WO2016021771A1

WO2016021771A1 - Apparatus and method for determining spinal disease

Info

Publication number: WO2016021771A1
Application number: PCT/KR2014/010315
Authority: WO
Inventors: 김근호; 장준수; 이준환
Original assignee: 한국 한의학 연구원
Priority date: 2014-08-07
Filing date: 2014-10-30
Publication date: 2016-02-11
Also published as: CN106793981B; KR101602704B1; KR20160017914A; CN106793981A

Abstract

A spinal muscular condition determining method may comprise the steps of: receiving an input of spinal muscle information determining the degree of muscle tone of the spine with respect to a measurement part of a user; calling a spinal disease determination function corresponding to the measured part; and determining a spinal muscular condition of the user using the spinal muscle information and the called spinal disease determination function.

Description

Spinal disease judgment device and method

The present invention relates to a spinal disease determining apparatus and method, and more particularly, to a device and a method for determining and diagnosing spinal muscle condition using spinal muscle information on a measurement site of a user.

The causes of low back pain, which 80% of the population experiences more than once, are postural abnormalities, degenerative changes, muscle inflammation and contractions, and dual postural abnormalities play a fundamental role. In addition, less than 5% of cases require surgical treatment. Low back pain is particularly important for the rapidly growing elderly population.

Conventional imaging modalities such as X-ray, MRI, CT, etc. diagnose the spinal disorder of the spine in a static state, but these imaging diagnoses show that spinal abnormality occurs in 30-40% of normal people without low back pain. Can be.

In addition, the abnormality is not found in the image diagnosis, but the diagnosis of patients complaining of pain when the function is not properly performed because the dynamic information and the function of the muscles are not considered simultaneously.

Low back pain patients develop pain in the lower back, secondary muscle tension due to pain, etc. As a result, the range of movement is reduced, and accordingly, various activities may be impaired (function dysfunction).

Determination of spinal disease, which is more efficient and more useful for objectively evaluating the patient's condition than measuring subjective assessment of pain and diagnosing organic changes by radiology by measuring muscle tension secondary to back pain. A device is needed.

According to one side, receiving the spinal muscle information for determining the muscle tension of the spine with respect to the measurement site of the user; Calling a spinal disease determination function corresponding to the measurement site; And determining the spinal muscle state of the user using the spinal muscle information and the called spinal disease determination function.

Here, the spinal muscle information may include at least one of motion information and biometric information of the user with respect to a predetermined 3D posture. It is possible to synchronize the operation of each part and the biological signal.

According to an embodiment, the method may further include generating the spinal disease determination function.

More specifically, the generating of the spinal disease determination function may include spinal muscle information for each measurement site of each of a plurality of users, a questionnaire for a preset spine for each of the plurality of users, and a diagnosis result for each of the plurality of users. Receiving at least one of the input information; Calculating muscle tension of each of a plurality of users using the input information; Classifying the plurality of users into normal and abnormal groups for spinal diseases by using the calculated muscle tension of each of the plurality of users; And generating the spinal disease judgment function based on the muscle tension of the normal person group and the muscle tension of the abnormal person group.

The generating of the spinal disease judgment function may include: determining a parameter constituting the spinal disease judgment function based on a correlation between the muscle tension of the normal person group and the muscle tension of the abnormal person group; And generating the spinal disease determination function based on the determined parameter.

The determining of the parameter constituting the spinal disease judgment function may include configuring the spinal disease judgment function using a parameter whose correlation between the muscle tension of the normal person and the muscle tension of the abnormal person is less than a preset threshold. Can be determined as a parameter.

According to an embodiment of the present disclosure, when the user takes the predetermined three-dimensional posture, the motion information may include a range of motion (ROM) that is a moving range of a measurement part.

According to another embodiment, the biometric information may include at least one of a body temperature, a bioimpedance, and a current perception threshold for the user.

Here, the measurement site may be a first measurement site and a second measurement site that are symmetrical with respect to the spine of the user.

