulation signal, and obtaining a corresponding abnormal fluctuation value according to the electrical stimulation signal, and then obtaining a corresponding fluctuation risk according to the abnormal fluctuation value; Determine the correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorders based on consciousness assessment indicators and fluctuation risks, and generate a correlation report; The correlation report includes awareness assessment indicators, volatility risks and correlation conclusions.

[0006] In a preferred embodiment, the step of obtaining physiological data of the patient in a normal state of consciousness, and preprocessing to remove noise and abnormal values ​​to obtain physiological parameters in a normal state of consciousness includes: Obtain the patient's physiological data in a normal state of consciousness and perform normalization processing; Perform denoising on the normalized physiological data to remove noise components in the physiological data; The physiological data after denoising is subjected to duplicate screening to eliminate duplicate parameters in the physiological data and obtain physiological parameters under a normal state of consciousness.

[0007] In a preferred embodiment, the step of obtaining the physiological data of the patient in the state of impaired consciousness and comparing it with the physiological parameters in the state of normal consciousness to obtain the consciousness assessment index includes: Acquire the physiological data of the patient in the state of impaired consciousness, and perform synchronous screening with the physiological parameters in the state of normal consciousness to obtain comparison parameters in the state of impaired consciousness; Performing difference processing on the physiological parameters in the normal consciousness state and the comparison parameters in the consciousness disorder state to obtain difference parameters; comparing the difference parameter with a preset evaluation threshold; When the difference parameter is greater than the evaluation threshold, it indicates that the difference between the physiological parameter in the normal consciousness state and the comparison parameter in the consciousness disorder state is too large, and it is determined that the consciousness information of the patient in the consciousness disorder state is abnormal; When the difference parameter is less than or equal to the evaluation threshold, it indicates that the difference between the physiological parameters in the normal consciousness state and the comparison parameters in the consciousness disorder state is acceptable, and it is determined that the consciousness information of the patient in the consciousness disorder state is normal.

[0008] In a preferred embodiment, the step of obtaining an electrical stimulation signal, obtaining a corresponding abnormal fluctuation value according to the electrical stimulation signal, and then obtaining a corresponding fluctuation risk according to the abnormal fluctuation value includes: Acquiring an electrical stimulation signal and recording a first fluctuation duration of the electrical stimulation signal; Obtaining a standard waveform function of the electrical stimulation signal, and comparing it with the electrical stimulation signal to obtain a plurality of abnormal nodes; Obtaining fluctuation values ​​of the electrical stimulation signals at the plurality of abnormal nodes, and recording them as abnormal fluctuation values; Obtaining a fluctuation delay parameter of the abnormal fluctuation value, and comparing the fluctuation delay parameter with a preset delay threshold; When the fluctuation delay parameter is less than the preset delay threshold, it indicates that the duration of the abnormal fluctuation is short, the electrical stimulation signal is stable, and the corresponding abnormal fluctuation value is determined as a short-term fluctuation risk; When the fluctuation delay parameter is greater than or equal to the delay threshold, it indicates that the abnormal fluctuation lasts for a long time and the electrical stimulation signal is unstable, and the corresponding abnormal fluctuation value is determined as a long-term fluctuation risk.

[0009] In a preferred embodiment, the step of obtaining a standard waveform function of the electrical stimulation signal and comparing it with the electrical stimulation signal to obtain a plurality of abnormal nodes includes: Obtaining a standard waveform function of an electrical stimulation signal; Perform Fourier transform on the standard waveform function to obtain the frequency domain characteristic parameters of the standard waveform; Acquire a sample waveform, and perform Fourier transform on the sample waveform to obtain frequency domain characteristic parameters of the sample waveform; Performing difference processing on the frequency domain characteristic parameters of the standard waveform and the frequency domain characteristic parameters of the sample waveform to obtain frequency domain difference parameters; Acquire the patient's brain wave waveform, and obtain a standard time period according to the brain wave waveform, and obtain an electrical stimulation signal that matches the frequency domain characteristic parameters of the standard waveform within the standard time period, and record it as a verification waveform; Performing the same processing on the time of the verification waveform and the standard waveform, and outputting them as comparison time parameters; When the frequency domain difference parameter is within a preset first comparison threshold, and the comparison time parameter is greater than or equal to a preset second comparison threshold, the verification waveform is calibrated as a standard waveform of the electrical stimulation signal, and the standard period is recorded as a sample period; When the frequency domain difference parameter is not within the preset first comparison threshold, or the comparison time parameter is less than or equal to the preset second comparison threshold, reselecting the verification waveform, and comparing the standard waveform with the verification waveform; The electrical stimulation waveform within the sample period is compared with the standard waveform, and nodes with abnormal comparison are recorded as abnormal nodes.

[0010] In a preferred embodiment, each of the abnormal fluctuation values ​​includes abnormal duration, fluctuation amplitude and fluctuation frequency, wherein the abnormal duration is used to determine short-term fluctuations or long-term fluctuations, the fluctuation amplitude is used to evaluate the degree of change of the fluctuation, and the fluctuation frequency is used to analyze the frequency of occurrence of fluctuations.

