An endoscopic nerve monitoring surgical instrument and an electronic device

Abstract

The present application discloses an endoscopic nerve monitoring surgical instrument and an electronic device, relating to the field of nerve avoidance feedback. The method includes: The nerve monitoring surgical instrument includes an integrated electrode, a jaw, a chip control device, and a nerve monitoring wire. The integrated electrode is connected to the nerve monitoring wire, the nerve monitoring wire is connected to the nerve monitor, and the nerve monitoring surgical instrument is connected to the electronic device; transmitting the nerve electrophysiological signal into the nerve monitor; based on the value of the nerve electrophysiological signal, determining whether there is nerve distribution in the target tissue area. In the case where there is no nerve distribution in the target tissue area, outputting a high-frequency stimulation current to perform electrocoagulation operation on the target tissue area. In the case where there is nerve distribution in the target tissue area, determining the nerve distribution of the target area tissue through impedance feedback and the intensity gradient value of the electromyographic signal. The present application can effectively improve the accuracy of nerve detection.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of nerve avoidance feedback, and in particular to an endoscopic nerve monitoring surgical instrument and an electronic device. Background Art

[0002] With the rapid development of technology, the field of medical surgery has also witnessed unprecedented changes. Especially in those extremely delicate surgeries involving endoscopic nerve tissues, every detail of the surgical process is of crucial importance. As one of the most complex and fragile systems in the human body, the integrity of the structure and function of nerve tissues plays a decisive role in the normal operation of the human body. Therefore, during the surgical process, minimizing the risk of nerve injury while maintaining surgical efficiency has become a key factor determining the success of the surgery.

[0003] Currently, for the traditional detection of the covered position of nerves, it mainly determines the covered position of the nerves by real-time monitoring of the electrophysiological signals around the nerve tissues and judging the positional relationship between the detection electrode and the nerve. Specifically, when the detection electrode is placed around the nerve tissue, the doctor will judge the positional relationship between the detection electrode and the nerve based on the characteristics of the electrophysiological signals. For example, when the detection electrode approaches the nerve tissue, the amplitude of the collected signal may increase, and the waveform may become clearer and more regular. However, during the surgical process, when the doctor judges the positional relationship between the detection electrode and the nerve based on the characteristics of the electrophysiological signals, it consumes a great deal of energy, and the doctor also needs to constantly monitor information such as the vital signs of the patient, which may lead to the doctor being fatigued and distracted. In a state of distraction and fatigue, the decision-making accuracy of the doctor is reduced, thus affecting the clinical effect and progress of the surgery. Summary of the Invention

[0004] The embodiments of the present application provide an endoscopic nerve monitoring surgical instrument and an electronic device for improving the accuracy of nerve detection.

[0005] To achieve the above object, the embodiments of the present application adopt the following technical solutions:

[0006] In a first aspect, an endoscopic nerve monitoring surgical instrument is provided. The nerve monitoring surgical instrument includes an integrated electrode, a jaw, a chip control device, and a nerve monitoring wire. The integrated electrode is disposed within the jaw, the integrated electrode is connected to the nerve monitoring wire, the nerve monitoring wire is connected to a nerve monitor, and the nerve monitoring surgical instrument is connected to an electronic device;

[0007] Among them, the electronic device is used to obtain the target tissue in the target surgical area, output a low-frequency stimulation current to the target tissue area by using the integrated electrode in the jaw, transmit the neuroelectrophysiological signal in the target tissue area to the neuro monitor through the nerve monitoring wire, and display the value of the neuroelectrophysiological signal. The neuroelectrophysiological signal includes impedance feedback and electromyogram signal, and based on the value of the neuroelectrophysiological signal, it is judged whether there is nerve distribution in the target tissue area. In the case where there is no nerve distribution in the target tissue area, a high-frequency stimulation current is output by using the integrated electrode in the jaw to perform electrocoagulation operation on the target tissue area. In the case where there is nerve distribution in the target tissue area, the impedance feedback is displayed in real time through the neuro monitor, and the intensity gradient value of the electromyogram signal determined by the chip control device is used to determine the nerve distribution of the target area tissue.

[0008] In a possible implementation manner of the first aspect, the jaw includes an upper jaw and a lower jaw. A cutter head and an integrated electrode are provided in the jaw. The integrated electrode includes a first electrode, a second electrode and a nerve detection electrode. The first electrode and the second electrode are respectively located on the upper jaw and the lower jaw of the jaw, and the nerve detection electrode is integrated on the first electrode or the second electrode. Among them, the cutter head is used to cut the target tissue area, the first electrode and the second electrode are used to perform electrocoagulation on the target tissue area, and the nerve detection electrode is used to detect the nerve distribution in the target tissue area.

[0009] In a possible implementation manner of the first aspect, a nerve monitoring bipolar circuit is provided in the jaw. The nerve monitoring bipolar circuit includes a base, a collector and an emitter. The collector includes a first power supply, a first control switch and a first resistor. One end of the first resistor is connected to the first common point of the base and the emitter, and the other end of the first resistor is connected to one end of the first control switch. The other end of the first control switch is connected to the positive pole of the first power supply. The base includes a second resistor, a third resistor and a second control switch. One end of the second control switch is connected to one end of the second resistor, the other end of the second resistor is connected to the first common point of the collector and the emitter, one end of the third resistor is connected to one end of the second resistor, and the other end of the third resistor is connected to the second common point of the emitter and the ground point. The emitter is connected to the second common point of the ground point and the other end of the third resistor.

[0010] In a possible implementation of the first aspect, a nerve stimulation current circuit is provided inside the jaws. The nerve stimulation current circuit includes an input terminal circuit and an output terminal circuit. The input terminal circuit includes a fourth resistor, a fifth resistor, a capacitor, a relay, and an electromyogram signal module. One end of the fourth resistor is connected to the electromyogram signal module, the other end of the fourth resistor is connected to the capacitor, the other end of the capacitor is connected to the fifth resistor, the other end of the fifth resistor is connected to the coil of the relay, and the other end of the coil is connected to the electromyogram signal module. The output terminal circuit includes a relay, a second power supply, a third control switch, and a sixth resistor. The positive pole of the second power supply is connected to the third control switch, the other end of the third control switch is connected to the sixth resistor, the other end of the sixth resistor is connected to the normally closed contact of the relay, and the other end of the normally closed contact of the relay is connected to the negative pole of the second power supply.

[0011] In a possible implementation of the first aspect, the value of the neuroelectrophysiological signal includes an impedance feedback value and an electromyogram signal. The nerve monitoring surgical instrument is further configured to determine whether the impedance feedback is a first preset impedance threshold based on the impedance feedback value. If the impedance feedback is the first preset impedance threshold, it is determined that there is nerve tissue in the target surgical area, and the integrated electrode stops outputting high-frequency stimulation current and outputs low-frequency stimulation current to implement continuous alternating operations of nerve detection and electrocoagulation operation on the target area tissue in the target surgical area;

[0012] If the impedance feedback is not the first preset impedance threshold, it is determined that there is no nerve tissue in the target surgical area, and the integrated electrode outputs high-frequency stimulation current to implement electrocoagulation operation on the target area tissue in the target surgical area.

[0013] In a possible implementation of the first aspect, the nerve monitoring surgical instrument is further configured to use the integrated electrode to output high-frequency stimulation current to the target surgical area to implement electrocoagulation operation on the target area tissue in the target surgical area. The chip control device is used to obtain the first impedance feedback of the target surgical area in real time. When the first impedance feedback reaches the second preset impedance threshold, the nerve stimulation current circuit is used to output nerve stimulation current to the target surgical area, and the second impedance feedback is obtained in real time. Based on the second impedance feedback, the relative position between the target area tissue and the nerve tissue is determined. When the relative position reaches the preset nerve threshold, the output of high-frequency stimulation current to the target surgical area is stopped.

[0014] In a possible implementation of the first aspect, determining the relative position between the target area tissue and the nerve tissue based on the second impedance feedback includes:

[0015] Comparing the value of the second impedance feedback of the target area tissue with the impedance feedback in the preset database to determine the tissue type of the target area tissue;

[0016] In the target surgical area, obtain the position and impedance value of each electrode in the preset array of electrodes;

[0017] Based on the position and impedance value of each electrode, construct the spatial distribution of impedance values;

[0018] Based on the spatial distribution, use the preset drawing software to draw the impedance value topology map;

[0019] Based on the impedance value topology map, determine the gradient direction of the impedance value change;

[0020] Combining the tissue type and the gradient direction, determine the relative position of the target area tissue and the nerve tissue.

