Biodegradable peripheral nerve interface with monitoring and repairing functions and preparation method

Abstract

The invention relates to the field of medical equipment, in particular to a biodegradable peripheral nerve interface with monitoring and repairing functions and a preparation method. The nerve interface is made of a biodegradable material and comprises a double-layer recording electrode array used for monitoring nerve signals of peripheral nerves; and the primary battery is used for providing an electric signal so as to promote repair of the damaged peripheral nerve. According to the biodegradable peripheral nerve interface provided by the embodiment of the invention, the nerve interface is made of the biodegradable material, so that a secondary operation required by implanting a non-degradable material can be reduced, the infection risk is reduced, and meanwhile, the integrated design of the double-layer recording electrode array and the primary battery is adopted, so that the cost is reduced. The dual functions of monitoring of neural signals and electrical stimulation repair are achieved, and the neural interface can effectively promote nerve regeneration and repair.

Description

Technical Field

[0001] The present disclosure relates to the field of medical equipment, and in particular to a biodegradable peripheral nerve interface with monitoring and repair functions and a preparation method thereof. Background Art

[0002] With the development of medical technology, the demand for the treatment of peripheral nerve injuries is growing. Traditional nerve repair methods have certain limitations. For example, autologous nerve transplantation may cause damage to the donor site, and non-biomaterial nerve conduits have problems with biocompatibility and degradation. Therefore, the development of new biodegradable peripheral nerve interfaces has become an important research direction. Summary of the invention

[0003] In view of this, the present disclosure proposes a biodegradable peripheral nerve interface with monitoring and repair functions and a preparation method thereof.

[0004] According to one aspect of the present disclosure, a biodegradable peripheral nerve interface with monitoring and repair functions is provided, wherein the nerve interface is made of a biodegradable material and comprises:

[0005] A dual-layer recording electrode array for monitoring neural signals in peripheral nerves;

[0006] A primary battery is used to provide an electrical signal to promote the repair of damaged peripheral nerves.

[0007] In a possible implementation, the double-layer recording electrode includes a molybdenum (English: Mo) electrode and a silicon (English: Si) film, the molybdenum electrode is used to monitor the neural signals of the peripheral nerves, and the silicon film serves as a protective layer of the molybdenum electrode to protect the molybdenum electrode.

[0008] In another possible implementation, the primary cell includes magnesium (English: Mg) as an anode material and iron-manganese alloy (English: FeMn) as a cathode material, and the magnesium and the iron-manganese alloy are respectively located on both sides of the double-layer recording electrode array.

[0009] In another possible implementation, the neural interface further includes a shape memory polymer (SMP), and the SMP is used to wrap around the peripheral nerve by self-curling at body temperature to adapt to the shape of the peripheral nerve.

[0010] In another possible implementation, the double-layer recording electrode array, the primary battery, and the shape memory polymer are all biodegradable.

[0011] In another possible implementation, the monitored nerve signal of the peripheral nerve is used to evaluate the repair progress of the peripheral nerve.

[0012] In another possible implementation, the monitored nerve signals of the peripheral nerves are used to detect whether a neuroma is formed.

[0013] According to another aspect of the present disclosure, a method for preparing a biodegradable peripheral nerve interface is provided, wherein the nerve interface includes the nerve interface provided by the first aspect or any possible implementation of the first aspect, and the method includes:

[0014] The double-layer recording electrode array and the primary cell are prepared on a preset substrate material by magnetron sputtering technology, thereby obtaining the neural interface.

[0015] In a possible implementation, the double-layer recording electrode array and the primary cell are prepared on a preset substrate material by magnetron sputtering technology to obtain the neural interface, including:

[0016] On the preset substrate material, a molybdenum electrode is prepared by the magnetron sputtering technology;

[0017] Prepare a silicon film by photolithography and reactive ion etching technology, and transfer the silicon film to the molybdenum electrode, wherein the molybdenum electrode and the silicon film constitute the double-layer recording electrode array;

[0018] On the double-layer recording electrode array, magnesium and iron-manganese alloy are prepared by the magnetron sputtering technology, and the magnesium and the iron-manganese alloy constitute the primary cell, thereby obtaining the neural interface.

[0019] In another possible implementation, the method further includes:

[0020] The neural interface is covered or encapsulated using a shape memory polymer.

[0021] The disclosed embodiments provide a biodegradable peripheral nerve interface with monitoring and repair functions, which is made of biodegradable materials and aims to provide a solution that can both monitor nerve signals and promote nerve repair. This neural interface includes a double-layer recording electrode array for monitoring the nerve signals of peripheral nerves, and a primary battery for providing electrical signals to promote the repair of damaged peripheral nerves. The advantage of this design is that since the neural interface is made of biodegradable materials, it can reduce the secondary surgery required for the implantation of non-degradable materials, thereby reducing the risk of infection. At the same time, the integrated design of the double-layer recording electrode array and the primary battery realizes the dual functions of monitoring nerve signals and electrical stimulation repair. This neural interface can effectively promote nerve regeneration and repair.

[0022] Further features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.

[0024] Figure 1 A schematic structural diagram of a biodegradable peripheral nerve interface with monitoring and repair functions provided by an exemplary embodiment of the present disclosure is shown.

[0025] Figure 2 A schematic diagram showing the structure and function of a neural interface provided by an exemplary embodiment of the present disclosure.

