A neurosurgery clinical operation data analysis system and method

Abstract

The present invention discloses a neurosurgery clinical operation data analysis system and method, which belongs to the field of electronic digital data processing. The present invention obtains nerve tissue recovery evaluation results and surgical nerve control recovery evaluation results to evaluate the surgical recovery effect, performs recovery abnormality warning according to the acquired surgical recovery effect evaluation results, accurately analyzes the nerve tissue recovery effect in the recovery process after surgery through nerve tissue recovery images, and comprehensively analyzes the nerve control recovery effect of the surgical position through the difference in limb training positions, and then accurately evaluates the surgical recovery effect by comprehensively evaluating the nerve tissue recovery effect and the nerve control recovery effect, thereby improving the evaluation efficiency and accuracy of the surgical recovery effect.

Description

Technical Field

[0001] The invention belongs to the field of electronic digital data processing, and in particular to a neurosurgery clinical operation data analysis system and method. Background Art

[0002] Neurosurgery can be used to treat a variety of diseases, such as brain tumors, cerebrovascular diseases, epilepsy, etc. The advantages of surgery include the ability to directly remove diseased tissue and restore neurological function, etc. However, surgery also has certain disadvantages and complications, such as surgical risks, postoperative infection, bleeding, cerebral edema, etc. The doctor will conduct a comprehensive assessment of the patient before surgery and inform the patient of the risks and possible complications of the surgery so that the patient can make an informed decision. The decision whether surgical intervention is needed usually depends on a comprehensive assessment of multiple factors. The doctor will consider the nature, location, size and relationship of the lesion with surrounding tissues based on the patient's medical history, physical examination, imaging examination results, etc. In addition, the doctor will also evaluate the patient's overall health, surgical risks and expected recovery to decide whether to perform surgical intervention;

[0003] During neurosurgery, the nerve tissue at the lesion site is often removed, resulting in the corresponding lesion site not being restored within a certain period of time, leading to functional disorders of the corresponding tissue. When evaluating the recovery of nerve tissue after surgery, the existing technology cannot comprehensively evaluate the recovery effect of the surgery by combining the patient's nerve control recovery and nerve tissue recovery, resulting in low evaluation efficiency. Most of the existing technologies have the above problems.

[0004] The above patents all have the problems raised by this background technology. In order to solve the problems raised by this background technology, this application designs a neurosurgery clinical operation data analysis system and method. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention proposes a neurosurgery clinical operation data analysis system and method.

[0006] To achieve the above object, the present invention provides the following technical solutions: In a first aspect, the present invention provides a method for analyzing clinical operation data of neurosurgery, which comprises the following specific steps:

[0007] Step 1: Acquire recovery data of the nerve at the surgical position and recovery data of the controlled limb corresponding to the nerve at the surgical position for a set period after the surgery;

[0008] Step 2: Obtaining nerve recovery data corresponding to the surgical position and importing it into the nerve tissue recovery assessment strategy to conduct nerve tissue recovery assessment;

[0009] Step 3: Obtain recovery data of the controlled limb corresponding to the nerve at the surgical position and import it into the surgical nerve control recovery evaluation strategy to perform surgical nerve control recovery evaluation;

[0010] Step 4: Obtain the obtained nerve tissue recovery assessment results and surgical nerve control recovery assessment results to evaluate the surgical recovery effect;

[0011] Step 5: Issue an abnormal recovery warning based on the obtained surgical recovery effect evaluation results.

[0012] As a preferred technical solution for a method of analyzing clinical neurosurgery data, the specific content of obtaining the recovery data of the nerves at the surgical site and the recovery data of the controlled limbs corresponding to the nerves at the surgical site for a set period after the surgery is as follows:

[0013] S11, acquiring image data of the nerve tissue corresponding to the surgical position before the operation, image data of the nerve tissue corresponding to the surgical position after the operation, and image data of the nerve tissue corresponding to the surgical position during the current detection, and storing them in a first storage component;

[0014] S12. Obtain the motion data of the controlled limbs corresponding to the surgical position nerves after the operation and the motion data of the controlled limbs corresponding to the surgical position nerves during this detection, and store them in the second storage component. The motion data of the controlled limbs corresponding to the surgical position nerves here are the three-dimensional position data of the motion of the controlled limbs corresponding to the surgical position nerves relative to the standard motion.