[0021] In a possible implementation manner of the first aspect, by the neural monitor to display the impedance feedback in real time, and the intensity gradient value of the myoelectric signal determined by the chip control device, determine the nerve distribution of the target area tissue, including:

[0022] Obtain the historical impedance feedback and historical myoelectric signals within a preset time period;

[0023] Based on the historical impedance feedback, historical myoelectric signals, and the preset time period, calculate the impedance change rate and the myoelectric signal amplitude slope respectively;

[0024] Based on the impedance change rate and the myoelectric signal amplitude slope, construct an impedance-EMG correlation model;

[0025] Obtain the myoelectric signals within a preset time period in real time, and calculate the amplitude slope of the myoelectric signals;

[0026] Using the preset image processing technology, convert the amplitude slope of the myoelectric signals into an amplitude slope distribution map;

[0027] Mark the areas in the amplitude slope distribution map that exceed the preset amplitude slope threshold to obtain the high-frequency discharge areas;

[0028] Using the preset interpolation algorithm, convert the high-frequency discharge areas into a dynamic EMG heat map;

[0029] Extract the image features of the impedance value topology map and the dynamic EMG heat map, and fuse the image features in the impedance-EMG correlation model to obtain a fused reconstructed image;

[0030] According to the fused reconstructed image, calculate the probability density function of the nerve distribution;

[0031] Convert the probability density function into a visualization image using the preset visualization software;

[0032] In the visualization image, mark the regions where the probability density is greater than a preset density threshold to determine the nerve distribution of the target regional tissue.

[0033] In a possible implementation of the first aspect, according to the fused reconstructed image, calculate the probability density function of the nerve distribution, including:

[0034] Obtain each data point in the fused reconstructed image;

[0035] Use a preset kernel function to calculate the probability density for each data point;

[0036] Superimpose the probability densities of each data point to obtain the probability density function curve of the fused reconstructed image, and the probability density function curve is used to characterize the probability density function.

[0037] In a second aspect, the present application provides an electronic device, including:

[0038] A memory; and

[0039] A processor configured to call instructions from the memory and, when executing the instructions, perform the following steps:

[0040] Obtain the target regional tissue in the target surgical area, use the integrated electrode in the jaw to output a low-frequency stimulation current to the target tissue area, transmit the neuroelectrophysiological signals in the target tissue area to the neuro monitor through the nerve monitoring wire, and display the numerical values of the neuroelectrophysiological signals. The neuroelectrophysiological signals include impedance feedback and electromyographic signals, and based on the numerical values of the neuroelectrophysiological signals, determine whether there is nerve distribution in the target tissue area. In the case where there is no nerve distribution in the target tissue area, use the integrated electrode in the jaw to output a high-frequency stimulation current to perform electrocoagulation operation on the target tissue area. In the case where there is nerve distribution in the target tissue area, display the impedance feedback in real time through the neuro monitor, and determine the intensity gradient value of the electromyographic signal determined by the chip control device to determine the nerve distribution of the target regional tissue.

[0041] Through the above technical solution, by combining the integrated electrode with the nerve monitoring wire, the surgical instrument can accurately locate the nerve position. Through the analysis of impedance feedback and electromyographic signals, the surgeon can clearly understand the nerve distribution, providing precise navigation for the surgery. Through real-time nerve monitoring, the surgical team can accurately determine whether there is nerve distribution in the target surgical area, thus avoiding accidental nerve injury during the surgery and greatly improving the safety of the surgery. After confirming that there is no nerve distribution in the target tissue area, the surgical instrument can quickly switch to the high-frequency stimulation current mode for electrocoagulation operation, simplifying the surgical procedure and improving the surgical efficiency. The endoscopic nerve monitoring surgical instrument significantly improves the safety and efficiency of the surgery through real-time and accurate nerve monitoring functions, reduces postoperative complications, enhances the confidence of the surgeon, and promotes the progress of medical technology.

[0042] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic structural diagram of an endoscopic nerve monitoring surgical instrument provided by an embodiment of the present application;

[0044] Figure 2 It is a schematic flowchart of an endoscopic nerve dynamic avoidance feedback monitoring method provided by an embodiment of the present application;

[0045] Figure 3 It is a nerve monitoring bipolar circuit diagram of an endoscopic nerve monitoring surgical instrument provided by an embodiment of the present application;

[0046] Figure 4 It is a nerve stimulation current circuit diagram of an endoscopic nerve monitoring surgical instrument provided by an embodiment of the present application;

[0047] Figure 5 It is a schematic structural diagram of a chip control device of an endoscopic nerve monitoring surgical instrument provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the specific implementation manners described herein are only used to illustrate and explain the embodiments of the present application, and are not used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0049] It should be noted that if there are directional indications (such as up, down, left, right, front, back...) involved in the embodiments of this application, then such directional indications are only used to explain the relative positional relationship, movement conditions, etc. between components in a certain specific posture (as shown in the drawings). If this specific posture changes, then the directional indications will also change accordingly.

[0050] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of this application, then such descriptions of "first", "second", etc. are only for descriptive purposes and should not be construed as indicating or implying their relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions between various embodiments can be combined with each other, but it must be based on what can be achieved by those of ordinary skill in the art. When the combination of technical solutions results in contradictions or cannot be achieved, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0051] Figure 1 Schematically shows a structural schematic diagram of a surgical instrument for endoscopic nerve monitoring according to an embodiment of the present application. As Figure 1 shown, the embodiment of the present application provides a structural schematic diagram of a surgical instrument for endoscopic nerve monitoring. The surgical instrument for nerve monitoring includes an integrated electrode, a jaw, a chip control device, and a nerve monitoring wire. The integrated electrode is disposed within the jaw. The integrated electrode is connected to the nerve monitoring wire, the nerve monitoring wire is connected to a nerve monitor, and the surgical instrument for nerve monitoring is connected to an electronic device. Among them, the electronic device is used to acquire the target regional tissue within the target surgical area.

[0052] Figure 2 It is a flowchart showing a method for endoscopic nerve dynamic avoidance feedback monitoring provided by an embodiment of the present application. This method may include the following steps.

[0053] S110: Output a low-frequency stimulation current to the target tissue area by using the integrated electrode within the jaw;

[0054] S120: Transmit the nerve electrophysiological signals within the target tissue area to the nerve monitor through the nerve monitoring wire, and display the numerical values of the nerve electrophysiological signals. The nerve electrophysiological signals include impedance feedback and electromyographic signals;

[0055] S130: Based on the numerical values of the nerve electrophysiological signals, determine whether there is a nerve distribution in the target tissue area;

[0056] S140: In the case where there is no nerve distribution in the target tissue area, output a high-frequency stimulation current by using the integrated electrode within the jaw to perform electrocoagulation operation on the target tissue area;

[0057] S150. When there is nerve distribution in the target tissue area, determine the nerve distribution of the target area tissue by using a nerve monitor to display impedance feedback in real time and the intensity gradient value of the electromyogram signal determined by a chip control device.

[0058] In this embodiment, the integrated electrode is disposed inside the jaw and is in close fit with the clamping surface of the jaw. The integrated electrode is used to output low-frequency or high-frequency stimulation currents. The high-frequency stimulation current is used for electrocoagulation treatment of the target tissue area, and the low-frequency stimulation current is used for nerve detection treatment of the target tissue area. The jaw is used to clamp and fix the tissue in the surgical area, providing a stable contact surface for the integrated electrode to ensure accurate transmission of electrical signals and effective action of the stimulation current. The chip control device is used to process and analyze the neuroelectrophysiological signals received from the integrated electrode, including impedance feedback and electromyogram signals, and control the working mode of the surgical instrument according to the analysis results. The nerve monitoring wire connects the integrated electrode and the nerve monitor and is responsible for transmitting the neuroelectrophysiological signals to the nerve monitor for display and analysis. In this embodiment, the electronic device can be a device with a processor such as a tablet computer, a desktop computer, a laptop computer, a handheld computer, a wearable device, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, etc. Of course, the electronic device can also be a server. The specific form of the electronic device in the embodiments of the present application is not particularly limited. The electronic device is used to obtain the target tissue information in the target surgical area, control the working mode of the surgical instrument, and display the values and analysis results of the neuroelectrophysiological signals.

[0059] The working principle of the endoscopic nerve monitoring surgical instrument. Specifically, first, use the electronic device to obtain the target area tissue in the target surgical area. Specifically, before the operation starts, the surgeon starts the electronic device and makes corresponding settings according to the operation requirements. The electronic device usually has a high-resolution display screen and advanced image processing functions, and can clearly display the tissue structure in the surgical area. Obtain real-time images of the target surgical area through an endoscope. In one embodiment, the surgeon can use these images, combined with their professional knowledge and experience, to identify and determine the target area tissue to be processed. In another embodiment, the target area tissue to be processed can be identified by a preset image recognition algorithm.