[0026] Figure 3 A schematic flow chart of a method for preparing a neural interface provided by an exemplary embodiment of the present disclosure is shown.

[0027] Figure 4 A schematic flow chart of a method for preparing a neural interface provided by another exemplary embodiment of the present disclosure is shown.

[0028] Figure 5 A schematic diagram showing the state change of a shape memory polymer provided by an exemplary embodiment of the present disclosure is shown.

[0029] Figure 6 A schematic diagram showing the DSC analysis results of a shape memory polymer provided by an exemplary embodiment of the present disclosure.

[0030] Figure 7 A schematic diagram showing electrochemical performance analysis and stability analysis of electrode materials of a double-layer recording electrode array provided by an exemplary embodiment of the present disclosure is shown.

[0031] Figure 8 A schematic diagram showing a process of accelerated degradation of a neural interface provided by an exemplary embodiment of the present disclosure is shown.

[0032] Fig. 9 A schematic diagram of a sciatic nerve signal trajectory recorded using a neural interface during flexion and extension movements of a rat model's hind limbs provided by an exemplary embodiment of the present disclosure is shown.

[0033] Fig.10 A schematic diagram showing an exemplary embodiment of the present disclosure after implantation of a neural interface on the sciatic nerve of a rat model.

[0034] Fig.11A schematic diagram showing an implantation process of implanting a neural interface on the sciatic nerve of a rat model provided by an exemplary embodiment of the present disclosure is shown.

[0035] Fig.12 A schematic diagram showing the neural signal trajectories recorded from two different types of neural interfaces three weeks after implantation in a rat model.

[0036] Fig.13 Schematic diagram showing gait recovery of two different neural interfaces in a rat model 3 weeks after implantation.

[0037] Fig.14 A schematic diagram showing the correspondence between the electrical performance and gait of a neural interface provided by an exemplary embodiment of the present disclosure at week 3 after implantation.

[0038] Fig.15 A schematic diagram showing representative images of evoked neural signals recorded by a neural interface provided by an exemplary embodiment of the present disclosure.

[0039] Fig.16 A schematic diagram showing the results of machine learning analysis of neural signals using a CNN model provided by an exemplary embodiment of the present disclosure.

[0040] Fig.17 A schematic diagram showing comparative images of the gastrocnemius muscle on the injured side and the contralateral (healthy side) side provided by an exemplary embodiment of the present disclosure is shown.

[0041] Fig.18 A schematic diagram of a Masson trichrome staining image of the gastrocnemius muscle provided by an exemplary embodiment of the present disclosure is shown.

[0042] Fig.19 A schematic diagram showing a representative composite electromyogram of the injured side provided by an exemplary embodiment of the present disclosure is shown.

[0043] Fig. 20 A schematic diagram showing the biodegradation characteristics and biocompatibility features of a neural interface provided by an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0044] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0045] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0046] In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the main purpose of the present disclosure.

[0047] The disclosed embodiment provides a biodegradable peripheral nerve interface with monitoring and repair functions, which is made of biodegradable materials and aims to provide a solution that can monitor nerve signals and promote nerve repair. Figure 1 , which shows a schematic structural diagram of a biodegradable peripheral nerve interface 11 with monitoring and repair functions provided by an exemplary embodiment of the present disclosure. The biodegradable peripheral nerve interface 11 with monitoring and repair functions includes a double-layer recording electrode array 12 and a primary battery 13, wherein the double-layer recording electrode array 12 is used to monitor the neural signals of the peripheral nerves, and the primary battery 13 is used to provide electrical signals to promote the repair of damaged peripheral nerves. For the convenience of subsequent introduction, this biodegradable peripheral nerve interface with monitoring and repair functions can be referred to as "biodegradable peripheral nerve interface" or "neural interface". For further information, please refer to Figure 2 , which shows a schematic diagram of the structure and function of a neural interface provided by an exemplary embodiment of the present disclosure.

[0048] The neural interface is made of biodegradable materials, which may be fully biodegradable materials, and is designed to monitor and repair damaged peripheral nerves. Figure 2 The key components and functions of the neural interface are shown in:

[0049] 1. Wireless recording: The remote device can wirelessly record the neural signals detected by the neural interface. The neural signals are the neural signals of the peripheral nerves, which can be used to remotely monitor neural activity.

[0050] 2. Double-layer recording electrode array: used to monitor the neural signals of peripheral nerves, that is, the electrical signals of peripheral nerves. A double-layer recording electrode array refers to an array composed of multiple tiny electrodes that can record the electrical activity of neurons or other electrically active cells at multiple locations at the same time. The double-layer recording electrode array is a multi-channel double-layer recording electrode array, such as a 7-channel double-layer recording electrode array. Among them, "multi-channel" means that the double-layer recording electrode array contains multiple independent electrodes, each of which is capable of recording electrical signals from different locations or different nerve fibers. This multi-channel design enables researchers to monitor multiple neural signals at the same time, thereby gaining a more comprehensive understanding of the activity patterns of neural networks.

[0051] The "double-layer" characteristic of this double-layer recording electrode refers to the two layers of different materials or two layers of electrodes in the electrode structure. Such a design can improve the recording efficiency and quality of the signal. For example, one layer is responsible for recording neural signals, while the other layer is used for other functions. In some embodiments, the double-layer recording electrode includes a platinum electrode and a silicon membrane. The platinum electrode is used to monitor the neural signals of the peripheral nerves, and the silicon membrane serves as a protective layer for the platinum electrode to protect the platinum electrode, thereby enhancing the service life of the platinum electrode. Both the platinum electrode and the silicon membrane are biodegradable materials.