According to another aspect, a method of generating a spinal disease determination function for generating a spinal disease determination function for determining a spinal muscle state of a user, comprising: spinal muscle information for each measurement site of a plurality of users, for each of the plurality of users Receiving at least one of a preset questionnaire for the spine and a diagnosis result for each of the plurality of users as input information; Calculating muscle tension of each of a plurality of users using the input information; Classifying the plurality of users into normal and abnormal groups for spinal diseases by using the calculated muscle tension of each of the plurality of users; And generating the spinal disease judgment function based on the muscle tension of the normal person group and the muscle tension of the abnormal person group.

According to an embodiment, the method may further include acquiring the spinal muscle information from each of the plurality of users from the first measurement site and the second measurement site which are symmetrical with respect to the spine.

According to another embodiment, the calculating of the muscle tension may include calculating a difference between a first measurement value obtained from the first measurement part and a second measurement value obtained from the second measurement part. can do.

According to another embodiment, the step of classifying the normal group and abnormal group for the spinal disease, the difference obtained from a first user of the plurality of users is greater than a first threshold value; Or classifying the first user as the abnormal group when the size of the first measurement value or the second measurement value obtained from the first user is greater than a second threshold value among the plurality of users. Can be.

In detail, the generating of the spinal disease judgment function may include: determining a parameter constituting the spinal disease judgment function based on a correlation between the muscle tension of the normal person group and the muscle tension of the abnormal person group; And generating the spinal disease determination function based on the determined parameter.

According to another aspect, the computer-readable recording medium recording a program for executing a method for generating a spinal disease determination function, wherein the method for generating a spinal disease determination function, spinal muscle information for each measurement site of the plurality of users, the Receiving at least one of a questionnaire for a spine preset for each of a plurality of users and a diagnosis result for each of the plurality of users as input information; Classifying the plurality of users into normal and abnormal groups for spinal diseases using the input information; And generating the spinal disease judgment function based on the muscle tone of the normal person group and the muscle tone of the abnormal person group.

According to one side, the input unit for receiving the spinal muscle information for determining the muscle tension of the spine with respect to the user's measurement site; A processor for calling a spinal disease determination function corresponding to the measurement site; And a determining unit configured to determine the spinal muscle state of the user by using the spinal muscle information and the called spinal disease determination function.

Here, the spinal muscle information may include at least one of motion information and biometric information of the user with respect to a predetermined 3D posture.

According to another aspect, a spinal disease determination function generating device for generating a spinal disease determination function for determining the spinal muscle state of the user, the spinal muscle information for each measurement site of a plurality of users, for each of the plurality of users An input unit configured to receive at least one of a preset questionnaire for the spine and a diagnosis result for each of the plurality of users as input information; A calculator configured to calculate muscle tension of each of a plurality of users using the input information; A processor configured to classify the plurality of users into normal and abnormal groups for spinal diseases by using the calculated muscle tension of each of the plurality of users; And a function generator configured to generate the spinal disease judgment function based on the muscle tension of the normal person group and the muscle tension of the abnormal person group.

According to one embodiment, for each of the plurality of users further comprises an information acquisition unit for obtaining the spinal muscle information from the first measurement site and the second measurement site symmetrical with respect to the spine, wherein the muscle tension is, The difference between the first measurement value obtained from the first measurement site and the second measurement value obtained from the second measurement site or the magnitude of the first measurement value and the second measurement value.

According to another embodiment, the processing unit may include: when the difference obtained from a first user of the plurality of users is greater than a first threshold value; Alternatively, when the size of the first measurement value or the second measurement value obtained from the first user among the plurality of users is larger than a second threshold value, the first user may be classified as the abnormal group.

1 is a conceptual diagram of a spinal muscle state determining apparatus according to an embodiment.

Figure 2 is a block diagram showing the configuration of a spinal muscle state determination apparatus according to an embodiment.

3 is a flow chart showing the flow of the method for determining spinal muscle state according to an embodiment.

4 is an exemplary diagram illustrating an operation of a user for determining a spinal muscle state according to an embodiment.

5 is a diagram illustrating a measurement site and a 3D location extraction site for determining a spinal muscle state of a user according to an embodiment.

6 is a block diagram illustrating a configuration of an apparatus for generating spinal disease determination function according to an embodiment.

7 is a flowchart illustrating a method of generating a spinal disease determination function according to an embodiment.

8 is a flowchart illustrating a method of generating a spinal disease determination function of FIG. 7 according to an embodiment.