[0060] After identifying the target regional tissue, the surgeon can use the positioning tool or marking function on the electronic device to accurately locate and mark the target regional tissue on the image. In this embodiment, the target surgical area refers to a specific anatomical area for the operation, which is determined by the surgical purpose and the specific condition of the patient; the target regional tissue refers to the specific tissue within the target surgical area that requires surgical operation or monitoring. Subsequently, a low-frequency stimulating current is output to the target tissue area through the integrated electrode within the jaw. The low-frequency stimulating current is used to stimulate the nerve to generate an electrophysiological response. While outputting the stimulating current, the integrated electrode receives the nerve electrophysiological signals within the target tissue area, including impedance feedback and electromyographic signals, which reflect the response of the nerve to the stimulating current. Through the nerve monitoring wire, the received nerve electrophysiological signals are transmitted into the nerve monitor. Based on the numerical values of the nerve electrophysiological signals, it is judged whether there is nerve distribution in the target regional tissue. And according to the judgment result of the nerve distribution, the surgeon will decide the next operation. If there is no nerve distribution in the target regional tissue, electrocoagulation operation can be performed; if there is nerve distribution, more cautious handling is required to avoid nerve injury. After confirming that there is no nerve distribution in the target regional tissue, the surgical instrument outputs a high-frequency stimulating current through the integrated electrode within the jaw. This high-frequency current has sufficient energy to destroy the tissue to achieve the purpose of hemostasis or cutting. The high-frequency stimulating current performs electrocoagulation operation on the target regional tissue to ensure that the bleeding during the operation is controlled and at the same time avoid damage to the surrounding tissue. If there is nerve distribution in the target regional tissue, the nerve monitor will display the impedance feedback in real time. The change of the impedance feedback can reflect the relative position relationship between the nerve and the electrode, helping the surgeon to more accurately locate the nerve. At the same time, the chip control device will analyze the electromyographic signal to determine its intensity gradient value. The intensity gradient of the electromyographic signal can reflect the intensity and direction of nerve activity. Combining the impedance feedback and the intensity gradient value of the electromyographic signal to avoid nerve injury.

[0061] Through the above technical solution, by combining the integrated electrode and the nerve monitoring wire, the surgical instrument can accurately locate the nerve position. Through the analysis of the impedance feedback and the electromyographic signal, the surgeon can clearly understand the nerve distribution, providing precise navigation for the operation. Through real-time nerve monitoring, the surgical team can accurately judge whether there is nerve distribution within the target surgical area, thus avoiding accidental nerve injury during the operation and greatly improving the safety of the operation. After confirming that there is no nerve distribution within the target tissue area, the surgical instrument can quickly switch to the high-frequency stimulating current mode for electrocoagulation operation, simplifying the surgical procedure and improving the surgical efficiency. The endoscopic nerve monitoring surgical instrument significantly improves the safety and efficiency of the operation through real-time and accurate nerve monitoring function, reduces postoperative complications, enhances the confidence of the surgeon, and promotes the progress of medical technology.

[0062] In one implementation of this embodiment, the jaw includes an upper jaw and a lower jaw. A cutter head and an integrated electrode are provided inside the jaw. The integrated electrode includes a first electrode, a second electrode, and a nerve detection electrode. The first electrode and the second electrode are respectively located in the upper jaw and the lower jaw of the jaw. The nerve detection electrode is integrated into the first electrode or the second electrode. Among them, the cutter head is used to cut the target tissue area, the first electrode and the second electrode are used to electrocoagulate the target tissue area, and the nerve detection electrode is used to detect the nerve distribution in the target tissue area.

[0063] In this embodiment, the jaw is composed of an upper jaw and a lower jaw. The upper jaw and the lower jaw can move relative to each other to clamp, cut, or process tissues. A cutter head is provided inside the jaw, which is a component for cutting the target tissue area. The cutter head is usually sharp and designed with a specific shape to meet different surgical needs; an integrated electrode is also provided inside the jaw, and these electrodes are used to provide electrical energy during the operation to achieve functions such as electrocoagulation or nerve detection; the integrated electrode includes a first electrode, a second electrode, and a nerve detection electrode; the first electrode and the second electrode are respectively located in the upper jaw and the lower jaw of the jaw, and are respectively used to electrocoagulate the clamped tissue area, that is, to coagulate the tissue through the action of electrical energy to achieve the purpose of hemostasis or tissue destruction; the nerve detection electrode is integrated into the first electrode or the second electrode, and is mainly used to detect the nerve distribution in the target tissue area. By sending and receiving electrical signals, it can identify the position and activity state of the nerve, thus helping the surgeon to avoid damaging the nerve during the operation.

[0064] Through the endoscopic nerve monitoring surgical instrument, tissue cutting, electrocoagulation, and nerve detection can be achieved simultaneously during the operation, improving the accuracy and safety of the operation. Especially the application of the nerve detection electrode enables the surgeon to understand the position and state of the nerve in real time during the operation, thus avoiding nerve damage and protecting the patient's nerve function.

[0065] In one implementation of this embodiment, a nerve monitoring bipolar circuit is provided inside the jaw. The nerve monitoring bipolar circuit includes a base, a collector, and an emitter. The collector includes a first power supply, a first control switch, and a first resistor. One end of the first resistor is connected to the first common point of the base and the emitter, and the other end of the first resistor is connected to one end of the first control switch. The other end of the first control switch is connected to the positive pole of the first power supply. The base includes a second resistor, a third resistor, and a second control switch. One end of the second control switch is connected to one end of the second resistor. The other end of the second resistor is connected to the first common point of the collector and the emitter. One end of the third resistor is connected to one end of the second resistor, and the other end of the third resistor is connected to the second common point of the emitter and the ground point. The emitter is connected to the second common point of the ground point and the other end of the third resistor.

[0066] In this embodiment, Figure 3 shows a neural monitoring bipolar circuit diagram of an endoscopic neural monitoring surgical instrument provided by an embodiment of the present application. Referring to Figure 3 , a neural monitoring bipolar circuit is provided inside the jaws of the endoscopic neural monitoring surgical instrument. The specific structure of the neural monitoring bipolar circuit includes three main parts: a base, a collector, and an emitter. Among them, the collector includes a first power supply, a first control switch, and a second resistor; one end of the second resistor is connected to the first common point of the base and the emitter, which is an important connection point in the circuit for connecting a part of the base and emitter circuits to the collector; the other end of the second resistor is connected to one end of the first control switch, and the first control switch is used to control the on and off of the circuit; the other end of the first control switch is connected to the positive pole of the first power supply, and the first power supply provides electrical energy for the circuit. The base includes a third resistor, a fourth resistor, and a second control switch; one end of the second control switch is connected to one end of the third resistor for controlling the on and off of the base part of the circuit; the other end of the third resistor is connected to the first common point of the collector and the emitter, forming a circuit connection with the collector; one end of the fourth resistor is connected to one end of the third resistor, jointly constituting a part of the base circuit; the other end of the fourth resistor is connected to the second common point of the emitter and the ground point, connecting the base to the emitter and the ground part. The emitter is connected to the second common point of the ground point and the other end of the fourth resistor, forming the ground part of the circuit.

[0067] Specifically, when both the first control switch and the second control switch are in the closed state, the circuit forms a path. The electrical energy provided by the first power supply flows through the collector, base, and emitter, forming a current loop. The second resistor, third resistor, and fourth resistor play a role in current limiting and voltage division in the circuit, protecting circuit components from damage caused by excessive current. The neural monitoring bipolar circuit can monitor the nerve distribution in the tissue area clamped by the jaws through a specific electrical signal sending and receiving mechanism. When a nerve is present, it may change the electrical characteristics (such as resistance, current, or voltage) of the circuit, which can then be detected by the circuit and converted into a usable neural monitoring signal.

[0068] By providing the neural monitoring bipolar circuit inside the jaws, the surgical instrument can monitor the nerve distribution and activity status in real time during the operation, providing accurate nerve position information for the surgeon, helping to avoid nerve damage and improve the safety of the operation.

[0069] In one implementation of this embodiment, a nerve stimulation current circuit is provided inside the jaw. The nerve stimulation current circuit includes an input terminal circuit and an output terminal circuit. The input terminal circuit includes a fourth resistor, a fifth resistor, a capacitor, a relay, and an electromyogram signal module. One end of the fourth resistor is connected to the electromyogram signal module, the other end of the fourth resistor is connected to the capacitor, the other end of the capacitor is connected to the fifth resistor, the other end of the fifth resistor is connected to the coil of the relay, and the other end of the coil is connected to the electromyogram signal module. The output terminal circuit includes a relay, a second power supply, a third control switch, and a sixth resistor. The positive pole of the second power supply is connected to the third control switch, the other end of the third control switch is connected to the sixth resistor, the other end of the sixth resistor is connected to the normally closed contact of the relay, and the other end of the normally closed contact of the relay is connected to the negative pole of the second power supply.