[0052] 3. PLLA-PTMC: refers to the copolymer of Poly-L-lactic acid (PLLA) and polytrimethylene carbonate (PTMC), which is a biodegradable material that constitutes the substrate of the neural interface. This copolymer combines the advantages of two polymers and provides good biocompatibility, biodegradability and mechanical properties. However, the embodiments of the present disclosure are not limited to the use of PLLA-PTMC as the substrate material of the neural interface. In fact, the substrate material of the neural interface can be other biodegradable materials, including but not limited to: polycaprolactone (PCL), polyglycolic acid (PGA), polylactic acid-glycolic acid copolymer (PLGA), etc., which are not limited in the embodiments of the present disclosure.

[0053] 4. Primary battery: used to provide electrical signals to promote the regeneration of damaged nerves, that is, electrically stimulate the repair of damaged nerves. In some embodiments, the primary battery may include magnesium as an anode material and an iron-manganese alloy as a cathode material, and the magnesium and the iron-manganese alloy are respectively located on both sides of the double-layer recording electrode array. Both magnesium and iron-manganese alloy are biodegradable materials. When designing the primary battery of a biodegradable neural interface, in addition to the combination of magnesium as an anode material and an iron-manganese alloy as a cathode material, other materials with biocompatibility and biodegradability may also be considered. For example, zinc and zinc oxide are a common biodegradable battery combination, which is not limited in the embodiments of the present disclosure.

[0054] 5. Shape memory polymer: Also known as shape memory polymer, it is used to wrap around peripheral nerves by self-curling at body temperature to adapt to the shape of the peripheral nerves, thereby assisting the implantation process of the neural interface into the peripheral nerves.

[0055] 6. Function 1: Evaluate nerve repair status: This neural interface can monitor nerve signals to help evaluate the progress of peripheral nerve repair.

[0056] 7. Function 2: Early detection of neuromas: Neural interfaces can monitor nerve signals to detect the formation of neuromas at an early stage, which is a possible complication after nerve damage.

[0057] The entire neural interface is designed to be biodegradable, that is, all materials of the neural interface (including substrate material, double-layer recording electrode array, primary battery, shape memory polymer) are biodegradable, which means that after completing its function, the neural interface can be naturally degraded without additional surgical intervention. The development of this technology has improved the efficiency of nerve damage repair. With the continuous progress of materials science, electronics and neuroscience, this biodegradable neural interface is expected to become an important tool in the field of neural repair in the future.

[0058] Figure 2 The application of the neural interface in a rat model is also schematically demonstrated, in which the neural interface is implanted into the damaged sciatic nerve of the rat model. It should be noted that the neural interface provided by the embodiment of the present disclosure has a very wide range of applications and is far more than limited to the sciatic nerve of the rat model. This neural interface design is intended to adapt to the peripheral nerves of various organisms and can be used in different animal models and clinical scenarios, especially in situations where nerve monitoring and repair are required.

[0059] In summary, the embodiments of the present disclosure provide a biodegradable peripheral nerve interface with monitoring and repair functions, which is made of biodegradable materials and aims to provide a solution that can both monitor nerve signals and promote nerve repair. This neural interface includes a double-layer recording electrode array for monitoring the nerve signals of peripheral nerves, and a primary battery for providing electrical signals to promote the repair of damaged peripheral nerves. The advantage of this design is that since the neural interface is made of biodegradable materials, it can reduce the secondary surgery required for the implantation of non-degradable materials, thereby reducing the risk of infection. At the same time, the integrated design of the double-layer recording electrode array and the primary battery realizes the dual functions of monitoring nerve signals and electrical stimulation repair. This neural interface can effectively promote nerve regeneration and repair.

[0060] In some embodiments, the method for preparing a biodegradable peripheral nerve interface with monitoring and repair functions provided by the embodiments of the present disclosure may include: preparing a double-layer recording electrode array and a primary cell on a preset substrate material by magnetron sputtering technology, and finally forming a neural interface. Figure 3 , which shows a schematic flow chart of a method for preparing a neural interface provided by an exemplary embodiment of the present disclosure.

[0061] Step 301, preparing a molybdenum electrode on a preset substrate material by magnetron sputtering technology.

[0062] The preset substrate material may include a flexible biodegradable copolymer substrate of PLLA and PTMC, or other materials as mentioned in the above embodiments. Different substrate materials may be selected according to the specific application requirements of the neural interface, which is not limited in the embodiments of the present disclosure.

[0063] Step 302, prepare a silicon film by photolithography and reactive ion etching technology, and transfer the silicon film to the molybdenum electrode, the molybdenum electrode and the silicon film constitute a double-layer recording electrode array.

[0064] The silicon membrane is prepared by photolithography and reactive ion etching technology. This delicate process step ensures the precise shape and size of the silicon membrane. Subsequently, the silicon membrane is transferred to the prepared molybdenum electrode, so that the molybdenum electrode and the silicon membrane together form a double-layer recording electrode array. This structure is designed to improve the stability of the electrode and the accuracy of signal monitoring.

[0065] Step 303, on the double-layer recording electrode array, magnesium and iron-manganese alloy are prepared by magnetron sputtering technology, and the magnesium and iron-manganese alloy constitute a primary cell, thereby obtaining a neural interface.

