KR101007964B1 - Electrodiagnosis support apparatus and method for diagnosing neural injury using the same - Google Patents

Abstract

The electrodiagnostic support device of the present invention loads an input file in which the structure of the nerves and muscles of the human body is loaded, displays the structure of the nerves and muscles, and receives a probe EMG (Electromyography) test result for the subject; A diagnostic result storage unit for updating the contents of the input file based on the input probe EMG test result and storing the input file in a matrix form, and diagnosing whether a nerve related to the muscle to be examined is damaged from matrix data stored in the diagnostic result storage unit; And a damage location determination unit that determines a damage location of the nerve to be diagnosed as damaged as a result of the diagnosis.

CDSS, ESS, electrodiagnostic support device, nerve, muscle, EMG test

Description

ELECTRODIAGNOSIS SUPPORT APPARATUS AND METHOD FOR DIAGNOSING NEURAL INJURY USING THE SAME}

The present invention relates to a clinical decision support system, and more particularly, to an electrodiagnostic support apparatus based on analysis of neural structure and a method for diagnosing nerve damage using the same.

Research on the Clinical Decision Support System (CDSS) has been ongoing for a long time. The purpose of the system is to enable doctors to make the right diagnosis among a number of symptoms and to suggest the right treatment for it. The method of developing this system generally follows the way of creating a model based on the knowledge base. By inputting medical symptoms, experimental results, etc., an information system is established for each domain. Based on this information system, the clinical decision support system suggests diagnosis or treatment as a result of input from a user, mainly a doctor.

 Research on these systems has continued across a variety of domains, from initial MYCIN to QMR, Protege, most recently to DSS for diagnosing lower back pain, and to glaucoma detection systems. However, the application of the system to the analysis of neural structure and applied to EMG (Electromyography) test is not known.

The EMG test is primarily for patients with diseases such as cervical / lumbar radiculopathy, plexopathy, and peripheral neuropathy / peripheral polyneuropathy. The EMG test can be divided into probe EMG (Needle EMG) and Nerve Conduction Study (NCS). Nerve conduction test is a method of diagnosing damage of peripheral nerves by stimulating motor and sensory nerves and determining the abnormality of nerves using conduction velocity and potential difference of action potentials. Probe EMG is a method of determining the abnormality of muscles by observing the abnormal spontaneous potential of the muscle and the action potential of contraction through the needle inserted into the muscle. Way. These two tests are not actually measured on different patients, but both methods are used to determine the muscles and nerves and their location of all patients visiting the rehabilitation department. The doctor will analyze the two results to determine whether there is an abnormality.

Although simple, the two tests are very painful for the patient, especially the probe EMG test, which is much more painful than nerve conduction tests. Probe EMG testing involves the use of needles to penetrate the skin, penetrate into the muscle, and detect the action potential of the muscle. In addition to the needle passing through the skin, a sharp needle passes through the muscle membrane, causing the patient to feel more pain. However, what makes the patient more painful is that such tests are never done once or twice. In order for doctors to make an accurate diagnosis, basically five to six meter readings are essential. In addition, the number of meter readings is actually much higher due to the complex neural structure. In addition, the complex neural structures inside humans not only increase the number of meter readings, but also make doctors who are relatively new to electromyography, such as training and medical doctors, increase the possibility of misdiagnosis. It is very important to solve such problems because the wrong diagnosis not only increases the pain of the patient due to the additional meter reading, but also can cause a big problem in determining the treatment method of the patient later.

Some embodiments of the present invention aim to provide an electrodiagnostic support apparatus capable of minimizing the number of probes in a probe EMG test.

In addition, an object of the present invention is to provide a method for diagnosing nerve damage by finding an optimal nerve injury site and informing a user using the electrodiagnostic support device.

As a technical means for achieving the above-described technical problem, the electrical diagnostic support device according to the first aspect of the present invention loads an input file storing the structure of the nerves and muscles of the human body to display the structure of the nerves and muscles, subject A user interface for receiving a probe EMG (Electromyography) test result, a diagnostic result storage unit for updating the contents of the input file based on the input probe EMG test result and storing the result in a matrix form, and the diagnostic result storage unit And a damage diagnosis unit for diagnosing whether the nerve associated with the muscle to be irradiated is damaged from the matrix data stored therein and a damage position determination unit that determines a damage location of the nerve that is diagnosed as damaged as a result of the diagnosis.