[0015] As a preferred technical solution for a method of analyzing clinical neurosurgery data, the method of obtaining nerve recovery data corresponding to the surgical position and importing it into a nerve tissue recovery evaluation strategy for nerve tissue recovery evaluation includes the following specific steps:

[0016] S21, obtaining image data of the nerve tissue corresponding to the surgical position before the operation and image data of the nerve tissue corresponding to the surgical position after the operation, and importing the obtained image data of the nerve tissue corresponding to the surgical position before the operation and image data of the nerve tissue corresponding to the surgical position after the operation into a nerve recovery difficulty calculation formula to calculate the nerve recovery difficulty, wherein the nerve recovery difficulty calculation formula is: , where x is the average distance between the pixels of the image data of the nerve tissue at the surgical position before the operation, xc is the standard distance of the pixels, n is the number of pixels of the image data of the nerve tissue at the surgical position before the operation, Ti is the pixel value of the i-th pixel of the image data of the nerve tissue at the corresponding surgical position after the operation, and Tim is the pixel value of the i-th pixel of the image data of the nerve tissue at the corresponding surgical position before the operation;

[0017] S22, importing the image data of the nerve tissue corresponding to the surgical position after the operation and the image data of the nerve tissue corresponding to the surgical position during the current detection into a nerve tissue recovery value calculation formula to calculate the nerve tissue recovery value, wherein the nerve tissue recovery value calculation formula is: , where Tik is the pixel value of the i-th pixel point of the image data of the nerve tissue corresponding to the surgical position during this detection;

[0018] S23, obtaining the calculated nerve recovery difficulty and nerve tissue recovery value, and substituting them into the nerve tissue recovery evaluation value calculation formula to calculate the nerve tissue recovery evaluation value, wherein the nerve tissue recovery evaluation value calculation formula is: ,Since the greater the recovery difficulty is and the greater the recovery value is, the better the recovery effect evaluation is, the recovery effect evaluation is proportional to the recovery difficulty and also proportional to the recovery value.

[0019] This step is used to conduct a comprehensive recovery analysis of the recovery status and difficulty of the nerve tissue damaged by the surgery.

[0020] As a preferred technical solution for a method of analyzing clinical surgical data in neurosurgery, the recovery data of the controlled limb corresponding to the nerve at the surgical position is obtained and imported into a surgical nerve control recovery evaluation strategy for surgical nerve control recovery evaluation, which includes the following specific contents:

[0021] The motion data of the controlled limbs corresponding to the nerves at the surgical position after the operation and the motion data of the controlled limbs corresponding to the nerves at the surgical position during this test are obtained, and the motion data of the controlled limbs corresponding to the nerves at the surgical position after the operation and the motion data of the controlled limbs corresponding to the nerves at the surgical position during this test are imported into the nerve control recovery evaluation value calculation formula to calculate the nerve control recovery evaluation value, wherein the nerve control recovery evaluation value calculation formula is: , where T is the limb training movement time, kt is the distance between the position of the controlled limb at the time t corresponding to the nerve at the surgical position of the limb training during this test and the standard position, ktm is the distance between the position of the controlled limb at the time t corresponding to the nerve at the surgical position of the limb training after surgery and the standard position, and dt is the time integral. In this step, the neural control recovery effect is evaluated by controlling the jitter displacement and cognitive displacement during limb movement.

[0022] As a preferred technical solution for a neurosurgery clinical operation data analysis method, the obtained nerve tissue recovery evaluation results and surgical nerve control recovery evaluation results are used to evaluate the surgical recovery effect, including the following specific contents:

[0023] Obtain the calculated nerve tissue recovery assessment value and nerve control recovery assessment value and substitute them into the nerve recovery assessment value calculation formula to calculate the nerve recovery assessment value, wherein the nerve recovery assessment value calculation formula is: ,in, is the neural control recovery ratio.