[0011] In a preferred embodiment, after obtaining the corresponding fluctuation risk according to the abnormal fluctuation value, the short-term fluctuation amplitude of the electrical stimulation signal is obtained based on the short-term fluctuation risk, and compared with the safety threshold of the short-term fluctuation amplitude; When the short-term volatility is greater than the safety threshold, the corresponding short-term volatility risk will be upgraded to long-term volatility risk; When the short-term fluctuation amplitude is less than or equal to the safety threshold, it is determined that the electrical stimulation signal is normal.

[0012] In a preferred embodiment, the step of determining the correlation between transcutaneous vagus nerve stimulation and consciousness disorder based on the consciousness assessment index and the fluctuation risk, and generating a correlation report, comprises: Obtain comprehensive risk assessment models; Inputting the awareness assessment index and the volatility risk parameter into a comprehensive risk assessment model to obtain a comprehensive risk assessment value; obtaining a comprehensive risk assessment threshold value and comparing it with the comprehensive risk assessment value; When the comprehensive risk assessment value is greater than or equal to the comprehensive risk assessment threshold, it is determined that there is a correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorder, and a correlation report is generated; When the comprehensive risk assessment value is less than the comprehensive risk assessment threshold, it is determined that there is no correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorder, and a non-correlation report is generated.

[0013] In addition, the present invention also provides a qualitative analysis system for the correlation between transcutaneous auricular vagus nerve electrical stimulation and consciousness disorders, comprising: A parameter acquisition module, which is used to obtain physiological data of the patient in a normal state of consciousness, and perform preprocessing to remove noise and abnormal values ​​to obtain physiological parameters in a normal state of consciousness; A state assessment module, which is used to obtain physiological data of the patient in a state of impaired consciousness and compare it with physiological parameters in a state of normal consciousness to obtain consciousness assessment indicators; A stimulation acquisition module, the stimulation acquisition module is used to acquire an electrical stimulation signal, and acquire a corresponding abnormal fluctuation value according to the electrical stimulation signal, and then acquire a corresponding fluctuation risk according to the abnormal fluctuation value; A correlation determination module, the correlation determination module is used to determine the correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorder according to the consciousness assessment index and the fluctuation risk, and generate a correlation report; The correlation report includes awareness assessment indicators, volatility risks and correlation conclusions.

[0014] The present invention also provides an electronic device, comprising: one or more processors; a storage device for storing a computer program executable by one or more processors; Wherein, by executing the computer program, the one or more processors implement the qualitative analysis method for the correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorders.

[0015] The present invention can more comprehensively reflect the patient's state of consciousness by constructing characteristic information of standard consciousness assessment index data distribution data. In addition, through the corresponding verification of abnormal fluctuation values ​​of electrical stimulation signals, it can more accurately identify and exclude the influencing factors of drug treatment and disease lesions, thereby improving the accuracy and effectiveness of patient etiology analysis and enabling medical resources to be reasonably allocated and used. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the method flow of the present invention; Figure 2 It is a schematic diagram of the structure of the system of the present invention. DETAILED DESCRIPTION

[0017] In order to more clearly illustrate the technical solution of the present invention, the following will be described in detail in conjunction with an embodiment. This embodiment is based on the basic solution of the present invention, and the difference is that this embodiment provides some specific parameters and data for better understanding and application of the present invention.

[0018] Example 1 See also Figure 1 The flowchart of the method provided by the present invention is shown in FIG. S1. Acquire the physiological data of the patient in a normal state of consciousness, and perform preprocessing to remove noise and abnormal values ​​to obtain physiological parameters in a normal state of consciousness; S2. Obtain the physiological data of the patient in the state of impaired consciousness, and compare it with the physiological parameters in the state of normal consciousness to obtain consciousness assessment indicators; S3, obtaining an electrical stimulation signal, and obtaining a corresponding abnormal fluctuation value according to the electrical stimulation signal, and then obtaining a corresponding fluctuation risk according to the abnormal fluctuation value; S4. Determine the correlation between transcutaneous vagus nerve stimulation and consciousness disorder based on the consciousness assessment index and the fluctuation risk, and generate a correlation report; wherein the correlation report includes the consciousness assessment index, the fluctuation risk and the correlation conclusion.

[0019] In this embodiment, the fluctuation range of blood pressure specifically refers to ±20 mmHg, the fluctuation range of the electrical stimulation signal specifically refers to ±10%, the normal consciousness state means that the patient is conscious, thinking and behaving normally, and the consciousness disorder means that the patient is unconscious, thinking and behaving abnormally.

[0020] For a voluntary patient: in his normal state of consciousness, his physiological data such as heart rate, brain waves, etc. were: heart rate: 65 beats / min, blood pressure: 90-100mmhg (±20mmhg), brain waves (α waves): 8-12Hz; after the occurrence of consciousness disorder, his physiological data were simultaneously measured and his heart rate fluctuated at 85-100 beats / min, blood pressure fluctuated at 120-160mmhg, and the frequency of abnormal fluctuations was 20 times / min.

[0021] Normal consciousness state refers to a normal body state, such as clear consciousness, normal thinking and behavior, and no abnormal interference. The recording period can be adjusted according to the doctor's advice, such as 1 to 2 days. The sampling period under the normal consciousness state is determined when the patient is conscious and without any abnormalities. Based on this, the patient's physiological data under the normal consciousness state can construct a corresponding feature information template to facilitate real-time comparison of the patient's physiological data under the state of consciousness disorder.

