Ultrasonic guidance nerve block training model based on 4D printing

Abstract

According to the ultrasound-guided nerve block training model based on 4D printing, on the basis that the 4D printing technology is introduced, a novel specific high-simulation model structure is designed for the ultrasound-guided nerve block training model, and a series of optimization settings are matched in the detail aspect; multiple advantages of high simulation degree, dynamic characteristics, electric signal blocking function, ultrasonic compatibility, real-time feedback mechanism, multifunctionality, portability, economy and the like are considered, a safer, more economical and more efficient tool can be provided for clinical skill training of ultrasound-guided nerve block, the quality and efficiency of medical education can be well improved, and the method is worthy of popularization and application. Good application prospects are realized.

Description

Technical Field

[0001] The present application relates to the field of medical teaching aids, and specifically to an ultrasound-guided nerve block training model based on 4D printing. Background Art

[0002] In clinical anesthesia and pain management, ultrasound-guided peripheral nerve block is an important skill. This skill is easy to understand, involves manual operation, and relies on operational experience. Therefore, for clinical medical staff, good training can help ensure the level of ultrasound-guided nerve block skills and promote high-quality medical services.

[0003] However, the inventors of the present application have found that for ultrasound-guided nerve block, the traditional training method involves real objects, specifically through plastic molds, animal experiments or cadaver dissection, which inevitably has many application inconveniences such as high training costs, limited resources and difficulty in simulating the real human environment. Summary of the Invention

[0004] The present application provides an ultrasound-guided nerve block training model based on 4D printing. Based on the introduction of 4D printing technology, a novel specific high-simulation model structure is designed for the ultrasound-guided nerve block training model, and a series of optimization settings are further provided in terms of details, taking into account multiple advantages such as high simulation, dynamic characteristics, electrical signal blocking function, ultrasound compatibility, real-time feedback mechanism, versatility, portability and economy. It can provide a safer, more economical and efficient tool for clinical skills training of ultrasound-guided nerve block, which is helpful to improve the quality and efficiency of medical education and has good application prospects.

[0005] The present application provides an ultrasound-guided nerve block training model based on 4D printing, which sequentially includes a conductive nerve fiber layer, a dynamic matrix layer, and an outer membrane layer obtained by 4D printing.

[0006] The conductive nerve fiber layer is structurally configured as liquid metal microchannels distributed along the nerve shape and covered with an insulating layer to simulate the differentiated electrical signal conduction of Aα fibers, Aδ fibers, and C fibers;

[0007] The dynamic matrix layer is configured as a honeycomb porous structure containing microfluidic channels to simulate the temperature-responsive deformation of surrounding tissues, including muscle, fat, blood vessels, and bone.

[0008] The outer film layer is structurally configured to be wrapped at the outermost layer to protect the internal structure and provide a real puncture feeling.

[0009] In a preferred implementation, the conductive nerve fiber layer is made of gallium indium tin liquid metal Ga 60 In 25 Sn 15 and biocompatible polymer polyurethane composite printing.

[0010] In another preferred implementation, the dynamic matrix layer is printed from the temperature-sensitive self-healing hydrogel PNIPAM, and the hydrogel properties automatically repair puncture damage below 25°C.

[0011] In another preferred implementation, the outer coating layer is printed from a silicone rubber-nanofiber composite film, and a polydopamine anti-adhesion layer is coated on the surface.

[0012] In another preferred implementation, the ultrasound-guided nerve block training model is further configured with a liquid injection system for the conductive nerve fiber layer;

[0013] The injection catheter system is structurally configured as a multi-lumen microfluidic catheter parallel to the conductive nerve fiber layer. The outlet is located next to the nerve sheath and is used to inject an ionic solution simulating local anesthetics to trigger electrical signal blocking.

[0014] In another preferred implementation, for the conductive nerve fiber layer, the ultrasound-guided nerve block training model is further configured with an electrical signal control module and a reset maintenance module;

[0015] The electrical signal control module is composed of an embedded microcircuit board and a resistor sensor array. When the liquid metal network comes into contact with potassium or calcium ions, it generates an insulating oxide layer, thereby blocking the conduction of electrical signals.

