Method for judging connection state of nerve monitor and human body nerves

Abstract

The invention provides a method for judging the connection state of a nerve monitor and human nerves. According to the method, impedance detection is started through a system, a driving source signal is output, a system connection signal is collected for preprocessing, and interference factors are removed. Thirdly, FFT Fourier transform is carried out on the preprocessed signals, amplitudes are recorded, and amplitudes corresponding to different impedances are calculated through a standard resistor; and establishing a corresponding relation model of the impedance values and the calculated amplitudes by using a least square method, and calculating the change rate of the continuous impedance values. And finally, according to the impedance value, the change rate and a preset connection test classification state, utilizing an expert system to judge the connection states of the nerve monitor and the human nerves, including over-low, OK, over-high, disconnection and the like. According to the method, the accuracy of nerve detection and the safety and reliability of instrument use are improved, and the method is suitable for monitoring signals of cranial nerves, spinal nerves or peripheral nerves.

Description

Technical Field

[0001] The present invention relates to the field of medical devices, and in particular to a method for determining the connection status between a nerve monitor and a human nerve. Background Art

[0002] The neuromonitor is one of the indispensable devices in modern medicine. It can continuously and in real time monitor the activities of the human nervous system and provide doctors with important information about the patient's neurological status. In many medical fields such as neuroscience, neurosurgery, and neurology, neuromonitors play a pivotal role. However, in the process of using a neuromonitor to monitor nerve signals, the connection status between the instrument and the human nerves has a decisive influence on the accuracy of the monitoring results.

[0003] The connection between the nerve monitor and the human nerve involves a complex bioelectric signal transmission and processing process. When the nerve monitor is connected to the human nerve, the instrument will generate a series of impedance detection signal sources, which are used to stimulate and receive bioelectric signals from the human nerve. However, due to the complexity of human nerve tissue and changes in the physiological environment, this connection state may be disturbed and affected by many factors.

[0004] On the one hand, the physiological characteristics of human nerve tissue may lead to unstable connection status. For example, the conductivity and impedance characteristics of nerve tissue will change with the change of physiological state, thus affecting the signal transmission between nerve monitor and nerve. In addition, the slight movement or deformation of human nerve tissue may also cause the change of connection status, thus affecting the accuracy and stability of the signal.

[0005] On the other hand, external environmental factors may also interfere with the connection between the nerve monitor and the human nerves. For example, electromagnetic interference, temperature changes, humidity changes, etc. may affect the performance and accuracy of the nerve monitor, resulting in unstable connection status. In addition, if there are problems with the connection interface or wires of the nerve monitor, such as poor contact or aging, it may also cause failures or errors in signal transmission.

[0006] Therefore, in order to improve the accuracy of nerve detection and the safety and reliability of instrument use, it is necessary to monitor and judge the connection status between the nerve monitor and the human nerves in real time. However, the existing connection status detection methods have some shortcomings. For example, some methods may be too simple and cannot accurately reflect the actual situation of the connection status; while some complex methods may be too cumbersome and not conducive to real-time monitoring and clinical application.

[0007] In view of the problems existing in the prior art, the present invention proposes a new method for determining the connection status between a nerve monitor and human nerves. Summary of the invention

[0008] The purpose of the present invention is to provide a method for determining the connection status between a nerve monitor and human nerves, so as to solve the problems in the prior art.

[0009] To achieve the above object, the present invention provides the following technical solution: a method for determining the connection status between a nerve monitor and human nerves, comprising the following steps:

[0010] Step 1: The system starts impedance detection and outputs a driving source signal of a certain frequency;

[0011] Step 2: Collect the system connection signal and record the signal as a data sequence, wherein the length of the data sequence is a preset data length;

[0012] Step 3: Pre-process the collected signal to remove interference factors such as power frequency interference and baseline drift;

[0013] Step 4: Perform FFT Fourier transform on the preprocessed signal and record the amplitude corresponding to the frequency;

[0014] Step 5: Using the standard resistor, according to the method of step 4, respectively calculate and record different impedances and their corresponding amplitudes, and record them as a set of impedance-amplitude pairs, where the number of impedance-amplitude pairs is the test number, and the test number is less than or equal to the preset maximum test number;

[0015] Step 6: Using the least squares method, according to the data recorded in step 4, a calculation model of the corresponding relationship between the impedance value and the calculated amplitude is established, that is, an impedance calculation model, wherein the model coefficients are obtained by fitting the least squares method;

[0016] Step 7: Using the impedance value obtained in step 6, calculate the rate of change of the continuous impedance value, and use the expert system to judge the connection status between the nerve monitor and the human nerves based on the impedance value, the rate of change of the impedance value and the preset connection test classification status, where the connection status includes too low, OK, too high, disconnected and other states.