Hereinafter, some embodiments will be described in detail with reference to the accompanying drawings. However, it is not limited or limited by these embodiments. Like reference numerals in the drawings denote like elements.

The terminology used in the following description has been selected as widely used as possible in the present invention in consideration of the functions in the present invention, but may vary according to the intention or custom of the person skilled in the art, the emergence of new technologies and the like.

In addition, in certain cases, there are terms arbitrarily selected by the applicant for the sake of understanding and / or convenience of description, and in this case, detailed meanings thereof will be described in the corresponding description. Therefore, the terms used in the following description should be understood based on the meanings of the terms and the contents throughout the specification, rather than simply the names of the terms.

According to an embodiment, the spinal muscle state determination apparatus 120 may receive the spinal muscle information 110 of the user and determine the spinal muscle state of the user. Here, the spinal muscle information 110 may include at least one of user's motion information and biometric information with respect to a predetermined 3D posture.

According to an embodiment, the apparatus for determining spinal muscle state may determine the spinal muscle state of the user using the spinal muscle information and the spinal disease determination function of the user. The spinal muscle state determination apparatus may present "A spinal disease 131", "B spinal disease 132", "C spinal disease 133", etc., when the user has spinal disease.

According to an embodiment, the spinal muscle state determining apparatus 120 may determine the spinal muscle state of the user using information around the lumbar and cervical spine.

2 to 3, a detailed description will be made of the apparatus and method for determining spinal muscle state.

According to an embodiment, the apparatus for determining spinal muscle state 120 may include an input unit 210, a processor 220, and a determiner 230. The spinal muscle state determination apparatus 120 may diagnose the spinal muscle state of the user using the spinal muscle information of the user.

The input unit 210 may receive spinal muscle information for determining muscle tension of the spine with respect to a user's measurement site. In this case, the spinal muscle information may include at least one of user's motion information and bio information about a predetermined 3D posture.

According to one embodiment, the operation information may include a range of motion (ROM), which is a moving range of the measurement site when the user takes a predetermined three-dimensional posture. Muscle tension can be compared by measuring the user's ROM through a three-dimensional pose. The measurement site may be a first measurement site and a second measurement site that are symmetrical with respect to the spine of the user. Muscle tension can be compared by comparing the ROM of the first measurement site with the ROM of the second measurement site. In addition, muscle tension can determine whether the spine is symmetrical.

According to another embodiment, the biometric information may include at least one of a body temperature, a bioimpedance, and a current perception threshold for the user. Body temperature may refer to the supply of blood and the degree of muscle activation. The bioimpedance may determine the degree of muscle degeneration through components such as muscle and fat. In addition, the current perception threshold may enable the distribution of perceptual nerves to be grasped. The current perception threshold can be measured while the operation is stopped.

According to an embodiment, the measurement part may be a first measurement part and a second measurement part which are symmetrical with respect to the spine of the user. Meanwhile, the muscle tension may be a difference between the first measurement value, which is the spinal muscle information obtained from the first measurement site, and the second measurement value, which is the spine muscle information obtained from the second measurement site. In addition, the muscle tension may be calculated in other ways besides being calculated as the difference between the first and second measured values. Muscle tension can be calculated using spinal muscle information as a parameter.

The processor 220 may call a spinal disease determination function corresponding to the measurement site. In addition, the processor 220 may generate a spinal disease determination function. The spinal disease determination function may be generated by receiving spinal muscle information on a measurement site from each of a plurality of users and calculating muscle tension. An apparatus and method for generating a spinal disease determination function will be described in detail with reference to FIGS. 6 to 8.

The determination unit 230 may determine the spinal muscle state of the user by using the spinal muscle information and the called spinal disease determination function.

Hereinafter, various operations or applications performed by the apparatus for determining spinal muscle state will be described, and a person skilled in the art will clearly understand and anticipate the present invention without specifying any configuration of the input unit, the processing unit, and the determination unit. As much as possible may be understood as a conventional implementation, the scope of the present invention is not limited by the specific configuration name or physical / logical structure.

According to an embodiment, the apparatus for determining spinal muscle state may receive spinal muscle information for determining muscle tension of the spine with respect to a user's measurement site. (Step 310)

According to one embodiment, the spinal muscle state determination apparatus may call a spinal disease determination function corresponding to the measurement site. The measuring site can be near the spine or near the cervical spine.