[0022] The physiological data of the patient in the state of impaired consciousness is the original information recorded in the state of impaired consciousness, and the confirmation of abnormal information lies in the physiological data in the normal state of consciousness is in the awake state of the body state, such as heart rate, brain waves, etc. The measurement method is conventional means to obtain weak fluctuations, and after the comparison is completed, the nerve electrical stimulation fluctuation parameters are recorded as ±10%, and the abnormal fluctuation duration is 0.5 hours.

[0023] The steps of obtaining physiological data of a patient in a normal state of consciousness, performing preprocessing, removing noise and abnormal values, and obtaining physiological parameters in a normal state of consciousness include: Obtain the patient's physiological data in a normal state of consciousness and perform normalization processing; Perform denoising on the normalized physiological data to remove noise components in the physiological data; The physiological data after denoising is subjected to duplicate screening to eliminate duplicate parameters in the physiological data and obtain physiological parameters under a normal state of consciousness.

[0024] For the physiological data of patients in a normal state of consciousness, preprocessing is required to remove noise and outliers. This process includes the following steps: First, the collected physiological data are normalized to eliminate the scale differences between different data.

[0025] Secondly, the normalized physiological data is denoised to filter out noise components such as electromagnetic interference.

[0026] The denoised data is subjected to duplicate screening to eliminate the repeatedly recorded physiological parameters, and finally the physiological parameters reflecting the patient's normal state of consciousness are obtained.

[0027] The steps of obtaining physiological data of a patient in a state of impaired consciousness and comparing it with physiological parameters in a state of normal consciousness to obtain consciousness assessment indicators include: Acquire the physiological data of the patient in the state of impaired consciousness, and perform synchronous screening with the physiological parameters in the state of normal consciousness to obtain comparison parameters in the state of impaired consciousness; Performing difference processing on the physiological parameters in the normal consciousness state and the comparison parameters in the consciousness disorder state to obtain difference parameters; comparing the difference parameter with a preset evaluation threshold; When the difference parameter is greater than the evaluation threshold, it indicates that the difference between the physiological parameter in the normal consciousness state and the comparison parameter in the consciousness disorder state is too large, and it is determined that the consciousness information of the patient in the consciousness disorder state is abnormal; When the difference parameter is less than or equal to the evaluation threshold, it indicates that the difference between the physiological parameters in the normal consciousness state and the comparison parameters in the consciousness disorder state is acceptable, and it is determined that the consciousness information of the patient in the consciousness disorder state is normal.

[0028] When the patient is in a state of impaired consciousness, the patient's physiological data is recorded synchronously to ensure data consistency, and then the temperature and other parameters in the state of impaired consciousness are output, and the physiological and psychological parameters (brain waves, heart rate, blood pressure, etc.) in normal consciousness and abnormal consciousness are compared.

[0029] The difference between each pair of parameters is calculated to obtain a difference parameter table, including a series of numerical values.

[0030] Set the assessment threshold (based on clinical data or expert opinion), assuming the threshold is: heart rate: ±5 beats / min, blood pressure: ±10mmhg, brain wave (alpha wave): 1Hz.

[0031] Compare the difference parameters with the evaluation thresholds. The maximum values ​​of the difference parameters are heart rate: 10 beats / min, blood pressure: 15 mmHg, and brain wave (α wave): 2 Hz. If all indicators exceed the evaluation thresholds, it can be determined that the consciousness information of the patient in the state of consciousness disorder is abnormal.

[0032] The steps of obtaining an electrical stimulation signal, obtaining a corresponding abnormal fluctuation value according to the electrical stimulation signal, and then obtaining a corresponding fluctuation risk according to the abnormal fluctuation value include: Acquiring an electrical stimulation signal and recording a first fluctuation duration of the electrical stimulation signal; Assume that the measured electrical fluctuation curve continues to fluctuate for 0.5 hours.

[0033] Obtaining a standard waveform function of the electrical stimulation signal, and comparing it with the electrical stimulation signal to obtain a plurality of abnormal nodes; The standard waveform is recorded when the patient is in a state of normal consciousness. The sampling period under normal consciousness can be determined when the patient is conscious and there are no abnormalities. The first fluctuation occurs once per minute and lasts for 0.5 hours. The frequency control result is 90.8%, sampling state.

[0034] It is calculated as the first fluctuation duration / (total number of abnormal nodes) = 0.5×60×60 / 30=60sec, which means that the electrical stimulation waveform is compared with the standard waveform every minute, and the abnormal node refers to the deviation point of the electrical signal of the neural electrical stimulation signal under the patient's impaired consciousness state and the partial comparison of the electrical signal under the normal consciousness state (assuming the electrical signal is 60%, the abnormal node is marked as 70%).

[0035] Obtaining fluctuation values ​​of the electrical stimulation signals at the plurality of abnormal nodes, and recording them as abnormal fluctuation values; Used to detect instantaneous data at abnormal nodes, at each abnormal node, the deviation amplitude of the electrical stimulation signal from the standard waveform; Assume that three abnormal fluctuation values ​​are defined: abnormal duration, fluctuation amplitude, and fluctuation frequency, which represent the duration, amplitude, and frequency of fluctuation respectively. At the abnormal node, the following data may be observed: abnormal duration is 0.5 seconds, fluctuation amplitude is 1.2 times (i.e., the stimulus signal is 20% higher than the standard waveform), and the fluctuation frequency is one peak per minute.