[0070] In this embodiment, referring to Figure 4 , the nerve stimulation current circuit diagram of an endoscopic nerve monitoring surgical instrument provided by the embodiment of the present application integrates a nerve stimulation current circuit inside the jaw. This circuit is designed to provide nerve stimulation under specific conditions. The nerve stimulation current circuit is mainly divided into two parts: an input terminal circuit and an output terminal circuit. The input terminal circuit is mainly responsible for receiving and processing external signals, which are usually the conditions or instructions required to trigger nerve stimulation. In this example, the input terminal circuit includes a fourth resistor, a fifth resistor, a capacitor, a relay, and an electromyogram signal module. The electromyogram signal module is used to detect the electromyogram signal of the patient, which is a possible condition for triggering nerve stimulation. The fourth resistor, the fifth resistor, and the capacitor together form a signal conditioning circuit for filtering, amplifying, or shaping the electromyogram signal to ensure the accuracy and reliability of the signal. The relay controls the on / off of the output terminal circuit according to the processed electromyogram signal. The connection relationship of the input terminal circuit is that one end of the fourth resistor is connected to the electromyogram signal module to receive the electromyogram signal as input. The other end of the fourth resistor is connected to the capacitor, and the capacitor is used for signal filtering or delay. The other end of the capacitor is connected to the fifth resistor to further adjust the signal. The other end of the fifth resistor is connected to the coil of the relay, and the coil controls the switch state of the relay according to the received signal. The other end of the coil returns to the electromyogram signal module to form a closed loop.

[0071] The output terminal circuit is mainly responsible for generating and outputting a nerve stimulation current after receiving the signal from the input terminal circuit. In this embodiment, the output terminal circuit includes a relay, a second power supply, a third control switch, and a sixth resistor; the second power supply provides electrical energy for the generation of the nerve stimulation current; the third control switch allows the user or the system to automatically control the start and stop of the nerve stimulation; the sixth resistor is used to limit the magnitude of the nerve stimulation current to ensure the safety and effectiveness of the stimulation; the relay controls the on / off of the output terminal circuit according to the signal from the input terminal circuit. When the relay is closed, the second power supply generates a nerve stimulation current through the sixth resistor. The connection relationship of the output terminal circuit is that the positive pole of the second power supply is connected to the third control switch, and the control switch is used to manually or automatically control the on / off of the circuit; the other end of the third control switch is connected to the sixth resistor, and the sixth resistor is used to limit the current magnitude; the other end of the sixth resistor is connected to the normally closed contact of the relay. When the relay coil is energized, the normally closed contact is disconnected and the circuit is disconnected; when the coil is de-energized, the normally closed contact is closed and the circuit is conducted; the other end of the normally closed contact of the relay is connected to the negative pole of the second power supply to form a complete output circuit.

[0072] The working principle of the nerve stimulation current circuit is that when the electromyogram signal module detects a specific electromyogram signal, it is transmitted to the coil of the relay through the fourth resistor, capacitor, and fifth resistor, so that the relay coil is energized, the normally closed contact of the relay is disconnected, and the output terminal circuit is disconnected, and no nerve stimulation current is generated. When the electromyogram signal module does not detect a specific electromyogram signal or the signal is lower than the threshold, the relay coil is de-energized, the normally closed contact of the relay is closed, and the second power supply forms a closed loop through the third control switch, the sixth resistor, and the normally closed contact of the relay to generate a nerve stimulation current.

[0073] The nerve stimulation current circuit can provide precise nerve stimulation during surgery or rehabilitation treatment. Through the control of the electromyogram signal, it is possible to adjust the stimulation intensity and frequency according to the patient's real-time physiological state, improving the accuracy and effectiveness of the treatment. And it realizes the control of the generation of the nerve stimulation current according to the electromyogram signal, providing a more intelligent and precise control method for medical devices.

[0074] In one implementation manner of this embodiment, the value of the neuroelectrophysiological signal includes an impedance feedback value and an electromyogram signal. The nerve monitoring surgical instrument is also used to judge whether the impedance feedback is a first preset impedance threshold based on the impedance feedback value. If the impedance feedback is the first preset impedance threshold, it is determined that there is nerve tissue in the target surgical area, and the integrated electrode stops outputting the high-frequency stimulation current and outputs a low-frequency stimulation current to realize the continuous alternating operation of nerve detection and electrocoagulation operation processing on the target area tissue in the target surgical area.

[0075] If the impedance feedback is not the first preset impedance threshold, it is determined that there is no nerve tissue in the target surgical area, and the integrated electrode outputs a high-frequency stimulation current to perform electrocoagulation operation on the target area tissue in the target surgical area.

[0076] In this embodiment, the value of the neuroelectrophysiological signal is used to monitor and judge whether there is nerve tissue in the target surgical area, and accordingly control the output current type of the integrated electrode to realize the intelligent alternation of nerve detection and electrocoagulation operation. The impedance feedback value is measured by a nerve monitoring surgical instrument and reflects the impedance between the surgical instrument and the target tissue. The change in impedance can indirectly reflect the nature of the tissue. For example, the presence of nerve tissue may cause specific changes in impedance; the electromyogram signal is a bioelectric signal that records muscle activity through electrodes, which reflects the state of muscle contraction and relaxation. The electromyogram signal is measured by a nerve monitoring surgical instrument and is used for nerve monitoring.

[0077] After obtaining the neuroelectrophysiological signal, based on the value of the impedance feedback, it is judged whether the impedance feedback is the first preset impedance threshold. In this embodiment, the first preset impedance threshold is determined according to experience or experiments and is a reference standard threshold for judging whether there is nerve tissue in the target surgical area. Specifically, the real-time monitored impedance feedback value is compared with the first preset impedance threshold. When the impedance feedback value is equal to or close to the first preset impedance threshold, the surgical system judges that there may be nerve tissue in the target surgical area. To avoid damaging the nerve tissue, the surgical instrument will immediately stop outputting the high-frequency current that may stimulate or damage the nerve tissue. At the same time, the surgical instrument may output a low-frequency stimulation current for nerve detection of the target area tissue to confirm the specific position and distribution of the nerve tissue. When the impedance feedback value is not equal to the first preset impedance threshold, the surgical system judges that there is no nerve tissue in the target surgical area. At this time, the integrated electrode will output a high-frequency stimulation current for electrocoagulation operation on the target area tissue. The high-frequency stimulation current has a strong coagulation effect and can stop bleeding or destroy tissue quickly and effectively. When it is determined that there is nerve tissue in the target surgical area, the surgical instrument will alternately perform nerve detection and electrocoagulation operation. This alternating operation can ensure that the nerve tissue is not damaged during the operation and the target tissue is effectively processed.

[0078] By monitoring the impedance feedback value to judge whether there is nerve tissue in the target surgical area and accordingly control the output current type of the integrated electrode. This intelligent alternating operation method can improve the safety and accuracy of the operation and reduce the risk of damaging the nerve tissue during the operation. At the same time, it also reflects the development trend of medical devices towards intelligence and precision.

[0079] In one implementation of this embodiment, the nerve monitoring surgical instrument is also used to output a high-frequency stimulation current to the target surgical area by using an integrated electrode, so as to perform electrocoagulation operation on the target area tissue in the target surgical area. Through the chip control device, the first impedance feedback of the target surgical area is obtained in real time. When the first impedance feedback reaches the second preset impedance threshold, the nerve stimulation current circuit is used to output a nerve stimulation current to the target surgical area, and the second impedance feedback is obtained in real time. Based on the second impedance feedback, the relative position between the target area tissue and the nerve tissue is determined. When the relative position reaches the preset nerve threshold, the output of the high-frequency stimulation current to the target surgical area is stopped.

[0080] In this embodiment, the nerve monitoring surgical instrument is equipped with an integrated electrode, which can apply a high-frequency stimulation current to the tissue in the target surgical area. The high-frequency stimulation current is mainly used for electrocoagulation operation, that is, the target area tissue is coagulated through the thermal effect of the current to achieve the purpose of hemostasis or cutting. The first impedance feedback is used to reflect the change in impedance between the surgical instrument and the target tissue. The first impedance feedback of the target surgical area is obtained through the surgical instrument. When the first impedance feedback reaches the second preset impedance threshold, the surgical instrument will trigger a specific response mechanism. The second preset impedance threshold is set according to surgical requirements and experience, and is used to judge when to switch to the nerve monitoring mode of the surgical instrument. Specifically, after reaching the second preset impedance threshold, the surgical instrument will use the nerve stimulation current circuit to output a nerve stimulation current to the target surgical area. The nerve stimulation current is a low-frequency and low-intensity current, which is used to stimulate nerve tissue and generate a detectable response.

[0081] Subsequently, while outputting the nerve stimulation current, the surgical instrument will obtain the second impedance feedback in real time. While outputting the nerve stimulation current, the surgical instrument will obtain the second impedance feedback in real time. And based on the second impedance feedback, the surgical instrument can determine the relative position between the target area tissue and the nerve tissue. That is to say, when the relative position reaches the preset nerve threshold, it means that the surgical instrument may be close to or has contacted the nerve tissue. To avoid damaging the nerve tissue, the surgical instrument will immediately stop outputting the high-frequency stimulation current to the target surgical area.