According to an embodiment, the apparatus for determining spinal muscle state may determine the spinal muscle state of the user using the spinal muscle information and the called spinal disease determination function. (Step 330)

410 is an exemplary diagram when the user takes a standing position with a sensor mounted near a spine. The sensor may be mounted to be symmetrical from side to side with respect to the centerline of the spine.

According to one embodiment, if the user moves left and right by a certain angle, the sensor can measure the movable range for the left and right direction. Here, the sensor may be wirelessly connected to measure the moving range electronically.

Meanwhile, although FIG. 410 illustrates an example in which a sensor is mounted near a user's spine, a moving range may be measured using a marker without mounting a sensor. In the case of using a marker, the moving range can be measured using image processing.

420 is an exemplary diagram when the user mounts the sensor near the spine and bends forward.

According to one embodiment, if the user moves forward and leftward by a predetermined angle in a state of bending forward, the sensor can measure the movable range for the left and right directions.

430 illustrates an example in which the user takes a sensor mounted near the spine and takes a back position.

According to one embodiment, when the user moves in the left and right directions by a predetermined angle while the user is in a back-turned position, the sensor may measure a movable range for the left and right directions.

5 is a diagram illustrating a measurement site for determining a spinal muscle state of a user, according to an exemplary embodiment.

510 is an exemplary diagram in which a marker is mounted on a measurement site symmetrically with respect to the center of the spine of the user. The measurement site may be at least one point. Here, as described in FIG. 4, when the user takes a predetermined three-dimensional pose, the moving range of the user may be measured for each pose. The moving range can be measured by extracting the marker region from the image through image processing.

520 illustrates an example of the spine when the user takes a predetermined three-dimensional posture. The spine may be obtained through image processing.

According to an embodiment, the marker may be attached to the vicinity of the spine of the user, and 3D motion information of the user may be obtained through image processing.

According to another embodiment, when the user wants to acquire the biosignal of the user, the biosignal may be sensed by attaching a sensor near the spine of the user. For example, when the user wants to measure the user's body temperature, the sensor may sense the temperature, and when the user wants to measure the user's bioimpedance, the sensor may sense the impedance.

On the other hand, a user with pain in the lower back may have a sprain in the lumbar spine or cervical spine. If there is a sprain, the user may feel pain. Sprains are diseases that cause inflammation. If this inflammation persists, the muscles in the vicinity of the pain are weakened, and the strength to support the bones is lost, and sprains can be aggravated by diseases such as spinal discs.

According to an embodiment, the biosignal of the user may be measured based on the lumbar spine and the cervical spine. If the user is inflamed, the user's body temperature may be low or high. Thus, bioimpedance may fluctuate due to inflammation. The bioimpedance may be asymmetric with respect to the spine of the user or may show a significant difference.

According to another embodiment, the sensor may be symmetrically attached to the spine of the user to measure the bioimpedance. For example, if eight sensors are attached in left and right symmetry, eight bioimpedance signals can be sensed and four symmetrical comparisons can be made in the vertical direction.

According to another embodiment, if the user has pain in the lower back, the sensor may be attached to the lower back. Specifically, the sensor may be attached at a distance of 2-5 cm from the waist centerline to the higher portion of the hip line of the user.

According to another embodiment, if the user has a pain around the neck, the sensor may be attached to the bottom of the neck. Specifically, the sensor may be attached at a distance of 2-5 cm from the waist centerline at a predetermined distance below the neck.

According to an embodiment, the spinal disease determination function generating device 600 may include an input unit 610, an operation unit 620, a processing unit 630, and a function generation unit 640.

The input unit 610 may receive spinal muscle information for each measurement site of the plurality of users. The measurement site may be the same location for each of the plurality of users. In addition, the measurement site may be a plurality of sites instead of one site. The spinal disease determination function generating device 600 may generate spinal disease determination functions by receiving spinal muscle information for a plurality of portions, respectively.

According to an embodiment, the measuring part may include a first measuring part and a second measuring part which are symmetrical with respect to the spine of the user.