[0024] As a preferred technical solution for a neurosurgery clinical surgery data analysis method, the abnormal recovery warning according to the obtained surgery recovery effect evaluation results includes the following specific contents:

[0025] The calculated neural recovery assessment value is compared with the set neural recovery assessment threshold. If the obtained neural recovery assessment value is greater than or equal to the set neural recovery assessment threshold, it means that the patient has recovered normally after surgery and no medical intervention or repair is required. If the obtained neural recovery assessment value is less than the set neural recovery assessment threshold, it means that the patient has recovered abnormally after surgery and an abnormal recovery warning is issued and medical intervention is required.

[0026] In a second aspect, the present invention provides a neurosurgery clinical operation data analysis system, which is implemented based on the above-mentioned neurosurgery clinical operation data analysis method, and specifically includes a data acquisition module, a nerve tissue recovery evaluation module, a nerve control recovery evaluation module, a surgery recovery effect evaluation module, a recovery abnormality warning module and a control module;

[0027] Wherein, the data acquisition module is used to acquire the recovery data of the nerves at the surgical position and the recovery data of the controlled limbs corresponding to the nerves at the surgical position in a set period after the surgery;

[0028] The neural tissue recovery assessment module is used to obtain the neural recovery data corresponding to the surgical position and import it into the neural tissue recovery assessment strategy to perform neural tissue recovery assessment;

[0029] The nerve control recovery assessment module is used to obtain the recovery data of the controlled limbs corresponding to the nerves at the surgical position and import it into the surgical nerve control recovery assessment strategy to perform surgical nerve control recovery assessment;

[0030] The surgical recovery effect evaluation module is used to obtain the obtained nerve tissue recovery evaluation results and surgical nerve control recovery evaluation results to perform surgical recovery effect evaluation;

[0031] The abnormal recovery warning module is used to issue an abnormal recovery warning according to the acquired surgical recovery effect evaluation result;

[0032] The control module is used for controlling the operation of the data acquisition module, the nerve tissue recovery evaluation module, the nerve control recovery evaluation module, the surgery recovery effect evaluation module and the recovery abnormality early warning module.

[0033] In a third aspect, the present invention provides an electronic device, comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0034] The processor executes the above-mentioned neurosurgery clinical operation data analysis method by calling the computer program stored in the memory.

[0035] In a fourth aspect, the present invention provides a computer-readable storage medium storing instructions, which, when executed on a computer, enable the computer to execute a neurosurgery clinical operation data analysis method as described above.

[0036] Compared with the prior art, the beneficial effects of this application are:

[0037] The present application obtains the nerve recovery data of the surgical position and the recovery data of the controlled limb corresponding to the nerve at the surgical position in a set period after the operation, obtains the corresponding nerve recovery data of the surgical position and imports it into the nerve tissue recovery evaluation strategy to perform the nerve tissue recovery evaluation, obtains the recovery data of the controlled limb corresponding to the surgical position nerve and imports it into the surgical nerve control recovery evaluation strategy to perform the surgical nerve control recovery evaluation, obtains the obtained nerve tissue recovery evaluation results and the surgical nerve control recovery evaluation results to perform the surgical recovery effect evaluation, performs the recovery abnormality warning according to the obtained surgical recovery effect evaluation results, accurately analyzes the nerve tissue recovery effect in the post-operative recovery process through the nerve tissue recovery image, and at the same time, comprehensively analyzes the nerve control recovery effect of the surgical position through the difference in limb training positions, and then accurately evaluates the surgical recovery effect by comprehensively combining the nerve tissue recovery effect and the nerve control recovery effect, thereby improving the evaluation efficiency and accuracy of the surgical recovery effect;

[0038] In the process of evaluating the effect of neural tissue recovery, this application analyzes the difficulty of tissue recovery by removing tissue aggregation and removal amount for different surgical scenarios, and then conducts a comprehensive neural tissue recovery evaluation based on the neural tissue recovery situation, thereby further improving the efficiency and accuracy of the recovery effect evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a schematic diagram of the overall process of a neurosurgery clinical operation data analysis method of the present invention;

[0040] Figure 2 This is a flowchart of step three of a method for analyzing clinical neurosurgery data of the present invention;

[0041] Figure 3 It is a schematic diagram of the overall framework of a neurosurgery clinical operation data analysis system of the present invention;

[0042] Figure 4 This is a schematic diagram of brain surgery recovery corresponding to the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present application and its application or use.