[0082] Through the nerve monitoring surgical instrument, through integrated electrode, real-time impedance monitoring, nerve stimulation current output and relative position judgment, an intelligent surgical operation process is realized. This surgical instrument can ensure the surgical effect while maximizing the safety of nerve tissue and improving the success rate and safety of the surgery.

[0083] In one implementation of this embodiment, determining the relative position between the target area tissue and the nerve tissue based on the second impedance feedback includes:

[0084] Compare the value of the second impedance feedback of the target region tissue with the impedance feedback in the preset database to determine the tissue type of the target region tissue;

[0085] In the target surgical area, obtain the position and impedance value of each electrode in the preset array electrode;

[0086] Construct the spatial distribution of impedance values based on the position and impedance value of each electrode;

[0087] Draw an impedance value topology map using the preset mapping software based on the spatial distribution;

[0088] Determine the gradient direction of the impedance value change based on the impedance value topology map;

[0089] Combine the tissue type and the gradient direction to determine the relative position of the target region tissue and the nerve tissue.

[0090] Compare the value of the second impedance feedback of the target region tissue with the impedance feedback in the preset database to determine the tissue type of the target region tissue. Specifically, bioimpedance is a complex quantity composed of a resistance value and a reactance value, which reflects the inherent properties of biological tissues in an electromagnetic field. Different tissue types will exhibit different bioimpedance characteristics due to differences in their cell structure, water content, and ion distribution. Therefore, by measuring bioimpedance, the identification of tissue types can be achieved. The second impedance feedback of the target region tissue will be obtained. Then, compare the value of this impedance feedback with the impedance feedback in the preset database to determine the tissue type of the target region tissue. Specifically, by comparing the real-time impedance feedback with the impedance feedback in the preset database, when the real-time impedance feedback highly matches the impedance feedback of a certain tissue type in the database, it can be preliminarily determined that the target region tissue belongs to this tissue type. If the real-time impedance feedback does not match any tissue type in the database, further analysis and judgment may be required, or other unknown factors may be considered.

[0091] Next, within the target surgical area, obtain the position and impedance value of each electrode in the preset array electrode. Specifically, in this embodiment, the preset array electrode can be determined according to the actual situation. The array electrode usually consists of multiple electrodes and is fixed on the surgical instrument at a certain spacing and arrangement. Before the surgery starts, through calibration or preset procedures, determine the specific position of each electrode on the surgical instrument. These position data can be stored in the control system of the surgical instrument for subsequent impedance measurement and tissue identification. Impedance measurement is achieved by applying an alternating current signal to the electrode and measuring the voltage and current between the electrodes. During the surgery, the surgical instrument will regularly or as needed apply an alternating current signal to each electrode in the array electrode. At the same time, measure the voltage and current between the electrodes and calculate the impedance value of each electrode. It can be achieved through Ohm's law, where the impedance value is equal to the voltage divided by the current. Subsequently, the measured impedance values will be transmitted to the control system of the surgical instrument in real time for subsequent tissue identification and analysis.

[0092] After obtaining the position and impedance value of each electrode in the preset array electrode, construct the spatial distribution of the impedance values through the position and impedance value of each electrode. First, after obtaining the specific position of each electrode in the array electrode within the surgical area, represent the position of each electrode in the surgical area in the form of three-dimensional coordinates, which can be obtained through the calibration procedure or preset settings of the surgical instrument. At the same time, it is also necessary to measure and record the impedance value corresponding to each electrode. The impedance value is calculated by applying an alternating current signal to the electrode and measuring the voltage and current between the electrodes. To construct the spatial distribution of the impedance values, a unified coordinate system needs to be established. One part of the surgical instrument can be used as the origin, and the length, width, and height of the surgical area can be used as the coordinate axes. Associate the position coordinates of each electrode with its corresponding impedance value. In the coordinate system, each electrode's position corresponds to an impedance value, obtaining a distribution of impedance values in space. Using three-dimensional drawing software or tools, the spatial distribution of the impedance values can be presented in the form of a three-dimensional graph. For example, color or height can be used to represent the magnitude of the impedance value, thus intuitively showing the distribution of impedance values in space. By analyzing the spatial distribution of the impedance values, the boundaries and distributions of different tissues within the surgical area can be identified. The differences in impedance values can reflect the characteristics of the tissue type, density, water content, etc., thus providing guidance for surgical operations. And by real-time monitoring of the changes in the spatial distribution of the impedance values, abnormal situations during the surgery can be detected in a timely manner. For example, when the impedance value of a certain area changes significantly, it may mean that the tissue state in that area has changed (such as bleeding, edema, etc.).

[0093] Subsequently, through spatial distribution, using preset drawing software, an impedance value topology map is drawn. Specifically, the impedance value topology map can be drawn through preset drawing software for 3D drawing and topology map drawing, such as MATLAB, the Matplotlib library of Python, etc. In the drawing software, select "3D scatter plot" or a similar function to create a scatter plot, and map the three-dimensional coordinate data of the electrodes to the X, Y, and Z axes of the scatter plot. And add a color mapping function to the scatter plot, mapping the impedance value data to the color of the scatter points. The color gradient can be set according to the magnitude of the impedance value, such as from blue (low impedance) to red (high impedance). Adjust the size and shape of the scatter points as needed to better display the distribution of the impedance values. Next, add axis labels to the 3D scatter plot to clarify the meaning represented by the X, Y, and Z axes (such as the spatial position of the electrodes), add a color bar, and label the corresponding relationship between the color and the impedance value to facilitate the observer to understand the topology map. Through 3D drawing, an impedance value topology map is obtained.

[0094] After obtaining the impedance value topology map, through the impedance value topology map, determine the gradient direction of the impedance value change. In this embodiment, the impedance value topology map is a graphical representation, where the positions of the electrodes and the corresponding impedance values are presented in the form of a 3D scatter plot or other forms, which can intuitively display the distribution of the impedance values in the surgical area or the research area. In three-dimensional space, the gradient is a vector representing the direction in which the function grows fastest at a certain point. For the impedance value topology map, calculate the gradient of the impedance value in space, which can be calculated by taking the derivative of the impedance value function in space. The impedance value function is a mathematical function that describes the relationship between the impedance in a circuit and the circuit parameters. The impedance value function expression is as follows:

[0095] Z = R + jX

[0096] Where Z is the impedance, with the unit of ohm (Ω). R is the resistance, representing the resistance suffered by the current when flowing in the conductor, with the unit of ohm (Ω). j is the imaginary unit. X is the reactance, representing the hindering effect of inductance and capacitance in the circuit on alternating current, with the unit of ohm (Ω).

[0097] In discrete data, the method of numerical differentiation can be used to calculate the gradient. For example, for each electrode point, the change rate of the impedance value in the X, Y, and Z directions can be calculated to obtain the gradient vector at that point. In the impedance value topology map, arrows or other vector graphics can be used to represent the gradient direction. The length and color of the arrow can represent the magnitude of the gradient, and the direction of the arrow represents the direction in which the impedance value changes fastest. By observing the visualization results of the impedance value topology map and the gradient direction, the change trend of the impedance value in space can be determined.

[0098] Next, in combination with the tissue type and the gradient direction, determine the relative position of the target region tissue and the nerve tissue. In this embodiment, the tissue type refers to different types of tissues in a living body, such as nerve tissue, muscle tissue, connective tissue, etc. Each tissue has its unique structure and function. For example, nerve tissue is mainly composed of nerve cells and neuroglial cells and is responsible for transmitting and processing nerve signals. The gradient direction generally refers to the direction in which the function value increases fastest in mathematics and physics. In the fields of biology and medicine, the gradient direction can be used to describe the spatial change trend of a certain property (such as density, hardness, impedance value, etc.) within biological tissues. Specifically, determine the tissue type of the target region through the value of the second impedance feedback of the target region tissue. And use mathematical and physical methods (such as numerical differentiation, image processing, etc.) to calculate and analyze the gradient direction of a certain property (such as impedance value) within the target region. Combine the tissue type and the gradient direction of the target region to determine the relative position of the target region tissue and the nerve tissue. For example, if the gradient direction points to a specific direction, and the impedance value gradually increases in this direction, and the tissue type gradually transitions to nerve tissue in this direction, then it can be determined that the target region tissue and the nerve tissue are adjacent or close in this direction.

[0099] By identifying the tissue type, and using the impedance value topological map to intuitively display the impedance distribution, determining the gradient direction of the impedance value change, and determining the relative position of the target region tissue and the nerve tissue, the organizational structure and characteristics within the target surgical area can be understood more accurately, so as to formulate a more precise and safe surgical plan, improve the success rate and safety of the surgery, and thus improve the safety and success rate of the surgery.