According to an embodiment, the spinal muscle information may include at least one of user's motion information and bio information about a predetermined 3D posture. Here, the operation information may include a range of motion (ROM), which is a moving range of the measurement site when the user takes a predetermined three-dimensional posture. In addition, the biometric information may include at least one of body temperature, bioimpedance, and current perception threshold for the user.

The calculator 620 may calculate muscle tension of each of the plurality of users using the spinal muscle information. The muscle tension may be a difference between the first measurement value which is the spinal muscle information obtained from the first measurement site and the second measurement value which is the spine muscle information obtained from the second measurement site. Here, the calculation unit 620 is not limited to calculating the muscle tension based on the difference between the first measured value and the second measured value, and may calculate the muscle tension by another method such as raising the threshold set by each measured value. Can be. Muscle tension can be calculated using spinal muscle information as a parameter. Muscle tension can also be calculated by combining a user's questionnaire (eg, low back pain disorder assessment: KRMDQ), physician diagnosis, and spinal muscle information.

The processor 630 may classify the plurality of users into normal and abnormal groups for spinal diseases by using the calculated muscle tension of each of the plurality of users.

According to an embodiment of the present disclosure, in the classification of the normal group and the non-settling group, when the difference between the first measurement value and the second measurement value is greater than a predetermined threshold value, the user corresponding to the difference may be classified as an abnormal person group.

According to another embodiment, the processor 630 may classify the first user as an abnormal group when a difference obtained from the first user among the plurality of users is greater than a predetermined threshold value. Here, the difference is muscle tension, and the muscle tension may be a difference between the first measurement value and the second measurement value. In addition, when each measured value is greater than the predetermined threshold value can be classified as an abnormal group. In addition, if the questionnaire score is greater than the given value, it can be classified as an abnormal group.

The function generator 640 may generate a spinal disease determination function based on the muscle tension of the normal person and the muscle tension of the abnormal person. The function generator 640 may determine a parameter constituting the spinal disease determination function based on the correlation between the muscle tension of the normal person and the muscle tension of the abnormal person. The function generator 640 may generate a spinal disease determination function based on the determined parameter.

The function of tracking the pattern of the ROM and the biosignal over time together with the ROM indicating posture or motion is as follows. The threshold value can be described below, but the magnitude of the change in the biosignal according to the change in motion with time is also an important judgment value. In the meantime, the parameter constituting the spinal disease judgment function may be determined as a parameter constituting the spinal disease judgment function using a parameter whose correlation between muscle tension in the normal group and muscle tension in the abnormal group is less than a preset threshold.

According to an embodiment, the function generator 640 may determine the body temperature as a parameter constituting the spinal disease determination function. For example, as shown in Equation 1, a value corresponding to muscle tension may be calculated.

Here, TempL (1, t) is the body temperature at the first measurement site when time t, and TempR (2, t) is the body temperature at the second measurement site when time t. The first and second measurement sites are symmetrical about the spine of the user. difTemp [1,2] [t] is the temperature difference between the first measurement site and the second measurement site at time t. In addition, muscle tension can be calculated using the trend of body temperature difference by tracking with time series data.

In addition, when the temperature difference for the first user is smaller than the predetermined threshold value, it may be classified as a normal person group, and if it is larger than the preset threshold value, it may be classified as an abnormal person group. In this case, other operational information other than body temperature, bioimpedance and current perception threshold may also be measured. Muscle tension can be calculated using information other than body temperature for each of the normal and abnormal groups. Based on the correlation between the muscle tensions of the normal and abnormal groups, parameters that constitute the spinal disease judgment function can be determined. Alternatively, if TemL (1, t) or TemR (1, t) is greater than the threshold value, muscle tone may belong to the abnormal group. In addition, the threshold of the change of the biosignal with movement is also important.

According to another embodiment, the function generator 640 may determine the bioimpedance as a parameter constituting the spinal disease determination function. For example, as shown in Equation 2, a value corresponding to muscle tension can be calculated. In addition, muscle tension can be calculated using the trend of bioimpedance difference by tracking with time series data.