[0016] The reset and maintenance module is structurally composed of a bidirectional micropump connected to a saline reservoir, which is used to flush and remove the insulating oxide layer to restore the conductivity of the liquid metal.

[0017] In another preferred implementation, for the dynamic matrix layer, the ultrasound-guided nerve block training model is further configured with a temperature control layer;

[0018] The temperature control layer is structurally configured with a flexible film heating element and a temperature sensor to maintain the surface temperature of the model at 32°C-37°C and trigger the softening of the hydrogel.

[0019] In another preferred implementation, for the conductive nerve fiber layer, the ultrasound-guided nerve block training model is further configured with a mechanical deformation driving layer;

[0020] The mechanical deformation driving layer is structurally configured as shape memory alloy wire NiTiNol embedded in hydrogel, and simulates nerve displacement caused by breathing and body posture through preset programs, which is used to dynamically interfere with puncture operations.

[0021] In yet another preferred implementation, the ultrasound-guided nerve block training model is further configured with a piezoelectric sensor array;

[0022] The piezoelectric sensor array is structurally configured with a 128-element linear array and integrated into the surface of the outer coating layer. It is used to capture the trajectory of the puncture needle in real time, and to generate and display ultrasound images corresponding to the electrical signal blockage based on the GAN network to show the puncture needle position and drug diffusion.

[0023] In another preferred implementation, the ultrasound-guided nerve block training model is further configured with an audible and visual alarm module;

[0024] When the sound and light alarm module detects abnormal operation such as accidental touching of blood vessels, insufficient puncture depth or improper drug diffusion based on the task information of the preset training task, it will issue an sound and light alarm to remind you.

[0025] From the above content, it can be concluded that this application has the following beneficial effects:

[0026] Aiming at the goal of ultrasound-guided nerve block training, this application, based on the introduction of 4D printing technology, designs a novel and specific high-simulation model structure for the ultrasound-guided nerve block training model, and continues to provide a series of optimization settings in terms of details, taking into account multiple advantages such as high simulation, dynamic characteristics, electrical signal blocking function, ultrasound compatibility, real-time feedback mechanism, versatility, portability and economy. It can provide a safer, more economical and efficient tool for clinical skills training of ultrasound-guided nerve block, which helps to improve the quality and efficiency of medical education and has good application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 This is a structural schematic diagram of the ultrasound-guided nerve block training model based on 4D printing in this application. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0030] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or modules is not necessarily limited to those steps or modules clearly listed, but may include other steps or modules that are not clearly listed or that are inherent to these processes, methods, products or devices. The naming or numbering of steps in this application does not mean that the steps in the method flow must be executed in the time / logical sequence indicated by the naming or numbering. The process steps that have been named or numbered can be changed in the execution order according to the technical purpose to be achieved, as long as the same or similar technical effects can be achieved.

[0031] The division of modules in this application is a logical division. In actual application, there may be other division methods. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection between modules can be electrical or other similar forms, which are not limited in this application. Moreover, the modules or submodules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed into multiple circuit modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this application.

[0032] First, see Figure 1 The schematic diagram of the structure of the ultrasound-guided nerve block training model based on 4D printing is shown in FIG. Figure 1 It can be clearly seen that the ultrasound-guided nerve block training model based on 4D printing provided by this application for ultrasound-guided nerve block training includes, from bottom to top and from inside to outside, three major parts: a conductive nerve fiber layer, a dynamic matrix layer, and an outer membrane layer obtained by 4D printing.

[0033] Among them, it is necessary to understand that Figure 1The three parts shown, namely the conductive nerve fiber layer, the dynamic matrix layer and the outer covering layer, are relatively flat. This is configured based on a better description of the scheme. However, in actual applications, with the clinical training in the hospital for ultrasound-guided nerve block training tasks for different human bodies / body parts, there will be different differences in the specific printed ultrasound-guided nerve block training models. Corresponding to different human body parts, the thickness of the conductive nerve fiber layer, the dynamic matrix layer and the outer covering layer is usually not fixed. Moreover, if special populations are involved, such as body parts with special conditions such as disabilities, deformities, and lesions (corresponding to highly detailed ultrasound-guided nerve block training tasks), the structures of the three also need to be further adapted.