[0100] In one implementation manner of this embodiment, determine the nerve distribution of the target region tissue by the impedance feedback displayed in real time by the nerve monitor and the intensity gradient value of the myoelectric signal determined by the chip control device, including:

[0101] Obtain the historical impedance feedback and historical myoelectric signals within a preset time period;

[0102] Based on the historical impedance feedback, historical myoelectric signals, and the preset time period, calculate the impedance change rate and the myoelectric signal amplitude slope respectively;

[0103] Based on the impedance change rate and the myoelectric signal amplitude slope, construct an impedance-EMG correlation model;

[0104] Obtain the myoelectric signals within a preset time period in real time, and calculate the amplitude slope of the myoelectric signals;

[0105] Use the preset image processing technology to convert the amplitude slope of the myoelectric signal into an amplitude slope distribution map;

[0106] Mark the region in the amplitude slope distribution map that exceeds the preset amplitude slope threshold to obtain the high-frequency discharge region;

[0107] Use the preset interpolation algorithm to convert the high-frequency discharge region into a dynamic EMG heat map;

[0108] Extract the image features of the impedance value topology map and the dynamic EMG heat map, and fuse the image features in the impedance-EMG correlation model to obtain the fused reconstructed image;

[0109] According to the fused reconstructed image, calculate the probability density function of the nerve distribution;

[0110] Convert the probability density function into a visualization image using the preset visualization software;

[0111] In the visualization image, mark the region where the probability density is greater than the preset density threshold to determine the nerve distribution of the target region tissue.

[0112] In this embodiment, refer to Figure 5 , the structural schematic diagram of a chip control device for an endoscopic nerve monitoring surgical instrument provided by an embodiment of the present application. IN1 represents input signal 1 (usually used to receive external control signals or data); IN2 represents input signal 2 (the second input channel or control signal); V1 represents voltage input / reference voltage 1 (possibly used for power input or internal voltage regulation); V0 represents voltage input / reference voltage 0 (another voltage input or ground reference point); GND represents ground wire (common ground terminal); OUT represents output signal (the signal output terminal after chip processing); SEL represents selection signal (used for mode selection, channel switching, or function configuration); VSV represents power supply voltage input (possibly the main power supply for the chip or power supply for specific functions, such as positive voltage input).

[0113] First, obtain the historical impedance feedback and historical EMG signals within a preset time period. Specifically, collecting historical impedance feedback can be achieved by retrieving impedance feedback data within the preset time period from a dedicated database. These data may be stored in the form of digital signals and contain information such as timestamps and impedance values. Collecting historical EMG signals can be done by retrieving EMG signal data within the preset time period from a dedicated database. These data may contain EMG signals of multiple channels, and each channel corresponds to the measurement result of an electrode.

[0114] After obtaining the historical impedance feedback and historical EMG signals, based on the historical impedance feedback, historical EMG signals, and a preset time period, calculate the impedance change rate and the EMG signal amplitude slope respectively. Specifically, extract the historical impedance feedback data from the preset time period. For the impedance value at each time point, calculate the impedance change amount compared to the previous time point. The impedance change amount can be obtained by subtracting the impedance value of the previous time point from the current impedance value. Subsequently, divide the impedance change amount by the time interval to obtain the impedance change rate. If the data is sampled at a fixed interval, the time interval is known; if the timestamps are not continuous, the time interval corresponding to each change amount needs to be calculated. Next, extract the historical EMG signal data from the preset time period, ensuring that the timestamps of the data are continuous or sampled at a fixed interval. For the EMG signal at each time point, calculate its amplitude. The amplitude can be obtained by calculating the difference between the maximum value and the minimum value of the signal. For the amplitude at each time point, calculate the amplitude change amount compared to the previous time point (or the time point before a fixed time interval). The amplitude change amount can be obtained by subtracting the amplitude of the previous time point from the current amplitude. Subsequently, divide the amplitude change amount by the time interval to obtain the amplitude slope. Similarly, if the data is sampled at a fixed interval, the time interval is known; if the timestamps are not continuous, the time interval corresponding to each change amount needs to be calculated.

[0115] After the impedance change rate and the EMG signal amplitude slope, based on the impedance change rate and the EMG signal amplitude slope, construct an impedance-EMG correlation model. Specifically, calculate the impedance change rate. For each time point, calculate the difference ΔZ between the impedance value Z and the impedance value of the previous time point. Calculate the time interval Δt (usually the sampling interval), and take the ratio of the impedance difference to the time interval as the impedance change rate. Subsequently, determine the amplitude of the EMG signal, which can be achieved by calculating the envelope or the root mean square value (RMS) of the signal. For each time point, calculate the difference ΔA between the amplitude and the amplitude of the previous time point, use the same time interval Δt, and take the ratio of the amplitude difference to the time interval as the EMG amplitude slope. Take the calculated impedance change rate and EMG amplitude slope as feature data, and divide the data into a training set and a validation set for model training and validation. Next, according to the data characteristics and research purposes, select a suitable mathematical model or machine learning algorithm, such as linear regression, support vector machine and other models. Use the training data set, take the impedance change rate as one of the input features, the EMG amplitude slope as another input feature, and the relationship between the two (such as correlation, causal relationship, etc.) as the output target. By training the model and adjusting the parameters to optimize the prediction performance, an impedance-EMG correlation model can be obtained.

[0116] Obtain the electromyogram (EMG) signals in real time within a preset time period, and calculate the amplitude slope of the EMG signals. Specifically, to determine the amplitude of the EMG signals, it can be achieved by calculating the envelope or the root mean square (RMS) value of the signals. For each time point, calculate the difference ΔA between the amplitude and the amplitude at the previous time point, use the same time interval Δt, and take the ratio of the amplitude difference to the time interval as the amplitude slope of the EMG signals.

[0117] After obtaining the amplitude slope of the EMG signals, use the preset image processing technology to convert the amplitude slope of the EMG signals into an amplitude slope distribution map. In this embodiment, the preset image processing technology can be a grayscale image, map the amplitude slope data to the gray level, and generate a grayscale image. In the grayscale image, the brightness value of the pixel represents the magnitude of the amplitude slope. And use the selected image processing algorithm to process the mapped data to generate the amplitude slope distribution map, which can be implemented by programming, using image processing tools such as the OpenCV library of Python, MATLAB, etc., to obtain the amplitude slope distribution map.

[0118] After obtaining the amplitude slope distribution map, mark the areas in the amplitude slope distribution map that exceed the preset amplitude slope threshold to obtain the high-frequency discharge areas. In this embodiment, the preset amplitude slope threshold can be determined according to experimental data, historical experience, or theoretical analysis. Specifically, use image processing software or programming tools (such as the OpenCV library of Python, MATLAB, etc.) to read the amplitude slope distribution map, and perform binary processing on the amplitude slope distribution map. That is, compare each pixel value in the image with the preset amplitude slope threshold. If the pixel value is greater than the threshold, set the pixel to white (or other high-brightness colors); otherwise, set it to black (or other low-brightness colors). In the binary image, the white (or high-brightness color) areas are the areas that exceed the preset amplitude slope threshold, that is, the high-frequency discharge areas. The marking tool in the image processing software or the drawing function in the programming tool can be used to mark these areas, such as highlighting them with a red border, filling color, etc. Observe the marked image, and the position and range of the high-frequency discharge areas can be clearly seen. These areas usually correspond to the parts with higher amplitude slopes in the EMG signals, which may indicate abnormal or special states of muscle activity, and obtain the high-frequency discharge areas.

[0119] After obtaining the high-frequency discharge region, using a preset interpolation algorithm, the high-frequency discharge region is transformed into a dynamic EMG heat map. The dynamic EMG heat map is a visualization technique used to display the dynamic changes of electromyogram (EMG) signals in time and space. The intensity or activity level of the EMG signal is represented by color mapping (such as from cold colors to warm colors), thus intuitively reflecting the distribution and changes of muscle activity. In this embodiment, the preset interpolation algorithm can be linear interpolation. Linear interpolation is used to estimate the values of unknown points between known data points, assuming that the change between two known points is linear, and calculating the values of unknown points through a linear equation. Specifically, using the selected interpolation algorithm, interpolation processing is performed on the amplitude slope values of the high-frequency discharge region to generate a smooth and continuous data set. The interpolated data set should include all time points on the time axis and the corresponding amplitude slope values. Map the interpolated amplitude slope values to the color range of the heat map. For example, a color gradient can be set, mapping lower amplitude slope values to colder colors (such as blue) and higher amplitude slope values to hotter colors (such as red). Image processing software or programming tools (such as the matplotlib library in Python, MATLAB, etc.) can be used to generate the heat map. In the heat map, the horizontal axis represents time, and the vertical axis can represent the electrode position (if it is multi-channel EMG data) or the range of amplitude slope (if it is single-channel data). The amplitude slope value at each time point is mapped to the corresponding color, forming a dynamic heat map that changes with time.