In addition, the method for diagnosing nerve damage according to the second aspect of the present invention includes the steps of updating the contents of an input file including information on muscles and nerves and storing them in a matrix form according to a probe EMG test result of the subject; Generating a representative representative vector obtained by summing values for the paths of the nerves connected to the normal muscles for each path in the stored matrix and an abnormal representative vector summing the values for the paths of the nerves connected to the abnormal muscles for each path; And generating a diagnostic vector obtained by adding the normal representative vector and the abnormal representative vector for each path and determining whether the nerve is damaged according to the value.

In addition, the application device according to the third aspect of the present invention diagnoses nerve damage using the nerve damage diagnosis method according to the present invention.

Further, the computer-readable recording medium according to the fourth aspect of the present invention performs each step of the nerve damage diagnosis method according to the present invention.

According to the above-described problem solving means of the present invention, it is possible to perform the diagnosis of nerve damage and the diagnosis of nerve damage based on the probe EMG test results. In addition, flexible diagnosis of changes in neural structure was enabled, as well as rapid diagnosis of nerve damage sites. In particular, it is possible to provide efficient guidelines for minimizing the number of probes in the probe EMG test. The availability of minimal meter reading can have the effect of alleviating the pain associated with meter reading in patients who need to take a real probe EMG test.

The system can also be widely used to reduce misunderstandings in medical education, training and majors.

DETAILED DESCRIPTION Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art may easily implement the present invention. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In the drawings, parts irrelevant to the description are omitted in order to clearly describe the present invention, and like reference numerals designate like parts throughout the specification.

Throughout the specification, when a part is "connected" to another part, this includes not only "directly connected" but also "electrically connected" with another element in between. . In addition, when a part is said to "include" a certain component, which means that it may further include other components, except to exclude other components unless otherwise stated.

1 is a view showing the concept of using an electrical diagnostic support device for diagnosing the upper extremity nerve injury site according to an embodiment of the present invention.

First, the probe EMG test apparatus 110 is a tool for a user to insert a probe into a muscle of a subject to be diagnosed to determine whether the muscle and nerve are abnormal or located. At this time, the user is mainly a doctor, and the subject is mainly a patient. Diagnosing the injured muscles of the patient through the probe EMG test device 110, the diagnosis result is transmitted to the electrical diagnostic support device 120 by the user. The user may check the test result through the probe EMG test apparatus 110 and input the corresponding result through the user interface 122 of the EMG support system 120. Alternatively, the probe EMG test apparatus 110 and the electrical diagnosis support apparatus 120 may be connected to directly transmit related information.

The electrodiagnosis support system (ESS) 120 includes a user interface 121, an input file manager 123, a diagnosis result storage unit 125, a damage diagnosis unit 127, and a damage location determination unit 129. It includes.

For reference, the components shown in FIG. 1 according to an embodiment of the present invention mean software components or hardware components such as a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC), and perform predetermined roles. .

However, 'components' are not meant to be limited to software or hardware, and each component may be configured to be in an addressable storage medium or may be configured to reproduce one or more processors.

Thus, as an example, a component may include components such as software components, object-oriented software components, class components, and task components, and processes, functions, properties, procedures, and subs. Routines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables.

Components and the functionality provided within those components may be combined into a smaller number of components or further separated into additional components.

The user interface 121 displays the most likely disease name or damage location analyzed based on the probe EMG test results entered by the user. In addition, the probe EMG test results are transferred to the diagnostic result storage unit 125 and stored in a data structure form. In addition, by executing the input file input by the user, and shows the structure of the nerves and muscles. It will be described with reference to the drawings.

2 is a diagram illustrating a user interface included in an apparatus for supporting electric diagnosis according to an exemplary embodiment of the present invention.

The user interface 121 includes a muscle neural structure display unit 210, a probe EMG test result input unit 220, an interface control unit 230, and a finding display unit 240.

The muscle nerve structure display unit 210 displays the muscle nerve structure set by the input file in the form of a two-dimensional graph, so that each muscle nerve can be viewed intuitively. The user can select the particular muscle or nerve displayed and enter the probe EMG test results. That is, when there is no abnormality in the corresponding muscle or nerve as a result of the test using the probe EMG test apparatus 110, the test target muscle or the target displayed on the muscle neural structure display unit 210 is selected and the probe EMG test result input unit 220 is used. You can enter information that is normal.

On the other hand, when the damage position determination unit 129 receives the information about the damage position is enlarged to display the portion. As a result, the probe EMG test can be focused on the site of damage and the results can be conveniently entered.