[0034] Therefore, for the 4D printing-based ultrasound-guided nerve block training model provided in this application, it can be learned that it includes three major parts from bottom to top and from inside to outside, namely, a conductive nerve fiber layer, a dynamic matrix layer and an outer membrane layer.

[0035] At the same time, with regard to 4D printing, it is understandable that this application does not make corresponding optimization and improvements to the 4D printing technology. It can be understood as a printing tool for the ultrasound-guided nerve block training model provided in this application. To facilitate the understanding of 4D printing, the following introduction can help you understand it.

[0036] 4D printing relies on smart materials and programming. Smart materials are materials that can sense and respond to environmental stimuli such as temperature, humidity, magnetic fields, and electric fields. Commonly used smart materials in 4D printing include shape memory alloys, shape memory polymers, magnetically controlled smart materials, and smart hydrogels. Shape memory alloys, for example, can deform at low temperatures and quickly return to their original shape when the temperature rises to a certain value. 4D printing combines these smart materials with computer-aided design and manufacturing technologies. By precisely designing the distribution and structure of materials in different areas and writing corresponding "programs," 4D printing can control how objects change over time and under different environments. This simplifies the process from design concept to physical object creation, allowing objects to automatically assemble and form, achieving an integrated fusion of product design, manufacturing, and assembly. Compared to 3D printing, 4D printing can meet the demand for higher-quality object printing.

[0037] Next, we will further introduce the present application solution. Specifically, the conductive nerve fiber layer, the dynamic matrix layer, and the outer membrane layer may have the following configuration contents:

[0038] (1) Conductive nerve fiber layer

[0039] The conductive nerve fiber layer is structurally configured as liquid metal microchannels distributed along the nerve shape and wrapped with an insulating layer to simulate the differentiated electrical signal conduction of Aα fibers, Aδ fibers and C fibers.

[0040] Among them, Aα fibers, Aδ fibers and C fibers (the first two can also be called type A fibers) are different types of nerve fibers, which are used in the human body to transmit information related to muscle control, pain perception, temperature perception, etc.

[0041] In this way, the underlying, deep conductive nerve fiber layer in the model is well restored and simulated by liquid metal to simulate the nerve fibers involved in ultrasound-guided nerve block operations.

[0042] Furthermore, in terms of details, the diameter of the meshed liquid metal microchannel can be specifically configured to be 50 μm (micrometer), and the speed range of the differentiated electrical signal conduction can be specifically configured to be 0.5 m / s-120 m / s.

[0043] In addition, the present application also provides further solutions for the specific materials that can be used. Specifically, the conductive nerve fiber layer can be made of gallium indium tin liquid metal Ga 60 In 25 Sn 15 and biocompatible polymer polyurethane composite printing.

[0044] (2) Dynamic matrix layer

[0045] The dynamic matrix layer is structurally configured as a honeycomb porous structure containing microfluidic channels to simulate the temperature-responsive deformation of surrounding tissues, including muscle, fat, blood vessels and bones.

[0046] It can be understood that the dynamic matrix layer combines a honeycomb multi-porous structure, microfluidic channels and temperature-responsive deformation to well restore the morphology and physical properties of multi-layered tissues inside the human body, such as muscles, fat, blood vessels and bones. It helps to simulate the behavior of human tissues under different conditions (such as temperature changes or mechanical forces), achieve temperature / mechanical dual-responsive deformation (accuracy ±0.3mm), support the simulation of complex scenes such as breathing and muscle contraction, and bring a close to real touch and operation experience. Compared with traditional training models (such as plastic molds, animal experiments or cadaver dissections) that are difficult to simulate the complex anatomical structure and dynamic responses of the human body, it has a high degree of simulation.