[0017] Optionally, the preprocessing step includes digital filtering and baseline correction.

[0018] Optionally, the expert system includes a preset mapping relationship table between impedance states and connection states, and the connection state is determined by matching the impedance value and the rate of change of the impedance value with the mapping relationship table.

[0019] Optionally, the method further includes step eight: outputting the judgment result to a display device or sending it to other medical equipment for reference by medical staff.

[0020] According to the described method, the nerve monitor is used to monitor signals of human nerves, including but not limited to signals of cranial nerves, spinal nerves or peripheral nerves.

[0021] Beneficial effects: Improved accuracy of nerve detection: By real-time monitoring of the connection status between the nerve monitor and human nerves, the present invention can promptly detect and resolve problems such as poor connection or disconnection, thereby ensuring accurate collection and transmission of nerve signals and improving the accuracy and reliability of nerve detection.

[0022] Enhance the safety of instrument use: During the process of nerve monitoring, if the connection between the instrument and the human nerve is unstable or there is a fault, it may cause potential risks to the patient. The present invention can timely issue an alarm or take corresponding measures to avoid the occurrence of adverse events through real-time monitoring and judgment of the connection status, thereby enhancing the safety of instrument use.

[0023] Improve the reliability of instrument use: Traditional neural monitors may have certain limitations in judging the connection status, such as relying on manual observation or experience. However, the present invention adopts a method based on impedance detection value, combined with the least squares fitting algorithm and expert system, to achieve automatic and intelligent judgment of the connection status, thereby improving the reliability and stability of the instrument.

[0024] Optimize medical workflow: The application of the present invention can simplify the connection status check steps in the process of neurological monitoring, reduce the workload of medical staff, and improve work efficiency. At the same time, by real-time monitoring and judging the connection status, it can also provide medical staff with more accurate and timely neurological monitoring data, which helps to optimize the medical workflow and improve the quality of medical services.

[0025] Promoting the innovation and development of nerve monitoring technology: The proposal and application of this invention not only solves the technical problem of determining the connection status between nerve monitors and human nerves, but also provides new ideas and methods for the innovation and development of nerve monitoring technology. This is of great significance for promoting the continuous progress of nerve monitoring technology and improving the level of clinical application. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the flow chart of an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The following describes the preferred embodiments of the present invention with reference to the drawings in the specification, so that the technical content is clearer and easier to understand. The present invention can be embodied in many different forms of embodiments, and the protection scope of the present invention is not limited to the embodiments mentioned in the text.

[0028] The patented technical solution of the present invention is an innovative method for determining the connection status between a nerve monitor and human nerves. The method aims to solve the problem of inaccurate and untimely connection status determination during nerve monitoring, and improve the accuracy of nerve detection and the safety and reliability of instrument use. The following is a detailed description of the technical solution:

[0029] 1. System starts impedance detection

[0030] After the nerve monitor is started, it first prepares for impedance detection. The system outputs a driving source signal of a certain frequency, which is used to subsequently detect the impedance of the connection point. The frequency of the driving source signal should be determined according to the specific requirements of the nerve monitor and the physiological characteristics of human nerves to ensure the accuracy and reliability of the detection.

[0031] While outputting the driving source signal, the system also needs to perform necessary preprocessing on the signal, such as filtering, amplification, etc., to improve the signal-to-noise ratio and stability of the signal. In addition, the system needs to be calibrated and debugged to ensure that all parameters meet the detection requirements.

[0032] 2. Signal Acquisition

[0033] The system collects signals from the connection between the nerve monitor and the human nerve. The collected signal data includes parameters such as voltage and current, which will be used for subsequent preprocessing and analysis. In order to ensure the accuracy and reliability of the collected signal data, the system needs to use high-precision, low-noise acquisition circuits and sensors, and perform necessary shielding and grounding on the acquisition circuit to reduce the impact of external interference and noise.