Here, ImpL (1, t) is the bioimpedance at the first measurement site when time t, and ImpR (2, t) is the bioimpedance at the second measurement site when time t. The first and second measurement sites are symmetrical about the spine of the user. difImp [1,2] [t] is the difference in bioimpedance between the first measurement site and the second measurement site at time t. Or, if ImpL (1, t) or ImpR (2, t) is greater than a given threshold, muscle tone is in the abnormal group.

According to another embodiment, the function generator 640 may determine the current perception threshold as a parameter constituting the spinal disease determination function. For example, as shown in Equation 3, a value corresponding to muscle tension can be calculated.

Since the current perception threshold is impossible to measure while moving, the current perception threshold can be measured at each position where the user can be aware of the current while standing still, left or right, bent as far as possible. CPTL 1 is the current perception threshold at the first measurement site and CPTR 2 is the current perception threshold at the second measurement site. The first and second measurement sites are symmetrical with respect to the spine of the user. Or when the CPTL 1 or CPTR 2 is greater than a given threshold, the muscle tension belongs to an abnormal group.

According to an embodiment, the spinal disease determination function generating device 600 may further include an information obtaining unit 650. The information acquisition unit 650 may obtain spinal muscle information from each of the plurality of users from the first measurement site and the second measurement site which are symmetrical with respect to the spine.

Hereinafter, various operations or applications performed by the apparatus for generating a spinal disease determination function will be described. Although any configuration of the input unit, the calculating unit, the processing unit, the function generating unit, and the information obtaining unit is not specified, it is common to those skilled in the art. The extent to which a person skilled in the art can clearly understand and anticipate can be understood as a typical implementation, and the scope of the present invention is not limited by the specific structure name or the physical / logical structure.

The spinal disease determination function generating device may receive spinal muscle information about a plurality of users. In operation 710, the input unit may receive spinal muscle information about the measurement part of each of the plurality of users. In this case, the spinal muscle information may include at least one of user's motion information and bio information about a predetermined 3D posture.

According to one embodiment, the measurement site may be a first measurement site and a second measurement site that are symmetrical with respect to the spine for each of the plurality of users.

The spinal disease determination function generating device may calculate muscle tension for each of the plurality of users. The operation unit may calculate muscle tension of each of the plurality of users by using a questionnaire and a doctor diagnosis such as spinal muscle information and low back pain disorder assessment (KRMDQ). The muscle tension may calculate a difference between the first measurement value obtained from the first measurement site and the second measurement value obtained from the second measurement site, the first measurement value, and the second measurement value. In addition, the amount of change (derived value) of the measured values according to the movement may be an important factor. In addition, the change amount of the measured value according to the movement may be expressed by a formula.

The device for generating a spinal disease judgment function may be classified into a normal group and an abnormal group for spinal disease. In operation 730, the processor may classify the plurality of users into a normal group and an abnormal group of spinal diseases by using the calculated muscle tension of each of the plurality of users.

According to one embodiment, the step of classifying the normal group and abnormal group for spinal disease is to classify the first user as an abnormal group, if the muscle tension obtained from the first user of the plurality of users is greater than a predetermined threshold value; It may include a step. Here, the muscle tension may be a difference between the first measurement value obtained from the first measurement site and the second measurement value obtained from the second measurement site. In addition, muscle tension may be calculated by another method using the first measurement value and the second measurement value instead of the above-described method. Alternatively, it can be calculated from the magnitude of the measured values.

The spinal disease determination function generating device may generate a spinal disease determination function. (Step 740) The function generator may generate a spinal disease determination function based on the muscle tension of the normal person group and the muscle tension of the abnormal person group. A detailed description of generating a spinal disease determination function will be given later with reference to FIG. 8.

According to an embodiment, the method for generating a spinal disease determination function may further include obtaining spinal muscle information from each of a plurality of users from a first measurement site and a second measurement site which are symmetrical with respect to the spine.

The function generator may determine a parameter constituting the spinal disease determination function. (Step 810) Here, the parameter may be determined based on spinal muscle information. The spinal muscle information may include at least one of user's motion information and bio information about a predetermined 3D posture.

According to one embodiment, the operation information may include a ROM, which is a moving range of the measurement site when the user takes a predetermined three-dimensional posture.