[0066] Based on the double-layer recording electrode array, we continued to prepare magnesium and iron-manganese alloy on the electrode by magnetron sputtering technology. These two materials were selected because they can form an effective galvanic cell to provide the required electrical signal for neural repair.

[0067] Finally, to protect the neural interface and ensure its stable operation in vivo, the neural interface can be covered or encapsulated with shape memory polymers, which are able to gradually degrade in the body while providing the necessary mechanical protection and biocompatibility.

[0068] Through the above steps, a complete biodegradable peripheral nerve interface can be obtained, which can not only monitor the nerve signals of peripheral nerves, but also provide electrical stimulation through the built-in primary battery to promote nerve repair. The preparation method of this interface combines multiple materials and technologies, showing innovation and progress in the field of biomedical engineering.

[0069] In an illustrative example, Figure 4 As shown, it shows a schematic flow chart of a method for preparing a neural interface provided by another exemplary embodiment of the present disclosure. The preparation method includes but is not limited to the following steps:

[0070] 1. Use PLLA-PTMC as the substrate material: In the preparation process of the neural interface, the drop coating of the PLLA-PTMC film is used as the first step to provide a basis for the subsequent electrode preparation and the construction of the neural interface. First, a dropper is used to drop a liquid containing the PLLA-PTMC polymer solution onto the substrate surface, and then it is converted into a uniform film through a series of steps such as solvent evaporation or curing reaction. This method has the advantages of low cost and simple preparation, and is suitable for the manufacture of biodegradable neural interface substrate materials.

[0071] 2. Magnetron sputtering molybdenum electrode: Molybdenum is deposited on the substrate material by magnetron sputtering technology to form an electrode. Molybdenum is a biocompatible metal that can be used as an electrode material.

[0072] 3. Photolithography and reactive ion etching of silicon film: Next, the desired pattern is formed on the silicon by photolithography and reactive ion etching, and then the silicon film is transferred to the molybdenum electrode by stamping. This step forms a double-layer recording electrode array.

[0073] 4. Magnetron sputtering of magnesium and iron-manganese: Magnesium and iron-manganese alloys are deposited on the double-layer recording electrode array by magnetron sputtering technology. These materials can form primary cells and provide the required electrical signals for neural repair.

[0074] 5. Shape memory function self-curling: Utilizing the shape memory properties of shape memory polymers, self-curling is achieved in phosphate buffered saline (PBS) at 37°C. This step enables the neural interface to better fit the peripheral nerves and improve its stability and biocompatibility.

[0075] 6. Prepare the neural interface: Finally, use a shape memory polymer to cover or encapsulate the neural interface to protect the electrodes and ensure its stability in the body.

[0076] Please refer to Figure 5, which shows a schematic diagram of the state change of a shape memory polymer provided by an exemplary embodiment of the present disclosure. By comparing two different states, the application of shape memory polymers in neural interfaces is demonstrated. This material can change its shape under certain conditions and return to its original shape after being properly stimulated. This property is crucial to the design of neural interfaces. 1. Temporary flattened state in room temperature air (left picture): Under room temperature conditions, the neural interface presents a planar state. This is obtained by temporarily flattening and fixing the shape memory polymer. In this state, the neural interface is easy to handle and implant. 2. Permanently rolled up state in 37°C PBS solution (right picture): When the neural interface is immersed in PBS at 37°C, the shape memory polymer begins to respond to temperature changes, triggering its shape memory effect. Under the action of body temperature, the neural interface gradually recovers from a planar state to a preset curled state. This self-curling property enables the neural interface to better fit the peripheral nerves and provide stable contact and signal transmission.

[0077] Please refer to Figure 6 , which shows a schematic diagram of the results of differential scanning calorimetry (DSC) analysis of a shape memory polymer provided by an exemplary embodiment of the present disclosure. DSC is a thermal analysis technique used to measure the amount of heat absorbed or released by a substance during heating or cooling, thereby studying its thermal properties. In this figure: the horizontal axis (X-axis) represents temperature (°C), and the vertical axis (Y-axis) represents heat flow (W / g), that is, the amount of heat absorbed or released per gram of a unit mass of a substance during heating or cooling. The curve in the figure shows the change in heat flow of the shape memory polymer at different temperatures. In particular, a key temperature point of 36.14°C is marked in the figure, which corresponds to the transition temperature of the shape memory polymer. At this temperature point, the shape memory polymer will undergo changes, such as restoring the neural interface from a planar state to a self-bending state. The significance of this temperature point is that it is close to the normal body temperature of the human body (approximately 37°C), indicating that this shape memory polymer can exhibit a shape memory effect at body temperature, that is, after implantation, this shape memory polymer can recover from a temporary shape to its memory shape under the action of body temperature, thereby achieving self-curling and surrounding peripheral nerves, assisting the implantation process.

[0078] Please refer to Figure 7 , which shows a schematic diagram of the electrochemical performance analysis and stability analysis of the electrode materials (molybdenum electrode and silicon film) of a double-layer recording electrode array provided by an exemplary embodiment of the present disclosure.

[0079] The left figure shows the electrochemical impedance spectroscopy (EIS) of the electrode material (molybdenum electrode and silicon film), which is usually used to evaluate the electrochemical properties of electrode materials, such as the charge transfer characteristics and interface stability of electrode materials. The right figure shows the impedance changes of the electrode material (molybdenum electrode and silicon film) before and after being immersed in PBS solution for 7 weeks at a frequency of 1kHz.