[0036] Obtaining a fluctuation delay parameter of the abnormal fluctuation value, and comparing the fluctuation delay parameter with a preset delay threshold; When the fluctuation delay parameter is less than the preset delay threshold, it indicates that the duration of the abnormal fluctuation is short, the electrical stimulation signal is stable, and the corresponding abnormal fluctuation value is determined as a short-term fluctuation risk; When the fluctuation delay parameter is greater than or equal to the delay threshold, it indicates that the abnormal fluctuation lasts for a long time and the electrical stimulation signal is unstable, and the corresponding abnormal fluctuation value is determined as a long-term fluctuation risk.

[0037] Specific examples: In human brain wave monitoring, it is assumed that the delay of the measured fluctuation curve of the standard electrical stimulation signal within 0.5 seconds, i.e. 500 milliseconds, is calibrated as a quantitative value, and the delay threshold is set to 100ms, and then compared: Calculate the actual delay quantization value: calculate the time difference between the time point at which each fluctuation value appears in the electrical stimulation signal and the corresponding point in the standard waveform as the quantization value.

[0038] For the first three fluctuation values, it is assumed that the actual delay quantization values ​​are 110ms, 95ms and 105ms respectively.

[0039] If a delay quantization value is greater than or equal to 100ms, it is identified as a long-term volatility risk.

[0040] If it is less than 100ms, it is identified as short-term fluctuation risk.

[0041] This step will classify the stability of the signal based on the delay of each fluctuation value.

[0042] The step of obtaining a standard waveform function of the electrical stimulation signal and comparing it with the electrical stimulation signal to obtain multiple abnormal nodes includes: Obtaining a standard waveform function of an electrical stimulation signal; Perform Fourier transform on the standard waveform function to obtain the frequency domain characteristic parameters of the standard waveform; Acquire a sample waveform and perform Fourier transform on the sample waveform to obtain frequency domain characteristic parameters of the sample waveform; Performing difference processing on the frequency domain characteristic parameters of the standard waveform and the frequency domain characteristic parameters of the sample waveform to obtain frequency domain difference parameters; Acquire the patient's brain wave waveform, and obtain a standard time period according to the brain wave waveform, and obtain an electrical stimulation signal that matches the frequency domain characteristic parameters of the standard waveform within the standard time period, and record it as a verification waveform; Performing the same processing on the time of the verification waveform and the standard waveform, and outputting them as comparison time parameters; When the frequency domain difference parameter is within a preset first comparison threshold, and the comparison time parameter is greater than or equal to a preset second comparison threshold, the verification waveform is calibrated as a standard waveform of the electrical stimulation signal, and the standard period is recorded as a sample period; When the frequency domain difference parameter is not within the preset first comparison threshold, or the comparison time parameter is less than or equal to the preset second comparison threshold, reselecting the verification waveform, and comparing the standard waveform with the verification waveform; The electrical stimulation waveform within the sample period is compared with the standard waveform, and nodes with abnormal comparison are recorded as abnormal nodes.

[0043] Obtaining a standard electrical stimulation waveform function includes performing Fourier transform on the electrical stimulation standard signal to extract frequency domain feature information and the extracted sample waveform and performing comparison processing.

[0044] Generate frequency domain feature parameters, perform difference processing, and obtain a frequency domain feature difference table.

[0045] For example, one frequency domain feature is the main frequency. Assume that the main frequency of the standard waveform is 10 Hz, and the main frequency of the sample waveform is 9.5 Hz after Fourier transform analysis; the frequency domain difference parameter is recorded as: 10 Hz - 9.5 Hz = 0.5 Hz.

[0046] The patient's brain wave waveform is obtained, and a standard time period is obtained according to the brain wave waveform. An electrical stimulation signal matching the frequency domain characteristic parameters of the standard waveform is obtained within the standard time period and recorded as a verification waveform.

[0047] For example: the comparison time parameter is 500ms. If the main frequency of a standard waveform is 10Hz in a certain period of time, and in the second period that follows, the main frequency of the electrical stimulation waveform continues to be higher than 10Hz and reaches 10.5Hz, it will not be calibrated as a standard waveform. Repeat the selection of the verification waveform and perform the above comparison until the standard waveform is finally calibrated.

[0048] Among them, it should be recognized that the standards for specific operating parameters and statistical time nodes can be determined according to different types of electrical stimulation signals, and the specific cycles are combined with physiological characteristics, such as real-time statistical time periods (the content is combined with the operator's understanding of the type of electrical stimulation signal, such as wavelength, frequency, etc.) and autonomic nerve sampling databases (such as sympathetic nerves, vagus nerves, etc.).

[0049] Secondly, it should be made clear that the determination of the standard waveform should be based on the standard time period, and the time polling state should be sampled according to the corresponding characteristic information. For example, if 50% of the normal waveform occurs in one minute and the duration is standard, it can be determined as a standard waveform, and then compared with the abnormal data of the desired period information for feedback.

[0050] Each of the abnormal fluctuation values ​​includes abnormal duration, fluctuation amplitude and fluctuation frequency, wherein the abnormal duration is used to determine short-term fluctuations or long-term fluctuations, the fluctuation amplitude is used to evaluate the degree of change of the fluctuation, and the fluctuation frequency is used to analyze the frequency of occurrence of fluctuations.