As described above, the probe EMG test result input unit 220 may select and input whether the test target muscle or nerve is normal or abnormal. The input content as to whether it is normal or abnormal is transmitted to and stored in the diagnosis result storage unit 125.

The interface controller 230 generates a control signal for loading an input file, a control signal for performing a diagnosis of a disease name, a control signal for deleting an input file, a control signal for initializing the displayed contents, respectively, and an input file manager 123, Damage to the diagnosis unit 127, muscle nerve structure display unit 210, probe EMG test result input unit 220, findings display unit 240 and the like.

The finding display unit 240 displays information on the disease name or damage location received through the damage location determination unit 129. Preferably, the first display window 242 displays the disease name or damage location having a high probability of coinciding with the actual damage location, and indicates the disease name or damage location with a relatively low probability of the second display window 244. ) To minimize the possibility of user error.

Referring back to FIG. 1, the input file manager 123 loads the input file input by the user into the user interface 120 according to a control signal. In addition, according to the user's selection, any one of the various input files stored in the electrical diagnostic support device 120 is loaded. It also provides an editing function for input files.

The input file is a file that stores data about each nerve structure or muscle structure. In the form of markup languages, users with relatively low levels of computer knowledge can easily edit. People's neural network structure is generally consistent, but can vary from person to person, so it may be more effective to use different input files for different patients. In addition, according to the medical theory, the system for distinguishing the neural network structure is also changed, and accordingly, the content stored in the input file may be changed.

3 is a diagram illustrating an example of an input file used in the apparatus for assisting electric diagnostics according to an embodiment of the present invention.

As shown is in the form of markup language. The name of each muscle, abbreviation, name of peripheral nerve (peripheral nerve), cord (cord), trunk (trunk) and the like is described, and can be input respectively according to user selection.

Considering that the actual neural structure is clinically slender wire-like structure, the shape is reflected, and the neural structure is easy to recognize accordingly.

4 is a diagram illustrating the brachial nerve structure of the general public to be applied to the present invention.

As can be seen there are several branches from the root to the hand. That is, each nerve passes through a path such as trunk, division, cord, peripheral nerve, and the like. In addition, the peripheral nerves are the axilla, arm, and forearm of the upper limb. A nerve branch is made to each muscle at a segmented area such as the hand. In this way, the actual muscle and neural structure is represented according to various points of view.

In the case of the input file shown in FIG. 3, the most clinically used theories currently [1]. Kendall FP, et al. (2005) Muscles: Testing and Function with Posture and Pain.Baltimore, Williams & Wilkins, 27-30, [2] .Dumitru D, Anthony AA, Machiel Z. (2002) Electrodiagnostic Medicine; 2nd edition.Hanley & Belfus, 713-776, [3] .Webb H, Barnes W. (1953) Peripheral Nerve Injuries Principles of Diagnosis.Philadelphia, WB Saunders, 209-272, [4] .Michael R, Joseph ES (2007) Netter's Concise Neuroanatomy.Philadelphia, Saunders, 310-311.

The input file manager 123 allows the user to modify the input file according to his or her medical opinions and the characteristics of the patient based on the previously produced input file. Accordingly, more specialized medical services can be provided for each individual.

Referring back to FIG. 1, the diagnosis result storage unit 125 stores the diagnosis result according to the probe EMG test in a matrix data structure.

FIG. 5 is a diagram illustrating a data structure stored in a diagnosis result storage unit according to an exemplary embodiment of the present invention.

The input file described above may be formed in the form of a sparse matrix composed of 0's and 1's. The items described in each row represent the motor nerves, and each column represents the path from which the motor nerves pass (peripheral nerve to root). In addition, the items described in Rows clinically represent the epigenetic relationship of the motor nerves, and the columns reflect the order of the path of movement from the peripheral nerves to the root. For example, the Serratus Anterior, which is controlled by the long thoracic nerve, has a lower row number than the Biceps Brachii. This indicates that the anterior muscles are closer to the root than the biceps biceps, and this is true clinically. Latissimus dorsi also originates from the C6, C7 and C8 routes, with the C6 line passing through the upper trunk, the C7 line passing through the middle trunk, and the C8 line passing through the lower trunk. Merged from terrier cords. Thereafter, the Thoracodorsal nerve is constructed to dominate the Latissimus dorsi. All positions along this muscle path are set to 1 and the rest are checked to 0. In this way, the entire matrix forms one giant sparse matrix.