[0080] according to Figure 7 The results show that the electrode materials (molybdenum electrode and silicon film) show stable electrochemical impedance in PBS, which means that the electrode materials have good stability in the simulated in vivo environment and are not prone to electrochemical degradation. In addition, the electrode materials have good stability at 37°C, indicating that they are suitable for use in the in vivo environment because the normal body temperature of the human body is about 37°C.

[0081] The degradation characteristics of the neural interface were evaluated under accelerated dissolution conditions, i.e., at pH 7.4 and 60°C. Schematic diagram of the accelerated degradation process of the neural interface Figure 8 As shown, the significant advantages of this biodegradable neural interface are revealed: the electrode material can disappear in about 9 days, and the entire neural interface is completely degraded in about 19 days. This feature not only reduces the complications that may arise from long-term implants, but also avoids the need for secondary surgery to remove it, thereby reducing patient risks and medical costs. This rapid and complete degradation capability demonstrates the potential of this neural interface in clinical applications, especially in medical scenarios that require temporary monitoring or stimulation of nerves to promote healing.

[0082] After the neural interface was implanted into the sciatic nerve of a rat model, the double-layer recording electrode array was able to seamlessly wrap the nerve, reduce tissue damage, and successfully record the induced neural signals. Fig. 9 A schematic diagram of the trajectory of sciatic nerve signals recorded using a neural interface during the flexion and extension movement of the hind limbs of a rat model provided by an exemplary embodiment of the present disclosure is shown. Neural signals in the anesthetized state of the rat model are recorded by a double-layer recording electrode array implanted on the sciatic nerve of the rat model, and these signals are captured during the periodic passive movement of the hind limbs of the rat model, including leg flexion and extension. It can be observed from the figure that the intensity of the neural signal shows obvious periodic changes with the flexion and extension movement of the hind limbs, which means that when the hind limbs perform periodic passive movements, the neural signals recorded by the double-layer recording electrode array show a strong correlation with the flexion and extension movement of the hind limbs, which indicates that the double-layer recording electrode array can accurately capture neural activity related to movement.

[0083] After a peripheral nerve is damaged, a neural interface is implanted, and during a preset period of time after implantation, the neural signals of the peripheral nerve are monitored through the neural interface. The monitored neural signals of the peripheral nerve are used to determine the test results, which include evaluating the progress of the repair of the peripheral nerve and / or detecting whether a neuroma has formed.

[0084] The detection result can be determined by a pre-trained target model, which is a neural network model used to analyze the neural signal characteristics of peripheral nerves to determine the target detection result. The neural network model can be trained using existing technology based on neural signal samples and detection result labels. For example, the target model is a convolutional neural network (CNN) model. This is not limited in the embodiments of the present disclosure.

[0085] The functions of the biodegradable peripheral nerve interface provided by the embodiments of the present disclosure are further introduced below.

[0086] On the one hand, the neural interface provided by the embodiments of the present disclosure can be used to track the neural recovery process. In some embodiments, a wireless circuit is combined with the neural interface provided by the embodiments of the present disclosure to record neural signals in real time and monitor them through wireless data transmission. Fig.10 A schematic diagram showing a neural interface implanted on the sciatic nerve of a rat model according to an exemplary embodiment of the present disclosure is shown. Fig.11 A schematic diagram of the implantation process of a neural interface on the sciatic nerve of a rat model provided by an exemplary embodiment of the present disclosure is shown. During the neural interface implantation process, delicate surgical techniques are used to ensure that the neural interface can be properly connected to the neural tissue. The following is an overview of the general steps: 1. Cut the skin of the leg, 2. Cut the sciatic nerve, 3. Implant the neural interface into the nerve defect, 4. Suture the leg muscles, 5. Fix the neural interface, 6. Suture the neck lead.

[0087] In some embodiments, the neural interface provided by the embodiments of the present disclosure is implanted after peripheral nerve injury, and the progress of neural recovery is evaluated by monitoring the signal trajectory of neural signals (such as whether neural signals of multiple electrode channels exist) during a preset time period after implantation. Fig.12A schematic diagram of the neural signal trajectories recorded after two different types of neural interfaces were implanted in a rat model for 3 weeks. These signals were collected when the rat model was walking on a treadmill and were used to evaluate the performance and biocompatibility of the neural interface. Two different types of neural interfaces include a neural interface in the related art (i.e., a neural interface that does not include a biodegradable battery), and a neural interface provided by the present disclosure (a neural interface that includes a biodegradable battery). The numbers 1 to 7 in the figure represent different electrode channels. Each channel is connected to an electrode of the neural interface for recording neural signals at that location.

[0088] In the waveform diagram of the neural interface in the related art, channels 1 to 4 show jagged waveforms, which indicates that these channels have detected neural signals. The waveforms of channels 5 to 7 are relatively flat, indicating that these channels have not detected neural signals. This means that the progress of neural repair has only reached the area covered by channel 4.

[0089] In the waveform diagram of the neural interface provided by the present disclosure, all channels 1 to 7 show sawtooth waveforms, indicating that these channels have successfully recorded neural signals. This shows that the progress of neural repair has reached the area covered by channel 7, and neural activity is active in these areas.

[0090] By comparing the signals recorded by the two neural interfaces, the extent of nerve repair can be assessed. Fig.12 The results showed that the neural interface has a good tracking ability for the axonal growth front, and the biodegradable battery has a significant effect on promoting the repair of damaged peripheral nerves.