[0051] In electroencephalogram (EEG) monitoring, a threshold is set as an abnormal duration greater than 200 milliseconds, and a short-term fluctuation when it is less than 200 milliseconds. The fluctuation amplitude exceeds 100 microvolts and is less than 50 microvolts. It is classified according to the electric field amplitude or other information and recorded as an abnormal fluctuation frequency state.

[0052] The classification basis of electrical stimulation signals is shown in Table 1: Table 1 Classification basis of short-term fluctuations and long-term fluctuations

[0053] After obtaining the corresponding fluctuation risk according to the abnormal fluctuation value, the short-term fluctuation amplitude of the electrical stimulation signal is obtained based on the short-term fluctuation risk, and compared with the safety threshold of the short-term fluctuation amplitude; When the short-term volatility is greater than the safety threshold, the corresponding short-term volatility risk will be upgraded to long-term volatility risk; When the short-term fluctuation amplitude is less than or equal to the safety threshold, it is determined that the electrical stimulation signal is normal.

[0054] For a short-term fluctuation risk, the safety threshold of the short-term fluctuation amplitude is set at 110 microvolts. In this case, if the short-term fluctuation amplitude is 120 microvolts (exceeding the threshold of 110 microvolts), the short-term fluctuation risk will be upgraded to a long-term fluctuation risk, and the brain area will be further examined.

[0055] The steps of determining the correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorder based on consciousness assessment indicators and fluctuation risk, and generating a correlation report, include: Obtain comprehensive risk assessment models; Inputting the awareness assessment index and the volatility risk parameter into a comprehensive risk assessment model to obtain a comprehensive risk assessment value; obtaining a comprehensive risk assessment threshold value and comparing it with the comprehensive risk assessment value; When the comprehensive risk assessment value is greater than or equal to the comprehensive risk assessment threshold, it is determined that there is a correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorder, and a correlation report is generated; When the comprehensive risk assessment value is less than the comprehensive risk assessment threshold, it is determined that there is no correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorder, and a non-correlation report is generated.

[0056] For example, setting up a comprehensive risk assessment model: based on clinical data and expert opinions, determine the comprehensive risk assessment threshold and assume that the threshold is 85. Considering the consciousness assessment index and the fluctuation risk parameter, it is assumed that the patient's assessment index score is 75 (between mild and moderate consciousness disorder) and the fluctuation risk parameter score is 80.

[0057] Output comprehensive risk assessment value: By substituting the awareness assessment index and volatility risk parameters into the comprehensive risk assessment model, a comprehensive risk assessment value is obtained.

[0058] Assume that three regions in the brain are tested and the resulting comprehensive risk assessment values ​​are 90, 88, and 62 respectively.

[0059] The comprehensive risk assessment values ​​and lipid assessment thresholds were compared.

[0060] For the first brain region, the value is 90, which is higher than 85.

[0061] For the second brain region, the value was 88, still higher than 85.

[0062] For the third brain region, the value was 62, down from 85.

[0063] Based on the comprehensive risk assessment value, an association report is generated. When the comprehensive risk assessment value obtained in one or more brain regions is higher than the assessment threshold, an association report is generated, which will contain detailed information about which regions are associated with impaired consciousness, and vice versa. For brain regions with a comprehensive risk assessment value below the threshold, a non-associated report is generated, confirming that the brain region is not sufficiently associated with impaired consciousness.

[0064] Example 2 like Figure 2 As shown, this embodiment provides a system for qualitatively analyzing the correlation between transcutaneous vagus nerve electrical stimulation and consciousness disorders, including: The parameter acquisition module is used to obtain the physiological data of the patient in a normal state of consciousness, and perform normalization, denoising and duplicate screening to remove noise and abnormal values ​​to obtain the physiological parameters in a normal state of consciousness; The state assessment module is used to obtain the physiological data of the patient in the state of impaired consciousness, and to screen and compare them with the physiological parameters in the normal state of consciousness. Specifically, it includes: Obtaining comparison parameters in the state of impaired consciousness; Calculate the difference parameter between the normal state and the disorder state and compare it with the evaluation threshold; Determine whether the difference parameter exceeds the threshold, thereby determining whether the patient's consciousness information is abnormal or not, and generate a consciousness assessment index accordingly; The stimulation acquisition module is used to obtain the electrical stimulation signal and obtain the abnormal fluctuation value and fluctuation risk based on it, specifically including: Acquiring an electrical stimulation signal and recording the duration of the first fluctuation; Obtaining a standard waveform function of the electrical stimulation signal, and performing Fourier transform to extract frequency domain characteristic parameters; Perform Fourier transform on the sample waveform of electrical stimulation and compare the frequency domain difference with the standard waveform; Selecting a brain wave signal verification waveform in a standard period, and judging whether it is a standard waveform according to a frequency domain difference parameter and a comparison time parameter; Identify multiple abnormal nodes in the comparison and obtain the abnormal fluctuation value of each abnormal node; Analyze the duration, amplitude and frequency of abnormal fluctuations to determine whether they are short-term or long-term fluctuations; Obtain the volatility delay parameter and compare it with the delay threshold to preliminarily determine the volatility risk type; Obtain the amplitude of short-term fluctuations and compare it with the safety threshold to further determine whether it has been upgraded to long-term fluctuation risk; The comprehensive assessment module is used to integrate awareness assessment indicators and volatility risk parameters and calculate through a comprehensive risk assessment model, including: Obtain comprehensive risk assessment models; Input the awareness assessment index and volatility risk parameters to obtain a comprehensive risk assessment value; Obtaining a comprehensive risk assessment threshold and comparing it with the comprehensive risk assessment value; Determine whether there is a correlation between impaired consciousness and electrical stimulation; The correlation determination module is used to determine the correlation between transcutaneous vagus nerve stimulation and consciousness disorder based on the comprehensive risk assessment value, and output and generate a correlation report or a non-correlation report containing consciousness assessment indicators, fluctuation risks and correlation conclusions.