[0047] Furthermore, in terms of details, the diameter of the microfluidic channel contained in the honeycomb porous structure can be specifically configured to be 100μm-500μm, and the deformation rate of the temperature-responsive deformation can be specifically configured to be n≤15%.

[0048] In addition, this application also provides further solutions for the specific materials that can be used. Specifically, the dynamic matrix layer can be printed from the temperature-sensitive self-healing hydrogel PNIPAM (i.e., poly N-isopropylacrylamide) with an elastic modulus of 0.5kPa-3kPa. It can automatically repair puncture damage below 25°C through the properties of the hydrogel, with a repair rate of >95% and a time consumption of <2 hours, and has a good self-repair mechanism.

[0049] (3) Outer coating layer

[0050] The outer film layer is structurally configured to be wrapped at the outermost layer to protect the internal structure and provide a real puncture feeling.

[0051] It is easy to understand that the outer film layer corresponds to the skin visible to the naked eye, which has the function of wrapping, fixing and protecting the internal structure of the model.

[0052] Furthermore, in terms of details, the thickness of the outer coating layer can be specifically configured to be 0.5 mm (millimeter), and the adjustable range of the puncture resistance can be specifically configured to be 0.5N-3N.

[0053] In addition, with respect to the specific materials that can be used, the present application also provides further solutions. Specifically, the outer coating layer can be printed from a silicone rubber-nanofiber composite film, and the surface is coated with a polydopamine anti-adhesion layer.

[0054] It can be understood that for the above-mentioned model structure, its structural content itself can be scanned and ultrasonic images can be collected by ultrasonic equipment. For example, the surface of the model, that is, the outer coating layer (i.e., silicone rubber-nanofiber composite film) itself is an ultrasonic transparent material with better effect, which can ensure clear images under ultrasound guidance.

[0055] Thus, under the structural configuration conditions of the above-mentioned simulation model / training model, in actual application, it can be combined with external ultrasound equipment or application environment to well meet the training needs of ultrasound-guided nerve block skills.

[0056] Under the further model optimization goal, this application also has a further model optimization solution, which involves additional configuration of software and hardware settings. Next, we will continue to explain these contents in detail.

[0057] Understandably, traditional models cannot simulate the effects of local anesthetics on nerve electrical signal conduction, making it difficult for students to intuitively understand the drug's mechanism of action.

[0058] In this regard, with respect to the conductive nerve fiber layer, the ultrasound-guided nerve block training model provided in this application may also be configured with a liquid injection system;

[0059] The injection catheter system is structurally configured as a multi-lumen microfluidic catheter parallel to the conductive nerve fiber layer, with the outlet located next to the (simulated) nerve sheath for injecting an ionic solution simulating local anesthetics to trigger electrical signal blocking.

[0060] In terms of details, the inner diameter of the multi-lumen microfluidic catheter can be specifically configured to be 0.5 mm, and the ionic solution used to simulate the local anesthetic can be specifically configured to be 0.15 mol / L KCl plus 0.05 mol / L CaCl2 (i.e., KCl 0.15 mol / L + CaCl2 0.05 mol / L).

[0061] In terms of specific electrical signal blocking operations, the ultrasound-guided nerve block training model can also be configured with an electrical signal control module and a reset maintenance module for the conductive nerve fiber layer.

[0062] The electrical signal control module is composed of an embedded microcircuit board and a resistor sensor array, which is used to control the liquid metal network in contact with potassium ions (K + ) or calcium ions (Ca 2+ ) after which an insulating oxide layer is formed, blocking the conduction of electrical signals;

[0063] The reset and maintenance module is structurally composed of a bidirectional micropump connected to a saline reservoir, which is used to flush and remove the insulating oxide layer to restore the conductivity of the liquid metal.

[0064] In terms of details, the resistance condition support that can be provided by the embedded microcircuit board, namely the microcontroller unit (MCU), and the resistance sensor array can be configured to have an accuracy of ±5Ω.