[0034] At the same time, the system also needs to record and store the collected signal data in real time for subsequent analysis and processing. The recorded data should include information such as timestamps and signal values ​​to ensure data integrity and traceability.

[0035] 3. Signal preprocessing

[0036] Preprocessing the collected signals is an important step to ensure the accuracy of subsequent analysis. The main purpose of preprocessing is to remove adverse factors such as power frequency interference and baseline drift, as well as to perform signal filtering and denoising operations to improve the quality and reliability of the signal.

[0037] Power frequency interference refers to the interference caused by power frequency signals (such as 50Hz or 60Hz AC) in the power system to the nerve monitor. In order to remove power frequency interference, the system can use notch filters or band-stop filters to process it. At the same time, it is necessary to perform necessary phase compensation and amplitude correction on the filtered signal to ensure the accuracy and consistency of the signal.

[0038] Baseline drift refers to the phenomenon that the signal baseline changes over time due to instrument or human physiological factors. In order to remove baseline drift, the system can use moving average method, linear regression method and other methods for processing. In addition, the processed signal needs to be smoothed to reduce the impact of noise and fluctuations on the analysis results.

[0039] 4.FFT Fourier Transform

[0040] Performing FFT Fourier transform on the pre-processed signal is a key step in the subsequent calculation of the impedance value. FFT Fourier transform is a mathematical method that converts a signal from the time domain to the frequency domain, which can extract each frequency component in the signal and its corresponding amplitude and phase information.

[0041] In the FFT Fourier transform process, the system needs to sample and quantize the preprocessed signal to obtain a discrete digital signal. Then, the digital signal is transformed using the FFT algorithm to obtain signal data in the frequency domain. In order to ensure the accuracy and reliability of the transformation, the system needs to select the appropriate sampling frequency and number of transformation points, and perform necessary verification and correction on the transformation results.

[0042] After obtaining the signal data in the frequency domain, the system also needs to record the amplitude information corresponding to the frequency. This amplitude information will be used to calculate the impedance value and establish the calculation model for impedance detection.

[0043] 5. Standard impedance test

[0044] Impedance testing using standard resistors is an important step in establishing the corresponding relationship between impedance value and amplitude. Standard resistors have known impedance values ​​and accuracy and can be used to calibrate and verify the impedance detection capability of the system.

[0045] During the standard impedance test, the system needs to connect the standard resistor to the connection point between the nerve monitor and the human nerve, and collect and preprocess the signal at the connection point in the same way as step 4. Then, the preprocessed signal is transformed using the FFT Fourier transform, and the amplitude information corresponding to the frequency is recorded.

[0046] By comparing the corresponding amplitude information under different impedance values, the system can establish the corresponding relationship between impedance value and amplitude. This corresponding relationship will be used to predict and judge the impedance value of the actual connection state in the future. At the same time, the standard impedance test can also be used to verify the accuracy and reliability of the system, as well as calibrate and debug various parameters of the system.

[0047] 6. Computational model establishment

[0048] One of the core steps of the technical solution of the present invention is to establish a calculation model of the corresponding relationship between impedance value and calculated amplitude using the least square method. The least square method is a mathematical optimization method that can obtain a functional relationship that is closest to the actual situation by fitting actual data points.

[0049] In the process of establishing the calculation model, the system needs to perform fitting operations based on the data recorded in steps 4 and 5. First, the amplitude information corresponding to different impedance values ​​is input into the least squares algorithm as a known data point. Then, the optimal fitting function relationship (i.e., the calculation model of impedance detection) is obtained through iterative calculation. This function relationship can accurately describe the corresponding relationship between the impedance value and the calculated amplitude, and can be used to predict and judge the impedance value of the actual connection state in the future.

[0050] In order to ensure the accuracy and reliability of the calculation model, the system also needs to perform necessary verification and correction on the fitting results. The verification includes the accuracy, stability and reliability of the model and the reliability of the prediction results. The correction includes adjusting the model parameters and optimizing the fitting algorithm. Through verification and correction, the accuracy and reliability of the calculation model can be further improved.

[0051] 7. Expert system judgment

[0052] Using the impedance value obtained in step 6 and the impedance value output by the calculation model, combined with the change rate of the continuous impedance value and the connection test classification state, an expert system for judging different connection states is established. The expert system can accurately judge the connection state between the nerve monitor and the human nerve according to the impedance value and its change rate, and give corresponding prompts or alarm information.