[0065] Example 3 This embodiment further limits embodiment 2: This embodiment provides a qualitative analysis system for the correlation between transcutaneous vagus nerve electrical stimulation and consciousness disorders. The system integrates multiple functional modules, can comprehensively evaluate the state of consciousness from multiple dimensions, and combine the fluctuation characteristics of the electrical stimulation signal to identify the risk and make correlation judgments on the abnormal consciousness of the patient. The working principle and specific implementation process of each module will be described in detail below.

[0066] The system as a whole includes: parameter acquisition module, state evaluation module, stimulus acquisition module, comprehensive evaluation module and association judgment module. The system is integrated with a graphical user interface or control system as a platform, and is suitable for scenarios such as neural regulation experiments, coma assessment, and tracking and treatment of patients with consciousness disorders.

[0067] The parameter acquisition module is used to obtain the patient's physiological data and perform multi-level preprocessing operations when the patient is in a normal state of consciousness. The data types collected by this module include but are not limited to electrocardiogram (ECG), electroencephalogram (EEG), blood oxygen saturation, skin conductivity and respiratory rhythm. These data are collected by physiological data acquisition instruments (such as multi-channel monitoring equipment) and input into the processing system through the data channel.

[0068] After the system receives the original physiological signal, it first normalizes the data to unify the amplitude range and time scale of various signals to avoid misjudgment due to unit differences. After normalization, the system calls a noise filtering algorithm, such as wavelet transform or bandpass filter, to remove noise factors such as power supply interference and physiological artifacts.

[0069] Furthermore, the system performs duplicate screening on the denoised data, mainly by comparing the signal change rate within the sampling period and eliminating consecutive repeated invalid records, thereby ensuring that the extracted "physiological parameters under normal consciousness state" are representative and information-dense.

[0070] The state assessment module is responsible for acquiring the patient's physiological data when he is in a state of impaired consciousness and comparing and analyzing it with the normal state, thereby forming a consciousness assessment index. The system uses the time period of impaired consciousness as the calibration time period by calling the patient's medical records, observation records and doctor's judgment results.

[0071] The physiological data collected during this time period will be screened synchronously, maintaining the same dimension and sampling frequency as the normal consciousness data obtained by the parameter acquisition module. The comparison analysis is completed through difference calculation. The system calculates the difference between various physiological parameters in the two states and compares them with the preset "consciousness assessment threshold".

[0072] For example, if the ratio of alpha waves to theta waves in the EEG is 1.5 in a normal state and 0.6 in a state of impaired consciousness, and the assessment threshold is set to 0.8, then this parameter will be marked as an abnormal difference and recorded as an "abnormal point of consciousness." The system combines the abnormal points of multiple parameters to generate a quantitative "consciousness assessment index."

[0073] When the difference parameters collectively exceed the threshold quantity or intensity standard, the system will identify it as abnormal consciousness information; otherwise, it will regard the physiological difference as acceptable and the consciousness state as normal.

[0074] The stimulation acquisition module mainly processes transcutaneous vagus nerve electrical stimulation signals to evaluate the impact of external neural control methods on changes in consciousness. This system supports direct input of signal sequences output by electrical stimulation devices or access through analog signal acquisition ports.

[0075] The system first records the duration of the first wave of the electrical stimulation signal and automatically matches it with the standard waveform function built into the system. The standard waveform function is derived from the statistical average waveform of multiple healthy samples. To ensure the accuracy of the comparison, the system performs Fourier transform operations on both the standard waveform and the current electrical stimulation waveform to extract their frequency domain characteristic parameters.

[0076] Next, by comparing the frequency domain feature difference parameters (such as main frequency offset, amplitude change, etc.) and the time parameters (such as signal alignment), it is determined whether the current signal deviates from the standard range. If the deviation exceeds the preset first comparison threshold (frequency domain) or the second comparison threshold (time domain), the abnormal points in the current waveform are marked as "abnormal nodes" and the fluctuation values ​​at these nodes are extracted as "abnormal fluctuation values".

[0077] For each abnormal fluctuation value, the system further calculates its fluctuation duration, amplitude and frequency. These parameters are used to classify the risk level: When the fluctuation duration is less than the delay threshold, the system determines it as "short-term fluctuation risk"; if it is greater than or equal to the delay threshold, it is "long-term fluctuation risk".

[0078] When it is judged as a short-term volatility risk, the system continues to evaluate whether the amplitude of the fluctuation exceeds the short-term volatility safety threshold. If it exceeds, it will be upgraded to "long-term volatility risk", otherwise it will be judged as a stable signal.