Referring back to FIG. 1, the damage diagnosis unit 127 analyzes whether damage has occurred based on the probe EMG test result stored in the diagnosis result storage unit 123, and transmits the damage to the damage location determination unit 129. do.

An analysis process for damage may be performed whenever a probe EMG test result is newly input through the user interface 121.

6 is a detailed algorithm describing a method of diagnosing damage in an electrodiagnostic support apparatus according to an embodiment of the present invention.

The diagnosis of damage is largely divided into the upper part of the radiculopathy, the middle part of the brachial plexopathy and the lower part of the peripheral neuropathy (pheripheral neuropathy). In other words, it is to diagnose which of the conditions belong.

The input probe EMG test results are configured to diagnose damage using a sparse matrix. First, extract the rows representing the muscles on which the test was performed, and if abnormal findings, change the column (marked with 1) representing the path through which the muscles passed to -1. If normal, the value (1) representing the original path is kept as it is. Next, all normal finding vectors (X) and abnormal finding vectors (Y) are added for each column, and are divided into normal representative vectors (N) and abnormal representative vectors (M).

If the value of the normal representative vector (N) is greater than 0, 1 is input to the diagnostic vector (D). That is, if the normal representative vector (N) is greater than zero, it indicates that the irradiated site is normal regardless of the state of the abnormal representative vector (M). The path through which the nerves that govern the abnormal muscles (damage paths) are candidates for the damage site, and if the nerve paths that govern the normal muscles overlap, the overlapping part is considered to be the normal site.

If the value of the normal representative vector (N) is 0 and the value of the abnormal representative vector (M) is negative, -1 is input to the diagnostic vector (D).

As such, if a result of normal or not is input to the muscle or nerve that is the target of the probe, the damage or not is displayed accordingly.

Referring back to FIG. 1, the damage location determination unit 129 analyzes the damage location based on the probe EMG test result stored in the diagnosis result storage unit 123, and transmits the damage location to the muscle neural structure display unit 210. The principle of diagnosing the location of damage is as follows.

When injury occurs in a specific area of the complex nerve structure that descends from the cervical spinal nerve to the upper limb, muscles dominated by the nerves passing through the damaged area show abnormalities. Clinically, EMG detects muscle electrophysiological abnormalities and divides normal and abnormal muscles and traces the damaged nerve area to determine the damaged area.

The nerves that descend into the muscles of the upper limbs start from each spinal segment and merge and divide to form the brachial plexus and peripheral nerves. The motor nerve that governs a muscle has its own path, which is the basis for tracking damage.

Theoretically, damage can occur at any site of the brachial plexus, but it is possible to determine the site of injury by dividing clinically possible anatomical sites into roots or segments, trunks, and cords. Make sure The path through which the nerves governing the abnormal muscles (damage paths) are candidates for the damage site, and if the nerve paths that overlap the normal muscles overlap, the overlapping areas are excluded. The area with the most overlapping damage pathways is the most likely nerve injury site, and if the number of overlapping paths is the same, the area near the center is likely to be the site of damage.

Peripheral neuropathy can be suspected when abnormalities are found in two or more muscles under the same peripheral nerve, and in most cases muscles from other peripheral nerves are normal. Basically, when the proximal muscle is normal and the distal muscle is abnormal, the nerve damage is between the two muscles. Conversely, if the proximal muscle is abnormal in the same peripheral nerve and the distal muscle is normal, the damaged part of the nerve can be found in the brachial plexus or spinal segment.

Based on this principle, an algorithm for diagnosing the location of damage was constructed.

FIG. 7 is a diagram illustrating a part of an algorithm for a method of diagnosing a damage location in an electrical diagnostic support apparatus according to an embodiment of the present invention.

First, the input values are the normal representative vector (N), the abnormal representative vector (M), and the diagnostic vector (D) calculated through the algorithm of FIG. 6.

When the diagnosis vector D is -1, that is, when the damage is diagnosed corresponding to a negative number, the judgment is made only for a path having a total probe count p of 1 or more.

If the column in which the diagnostic vector (D) is negative is a peripheral nerve region, if the total number of probes is more than the maximum number of probes (max (N + abs (M)), the peripheral nerve region is likely to be a major damage site. And display on the first display window 242. However, if not, it is regarded as a less likely damage site and displayed on the second display window 244. The fact that the number of probes is large, the user concentrates on the inspection. Since it means that it has progressed, it is necessary to determine the damage area in consideration of such a situation.

If the column in which the diagnostic vector D is negative is the root site, the site is basically regarded as the most likely major damage site and displayed on the first display window 242. That is, the determination is made regardless of the maximum number of probes (max (N + abs (M)).