The function generator may generate a spinal disease determination function based on the determined parameter. (Step 820)

The apparatus described above may be implemented as a hardware component, a software component, and / or a combination of hardware components and software components. For example, the devices and components described in the embodiments may be, for example, processors, controllers, arithmetic logic units (ALUs), digital signal processors, microcomputers, field programmable arrays (FPAs), It may be implemented using one or more general purpose or special purpose computers, such as a programmable logic unit (PLU), microprocessor, or any other device capable of executing and responding to instructions.

The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to the execution of the software.

For convenience of explanation, one processing device may be described as being used, but one of ordinary skill in the art will appreciate that the processing device includes a plurality of processing elements and / or a plurality of types of processing elements. It can be seen that it may include. For example, the processing device may include a plurality of processors or one processor and one controller. In addition, other processing configurations are possible, such as parallel processors.

The software may include a computer program, code, instructions, or a combination of one or more of the above, and configure the processing device to operate as desired, or process it independently or collectively. You can command the device.

Software and / or data may be any type of machine, component, physical device, virtual equipment, computer storage medium or device in order to be interpreted by or to provide instructions or data to the processing device. Or may be permanently or temporarily embodied in a signal wave to be transmitted. The software may be distributed over networked computer systems so that they may be stored or executed in a distributed manner. Software and data may be stored on one or more computer readable recording media.

The method according to the embodiment may be embodied in the form of program instructions that can be executed by various computer means and recorded in a computer readable medium. The computer readable medium may include program instructions, data files, data structures, etc. alone or in combination. The program instructions recorded on the media may be those specially designed and constructed for the purposes of the embodiments, or they may be of the kind well-known and available to those having skill in the computer software arts.

Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tape, optical media such as CD-ROMs, DVDs, and magnetic disks, such as floppy disks. Magneto-optical media, and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like.

Examples of program instructions include not only machine code generated by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like.

The hardware device described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

Although the embodiments have been described by the limited embodiments and the drawings as described above, various modifications and variations are possible to those skilled in the art from the above description. For example, the described techniques may be performed in a different order than the described method, and / or components of the described systems, structures, devices, circuits, etc. may be combined or combined in a different form than the described method, or other components. Or even if replaced or substituted by equivalents, an appropriate result can be achieved.

Therefore, the scope of the present invention should not be limited to the described embodiments, but should be determined not only by the claims below but also by the equivalents of the claims.

Claims

Receiving spinal muscle information for determining muscle tension of the spine with respect to a measurement site of the user;

Calling a spinal disease determination function corresponding to the measurement site; And

Determining the spinal muscle state of the user by using the spinal muscle information and the called spinal disease determination function

Spinal muscle state determination method comprising a.
The method of claim 1,

The spine muscle information,

Method of determining the spinal muscles state comprising at least one of the user's motion information and biometric information for a predetermined three-dimensional posture.
The method of claim 2,

Generating the spinal disease judgment function

Spinal muscle state determination method further comprising.
The method of claim 3,

Generating the spinal disease judgment function,

Receiving at least one of spinal muscle information for each measurement site of each of a plurality of users, a questionnaire for a spine preset for each of the plurality of users, and a diagnosis result for each of the plurality of users as input information;

Calculating muscle tension of each of a plurality of users using the input information;

Classifying the plurality of users into normal and abnormal groups for spinal diseases by using the calculated muscle tension of each of the plurality of users; And

Generating the spinal disease judgment function based on muscle tension of the normal person group and muscle tension of the abnormal person group

Spinal muscle state determination method comprising a.
The method of claim 4

Generating the spinal disease judgment function,

Determining a parameter constituting the spinal disease judgment function based on a correlation between muscle tension in the normal person group and muscle tension in the abnormal person group; And

Generating the spinal disease judgment function based on the determined parameter

Spinal muscle state determination method comprising a.
The method of claim 5

Determining a parameter constituting the spinal disease judgment function,

And a parameter whose correlation between the muscle tension of the normal person and the muscle tension of the abnormal person is less than a preset threshold as a parameter constituting the spinal disease judgment function.
The method of claim 2,

The operation information,

When the user takes the predetermined three-dimensional posture, spine muscle state determination method comprising a range of motion (ROM) which is a moving range for the measurement site.
The method of claim 2,

The biometric information,

Spinal muscle state determination method comprising at least one of the body temperature, bioimpedance and current perception threshold for the user.
The method of claim 1,