[0044] Example 1

[0045] The application scenarios of this embodiment are: Figure 4 As shown, Figure 4 For brain surgery recovery images at two different periods, the image acquisition terminal acquires the nerve recovery data of the surgical position at a set period after the surgery, and simultaneously acquires the recovery data of the controlled limbs corresponding to the nerves at the surgical position during training, and transmits the acquired data to the processing terminal, which performs a nerve tissue recovery evaluation result and a surgical nerve control recovery evaluation result to evaluate the surgical recovery effect, and obtains a surgical recovery effect evaluation result;

[0046] In order to solve the technical problems raised in the background technology, the present invention provides a preferred embodiment: Figure 1-Figure 2 As shown, a method for analyzing clinical neurosurgery data comprises the following specific steps:

[0047] Step 1: Acquire recovery data of the nerves at the surgical site and recovery data of the controlled limbs corresponding to the nerves at the surgical site for a set period after the surgery;

[0048] In one specific embodiment, the specific contents of obtaining the recovery data of the nerves at the surgical position and the recovery data of the controlled limbs corresponding to the nerves at the surgical position for a set period after the surgery are as follows:

[0049] S11, obtaining image data of the nerve tissue corresponding to the surgical position before the operation, image data of the nerve tissue corresponding to the surgical position after the operation, and image data of the nerve tissue corresponding to the surgical position during the current detection, and storing them in the first storage component, wherein the image data of the nerve tissue can be obtained by a variety of technologies, and the following are several commonly used brain imaging technologies:

[0050] Functional Magnetic Resonance Imaging (fMRI): fMRI is a non-invasive imaging technique that indirectly measures neural activity by detecting changes in blood flow in the brain. It can be used to observe the functional activity of the brain under specific tasks or stimuli and generate detailed brain images;

[0051] Magnetic resonance imaging (MRI): MRI is an imaging technique based on magnetic fields and radiofrequency pulses that can provide detailed structural images of the brain. By adjusting the parameters of the magnetic field and radiofrequency pulses, MRI can produce images of varying contrast, highlighting different tissues and structures in the brain;

[0052] Computed tomography (CT): CT is an X-ray imaging technique that uses a rotating X-ray source and detector to scan around the patient's head to obtain structural images of the brain.

[0053] S12, obtaining the motion data of the limbs controlled by the nerves at the surgical position after the operation and the motion data of the limbs controlled by the nerves at the surgical position during the current detection, wherein the motion data of the limbs controlled by the nerves at the surgical position is the three-dimensional position data of the motion of the limbs controlled by the nerves at the surgical position relative to the standard motion, for example, the motion area corresponding to the leg of the left brain controls the motion of the right leg, and storing the data in the second storage component;

[0054] Step 2: Obtaining nerve recovery data corresponding to the surgical position and importing it into the nerve tissue recovery assessment strategy to conduct nerve tissue recovery assessment;

[0055] In one specific embodiment, obtaining the nerve recovery data corresponding to the surgical position and importing it into the nerve tissue recovery assessment strategy to perform nerve tissue recovery assessment includes the following specific steps:

[0056] S21, obtaining image data of the nerve tissue corresponding to the surgical position before the operation and image data of the nerve tissue corresponding to the surgical position after the operation, and importing the obtained image data of the nerve tissue corresponding to the surgical position before the operation and image data of the nerve tissue corresponding to the surgical position after the operation into a nerve recovery difficulty calculation formula to calculate the nerve recovery difficulty, wherein the nerve recovery difficulty calculation formula is: , where x is the average distance between the pixels of the image data of the neural tissue at the surgical position before the operation, xc is the standard distance of the pixels, n is the number of pixels of the image data of the neural tissue at the surgical position before the operation, Ti is the pixel value of the i-th pixel of the image data of the neural tissue at the corresponding surgical position after the operation, and Tim is the pixel value of the i-th pixel of the image data of the neural tissue at the corresponding surgical position before the operation. It should be noted that in the process of nerve recovery after brain tissue surgery, for the same tissue, the more it is removed, the more difficult it is to recover, and x is the average distance between the pixels of the image data of the neural tissue at the surgical position before the operation, that is, the aggregation of the removed tissue. The more aggregated the removed tissue is, the more difficult it is to recover, and Ti is the pixel value of the i-th pixel of the image data of the neural tissue at the corresponding surgical position after the operation, and Tim is the pixel value of the i-th pixel of the image data of the neural tissue at the corresponding surgical position before the operation. Ti-Tim is used to distinguish whether the tissue at the corresponding pixel is removed and how much is removed;

[0057] S22, importing the image data of the nerve tissue corresponding to the surgical position after the operation and the image data of the nerve tissue corresponding to the surgical position during the current detection into a nerve tissue recovery value calculation formula to calculate the nerve tissue recovery value, wherein the nerve tissue recovery value calculation formula is: , where Tik is the pixel value of the i-th pixel point of the image data of the nerve tissue corresponding to the surgical position during this detection;

[0058] S23, obtaining the calculated nerve recovery difficulty and nerve tissue recovery value, and substituting them into the nerve tissue recovery evaluation value calculation formula to calculate the nerve tissue recovery evaluation value, wherein the nerve tissue recovery evaluation value calculation formula is: ,Since the greater the recovery difficulty is and the greater the recovery value is, the better the recovery effect evaluation is, the recovery effect evaluation is proportional to the recovery difficulty and the recovery value;

[0059] Step 3: Obtain recovery data of the controlled limb corresponding to the nerve at the surgical position and import it into the surgical nerve control recovery evaluation strategy to perform surgical nerve control recovery evaluation;

[0060] In one specific embodiment, obtaining recovery data of the controlled limb corresponding to the nerve at the surgical position and importing it into the surgical nerve control recovery evaluation strategy for surgical nerve control recovery evaluation includes the following specific contents:

[0061] The motion data of the controlled limbs corresponding to the nerves at the surgical position after the operation and the motion data of the controlled limbs corresponding to the nerves at the surgical position during this test are obtained, and the motion data of the controlled limbs corresponding to the nerves at the surgical position after the operation and the motion data of the controlled limbs corresponding to the nerves at the surgical position during this test are imported into the nerve control recovery evaluation value calculation formula to calculate the nerve control recovery evaluation value, wherein the nerve control recovery evaluation value calculation formula is: , where T is the limb training movement time, kt is the distance between the position of the controlled limb at the time t of the nerve corresponding to the surgical position of the limb training during this test and the standard position, ktm is the distance between the position of the controlled limb at the time t of the surgical position of the limb training after surgery and the standard position, and dt is the time integral. In this step, the effect of neural control recovery is evaluated by controlling the jitter displacement and cognitive displacement during limb movement;

[0062] Step 4: Obtain the obtained nerve tissue recovery assessment results and surgical nerve control recovery assessment results to evaluate the surgical recovery effect;

[0063] In one specific embodiment, obtaining the obtained nerve tissue recovery assessment results and surgical nerve control recovery assessment results to evaluate the surgical recovery effect includes the following specific contents:

[0064] Obtain the calculated nerve tissue recovery assessment value and nerve control recovery assessment value and substitute them into the nerve recovery assessment value calculation formula to calculate the nerve recovery assessment value, wherein the nerve recovery assessment value calculation formula is: ,in, is the neural control recovery ratio;

[0065] Step 5: Providing an abnormal recovery warning based on the obtained surgical recovery effect evaluation results;