Now with reference to the drawings will be described the overall configuration of the nerve damage diagnosis method of the present invention.

8 is a flowchart illustrating a method of diagnosing nerve injury according to an embodiment of the present invention.

First, a probe EMG test is performed on the subject, primarily patients (step 810).

Next, the test result is input through the user interface of the electrodiagnostic support device, and the input file is updated (step 820).

The contents of the update of the input file and the process of changing the matrix value in the data structure form of the diagnostic result storage unit 125 according to the update are as described above.

Next, a normal representative vector and an abnormal representative vector are generated from the data stored in the diagnosis result storage unit 125 (step 830).

In this case, the normal representative vector is the sum of the paths of the nerves connected to normal muscles for each path, and the abnormal representative vector is the sum of the values of the paths of the nerves connected to the abnormal muscles for each path.

Next, a diagnostic vector obtained by adding the normal representative vector and the abnormal representative vector for each path is generated, and it is determined therefrom whether or not the nerve is damaged (step 840).

Whether each column value in the diagnostic vector is negative or positive is determined as being damaged. Each column corresponds to a neural pathway, so that the name of the damaged pathway, that is, the disease name, can be displayed to the user.

Next, the column value of the diagnostic vector is analyzed to determine the location of the damage (step 850).

The value of each column can be used to determine where the nerve pathways are damaged. For example, if you have abnormalities in two or more muscles that are controlled by the same peripheral nerve, you may suspect peripheral neuropathy. In the case of muscles from other peripheral nerves are normal. Basically, when the proximal muscle is normal and the distal muscle is abnormal, the nerve damage is between the two muscles. Conversely, if the proximal muscle is abnormal in the same peripheral nerve and the distal muscle is normal, the damaged part of the nerve can be found in the brachial plexus or spinal segment.

As described above, the result of the user input may be arranged into a matrix value by performing the probe, and the damage and the location of the damaged portion may be confirmed based on the result.

According to this configuration, it is possible to quickly diagnose the site of nerve damage. In addition, flexible diagnosis of changes in neural structure is enabled, and an efficient guideline can be provided to minimize the number of probes in the probe EMG test.

One embodiment of the present invention can also be implemented in the form of a recording medium containing instructions executable by a computer, such as a program module executed by the computer. Computer readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. In addition, computer readable media may include both computer storage media and communication media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Communication media typically includes computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave, or other transmission mechanism, and includes any information delivery media.

While the methods and systems of the present invention have been described in connection with specific embodiments, some or all of those elements or operations may be implemented using a computer system having a general purpose hardware architecture.

The foregoing description of the present invention is intended for illustration, and it will be understood by those skilled in the art that the present invention may be easily modified in other specific forms without changing the technical spirit or essential features of the present invention. will be. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive. For example, each component described as a single type may be implemented in a distributed manner, and similarly, components described as distributed may be implemented in a combined form.

The scope of the present invention is shown by the following claims rather than the above description, and all changes or modifications derived from the meaning and scope of the claims and their equivalents should be construed as being included in the scope of the present invention. do.

1 is a view showing the concept of using an electrical diagnostic support device for diagnosing the upper extremity nerve injury site according to an embodiment of the present invention.

2 is a diagram illustrating a user interface included in an apparatus for supporting electric diagnosis according to an exemplary embodiment of the present invention.

3 is a diagram illustrating an example of an input file used in the apparatus for assisting electric diagnostics according to an embodiment of the present invention.

4 is a diagram illustrating the brachial nerve structure of the general public to be applied to the present invention.

FIG. 5 is a diagram illustrating a data structure stored in a diagnosis result storage unit according to an exemplary embodiment of the present invention.

6 is a detailed algorithm describing a method of diagnosing damage in an electrodiagnostic support apparatus according to an embodiment of the present invention.

FIG. 7 is a diagram illustrating a part of an algorithm for a method of diagnosing a damage location in an electrical diagnostic support apparatus according to an embodiment of the present invention.