[0091] In some embodiments, recording neural signals in a freely moving rat model can provide insight into changes in gait parameters during the assessment of recovery from neural injury. Fig.13 Schematic diagram showing gait recovery of two different neural interfaces in a rat model 3 weeks after implantation.

[0092] Fig.13 (a) Shows a stick figure decomposition of the kinematics of hindlimb locomotion on a treadmill, a visualization method used to show the positional changes of the hindlimbs of a rat model during a locomotion cycle. Fig.13 (b) provides a statistical analysis of the actual swing phase time of the neural interface in the related art (i.e., the neural interface without a biodegradable battery) and the neural interface provided by the present disclosure (the neural interface including a biodegradable battery) at 2 weeks and 3 weeks after implantation. These data reveal the difference in efficiency of the two interfaces during the recovery period. Fig.13(c) shows representative images of the injured side and the contralateral (healthy side) hind limb footprints, which were collected 2 weeks after the neural interface implantation in the related art and 3 weeks after the neural interface implantation provided by the present disclosure. By comparing these footprints, obvious differences in gait recovery can be observed.

[0093] Fig.14 It further shows a schematic diagram of the correspondence between the electrical performance and gait of the neural interface provided by an exemplary embodiment of the present disclosure at the third week after implantation. Fig.14 The performance of the neural interface at week 3 after implantation is shown in three different graphs: 1. Predicted swing phase (top): This part shows the swing phase of gait predicted by the neural network model. These predictions are based on the electrical signals recorded by the neural interface, and the neural network model is able to learn the relationship between these electrical signals and the gait cycle and predict the swing phase of gait.

[0094] 2. Electrical signal grid diagram (middle): This part shows the electrical signal recorded by the neural interface, which may be presented in the form of a time series, where the peak of each signal corresponds to a specific event in the gait cycle. This grid diagram can intuitively show the correspondence between the pattern of the electrical signal and the gait cycle.

[0095] 3. Actual swing phase (bottom): This part shows the actual swing phase based on gait video analysis. Through video analysis, the swing phase in the gait cycle can be accurately determined, which provides a benchmark for evaluating the accuracy of neural interfaces and neural network models.

[0096] Using a treadmill and an animal gait analysis system to evaluate changes in gait during nerve injury recovery, and combining a neural network model to process and analyze data, can more accurately reveal changes in gait parameters during nerve injury recovery. Among them, the animal gait analysis system can be a Catwalk gait analysis system, and the neural network model can be a CNN model. The embodiments of the present disclosure are not limited to this. These results show that the neural interface provided by the present disclosure (a neural interface comprising a biodegradable battery) shows better effects on gait recovery than the control group.

[0097] On the other hand, the neural interface provided by the embodiments of the present disclosure can be used for early detection of neuromas. Neuromas usually occur after severe nerve damage or amputation, and appear as a messy cluster of axons wrapped in fibrous scar tissue, which seriously affects recovery. After peripheral nerve damage, the neural interface provided by the embodiments of the present disclosure is implanted. Within a preset time period after implantation, the formation of neuromas can be detected early by monitoring changes in the neural signals of the peripheral nerves (such as a decrease in the amplitude of the neural signals). In addition to detecting whether a neuroma has formed, the development stage of the formed neuroma can also be predicted.

[0098] Fig.15 Schematic diagram showing representative images of evoked neural signals recorded by a neural interface provided by an exemplary embodiment of the present disclosure. These images represent three different experimental groups: a control group (intact nerve), a 2-week neuroma group, and a 3-week neuroma group. Fig.15 As can be seen from the displayed electrical signal recordings, the neural interface is able to detect the formation of a neuroma 2 to 3 weeks after nerve injury. The presence of a neuroma causes a significant decrease in the amplitude of the induced neural signal, and as the neuroma gradually grows, the signal amplitude decreases further. This change in amplitude provides a clear biomarker for the early diagnosis of a neuroma. This capability of the neural interface provided by the disclosed embodiments enables it to provide critical diagnostic information at an early stage when conventional ultrasound technology cannot detect a neuroma, i.e., within three weeks after injury. This early detection not only helps to take timely therapeutic measures, but may also improve the patient's prognosis because it allows intervention before the neuroma develops to a more serious stage.

[0099] In some embodiments, early detection of neuroma formation can be identified by a neural network model, which is used to perform machine learning analysis on the recorded peripheral nerve nerve signals, and can achieve high-accuracy early diagnosis of neuroma. For example, the neural network model is a CNN model, which is mainly composed of two layers of convolution blocks, two layers of fully connected layers (or one hidden layer and one output layer). The convolution block realizes feature extraction and feature aggregation through convolution operation, and the two layers of fully connected layers realize the role of neural network classifier. The analysis process of the CNN model is divided into three key steps: 1. Data preparation: First, the neural signal is filtered to remove noise, and then downsampled to 200Hz to reduce the data dimension and retain key information. Then, these signals are divided into 2-second long, non-overlapping segments, each containing 400 data points. These segments are then divided into training sets and test sets for model training and evaluation. 2. Model training: During the training phase, the CNN model uses a preset loss function to evaluate its performance on the training set, and adjusts the model weights through the optimizer to minimize the loss function, thereby improving the prediction accuracy of the model. 3. Model evaluation: Finally, use the test set to evaluate the training effect and accuracy of the model. This step ensures the generalization ability of the model on unseen data and is the key to evaluating the practical application value of the model.