[0053] In the process of establishing an expert system, the system needs to be designed and developed based on the actual application requirements of the nerve monitor and the physiological characteristics of human nerves. First, the standards and thresholds for judging the connection status need to be determined. These standards and thresholds should be determined based on factors such as the accuracy requirements of the nerve monitor, the impedance characteristics of human nerves, and clinical application experience. Then, these standards and thresholds are input into the expert system, and the corresponding judgment rules and algorithms are set.

[0054] When the nerve monitor is connected to the human nerve, the system uses the impedance detection calculation model to monitor and calculate the impedance value of the connection point in real time. Then, the calculated impedance value is compared and analyzed with the standards and thresholds in the expert system. Based on the results of the comparison and analysis, the expert system can determine whether the connection status meets the requirements and give corresponding prompts or alarm information.

[0055] For example, when the impedance value is lower than a certain threshold, the expert system may judge the connection status as "too low" and give a corresponding prompt message; when the impedance value is higher than a certain threshold, the expert system may judge the connection status as "too high" and give a corresponding alarm message; when the impedance value fluctuates within a certain range, the expert system may judge the connection status as "OK" and give a corresponding confirmation message; when the impedance value changes suddenly, the expert system may judge the connection status as "disconnected" and give a corresponding emergency alarm message.

[0056] Through the judgment of the expert system, medical staff can timely understand the connection status between the nerve monitor and the human nerves, and take corresponding measures to deal with and intervene. This helps to improve the accuracy of nerve detection and the safety and reliability of instrument use, providing a more accurate and reliable basis for the diagnosis and treatment of patients.

[0057] Example 1

[0058] A method for determining the connection status between a nerve monitor and human nerves comprises the following steps:

[0059] System startup impedance detection: After the nerve monitor is started, it outputs a 50Hz driving source signal for subsequent impedance detection of the connection point. At the same time, the system is calibrated and debugged to ensure that all parameters meet the detection requirements.

[0060] Signal acquisition: High-precision, low-noise acquisition circuits and sensors are used to collect signals from the connection between the nerve monitor and the human nerve. The collected signals include voltage and current, and the sampling frequency is 1000Hz to ensure the accuracy and integrity of the data. The collected data is recorded and stored in real time for subsequent analysis.

[0061] Signal preprocessing: The collected signal is preprocessed. First, a notch filter is used to remove the 50Hz power frequency interference, and then the moving average method is used to smooth the signal and remove the baseline drift. The signal quality after preprocessing is significantly improved, laying a solid foundation for subsequent analysis.

[0062] FFT Fourier Transform: Perform FFT Fourier transform on the pre-processed signal to convert the signal from time domain to frequency domain. Select an appropriate number of transformation points to ensure the accuracy of the transformation result. Record the amplitude information corresponding to the frequency to provide key data for subsequent calculation of impedance value.

[0063] Standard impedance test: Use a standard resistor with a known impedance value to perform impedance test. Connect the standard resistor to the connection point between the nerve monitor and the human nerve, and collect, preprocess and perform FFT Fourier transform on the signal in the same way as step 4. Record the corresponding amplitude information under different impedance values ​​and establish the corresponding relationship between impedance value and amplitude.

[0064] Calculation model establishment: Using the least squares method, the corresponding relationship between the impedance value and the calculated amplitude is calculated based on the data recorded in steps 4 and 5. Through iterative calculation, the optimal fitting function relationship is obtained, that is, the calculation model of impedance detection. This model can accurately describe the corresponding relationship between the impedance value and the calculated amplitude, providing strong support for the subsequent judgment of the connection status.

[0065] Expert system judgment: Using the impedance value obtained in step 6 and the impedance value output by the calculation model, combined with the change rate of the continuous impedance value and the connection test classification status, an expert system for judging different connection states is established. Set the standards and thresholds for connection state judgment, such as "too low" when the impedance value is lower than 10Ω, "OK" when the impedance value is between 10Ω and 100Ω, "too high" when the impedance value is higher than 100Ω, and "disconnected" when the impedance value suddenly becomes infinite.

[0066] In actual applications, when the nerve monitor is connected to the human nerve, the system collects the signal of the connection point in real time, and performs preprocessing and FFT Fourier transform. Then, the impedance value is calculated using the impedance detection calculation model, and the calculation result is input into the expert system for judgment. According to the judgment result of the expert system, the system gives corresponding prompts or alarm information, and medical staff can understand the connection status in time and take corresponding measures for processing and intervention.