[0065] With the introduction of the above-mentioned electrical signal control module, the conductive nerve fiber layer has a mesh of liquid metal microchannels, namely the liquid metal network, which is in contact with K + / Ca 2+ Afterwards, an insulating oxide layer (Ga2O3-K complex) is formed, and the resistance increases from 1Ω to ≥200Ω, effectively blocking the conduction of electrical signals.

[0066] In this way, the ultrasound-guided nerve block training model provided by this application has achieved for the first time the blocking of electrical signal conduction in the nerve conductive module by injecting liquid, so as to truly reproduce the effect of human nerves being blocked by local anesthetics. This function has obviously filled the market gap in details based on the model structure conditions provided by this application, enabling trainees to have a deeper understanding of the operating principles and physiological effects of peripheral nerve block during training, thereby promoting better ultrasound-guided nerve block training effects.

[0067] At the same time, it can be seen in the setting here that the physiological saline that can be applied by the reset maintenance module is used to flush out the insulating oxide layer formed by the electrical signal control module, thereby restoring the original conductivity. This is similar to the self-repair mechanism of the hydrogel mentioned above, and is also a long-life reversible design for the model of this application, which can meet the needs of ultrasound-guided nerve block training in actual situations a large number of times and for a long time.

[0068] The physiological saline stored in and provided by the physiological saline reservoir can be input and output by a bidirectional micropump with a flow rate of 0.1L / s-1mL / s connected to the reservoir, and the number of flushing times or recycling times can be specifically greater than 500 times.

[0069] At the same time, corresponding to the temperature response deformation of the surrounding tissue simulated by the dynamic matrix layer, the ultrasound-guided nerve block training model can also be configured with a temperature control layer for the dynamic matrix layer;

[0070] The temperature control layer is structurally configured with a flexible film heating element and a temperature sensor to maintain the surface temperature of the model at 32°C-37°C and trigger the softening of the hydrogel.

[0071] Among them, in terms of details, the thickness of the flexible film heating element can be specifically configured to 0.1mm, the accuracy of the temperature sensor can be specifically configured to ±0.1℃, and the hydrogel softening or deformation response time can be specifically configured to <1 second.

[0072] Thus, under the setting here, through the specific implementation structure, the behavior of human tissue under temperature changes can be better simulated, so as to better realize the temperature / mechanical dual response deformation.

[0073] In addition, corresponding to the additional mechanical response deformation of the conductive nerve fiber layer, the ultrasound-guided nerve block training model can also be configured with a mechanical deformation driving layer for the conductive nerve fiber layer;

[0074] The mechanical deformation driving layer is structurally configured as shape memory alloy wire NiTiNol (Nitinol) embedded in hydrogel, and simulates nerve displacement caused by breathing and body posture through preset programs, which is used to dynamically interfere with puncture operations.

[0075] Among them, the amplitude of nerve displacement can be specifically configured to 0.5mm-5mm. By restoring and simulating nerve displacement, the high simulation degree of the model is further improved, thereby enhancing the training effect.

[0076] In addition, it should be noted that, taking the example of configuring the mechanical deformation driving layer for the conductive nerve fiber layer here, it does not mean that the mechanical deformation driving layer is configured in the conductive nerve fiber layer or configured along with the conductive nerve fiber layer. At the specific operational level, the mechanical deformation driving layer can be conveniently deployed in the dynamic matrix layer, and the dynamic matrix layer can simulate the activities of breathing and body posture to drive the conductive nerve fiber layer to perform corresponding nerve displacement. The previous or subsequent settings are similar. "Targeted" mainly points out the main target object of the specific configuration, and this does not mean that there is an absolute and fixed structural relationship. Various structures may be contained, adjacent or separated.

[0077] At the same time, in order to promote better ultrasound image presentation effects, this application may also involve specific configuration schemes for ultrasound image feedback.