[0100] Through this CNN model, neural signals can be converted into predictions of the stage of neuroma development. The input of the CNN model is neural signals that can be preprocessed, such as 2-second long electrical signal segments, which have been filtered and downsampled to 200Hz to obtain a sequence of 400 data points. The output of the model can be two numerical values, corresponding to the absence of neuroma and the presence of neuroma. The output of the model can also be three probability values, corresponding to the probabilities of no neuroma, 2-week neuroma, and 3-week neuroma. The disclosed embodiments are not limited to this.

[0101] Fig.16 A schematic diagram of the results of machine learning analysis of neural signals by a CNN model provided by an exemplary embodiment of the present disclosure is shown. The figure shows the comparison between the prediction and actual results of the CNN model for the control group, the 2-week neuroma group, and the 3-week neuroma group based on the induced neural signals and the electrical signals recorded during treadmill walking, respectively.

[0102] 1. Confusion matrix of evoked neural signals (left): This matrix reflects the classification performance of the CNN model when analyzing evoked neural signals. The values ​​in the matrix represent the proportion of the categories predicted by the model that match the actual categories. For example, if the value in the upper left corner is 0.94, it means that the model can correctly identify the signals of the control group in 94% of cases.

[0103] 2. Confusion matrix of electrical signals recorded while walking on a treadmill (right): This matrix shows the performance of the model in analyzing the electrical signals recorded while the rat model was walking on a treadmill. Similarly, the higher the value on the diagonal, the higher the classification accuracy of the model. For example, the value in the lower right corner is 0.96, indicating that the model can correctly identify the signals of the 3-week neuroma group in 96% of cases.

[0104] During treadmill walking, neuroma formation may lead to a significant decrease in the relative energy of the high-frequency band. This change may be captured by the CNN model and used to distinguish different neuroma stages. Fig.16 The results further confirmed the potential of the CNN model in analyzing electrical signals through machine learning and achieving high-accuracy early diagnosis of neuromas.

[0105] Early detection of neuroma is crucial for timely intervention and improving treatment efficacy. By comparing the effects of intervention at different time points 12 weeks later, the atrophy of the gastrocnemius muscle and the recovery of nerve conduction function were deeply explored.

[0106] Fig.17A schematic diagram of comparison images of the injured side and the contralateral (healthy side) gastrocnemius muscle provided by an exemplary embodiment of the present disclosure is shown. The effects after intervention at the 2nd and 5th weeks are shown, respectively, revealing the significant muscle atrophy phenomenon that may be caused by late intervention (after 5 weeks). These images provide intuitive evidence for understanding the long-term effects of nerve damage on muscle structure.

[0107] Fig.18 A schematic diagram of a Masson's trichrome staining image of the gastrocnemius muscle provided by an exemplary embodiment of the present disclosure is shown, and the conditions of collagen fibers and muscle fibers in the gastrocnemius muscle tissue are shown by the Masson's trichrome staining technique. In the early intervention (2 weeks) group, a significant reduction in collagen deposition was observed, while the average cross-sectional area of ​​the muscle fibers was larger, indicating that the muscle tissue maintained a better structure and function.

[0108] Fig.19 A schematic diagram of a representative compound electromyogram of the injured side provided by an exemplary embodiment of the present disclosure is shown, and the recovery of nerve conduction function is quantitatively analyzed by evaluating the compound muscle action potential (CMAP) recorded on the target gastrocnemius muscle when the proximal sciatic nerve stump on the injured side is electrically stimulated. The results showed that the CMAP amplitude in the early intervention group (2 weeks) was significantly higher than that in the late intervention group (5 weeks). This finding emphasizes the importance of early intervention in promoting reinnervation and functional recovery. The above results show that early neuroma detection and intervention are of great significance and can greatly promote reinnervation and reduce muscle atrophy.

[0109] In addition, an important feature of the neural interface provided by the embodiments of the present disclosure is that it is made of biodegradable materials, which can be fully biodegradable materials. Therefore, it can be gradually absorbed by the body after tracking the neural recovery process, thereby avoiding secondary damage to fragile neural tissue that may be caused by device removal surgery.

[0110] Fig. 20 A schematic diagram showing the biodegradation characteristics and biocompatibility features of a neural interface provided by an exemplary embodiment of the present disclosure. Fig. 20 (a) Demonstrates the gradual degradation of the degradable neural interface in vivo. The recorded electrical signals remained stable at 2 and 3 weeks, which provided a sufficient time window to monitor the critical stages of long-gap nerve injury.

[0111] Fig. 20 (b) shows the neural signals collected during the degradation process. The neural signals began to decay in the 5th week and completely lost the ability to record in the 7th week. This change is consistent with the degradation process of the neural interface, further confirming its biodegradability.

[0112] also, Fig. 20 (c) shows the results of biochemical analysis of blood samples from the implanted rat model. The indicators in the figure are as follows: 1. Alanine Aminotransferase (ALT), in U / L, is used to evaluate liver function. 2. Total Bilirubin (TBIL), in μmol / L, is used to evaluate liver function and biliary system. 3. Blood Urea Nitrogen (BUN), in mg / dL, is used to evaluate kidney function. 4. Creatinine (CR), in μmol / L, is also used to evaluate kidney function. These indicators are commonly used in blood biochemical analysis to monitor and evaluate organ health. By comparing the biochemical analysis results of blood samples from the implanted rat model with those of the control group, it was shown that no physiological abnormalities occurred in the experimental group within 3 weeks after implantation. This finding suggests that the degradation process of the neural interface has no negative impact on the physiological function of the rat model.