Description of the main parts of the drawing

110: probe EMG test device 120: electrical diagnostic support device

121: user interface 123: input file management unit

125: diagnostic result storage unit 127: damage diagnosis unit

129: damage position determination unit

Claims (17)

A user interface that loads an input file that stores the structure of the nerves and muscles of the human body to display the structure of the nerves and muscles, and receives a probe EMG (Electromyography) test result for the subject; A diagnostic result storage unit for updating the content of the input file based on the input probe EMG test result and storing the content in the form of matrix data; An injury diagnosis unit configured to generate diagnosis data indicating whether the nerve associated with the muscle to be examined is damaged based on a calculation result using the matrix data stored in the diagnosis result storage unit; Damage location determination unit for distinguishing the damage location of the nerve to be diagnosed as damaged according to the diagnostic data generated by the damage diagnosis unit Electrical diagnostic support device comprising a. The method of claim 1, An input file manager to load the input file into the user interface Electrical diagnostic support device further comprising. The method of claim 1, The user interface includes a muscle nerve structure display unit for displaying the muscle and nerve structure set by the input file in a graphic form; A remarks display unit for displaying information on the damage position; Probe EMG test result input for selecting and entering whether the muscle under test is normal or abnormal Electrical diagnostic support device comprising a. The method of claim 3, wherein And the muscle nerve structure display unit enlarges and displays the damaged position according to the information on the damaged position. The method of claim 3, wherein The finding display unit includes a first display window and a second display window for displaying information about the damage location, And a probability that the damage location displayed on the first display window coincides with the actual damage location is greater than the probability that the damage location displayed on the second display window matches the actual damage location. The method of claim 1, The damage diagnosis unit comprises a normal representative vector that adds the values for the paths of nerves connected to normal muscles for each path; Generate an abnormal representative vector by adding the values for the paths of the nerves connected to the abnormal muscles for each path, An electrodiagnostic support device for generating a diagnostic vector indicating whether a nerve is damaged by summing each representative vector for each path. The method of claim 1, Wherein the damage position determination unit in the peripheral nerve (proximal muscle) is normal, distal muscle (distal muscle) is abnormal, the location of the injury site is divided between the muscle of the proximal and distal muscles, When the proximal muscle is abnormal in the peripheral nerve and the distal muscle is normal, the electrical diagnostic support for classifying the location of the injury site into the brachial plexus or the spinal segment Device. In the method of generating nerve damage diagnostic data using an electrical diagnostic support device for diagnosing nerve damage, Updating the contents of an input file including information on muscles and nerves according to the results of the electromagnetism (EMG) test on the subject, and storing them in a matrix form; Generating a normal representative vector obtained by summing values of paths of nerves connected to normal muscles for each path in the stored matrix, and an abnormal representative vector summing values of paths of nerves connected to abnormal muscles for each path; and Generating a diagnostic vector indicating whether the nerve is damaged by adding the normal representative vector and the abnormal representative vector for each path; Neuronal damage diagnostic data generation method comprising a. The method of claim 8, Updating the contents of the input file and storing the contents in a matrix form Setting a value for each path of a nerve associated with the abnormal muscle to -1, respectively; Maintaining an initial value for each path of a nerve associated with the normal muscle Neuronal damage diagnostic data generation method comprising a. The method of claim 8, Generating the diagnostic vector and determining whether the nerve is damaged according to the value Outputting data indicating that the corresponding neural pathway is damaged when the column value of the diagnostic vector is negative Neuronal damage diagnostic data generation method comprising a. The method of claim 8, When the generated diagnostic vector indicates nerve damage, identifying a location where nerve damage occurs Neuronal damage diagnostic data generation method further comprising. The method of claim 11, The step of distinguishing the location of the injury occurs when the nerve region where the column value of the diagnostic vector is negative is the peripheral nerve area, if the total number of probes is more than the maximum number of probes, the location of the damage site peripheral nerve area Step to distinguish with Neuronal damage diagnostic data generation method comprising a. The method of claim 11, The step of distinguishing the location of the injury occurs, if the nerve region of the negative column value of the diagnostic vector is a root (root), the step of dividing the location of the injury site to the peripheral nerve area Neuronal damage diagnostic data generation method comprising a. The method of claim 11, The determining of the location of the injury may include determining the location of the injury between the proximal muscle and the distal muscle when the proximal muscle is normal and the distal muscle is abnormal in the peripheral nerve. Step to distinguish Neuronal damage diagnostic data generation method comprising a. The method of claim 11, The determining of the location of the injury is performed when the proximal muscle is abnormal in the peripheral nerve and the distal muscle is normal, and the damaged part is the brachial plexus or the spinal segment. ) Neuronal damage diagnostic data generation method comprising a. Application device for diagnosing nerve damage using a method according to any one of claims 8 to 15. A computer-readable recording medium having recorded thereon a program for performing the steps according to any one of claims 8 to 15.

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