[0078] Specifically, the ultrasound-guided nerve block training model can also be configured with a piezoelectric sensor array;

[0079] The piezoelectric sensor array is structurally configured with a 128-element linear array and integrated into the surface of the outer coating layer. It is used to capture the trajectory of the puncture needle in real time, and to generate and display ultrasound images corresponding to the electrical signal blockage based on the GAN network to show the puncture needle position and drug diffusion.

[0080] In terms of details, the specific operating frequency of the 128-element linear array can be configured to 5MHz-15MHz, and the resolution of the generated ultrasound image can be specifically configured to 0.1mm.

[0081] In this way, based on the artificial intelligence (AI) image fusion algorithm based on generative adversarial networks (GAN), the puncture needle trajectory captured by the 128-element linear array (presented as image features) and the basic ultrasound images involved in ultrasound-guided nerve block itself are fused to generate ultrasound images with more vivid image content that can better assist ultrasound-guided nerve block training. In this ultrasound image, the ultrasound image features / content corresponding to the electrical signal block can be highlighted, such as the ultrasound image features / content of a 20HU-40HU decrease in the grayscale value of nerve edema. This ultrasound image feature / content itself is obtained by the AI image fusion algorithm through matching. In this way, the current ultrasound-guided nerve block training situation (puncture needle position and drug diffusion) is better reflected through the synchronous adjustment of the neural grayscale and boundary fuzziness, thereby assisting in better training effects.

[0082] In addition, corresponding to the feedback of training status / results, the present application may also involve an audible and visual alarm mechanism. For this ultrasound-guided nerve block training model, an audible and visual alarm module may also be configured.

[0083] The sound and light alarm module detects the presence of an accidental blood vessel touch (resistance mutation, <50 Ω ), when there are abnormal operation such as insufficient puncture depth or improper drug diffusion, an audible and visual alarm will be issued to remind you.

[0084] It can be understood that the detection and judgment of the operation status can be specifically processed based on image changes in ultrasound images (which can observe the position of the puncture needle and the diffusion of the drug), resistance changes (which can be used to determine whether a blood vessel is accidentally touched), or the state of electrical signal conduction. While improving the accuracy and safety of the operation, specific acoustic and visual feedback (such as acoustic and visual feedback at a frequency of 2kHz) can also be performed through monitoring of abnormal operation conditions.

[0085] For the above program content, as an operational example in a specific application, the training process of ultrasound-guided nerve block training can be as follows:

[0086] 1. Injection triggers electrical signal blockade;

[0087] 2. Injection of K + / Ca 2+ After the simulated local anesthetic is applied, the ions react with the oxide layer on the surface of the liquid metal:

[0088] Ga2O3+2K + +Ca 2+ +3H2O→2GaO(OH)·KCa+2H3O + +Ga2O3+2K + +Ca 2+ +3H2O→2GaO(OH)·KCa+2H3O +

[0089] Insulating gallium oxyhydroxide-potassium calcium complex is generated, with a resistivity of 10 -8 Ω·m increases to 10 -3 Ω·m, blocking electrical signal conduction (simulating nerve block);

[0090] 3. Dynamic deformation and ultrasonic feedback linkage;

[0091] 4. When the operator applies ultrasound probe pressure (0.5N-5N):

[0092] 5. The pressure sensor triggers the deformation of the NiTiNol wire to simulate tissue displacement;

[0093] 6. The piezoelectric array generates real-time ultrasound images, and the AI algorithm simultaneously adjusts the neural grayscale and boundary blur;

[0094] 7. Operational evaluation and error correction:

[0095] Success criteria: resistance > 200Ω for 10 seconds + disappearance of nerve boundary on ultrasound imaging;

[0096] Error alarm: When the puncture needle accidentally touches the blood vessel (resistance mutation <50Ω), an audible and visual alarm (frequency 2kHz) is triggered.

[0097] Finally, regarding the above-mentioned solution content, in general, for the goal of ultrasound-guided nerve block training, this application, based on the introduction of 4D printing technology, has designed a set of novel specific high-simulation model structures for the ultrasound-guided nerve block training model, and continued to provide a series of optimization settings in terms of details, taking into account multiple advantages such as high simulation, dynamic characteristics, electrical signal blocking function, ultrasound compatibility, real-time feedback mechanism, versatility, portability and economy, which can provide a safer, more economical and efficient tool for clinical skills training of ultrasound-guided nerve block, which is helpful to improve the quality and efficiency of medical education and has good application prospects.