[0113] Fig. 20 (d) Histological examination results of major organs including the heart, liver, spleen, lungs, and kidneys were shown, with no significant adverse effects compared with the control group, indicating that the degradable neural interface has good biocompatibility and does not induce unnecessary immune responses or tissue damage.

[0114] therefore Fig. 20 The results not only demonstrate the biodegradability of the degradable neural interface, but also prove its excellent performance in biocompatibility. The design of this neural interface provides a safe and effective new option for the treatment of nerve damage and is expected to play an important role in the field of medical devices.

[0115] In summary, compared with the related art, the embodiment of the present disclosure provides a biodegradable peripheral nerve interface with monitoring and repair functions. The beneficial effects of this solution include but are not limited to the following points:

[0116] 1. Biodegradability: The neural interface is made of biodegradable materials and can be gradually absorbed by the body after completing its function, avoiding the complications caused by long-term implantation and the risk of secondary surgery.

[0117] 2. Dual functions: The neural interface has the dual functions of monitoring and repair. The double-layer recording electrode array is used to monitor neural signals, while the primary battery provides electrical signals to promote neural repair, which helps to accelerate the recovery process of damaged nerves.

[0118] 3. Protectiveness: The molybdenum electrode is protected by a silicon film, which serves as a protective layer, which helps to improve the stability and durability of the electrode while reducing damage to surrounding tissues.

[0119] 4. Optimized primary cell design: The primary cell uses magnesium as the anode material and iron-manganese alloy as the cathode material. This combination may provide more stable and lasting electrical signals, which is beneficial for nerve repair.

[0120] 5. Application of shape memory polymers: Shape memory polymers can self-curl at body temperature to adapt to the shape of peripheral nerves, which helps to improve the fit between the neural interface and the peripheral nerves, thereby improving the efficiency of monitoring and repair.

[0121] 6. Fully biodegradable: The double-layer recording electrode array, primary battery, and shape memory polymer are all biodegradable, which further ensures that the neural interface can be safely absorbed by the body after completing its task.

[0122] 7. Evaluation of the progress of neural repair: The monitored neural signals can be used to evaluate the progress of neural repair and provide important feedback information for clinical treatment.

[0123] 8. Early detection of neuromas: Neural interfaces are able to detect the formation of neuromas, which is crucial for timely treatment measures to prevent neuromas from developing to more serious stages.

[0124] These beneficial effects collectively demonstrate the innovative design and practicality of this neural interface, providing a new solution for the treatment of neural damage.

[0125] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A biodegradable peripheral nerve interface with monitoring and repair functions, characterized in that: The neural interface is made of biodegradable materials, including: A dual-layer recording electrode array for monitoring neural signals in peripheral nerves; A primary battery is used to provide an electrical signal to promote the repair of damaged peripheral nerves.

2. The neural interface according to claim 1, characterized in that The double-layer recording electrode includes a molybdenum electrode and a silicon membrane. The molybdenum electrode is used to monitor the neural signals of the peripheral nerves, and the silicon membrane serves as a protective layer of the molybdenum electrode to protect the molybdenum electrode.

3. The neural interface according to claim 1, characterized in that The primary cell includes magnesium as an anode material and an iron-manganese alloy as a cathode material, and the magnesium and the iron-manganese alloy are respectively located on both sides of the double-layer recording electrode array.

4. The neural interface according to any one of claims 1 to 3, characterized in that The neural interface further comprises a shape memory polymer, which is configured to wrap around the peripheral nerve by self-curling at body temperature to adapt to the shape of the peripheral nerve.

5. The neural interface according to claim 4, characterized in that The double-layer recording electrode array, the primary battery, and the shape memory polymer are all biodegradable.

6. The neural interface according to any one of claims 1 to 5, characterized in that The monitored nerve signals of the peripheral nerve are used to evaluate the repair progress of the peripheral nerve.

7. The neural interface according to any one of claims 1 to 5, characterized in that: The monitored nerve signals of the peripheral nerves are used to detect whether a neuroma is formed.

8. A method for preparing a biodegradable peripheral nerve interface, characterized in that: The neural interface comprises a neural interface as claimed in any one of claims 1 to 7, and the method comprises: The double-layer recording electrode array and the primary cell are prepared on a preset substrate material by magnetron sputtering technology, thereby obtaining the neural interface.

9. The method according to claim 8, characterized in that The double-layer recording electrode array and the primary cell are prepared on a preset substrate material by magnetron sputtering technology to obtain the neural interface, comprising: On the preset substrate material, a molybdenum electrode is prepared by the magnetron sputtering technology; Prepare a silicon film by photolithography and reactive ion etching technology, and transfer the silicon film to the molybdenum electrode, wherein the molybdenum electrode and the silicon film constitute the double-layer recording electrode array; On the double-layer recording electrode array, magnesium and iron-manganese alloy are prepared by the magnetron sputtering technology, and the magnesium and the iron-manganese alloy constitute the primary cell, thereby obtaining the neural interface.

10. The method according to claim 9, characterized in that The method further comprises: The neural interface is covered or encapsulated using a shape memory polymer.

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