KR20180122157A - A method of estimating patient in-vivo properties using motion capture - Google Patents

Abstract

The present invention relates to a method for extracting an in-vivo physical property of a patient through a comparison with a real captured musculoskeletal image by capturing motion of a subject to obtain kinematic data, calculating a muscle power from the obtained data and applying the data to a musculoskeletal model. According to an embodiment of the present invention, the method for extracting an in-vivo physical property of a patient using motion capture comprises: a step (A) of collecting kinematic behavior data through motion capture of the subject; a step (B) of calculating the muscle power of the subject from the collected behavior data; a step (C) of establishing a target musculoskeletal model for a specific subject to apply the calculated muscle power; a step (D) of applying the muscle power calculated from the subject to the established musculoskeletal model, and comparing the kinematic behavior of the musculoskeletal model with the obtained target musculoskeletal image; and a step (E) of performing optimization for an in-vivo physical property by using a probabilistic analysis technique.

Description

TECHNICAL FIELD [0001] The present invention relates to a method of extracting in vivo physical properties of a patient using motion capture,

The present invention captures the motion of the subject to obtain kinematical data, calculates the muscle power from the obtained data, and applies it to the musculoskeletal model to compare the musculoskeletal image with the actually photographed musculoskeletal image, The present invention relates to a method for extracting physical properties.

When a disease occurs in the musculoskeletal system, diagnosis and surgery should be adopted according to the condition of the patient. In this process, the patient should be treated with a bio-assistive device, orthodontic appliance, and implant.

It is desirable to fabricate the devices by reflecting the biomaterial properties of individual patients in manufacturing the devices, auxiliary devices, orthodontic appliances, and implants, but it is impossible to visually confirm them, and in reality, It is a reality that it is virtually impossible to manufacture the devices by securing the biomechanical properties of individual patients in consideration of the time and cost aspects.

In addition, since biometric information unique to each patient is different from each other, it takes a lot of time and money to treat the disease through the process of repeatedly acquiring such data for each patient.

On the other hand, the biological properties of the patient can be obtained through in-vivo tests and in-vitro tests. The in-vivo test refers to a test performed in the body of a test subject, and the in-vitro test refers to a test in which some tissue cells of the test subject are incised or cells are cultured and the condition is adjusted in a separate test tube.

In the prior art, in-vitro tests for directly extracting cells from the body have been mainly used as methods for extracting biological properties of a patient.

However, securing of biological properties through the in-vitro test, which has been known so far, requires a process of collecting and inspecting cells from the body, resulting in considerable time and cost.

In the prior art for ensuring biocompatibility through an in-vivo test, a method of imaging an image through an endoscope was used.

However, the in-vivo test according to the prior art is only limited to the indirect estimation of the biomaterial properties through the image captured by the endoscope, and thus there is a limitation in directly extracting the biomaterial properties.

Korean Patent Registration No. 10-1690425 entitled " Apparatus for Measuring Electrical Properties of Biological Tissues and Method Thereof " Korean Patent Registration No. 10-1726054 entitled " Apparatus and Method for Determining Biological Tissue, US-A-2016-0194588 "DEVICE FOR IN-VITRO MODELING IN-VIVO TISSUES OF ORGANS" U.S. Patent No. 8743189 entitled "Image processing apparatus, image processing method, and computer-readable recording medium storing image processing program"

In the present invention, a method of optimizing a physical characteristic of a specific patient based on a method of acquiring motion data of a specific patient by capturing motion of the patient is proposed.

According to an embodiment of the present invention, there is provided a method of analyzing an object, comprising: (A) collecting kinematic behavior data through motion capture of an object to be examined; (B) calculating muscle power of the subject from the collected behavior data; (C) constructing a model of the target musculoskeletal system for a specific subject to be applied with the calculated muscle power; (D) applying the muscle force calculated from the subject to the constructed musculoskeletal model and comparing the kinematic behavior of the musculoskeletal model with the image of the acquired musculoskeletal system; And (E) optimizing in vivo physical properties in vivo using a stochastic analysis technique. The present invention also provides a method for extracting in vivo physical properties of a patient using motion capture.

According to one embodiment, the motion capture may be extracted by a marker attached to the subject,

According to an embodiment of the present invention, the musculoskeletal-dynamics may be constructed in the process of calculating the muscle force from the subject in the step (B).