[0066] In one specific embodiment, the abnormal recovery warning according to the obtained surgical recovery effect evaluation result includes the following specific contents:

[0067] The calculated neural recovery assessment value is compared with the set neural recovery assessment threshold. If the obtained neural recovery assessment value is greater than or equal to the set neural recovery assessment threshold, it means that the patient has recovered normally after surgery and no medical intervention or repair is required. If the obtained neural recovery assessment value is less than the set neural recovery assessment threshold, it means that the patient has recovered abnormally after surgery and an abnormal recovery warning is issued and medical intervention is required.

[0068] It should be noted that in this embodiment, the method for determining the value of the neural control recovery ratio coefficient and the neural recovery evaluation threshold is preferably as follows: 500 groups of neural recovery data of the surgical position and the recovery data of the controlled limbs corresponding to the neural at the surgical position for a set period after surgery without medical intervention recovery are obtained, and the data are substituted into the neural recovery evaluation value calculation formula to calculate the neural recovery evaluation value, and the judgment on whether the patient has recovered after these 500 groups of surgical recovery periods is obtained, and the neural recovery evaluation values ​​and the judgment on whether the patient has recovered after the surgical recovery period are imported into the fitting software, and the values ​​of the neural control recovery ratio coefficient and the neural recovery evaluation threshold that meet the maximum judgment accuracy are output.

[0069] The advantages of this embodiment over the prior art are as follows: obtaining the nerve recovery data of the surgical position and the recovery data of the controlled limbs corresponding to the nerves at the surgical position in a set period after the operation, obtaining the corresponding nerve recovery data at the surgical position and importing them into the nerve tissue recovery assessment strategy to perform nerve tissue recovery assessment, obtaining the recovery data of the controlled limbs corresponding to the nerves at the surgical position and importing them into the surgical nerve control recovery assessment strategy to perform surgical nerve control recovery assessment, obtaining the obtained nerve tissue recovery assessment results and the surgical nerve control recovery assessment results to perform surgical recovery effect assessment, performing recovery abnormality warning according to the obtained surgical recovery effect assessment results, accurately analyzing the nerve tissue recovery effect in the recovery process after the operation through the nerve tissue recovery image, and comprehensively analyzing the nerve control recovery effect of the surgical position through the difference in limb training positions, and then accurately evaluating the surgical recovery effect by comprehensively analyzing the nerve tissue recovery effect and the nerve control recovery effect, thereby improving the evaluation efficiency and accuracy of the surgical recovery effect, and in the process of evaluating the nerve tissue recovery effect, analyzing the recovery difficulty of the tissue by removing the aggregation and removal amount of the tissue for different surgical scenarios, and then comprehensively evaluating the nerve tissue recovery by comprehensively analyzing the nerve tissue recovery situation, thereby further improving the evaluation efficiency and accuracy of the recovery effect.

[0070] Example 2

[0071] like Figure 3 As shown, a neurosurgery clinical operation data analysis system is implemented based on the above-mentioned neurosurgery clinical operation data analysis method, and specifically includes a data acquisition module, a neural tissue recovery evaluation module, a neural control recovery evaluation module, a surgery recovery effect evaluation module, a recovery abnormality warning module and a control module, wherein the data acquisition module is used to obtain the nerve recovery data of the surgical position and the recovery data of the controlled limbs corresponding to the surgical position nerves in a set period after the operation, the neural tissue recovery evaluation module is used to obtain the corresponding surgical position nerve recovery data and import it into the neural tissue recovery evaluation strategy to perform neural tissue recovery evaluation, the neural control recovery evaluation module is used to obtain the recovery data of the controlled limbs corresponding to the surgical position nerves and import it into the surgical nerve control recovery evaluation strategy to perform surgical nerve control recovery evaluation, the surgical recovery effect evaluation module is used to obtain the obtained neural tissue recovery evaluation results and the surgical nerve control recovery evaluation results to perform surgical recovery effect evaluation, the recovery abnormality warning module is used to perform recovery abnormality warning according to the obtained surgical recovery effect evaluation results, and the control module is used to control the operation of the data acquisition module, the neural tissue recovery evaluation module, the neural control recovery evaluation module, the surgery recovery effect evaluation module and the recovery abnormality warning module.