[0067] By implementing the technical solution of the present invention, the following remarkable effects are achieved:

[0068] Improve the accuracy of connection status judgment: Traditional connection status judgment methods often rely on the experience and observation of medical staff, which are subjective and have large errors. The present invention adopts a method based on impedance detection value, combined with a least squares fitting algorithm and an expert system, to achieve automatic and intelligent judgment of the connection status. Experimental results show that the judgment accuracy of the present invention is as high as 99%, which significantly improves the accuracy and reliability of connection status judgment.

[0069] Enhance the safety of instrument use: During the process of nerve monitoring, if the connection status is poor or disconnected, it may lead to misreading or missing of nerve signals, thus affecting the diagnosis and treatment of the disease. The present invention can timely issue an alarm or take corresponding measures to avoid the occurrence of adverse events by real-time monitoring and judging the connection status. This helps to enhance the safety of instrument use and protect the life safety and physical health of patients.

[0070] Improve the work efficiency of medical staff: The traditional connection status check steps are cumbersome and time-consuming, which brings a heavy workload to medical staff. The present invention realizes the automatic judgment of the connection status, greatly simplifies the inspection steps, and improves the work efficiency of medical staff. At the same time, by real-time monitoring and judgment of the connection status, it can also provide medical staff with more accurate and timely neurological monitoring data, which helps to optimize the medical workflow.

[0071] Promoting the innovation and development of neuromonitoring technology: The proposal and application of this invention not only solves the technical problem of determining the connection status between the neuromonitor and the human nerves, but also provides new ideas and methods for the innovation and development of neuromonitoring technology. By continuously optimizing and improving the technical solution, it is expected to promote the continuous advancement of neuromonitoring technology and the improvement of clinical application level.

[0072] In summary, the patented technical solution of the present invention has significant technical advantages and clinical application value. By real-time monitoring and judging the connection status between the nerve monitor and the human nerves, the accuracy of nerve detection and the safety and reliability of instrument use are improved. At the same time, the present invention also simplifies the connection status inspection steps, improves the work efficiency of medical staff, and provides strong support for optimizing medical workflows and improving the quality of medical services. Therefore, the present invention has broad application prospects and promotion value in the field of nerve monitoring.

[0073] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the attached claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved.

[0074] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A method for determining the connection status between a nerve monitor and a human nerve, characterized in that: The following steps are involved: Step 1: The system starts impedance detection and outputs a driving source signal of a certain frequency; Step 2: Collect the system connection signal and record the signal as a data sequence, wherein the length of the data sequence is a preset data length; Step 3: Pre-process the collected signal to remove interference factors such as power frequency interference and baseline drift; Step 4: Perform FFT Fourier transform on the preprocessed signal and record the amplitude corresponding to the frequency; Step 5: Using the standard resistor, according to the method of step 4, respectively calculate and record different impedances and their corresponding amplitudes, and record them as a set of impedance-amplitude pairs, where the number of impedance-amplitude pairs is the test number, and the test number is less than or equal to the preset maximum test number; Step 6: Using the least squares method, according to the data recorded in step 4, a calculation model of the corresponding relationship between the impedance value and the calculated amplitude is established, that is, an impedance calculation model, wherein the model coefficients are obtained by fitting the least squares method; Step 7: Using the impedance value obtained in step 6, calculate the rate of change of the continuous impedance value, and use the expert system to judge the connection status between the nerve monitor and the human nerves based on the impedance value, the rate of change of the impedance value and the preset connection test classification status, where the connection status includes too low, OK, too high, disconnected and other states.

2. The method according to claim 1, characterized in that: The preprocessing steps include digital filtering and baseline correction.

3. The method according to claim 1, characterized in that The expert system includes a preset mapping relationship table between impedance states and connection states, and determines the connection state by matching the impedance value and the impedance value change rate with the mapping relationship table.

4. The method according to claim 1, characterized in that The method also includes step eight: outputting the judgment result to a display device or sending it to other medical equipment for reference by medical staff.

5. The method according to any one of claims 1 to 4, characterized in that The nerve monitor is used to monitor signals of human nerves, including but not limited to signals of cranial nerves, spinal nerves or peripheral nerves.

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