[0079] The comprehensive assessment module introduces a risk assessment model to integrate and evaluate the "awareness assessment index" and "volatility risk" parameters output by the above modules. The assessment model uses multivariate linear discriminant analysis or machine learning classification models, such as support vector machines (SVM) or random forest models.

[0080] After receiving the input, the system calculates a comprehensive risk assessment value, which represents the strength of the possible relationship between abnormal electrical stimulation and abnormal consciousness. To ensure the objectivity of the assessment, the system sets a dynamically adjusted comprehensive risk assessment threshold, which can be adaptively adjusted based on historical samples and patient characteristics.

[0081] When the comprehensive evaluation value is greater than or equal to the threshold, it indicates a high correlation; if it is lower than the threshold, a strong correlation between the two is preliminarily ruled out.

[0082] Based on the processing results of all modules, the association determination module outputs a qualitative analysis report, which includes three items: Consciousness assessment index report: lists the comparative difference analysis results and assessment levels of each physiological signal; Fluctuation risk level analysis: Displays the fluctuation of electrical stimulation signals, risk categories and trend changes; Final relevance conclusion: Determine whether transcutaneous auricular vagus nerve stimulation can induce or improve the state of consciousness disorder, and output a "relevant" or "irrelevant" conclusion.

[0083] If the judgment result is "related", the system will also prompt the doctor to further verify the causal logic based on the delay relationship between the time point of electrical stimulation and the event point of consciousness change; if it is "unrelated", the system can also allow doctors to eliminate interference factors and improve diagnostic efficiency.

[0084] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A qualitative analysis method for the correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorders, characterized in that: include: S1. Acquire the physiological data of the patient in a normal state of consciousness, and perform preprocessing to remove noise and abnormal values ​​to obtain physiological parameters in a normal state of consciousness; S2. Obtain the physiological data of the patient in the state of impaired consciousness, and compare it with the physiological parameters in the state of normal consciousness to obtain consciousness assessment indicators; S3, obtaining an electrical stimulation signal, and obtaining a corresponding abnormal fluctuation value according to the electrical stimulation signal, and then obtaining a corresponding fluctuation risk according to the abnormal fluctuation value; S4. Determine the correlation between transcutaneous vagus nerve stimulation and consciousness disorder based on the consciousness assessment index and the fluctuation risk, and generate a correlation report; wherein the correlation report includes the consciousness assessment index, the fluctuation risk and the correlation conclusion.

2. The method for qualitative analysis of the correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorders according to claim 1, characterized in that: The step of obtaining the physiological data of the patient in a normal state of consciousness, and performing preprocessing to remove noise and abnormal values ​​to obtain the physiological parameters in a normal state of consciousness includes: S11, obtaining physiological data of the patient in a normal consciousness state and performing normalization processing; S12, performing denoising on the normalized physiological data to remove noise components in the physiological data; S13, performing duplicate item screening on the physiological data after denoising, eliminating duplicate parameters in the physiological data, and obtaining physiological parameters under a normal consciousness state.

3. The method for qualitative analysis of the correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorders according to claim 1, characterized in that: The step of obtaining the physiological data of the patient in the state of impaired consciousness and comparing it with the physiological parameters in the state of normal consciousness to obtain the consciousness assessment index includes: S21, obtaining physiological data of the patient in a state of impaired consciousness, and synchronously screening the physiological parameters with those in a state of normal consciousness to obtain comparison parameters in the state of impaired consciousness; S22, performing difference processing on the physiological parameters in the normal consciousness state and the comparison parameters in the consciousness disorder state to obtain difference parameters; S23, comparing the difference parameter with a preset evaluation threshold; S24. When the difference parameter is greater than the evaluation threshold, it indicates that the difference between the physiological parameter in the normal consciousness state and the comparison parameter in the consciousness disorder state is too large, and it is determined that the consciousness information of the patient in the consciousness disorder state is abnormal; S25. When the difference parameter is less than or equal to the evaluation threshold, it indicates that the difference between the physiological parameters in the normal consciousness state and the comparison parameters in the consciousness disorder state is acceptable, and it is determined that the consciousness information of the patient in the consciousness disorder state is normal.

4. The method for qualitative analysis of the correlation between transcutaneous auricular vagus nerve electrical stimulation and consciousness disorders according to claim 2 or 3, characterized in that: The step of obtaining the electrical stimulation signal, obtaining the corresponding abnormal fluctuation value according to the electrical stimulation signal, and then obtaining the corresponding fluctuation risk according to the abnormal fluctuation value includes: S31, obtaining an electrical stimulation signal, and recording a first fluctuation duration of the electrical stimulation signal; S32, obtaining a standard waveform function of the electrical stimulation signal, and comparing it with the electrical stimulation signal to obtain a plurality of abnormal nodes; S33, obtaining fluctuation values ​​of the electrical stimulation signals at the plurality of abnormal nodes, and recording them as abnormal fluctuation values; S34, obtaining a fluctuation delay parameter of the abnormal fluctuation value, and comparing the fluctuation delay parameter with a preset delay threshold; S35. When the fluctuation delay parameter is less than the preset delay threshold, it indicates that the duration of the abnormal fluctuation is short and the electrical stimulation signal is stable, and the corresponding abnormal fluctuation value is determined as a short-term fluctuation risk; S36. When the fluctuation delay parameter is greater than or equal to the delay threshold, it indicates that the abnormal fluctuation lasts for a long time and the electrical stimulation signal is unstable, and the corresponding abnormal fluctuation value is determined as a long-term fluctuation risk.