[0072] Example 3

[0073] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0074] The processor executes the above-mentioned neurosurgery clinical operation data analysis method by calling the computer program stored in the memory.

[0075] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors and one or more memories, wherein the memory stores at least one computer program, and the computer program is loaded and executed by the processor to implement a neurosurgery clinical operation data analysis method provided by the above method embodiment. The electronic device may also include other components for realizing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data. This embodiment will not be described in detail here.

[0076] Example 4

[0077] This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon;

[0078] When the computer program runs on a computer device, the computer device executes the above-mentioned neurosurgery clinical operation data analysis method.

[0079] For example, the computer readable storage medium can be a read-only memory, a random access memory, a read-only CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0080] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

Claims

1. A method for analyzing clinical neurosurgery data, characterized in that: It includes the following specific steps: Step 1: Acquire recovery data of the nerve at the surgical position and recovery data of the controlled limb corresponding to the nerve at the surgical position for a set period after the surgery; Step 2: Obtaining nerve recovery data corresponding to the surgical position and importing it into the nerve tissue recovery assessment strategy to conduct nerve tissue recovery assessment; Step 3: Obtain recovery data of the controlled limb corresponding to the nerve at the surgical position and import it into the surgical nerve control recovery evaluation strategy to perform surgical nerve control recovery evaluation; Step 4: Obtain the obtained nerve tissue recovery assessment results and surgical nerve control recovery assessment results to evaluate the surgical recovery effect; Step 5: Providing an abnormal recovery warning based on the obtained surgical recovery effect evaluation results; The step of obtaining the nerve recovery data corresponding to the surgical position and importing it into the nerve tissue recovery assessment strategy to perform nerve tissue recovery assessment includes the following specific steps: S21, obtaining image data of the nerve tissue corresponding to the surgical position before the operation and image data of the nerve tissue corresponding to the surgical position after the operation, and importing the obtained image data of the nerve tissue corresponding to the surgical position before the operation and image data of the nerve tissue corresponding to the surgical position after the operation into a nerve recovery difficulty calculation formula to calculate the nerve recovery difficulty, wherein the nerve recovery difficulty calculation formula is: , where x is the average distance between the pixels of the image data of the nerve tissue at the surgical position before the operation, xc is the standard distance of the pixels, n is the number of pixels of the image data of the nerve tissue at the surgical position before the operation, Ti is the pixel value of the i-th pixel of the image data of the nerve tissue at the corresponding surgical position after the operation, and Tim is the pixel value of the i-th pixel of the image data of the nerve tissue at the corresponding surgical position before the operation; S22, importing the image data of the nerve tissue corresponding to the surgical position after the operation and the image data of the nerve tissue corresponding to the surgical position during the current detection into a nerve tissue recovery value calculation formula to calculate the nerve tissue recovery value, wherein the nerve tissue recovery value calculation formula is: , where Tik is the pixel value of the i-th pixel point of the image data of the nerve tissue corresponding to the surgical position during this detection; S23, obtaining the calculated nerve recovery difficulty and nerve tissue recovery value, and substituting them into the nerve tissue recovery evaluation value calculation formula to calculate the nerve tissue recovery evaluation value, wherein the nerve tissue recovery evaluation value calculation formula is: .

2. A neurosurgery clinical operation data analysis method as claimed in claim 1, characterized in that: The specific contents of obtaining the recovery data of the nerves at the surgical position and the recovery data of the controlled limbs corresponding to the nerves at the surgical position in a set period after the surgery are as follows: S11, acquiring image data of the nerve tissue corresponding to the surgical position before the operation, image data of the nerve tissue corresponding to the surgical position after the operation, and image data of the nerve tissue corresponding to the surgical position during the current detection, and storing them in a first storage component; S12, obtaining the movement data of the controlled limbs corresponding to the nerves at the surgical position after the operation and the movement data of the controlled limbs corresponding to the nerves at the surgical position during this detection, and storing them in the second storage component.