[0120] Next, extract the image features of the impedance value topology map and the dynamic EMG heat map, and fuse the image features in the impedance-EMG correlation model to obtain the fused reconstructed image. Specifically, for the extraction of impedance value topology map features, texture features and shape features of the impedance value topology map can be extracted through image processing techniques. Texture features can be extracted using methods such as gray-level co-occurrence matrix and local binary pattern (LBP). If there are obvious shapes or contours in the impedance value topology map, these shape features can be extracted, such as area, perimeter, aspect ratio, etc. For the extraction of dynamic EMG heat map features, color distribution features in the heat map can be extracted, such as color histogram, color moment, etc. Similar to the impedance value topology map, texture features of the heat map can also be extracted to capture the dynamic changes of muscle activity. Subsequently, the features extracted from the impedance value topology map and the dynamic EMG heat map are concatenated to form a unified feature vector. Feature selection algorithms (such as principal component analysis PCA, linear discriminant analysis LDA, etc.) are used to reduce the dimension and select the concatenated feature vector to retain the most important features. The fused feature vector is used as the input of the model, and the corresponding labels (such as muscle activity state, impedance value, etc.) are used as the output of the model, and the model is trained using the training set to adjust the parameters and settings of the model to obtain the best model performance. The trained impedance-EMG correlation model is used to predict new input data to obtain the reconstructed impedance value or muscle activity state. According to the prediction results, combined with the topological structure and color mapping relationship of the original image, a fused reconstructed image is generated. For example, interpolation algorithms can be used to map the predicted impedance value onto the topology map to form a new impedance value topology map, or map the predicted muscle activity state onto the heat map to form a new dynamic EMG heat map.

[0121] Based on the fused reconstructed image, calculate the probability density function of nerve distribution. First, the image needs to be segmented to isolate each region. This can be achieved through methods such as threshold segmentation, edge detection, and region growing. For each segmented region, features related to nerve activity are extracted. These features may include the area, shape, texture, color intensity, etc. of the region. If the image is dynamic (such as a time series image), time series features such as amplitude change and frequency can also be extracted. The probability density function of nerve distribution can be calculated through the method of kernel density estimation (KDE). Kernel density estimation is a non-parametric statistical method used to estimate the probability density function of a random variable. Subsequently, the estimated probability density function is visualized for intuitive understanding and analysis, which can be achieved by plotting probability density curves, contour plots, etc.

[0122] Next, in the visualization image, mark the regions where the probability density is greater than a preset density threshold to determine the nerve distribution of the target region tissue. In this embodiment, the preset density threshold can be determined according to the specific application background and requirements. For example, if the goal is to identify regions with high-density nerve distribution, the threshold can be set relatively high so that only regions with significantly higher probability density are marked. Specifically, in the visualization image, traverse the probability density values of each pixel and mark those pixels that are greater than the preset density threshold. Convert the probability density image into a binary image, where pixel values greater than the threshold are set to 1 (or white), and pixel values less than or equal to the threshold are set to 0 (or black). Then perform connected component labeling on the binary image to distinguish different high-density regions, and overlay the marked high-density regions on the original image or mark them with different colors for a more intuitive observation of the nerve distribution.

[0123] Through the visualization image and analysis results, it not only helps to understand the mechanism of muscle activity and the process of neuromuscular conduction, but also can intuitively observe the active regions and distribution patterns of the neuromuscular system. At the same time, by real-time monitoring and analyzing EMG signals, abnormal changes in muscle activity can be detected in a timely manner, providing new methods and means for aspects such as movement control research and rehabilitation training evaluation.

[0124] In one implementation manner of this embodiment, according to the fused reconstructed image, calculate the probability density function of the nerve distribution, including:

[0125] Obtain each data point in the fused reconstructed image;

[0126] Use a preset kernel function to calculate the probability density for each data point;

[0127] Overlay the probability densities of each data point to obtain the probability density function curve of the fused reconstructed image, and the probability density function curve is used to characterize the probability density function.

[0128] First, obtain each data point in the fused reconstructed image. In this embodiment, the fused reconstructed image is usually composed of a series of pixels or grid points. Each pixel or grid point represents a specific spatial position and has a value associated with that position (such as brightness, color intensity, etc.). By traversing each element of the image matrix, the value of each data point can be extracted, which can be implemented using programming, such as using loops or vectorized operations to access and process each element in the matrix. For each data point, in addition to its value, its position information may also need to be recorded.

[0129] Calculate the probability density for each data point using a preset kernel function. Specifically, the kernel function can be selected from Gaussian kernel, Epanechnikov kernel, rectangular kernel, etc. The choice of which kernel function depends on the characteristics of the data and application requirements. The bandwidth is another important parameter in the kernel function, which controls the width of the kernel function, that is, the smoothing range around the data point. The bandwidth can be determined by methods such as cross-validation, Silverman's rule, etc. First, create an array of the same size as the dataset to store the probability density of each data point. For each data point, calculate its distance from all other data points in the dataset. For each distance, apply the preset kernel function to calculate the weight. The kernel function is usually a function with the distance as the independent variable, and its value decreases as the distance increases. Accumulate all the calculated weights and divide by the size of the dataset (or a certain function of the bandwidth) to obtain the probability density of this data point.

[0130] Overlay the probability density of each data point to obtain the probability density function curve of the fused reconstructed image. The probability density function curve is used to characterize the probability density function. That is to say, after calculating the probability density of each data point, these probability densities need to be overlaid. Sum up the probability density values of each data point to obtain the total probability density of the entire dataset. Secondly, in order to generate the probability density function curve, the overlaid probability density values need to be associated with the corresponding data point positions (such as pixel coordinates, feature values, etc.). Drawing software (such as Matplotlib, Seaborn, etc.) can be used to plot these points into a continuous curve, and this curve is the probability density function curve of the fused reconstructed image. The generated probability density function curve can be used to characterize the probability density distribution of the fused reconstructed image. By observing this curve, features such as the distribution of image data, density peaks and valleys can be understood.

[0131] By obtaining the probability density of each data point in the fused reconstructed image and overlaying to obtain the probability density function curve, the characteristics of the image data can be understood more deeply, a comprehensive understanding of the image data can be obtained, which helps to improve the accuracy of neural detection.

[0132] This application also provides an electronic device, including:

[0133] A memory; and

[0134] A processor configured to call instructions from the memory and, when executing the instructions, perform the following steps:

[0135] Obtain the target tissue in the target surgical area, use the integrated electrode in the jaw to output a low-frequency stimulation current to the target tissue area, transmit the neuroelectrophysiological signal in the target tissue area to the neuro monitor through the nerve monitoring wire, and display the value of the neuroelectrophysiological signal. The neuroelectrophysiological signal includes impedance feedback and electromyogram signal. Based on the value of the neuroelectrophysiological signal, determine whether there is nerve distribution in the target tissue area. In the case where there is no nerve distribution in the target tissue area, use the integrated electrode in the jaw to output a high-frequency stimulation current to perform electrocoagulation operation on the target tissue area. In the case where there is nerve distribution in the target tissue area, display the impedance feedback in real time through the neuro monitor, and determine the intensity gradient value of the electromyogram signal determined by the chip control device to determine the nerve distribution of the target tissue area.

[0136] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0137] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in Figure 1 one or more flows Figure 1 or multiple flows and / or blocks

[0138] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device realizes the functions specified in Figure 1 one or more flows Figure 1 or multiple flows and / or blocks

[0139] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, causing a series of operational steps to be performed on the computer or other programmable apparatus to generate a computer-implemented process, so that the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one process Figure 1 one process or a plurality of processes and / or boxes Figure 1 steps for implementing the functions specified in one box or a plurality of boxes.

[0140] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0141] The memory may include non-permanent memory in the computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.