The measurement site,

Spinal muscle state determination method of the first measurement site and the second measurement site symmetrical with respect to the user's spine.
In the spinal disease judgment function generating method for generating a spinal disease judgment function for determining the spinal muscle state of the user,

Receiving at least one of spinal muscle information for each measurement site of each of a plurality of users, a questionnaire for a spine preset for each of the plurality of users, and a diagnosis result for each of the plurality of users as input information;

Calculating muscle tension of each of a plurality of users using the input information;

Classifying the plurality of users into normal and abnormal groups for spinal diseases by using the calculated muscle tension of each of the plurality of users; And

Generating the spinal disease judgment function based on muscle tension of the normal person group and muscle tension of the abnormal person group

Spinal disease judgment function generation method comprising a.
The method of claim 10,

And obtaining the spinal muscle information from each of the plurality of users from the first measurement site and the second measurement site which are symmetrical with respect to the spine.
The method of claim 11,

Computing the muscle tension,

And calculating a difference between a first measurement obtained from the first measurement site and a second measurement value obtained from the second measurement site.
The method of claim 12,

The step of classifying the normal group and abnormal group for the spinal disease,

The difference obtained from a first user of the plurality of users is greater than a first threshold; or

When the magnitude of the first measurement value or the second measurement value obtained from the first user of the plurality of users is greater than a second threshold value,

And a step of classifying the first user into the abnormal group.
The method of claim 10,

Generating the spinal disease judgment function,

Determining a parameter constituting the spinal disease judgment function based on a correlation between muscle tension in the normal person group and muscle tension in the abnormal person group; And

Generating the spinal disease judgment function based on the determined parameter

Spinal disease judgment function generation method comprising a.
In a computer-readable recording medium recording a program for executing a method for generating a spinal disease judgment function, the method for generating a spinal disease judgment function includes:

Receiving at least one of spinal muscle information for each measurement site of each of a plurality of users, a questionnaire for a spine preset for each of the plurality of users, and a diagnosis result for each of the plurality of users as input information;

Calculating muscle tension of each of a plurality of users using the input information;

Classifying the plurality of users into normal and abnormal groups for spinal diseases by using the calculated muscle tension of each of the plurality of users; And

Generating the spinal disease judgment function based on muscle tension of the normal person group and muscle tension of the abnormal person group

Computer-readable recording medium comprising a.
An input unit configured to receive spinal muscle information for determining muscle tension of the spine with respect to a measurement site of the user;

A processor for calling a spinal disease determination function corresponding to the measurement site; And

Determination unit for determining the spinal muscle state of the user using the spinal muscle information and the called spinal disease determination function

Spinal muscle state determination device comprising a.
The method of claim 16,

The spine muscle information,

Spinal muscle state determination device comprising at least one of the user's motion information and biometric information for a predetermined three-dimensional posture.
In the spinal disease determination function generating device for generating a spinal disease determination function for determining the spinal muscle state of the user,

An input unit configured to receive at least one of spinal muscle information for each measurement site of each of a plurality of users, a questionnaire for a spine preset for each of the plurality of users, and a diagnosis result for each of the plurality of users as input information;

A calculator configured to calculate muscle tension of each of a plurality of users using the input information;

A processor configured to classify the plurality of users into normal and abnormal groups for spinal diseases by using the calculated muscle tension of each of the plurality of users; And

A function generator for generating the spinal disease judgment function based on the muscle tension of the normal group and the muscle tension of the abnormal group

Spinal disease determination function generating device comprising a.
The method of claim 18,

An information acquisition unit for acquiring the spinal muscle information from each of the plurality of users from the first measurement site and the second measurement site that are symmetrical with respect to the spine.

More,

The muscle tension is,

And a difference between the first measurement value obtained from the first measurement site and the second measurement value obtained from the second measurement site, or the magnitude of the first measurement value and the second measurement value.
The method of claim 19,

The processing unit,

The difference obtained from a first user of the plurality of users is greater than a first threshold; or

When the magnitude of the first measurement value or the second measurement value obtained from the first user of the plurality of users is greater than a second threshold value,

Spinal disease determination function generation device for classifying the first user into the abnormal group.