5. The method for qualitative analysis of the correlation between transcutaneous auricular vagus nerve electrical stimulation and consciousness disorders according to claim 4, characterized in that: The step of obtaining a standard waveform function of the electrical stimulation signal and comparing it with the electrical stimulation signal to obtain a plurality of abnormal nodes includes: S321, obtaining a standard waveform function of an electrical stimulation signal; S322, performing Fourier transform on the standard waveform function to obtain frequency domain characteristic parameters of the standard waveform; S323, obtaining a sample waveform, and performing Fourier transform on the sample waveform to obtain frequency domain characteristic parameters of the sample waveform; S324, performing difference processing on the frequency domain characteristic parameters of the standard waveform and the frequency domain characteristic parameters of the sample waveform to obtain frequency domain difference parameters; S325, obtaining the patient's brain wave waveform, and obtaining a standard time period according to the brain wave waveform, and obtaining an electrical stimulation signal that matches the frequency domain characteristic parameters of the standard waveform within the standard time period, and recording it as a verification waveform; S326, performing the same processing on the time of the verification waveform and the standard waveform, and outputting them as comparison time parameters; S327, when the frequency domain difference parameter is within a preset first comparison threshold, and the comparison time parameter is greater than or equal to a preset second comparison threshold, calibrating the verification waveform as a standard waveform of the electrical stimulation signal, and recording the standard period as a sample period; S328, when the frequency domain difference parameter is not within the preset first comparison threshold, or the comparison time parameter is less than or equal to the preset second comparison threshold, reselecting a verification waveform, and comparing the standard waveform with the verification waveform; S329, comparing the electrical stimulation waveform within the sample period with the standard waveform, and recording nodes with abnormal comparison as abnormal nodes.

6. The method for qualitative analysis of the correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorders according to claim 4, characterized in that: Each of the abnormal fluctuation values ​​includes abnormal duration, fluctuation amplitude and fluctuation frequency, wherein the abnormal duration is used to determine short-term fluctuations or long-term fluctuations, the fluctuation amplitude is used to evaluate the degree of change of the fluctuation, and the fluctuation frequency is used to analyze the frequency of occurrence of fluctuations.

7. The method for qualitative analysis of the correlation between transcutaneous auricular vagus nerve electrical stimulation and consciousness disorders according to claim 4, characterized in that: After obtaining the corresponding fluctuation risk according to the abnormal fluctuation value, the short-term fluctuation amplitude of the electrical stimulation signal is obtained based on the short-term fluctuation risk, and compared with the safety threshold of the short-term fluctuation amplitude; When the short-term volatility is greater than the safety threshold, the corresponding short-term volatility risk will be upgraded to long-term volatility risk; When the short-term fluctuation amplitude is less than or equal to the safety threshold, it is determined that the electrical stimulation signal is normal.

8. The method for qualitative analysis of the correlation between transcutaneous auricular vagus nerve electrical stimulation and consciousness disorders according to claim 1, characterized in that: The step of determining the correlation between transcutaneous vagus nerve stimulation and consciousness disorder based on the consciousness assessment index and the fluctuation risk, and generating a correlation report, comprises: S41. Obtain a comprehensive risk assessment model; S42, inputting the awareness assessment index and the volatility risk parameter into a comprehensive risk assessment model to obtain a comprehensive risk assessment value; S43, obtaining a comprehensive risk assessment threshold, and comparing it with the comprehensive risk assessment value; S44. When the comprehensive risk assessment value is greater than or equal to the comprehensive risk assessment threshold, it is determined that there is a correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorder, and a correlation report is generated; S45. When the comprehensive risk assessment value is less than the comprehensive risk assessment threshold, it is determined that there is no correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorder, and a non-correlation report is generated.

9. A system for qualitative analysis of the correlation between transcutaneous electrical stimulation of the auricular vagus nerve and disorders of consciousness, used for implementing the method according to any one of claims 1 to 8, characterized in that: include: A parameter acquisition module, which is used to obtain physiological data of the patient in a normal state of consciousness, and perform preprocessing to remove noise and abnormal values ​​to obtain physiological parameters in a normal state of consciousness; A state assessment module, which is used to obtain physiological data of the patient in a state of impaired consciousness and compare it with physiological parameters in a state of normal consciousness to obtain consciousness assessment indicators; A stimulation acquisition module, the stimulation acquisition module is used to acquire an electrical stimulation signal, and acquire a corresponding abnormal fluctuation value according to the electrical stimulation signal, and then acquire a corresponding fluctuation risk according to the abnormal fluctuation value; A correlation determination module, the correlation determination module is used to determine the correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorder according to the consciousness assessment index and the fluctuation risk, and generate a correlation report; The correlation report includes awareness assessment indicators, volatility risks and correlation conclusions.

10. An electronic device, characterized in that: include: one or more processors; a storage device for storing a computer program executable by one or more processors; Wherein, by executing the computer program, the one or more processors implement the qualitative analysis method for the correlation between transcutaneous auricular vagus nerve stimulation and consciousness disorders as described in any one of claims 1 to 8.

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