[0098] The excellent results it can achieve in different aspects are:

[0099] 1) High degree of simulation

[0100] Traditional technology issues: Traditional training models (such as plastic molds, animal experiments or cadaver dissections) cannot fully simulate the complex anatomical structure and dynamic response of the human body.

[0101] Advantages of this application:

[0102] Based on 4D printing technology, the morphology and physical properties of multi-layered tissues such as skin, fat, muscle, and bone are restored to provide a close-to-real touch and operation experience. The model can also deform dynamically to simulate the behavior of human tissue under different conditions (such as temperature changes or mechanical forces), further improving the degree of simulation.

[0103] 2)Electrical signal blocking function

[0104] Traditional technical issues: Traditional training models cannot simulate the effects of local anesthetics on nerve electrical signal conduction, making it difficult for trainees to intuitively understand the drug's mechanism of action.

[0105] Advantages of this application:

[0106] For the first time, it has been possible to block the conduction of electrical signals in the nerve conductive module by injecting liquid, realistically reproducing the effect of human nerves being blocked by local anesthetics. This function fills a gap in the market and enables trainees to have a deeper understanding of the operating principles and physiological effects of peripheral nerve blockade during training.

[0107] 3) Ultrasound compatibility

[0108] Traditional technical issues: Traditional training models are not compatible with actual ultrasound equipment, resulting in trainees being unable to master ultrasound-guided puncture techniques during the learning process.

[0109] Advantages of this application:

[0110] The surface of the model is covered with ultrasound transparent material to ensure clear images under ultrasound guidance. Trainees can use ultrasound equipment to observe the position of the puncture needle and drug diffusion in real time, thereby improving the accuracy and safety of the operation.

[0111] 4) Real-time feedback mechanism

[0112] Traditional technology issues: Traditional training models lack real-time feedback functions, making it difficult for trainees to detect and correct incorrect operations in a timely manner.

[0113] Advantages of this application:

[0114] It can monitor the position of the puncture needle, the range of drug diffusion, and the state of electrical signal conduction in real time. If the operation is wrong (such as insufficient puncture depth or improper drug diffusion), it will also use sound and light alarms to prompt students to adjust the operation, thereby improving learning efficiency.

[0115] 5) Versatility

[0116] Traditional technology issues: Traditional training models with a single function are difficult to meet diverse training needs.

[0117] Advantages of this application:

[0118] It combines multiple functions such as neural electrical signal conduction, ultrasound visualization, real-time feedback and local anesthetic block simulation. It is suitable for learners of different levels and can be used for basic skills training of medical students, standardized training of residents and continuing education of medical staff.

[0119] 6) Portability and economy

[0120] Problems with traditional technology: High-end simulators are bulky and expensive, making them unaffordable for many medical institutions and individuals.

[0121] Advantages of this application:

[0122] The model adopts a lightweight design, which is easy to carry and store. It is suitable for various teaching and training scenarios. It is low-cost and cost-effective, and is especially suitable for application scenarios with limited resources.

[0123] 7) Security

[0124] Traditional technical issues: Traditional training models involve animal experiments and autopsies, which pose ethical controversies and biosafety risks.

[0125] Advantages of this application:

[0126] It completely avoids the need for animal experiments and autopsies, eliminates ethical disputes and biosafety risks, and is made of environmentally friendly materials that are harmless to humans and the environment.

[0127] The above is a detailed introduction to the 4D printing-based ultrasound-guided nerve block training model provided by this application. This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the core idea of this application; at the same time, for technical personnel in this field, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on this application.