3. A neurosurgery clinical operation data analysis method as claimed in claim 1, characterized in that: The acquisition of recovery data of the controlled limb corresponding to the nerve at the surgical position and importing it into the surgical nerve control recovery evaluation strategy for surgical nerve control recovery evaluation includes the following specific contents: The motion data of the controlled limbs corresponding to the nerves at the surgical position after the operation and the motion data of the controlled limbs corresponding to the nerves at the surgical position during this test are obtained, and the motion data of the controlled limbs corresponding to the nerves at the surgical position after the operation and the motion data of the controlled limbs corresponding to the nerves at the surgical position during this test are imported into the nerve control recovery evaluation value calculation formula to calculate the nerve control recovery evaluation value, wherein the nerve control recovery evaluation value calculation formula is: , where T is the limb training movement time, kt is the distance between the position of the controlled limb at time t corresponding to the nerve at the surgical position of the limb training during this test and the standard position, ktm is the distance between the position of the controlled limb at time t corresponding to the nerve at the surgical position of the limb training after surgery and the standard position, and dt is the time integral.

4. A neurosurgery clinical operation data analysis method as claimed in claim 3, characterized in that: The obtained nerve tissue recovery assessment results and surgical nerve control recovery assessment results for surgical recovery effect assessment include the following specific contents: Obtain the calculated nerve tissue recovery assessment value and nerve control recovery assessment value and substitute them into the nerve recovery assessment value calculation formula to calculate the nerve recovery assessment value, wherein the nerve recovery assessment value calculation formula is: ,in, is the neural control recovery ratio.

5. A neurosurgery clinical operation data analysis method as claimed in claim 4, characterized in that: The abnormal recovery warning according to the obtained surgical recovery effect evaluation result includes the following specific contents: The calculated neural recovery assessment value is compared with the set neural recovery assessment threshold. If the obtained neural recovery assessment value is greater than or equal to the set neural recovery assessment threshold, it means that the patient has recovered normally after surgery and no medical intervention or repair is required. If the obtained neural recovery assessment value is less than the set neural recovery assessment threshold, it means that the patient has recovered abnormally after surgery and an abnormal recovery warning is issued and medical intervention is required.

6. A neurosurgery clinical operation data analysis system, which is implemented based on the neurosurgery clinical operation data analysis method according to any one of claims 1 to 5, characterized in that: It specifically includes a data acquisition module, a nerve tissue recovery assessment module, a nerve control recovery assessment module, a surgery recovery effect assessment module, a recovery abnormality warning module and a control module; Wherein, the data acquisition module is used to acquire the recovery data of the nerves at the surgical position and the recovery data of the controlled limbs corresponding to the nerves at the surgical position in a set period after the surgery; The neural tissue recovery assessment module is used to obtain the neural recovery data corresponding to the surgical position and import it into the neural tissue recovery assessment strategy to perform neural tissue recovery assessment; The nerve control recovery assessment module is used to obtain the recovery data of the controlled limbs corresponding to the nerves at the surgical position and import it into the surgical nerve control recovery assessment strategy to perform surgical nerve control recovery assessment; The surgical recovery effect evaluation module is used to obtain the obtained nerve tissue recovery evaluation results and surgical nerve control recovery evaluation results to perform surgical recovery effect evaluation; The abnormal recovery warning module is used to issue an abnormal recovery warning according to the acquired surgical recovery effect evaluation result; The control module is used for controlling the operation of the data acquisition module, the nerve tissue recovery evaluation module, the nerve control recovery evaluation module, the surgery recovery effect evaluation module and the recovery abnormality early warning module.

7. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes a neurosurgery clinical operation data analysis method as described in any one of claims 1-5 by calling a computer program stored in the memory.

8. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer is caused to execute a neurosurgery clinical operation data analysis method as described in any one of claims 1 to 5.

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