[0142] Computer-readable media includes both permanent and non-permanent, removable and non-removable media implemented by any method or technology for storing information. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0143] It should also be noted that the term "comprising", "including" or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0144] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. An endoscopic nerve monitoring surgical instrument, characterized in that, The nerve monitoring surgical instrument includes an integrated electrode, a jaw, a chip control device, and a nerve monitoring wire. The integrated electrode is disposed within the jaw, the integrated electrode is connected to the nerve monitoring wire, the nerve monitoring wire is connected to the nerve monitor, and the nerve monitoring surgical instrument is connected to the electronic device; Among them, the electronic device is used to obtain the target regional tissue within the target surgical area, output a low-frequency stimulating current to the target tissue area by using the integrated electrode within the jaw, transmit the neuroelectrophysiological signal within the target tissue area to the nerve monitor through the nerve monitoring wire, and display the value of the neuroelectrophysiological signal. The neuroelectrophysiological signal includes impedance feedback and electromyographic signal, and based on the value of the neuroelectrophysiological signal, it is judged whether there is nerve distribution in the target tissue area. In the case where there is no nerve distribution in the target tissue area, a high-frequency stimulating current is output by using the integrated electrode within the jaw to perform electrocoagulation operation on the target tissue area. In the case where there is nerve distribution in the target tissue area, the impedance feedback is displayed in real time through the nerve monitor, and the intensity gradient value of the electromyographic signal determined by the chip control device is used to determine the nerve distribution of the target regional tissue; The jaw includes an upper jaw and a lower jaw. A cutter head and an integrated electrode are disposed within the jaw. The integrated electrode includes a first electrode, a second electrode, and a nerve detection electrode. The first electrode and the second electrode are respectively located in the upper jaw and the lower jaw of the jaw, and the nerve detection electrode is integrated into the first electrode or the second electrode. Among them, the cutter head is used to cut the target tissue area, the first electrode and the second electrode are used to perform electrocoagulation on the target tissue area, and the nerve detection electrode is used to detect the nerve distribution within the target tissue area; A nerve monitoring bipolar circuit is disposed within the jaw. The nerve monitoring bipolar circuit includes a base, a collector, and an emitter. The collector includes a first power supply, a first control switch, and a first resistor. One end of the first resistor is connected to the first common point of the base and the emitter, the other end of the first resistor is connected to one end of the first control switch, and the other end of the first control switch is connected to the positive pole of the first power supply. The base includes a second resistor, a third resistor, and a second control switch. One end of the second control switch is connected to one end of the second resistor, the other end of the second resistor is connected to the first common point of the collector and the emitter, one end of the third resistor is connected to one end of the second resistor, the other end of the third resistor is connected to the second common point of the emitter and the ground point, and the emitter is connected to the second common point of the ground point and the other end of the third resistor.

2. The endoscopic nerve monitoring surgical instrument according to claim 1, characterized in that, A nerve stimulation current circuit is provided inside the jaw. The nerve stimulation current circuit includes an input terminal circuit and an output terminal circuit. The input terminal circuit includes a fourth resistor, a fifth resistor, a capacitor, a relay, and an electromyogram signal module. One end of the fourth resistor is connected to the electromyogram signal module, the other end of the fourth resistor is connected to the capacitor, the other end of the capacitor is connected to the fifth resistor, the other end of the fifth resistor is connected to the coil of the relay, and the other end of the coil is connected to the electromyogram signal module. The output terminal circuit includes a relay, a second power supply, a third control switch, and a sixth resistor. The positive pole of the second power supply is connected to the third control switch, the other end of the third control switch is connected to the sixth resistor, the other end of the sixth resistor is connected to the normally closed contact of the relay, and the other end of the normally closed contact of the relay is connected to the negative pole of the second power supply.

3. An endoscopic nerve monitoring surgical instrument according to claim 1, wherein, The value of the neuroelectrophysiological signal includes an impedance feedback value and an electromyogram signal. The nerve monitoring surgical instrument is also used to determine whether the impedance feedback is a first preset impedance threshold based on the impedance feedback value. If the impedance feedback is the first preset impedance threshold, it is determined that there is nerve tissue in the target surgical area, and the integrated electrode stops outputting high-frequency stimulation current and outputs low-frequency stimulation current to achieve continuous alternating operations of nerve detection and electrocoagulation operation processing on the target area tissue in the target surgical area. If the impedance feedback is not the first preset impedance threshold, it is determined that there is no nerve tissue in the target surgical area, and the integrated electrode outputs high-frequency stimulation current to achieve electrocoagulation operation processing on the target area tissue in the target surgical area.

4. The endoscopic nerve monitoring surgical instrument according to claim 2, wherein, The nerve monitoring surgical instrument is also used to output high-frequency stimulation current to the target surgical area by using the integrated electrode to achieve electrocoagulation operation processing on the target area tissue in the target surgical area. Through the chip control device, the first impedance feedback of the target surgical area is obtained in real time. When the first impedance feedback reaches the second preset impedance threshold, the nerve stimulation current circuit outputs nerve stimulation current to the target surgical area, and the second impedance feedback is obtained in real time. Based on the second impedance feedback, the relative position between the target area tissue and the nerve tissue is determined. When the relative position reaches the preset nerve threshold, the output of high-frequency stimulation current to the target surgical area is stopped.

5. An endoscopic nerve monitoring surgical instrument according to claim 4, wherein, Determining the relative position between the target area tissue and the nerve tissue based on the second impedance feedback includes: Comparing the value of the second impedance feedback of the target area tissue with the impedance feedback in the preset database to determine the tissue type of the target area tissue; In the target surgical area, obtaining the position and impedance value of each electrode in the preset array electrode; Constructing the spatial distribution of impedance values through the position and impedance value of each electrode; Drawing an impedance value topology map by using the preset drawing software through the spatial distribution; Determining the gradient direction of the impedance value change through the impedance value topology map; Combining the tissue type and the gradient direction to determine the relative position between the target area tissue and the nerve tissue.

6. The endoscopic nerve monitoring surgical instrument according to claim 5, characterized in that, Determining the nerve distribution of the target area tissue by displaying the impedance feedback in real time through the nerve monitor and the intensity gradient value of the electromyogram signal determined by the chip control device, including: Obtain historical impedance feedback and historical electromyogram signals within a preset time period; Based on the historical impedance feedback, historical electromyogram signals, and preset time period, calculate the impedance change rate and the electromyogram signal amplitude slope respectively; Based on the impedance change rate and the electromyogram signal amplitude slope, construct an impedance-EMG correlation model; Obtain the electromyogram signals within a preset time period in real time, and calculate the amplitude slope of the electromyogram signals; Using a preset image processing technique, convert the amplitude slope of the electromyogram signals into an amplitude slope distribution map; Mark the regions in the amplitude slope distribution map that exceed the preset amplitude slope threshold to obtain high-frequency discharge regions; Using a preset interpolation algorithm, convert the high-frequency discharge regions into a dynamic EMG heat map; Extract the image features of the impedance value topology map and the dynamic EMG heat map, and fuse the image features in the impedance-EMG correlation model to obtain a fused reconstructed image; According to the fused reconstructed image, calculate the probability density function of the nerve distribution; Convert the probability density function into a visualization image using a preset visualization software; In the visualization image, mark the regions where the probability density is greater than the preset density threshold to determine the nerve distribution of the target regional tissue.

7. The endoscopic nerve monitoring surgical instrument according to claim 6, characterized in that, According to the fused reconstructed image, calculate the probability density function of the nerve distribution, including: Obtain each data point in the fused reconstructed image; Using a preset kernel function, calculate the probability density for each data point; Overlay the probability densities of each data point to obtain the probability density function curve of the fused reconstructed image, and the probability density function curve is used to characterize the probability density function.

8. An electronic device, characterized in that, Including: A memory; And A processor configured to call instructions from the memory and, when executing the instructions, perform the following steps: Obtain the target regional tissue within the target surgical area, use the integrated electrode within the jaw to output a low-frequency stimulation current to the target tissue area, transmit the neuroelectrophysiological signals within the target tissue area to the neuromonitor through the nerve monitoring wire, and display the numerical values of the neuroelectrophysiological signals. The neuroelectrophysiological signals include impedance feedback and electromyogram signals, and based on the numerical values of the neuroelectrophysiological signals, determine whether there is a nerve distribution in the target tissue area. In the case where there is no nerve distribution in the target tissue area, use the integrated electrode within the jaw to output a high-frequency stimulation current to perform electrocoagulation operation on the target tissue area. In the case where there is a nerve distribution in the target tissue area, display the impedance feedback in real time through the neuromonitor, and the intensity gradient numerical value of the electromyogram signal determined by the chip control device, and determine the nerve distribution of the target regional tissue; Wherein, the jaw includes an upper jaw and a lower jaw, and a cutter head and an integrated electrode are provided within the jaw. The integrated electrode includes a first electrode, a second electrode, and a nerve detection electrode. The first electrode and the second electrode are respectively located on the upper jaw and the lower jaw of the jaw, and the nerve detection electrode is integrated with the first electrode or the second electrode. Among them, the cutter head is used to cut the target tissue area, the first electrode and the second electrode are used to perform electrocoagulation on the target tissue area, and the nerve detection electrode is used to detect the nerve distribution within the target tissue area; A nerve monitoring bipolar circuit is provided inside the jaw. The nerve monitoring bipolar circuit includes a base, a collector, and an emitter. The collector includes a first power supply, a first control switch, and a first resistor. One end of the first resistor is connected to the first common point of the base and the emitter, and the other end of the first resistor is connected to one end of the first control switch. The other end of the first control switch is connected to the positive pole of the first power supply. The base includes a second resistor, a third resistor, and a second control switch. One end of the second control switch is connected to one end of the second resistor, and the other end of the second resistor is connected to the first common point of the collector and the emitter. One end of the third resistor is connected to one end of the second resistor, and the other end of the third resistor is connected to the second common point of the emitter and the ground point. The emitter is connected to the second common point of the ground point and the other end of the third resistor.

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