Claims

1. A 4D-printed ultrasound-guided nerve block training model, characterized in that: The ultrasound-guided nerve block training model includes a conductive nerve fiber layer, a dynamic matrix layer and an outer membrane layer obtained by 4D printing in sequence; The conductive nerve fiber layer is structurally configured as liquid metal microchannels distributed along the nerve shape and covered with an insulating layer to simulate the differentiated electrical signal conduction of Aα fibers, Aδ fibers and C fibers; The dynamic matrix layer is configured as a honeycomb porous structure and contains microfluidic channels to simulate the temperature-responsive deformation of surrounding tissues, wherein the surrounding tissues include muscles, fat, blood vessels and bones; The outer film layer is structurally configured to be wrapped at the outermost layer to protect the internal structure and provide a real puncture feeling.

2. The ultrasound-guided nerve block training model according to claim 1, characterized in that: The conductive nerve fiber layer is made of gallium indium tin liquid metal Ga 60 In 25 Sn 15 and biocompatible polymer polyurethane composite printing.

3. The ultrasound-guided nerve block training model according to claim 1, characterized in that: The dynamic matrix layer is printed from the temperature-sensitive self-repairing hydrogel PNIPAM, and automatically repairs puncture damage below 25°C through the hydrogel properties.

4. The ultrasound-guided nerve block training model according to claim 1, characterized in that: The outer coating layer is obtained by printing a silicone rubber-nanofiber composite film, and a polydopamine anti-adhesion layer is coated on the surface.

5. The ultrasound-guided nerve block training model according to claim 1, characterized in that: Regarding the conductive nerve fiber layer, the ultrasound-guided nerve block training model is further configured with a liquid injection system; The injection catheter system is structurally configured as a multi-lumen microfluidic catheter parallel to the conductive nerve fiber layer, with an outlet located next to the nerve sheath for injecting an ionic solution simulating local anesthetics to trigger electrical signal blocking.

6. The ultrasound-guided nerve block training model according to claim 5, characterized in that: For the conductive nerve fiber layer, the ultrasound-guided nerve block training model is further configured with an electrical signal control module and a reset maintenance module; The electrical signal control module is structurally composed of an embedded microcircuit board and a resistance sensor array, which is used to generate an insulating oxide layer when the liquid metal network comes into contact with potassium ions or calcium ions, thereby blocking the conduction of electrical signals. The resetting and maintenance module is structurally connected to a physiological saline reservoir by a bidirectional micro pump, and is used for flushing and removing the insulating oxide layer to restore the conductivity of the liquid metal.

7. The ultrasound-guided nerve block training model according to claim 1, characterized in that: Regarding the dynamic matrix layer, the ultrasound-guided nerve block training model is further configured with a temperature control layer; The temperature control layer is structurally configured with a flexible film heating element and a temperature sensor, which is used to maintain the surface temperature of the model at 32° C.-37° C. and trigger the softening of the hydrogel.

8. The ultrasound-guided nerve block training model according to claim 1, characterized in that: Regarding the conductive nerve fiber layer, the ultrasound-guided nerve block training model is further configured with a mechanical deformation driving layer; The mechanical deformation driving layer is structurally configured as shape memory alloy wire NiTiNol embedded in hydrogel, and simulates nerve displacement caused by breathing and body posture through a preset program, which is used to dynamically interfere with the puncture operation.

9. The ultrasound-guided nerve block training model according to claim 1, characterized in that: The ultrasound-guided nerve block training model is also configured with a piezoelectric sensor array; The piezoelectric sensor array is structurally configured with a 128-element linear array and integrated on the surface of the outer coating layer, which is used to capture the trajectory of the puncture needle in real time, so as to generate and display ultrasound images corresponding to the electrical signal blockage based on the GAN network to show the puncture needle position and drug diffusion.

10. The ultrasound-guided nerve block training model according to claim 9, characterized in that: The ultrasound-guided nerve block training model is also equipped with an audible and visual alarm module; When the sound and light alarm module detects an abnormal operation such as accidental touching of a blood vessel, insufficient puncture depth or improper drug diffusion in combination with the task information of a preset training task, it will issue a sound and light alarm to remind.

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