According to one embodiment, in the step (B), the calculated muscle force is calculated by calculating kinematic dynamics of the musculoskeletal system using kinematic behavior data of the musculoskeletal system obtained through motion capture of the subject and surface reaction force can do.

According to one embodiment, in the step (B), the calculated muscle power is compared with the EMG data obtained by using the EMG sensor at the time of motion capture of the subject, and the EMG data is verified.

According to an embodiment, the step of constructing a model of the object musculoskeletal system for a specific subject to be applied with the calculated muscle force comprises the steps of: (C-1) Obtaining a plurality of images for the plurality of subjects, and constructing a statistical 3D model for the plurality of subjects; (C-2) extracting a two-dimensional image from a specific object to be examined; (C-3) forming a customized biometric model for a specific subject by matching statistical 3D models of the plurality of subjects with the extracted two-dimensional image.

According to an embodiment, the image of the target musculoskeletal system acquired in the step (D) may be obtained together with the motion capturing process.

According to an embodiment of the present invention, bio-physical properties of individual patients can be more easily obtained by using behavior data of a specific patient.

In particular, the present invention has a different meaning from the prior art in that it provides a non-invasive biological material property extraction method by an in-vivo method unlike the conventional biological material property extraction method which mainly uses the in-vitro method.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram of a biological in vivo physical property extraction method of a patient using motion capture according to an embodiment of the present invention; FIG.
2 is a diagram showing a configuration for a method of capturing motion of a test subject.
3 is a conceptual diagram illustrating a method of deriving muscular power according to an embodiment of the present invention.
FIG. 4 is a conceptual diagram illustrating a method for performing in-vivo physical property optimization using a stochastic analysis technique according to an embodiment of the present invention.
5 is a diagram showing a process of deriving in vivo physical properties in vivo.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the description of the present invention, a detailed description of known configurations will be omitted, and a detailed description of configurations that may unnecessarily obscure the gist of the present invention will be omitted.

First, with reference to FIG. 1 and FIG. 2, a basic embodiment of a method for extracting a biological in vivo physical property of a patient using motion capture will be described.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram of a biological in vivo physical property extraction method of a patient using motion capture according to an embodiment of the present invention; FIG.

According to an embodiment of the present invention, there is provided a method of analyzing an object, comprising the steps of: (A) collecting kinematic behavior data through motion capture of an object to be examined; (B) calculating muscle power of the subject from the collected behavior data; (C) constructing a model of the target musculoskeletal system for a specific subject to be applied with the calculated muscle power; (D) applying the muscle force calculated from the subject to the constructed musculoskeletal model and comparing the kinematic behavior of the musculoskeletal model with the image of the acquired musculoskeletal system; And (E) performing an optimization for in vivo physical properties in vivo using probabilistic analysis techniques. For reference, reference numerals (A), (B), (C), (D), and (E) are used for convenience of description only and do not limit the time series of the present invention.

In the present invention, terms such as subject, patient, and normal person can be used for convenience of explanation, but it should be noted that the subject to be treated in the present invention is not limited to a specific animal including human.

Further, the subject of the present invention does not distinguish between the subject to be treated having no disease and the subject to be treated.

In the present invention, the musculoskeletal system can mainly mean bones, joints or parts thereof. Here, bones and joints may include animal heads, shoulders, hips, knees, ankles, spines, and the like, and may include tissues such as ligaments, cartilage, and especially muscles.

2 is a diagram showing a configuration for a method of capturing motion of a test subject.

According to an embodiment of the present invention, the motion capture may be extracted by the marker 100 attached to the subject.

Referring to FIG. 2, an object to be tested may be placed in a prepared studio 10, and a plurality of markers 100 may be attached to an object to be tested. (Not shown) for measuring the movement of the marker 100, so that kinematic behavior data can be measured through the motion of the subject.

Here, the plurality of markers 100 may be attached in the vicinity of the musculoskeletal region of interest in the subject. The figure shows that the marker 100 is attached to the head and the upper body of the test subject, but the present invention is not limited thereto. For example, when a musculoskeletal region of interest is a knee, the marker 100 may be attached to the upper part of the tibia and the condyle part of the femur. Further, the marker may be attached to the subject together with an EMG sensor to be described later.

According to an embodiment of the present invention, a plurality of images may be acquired together in the process of capturing motion of the subject.

The studio 10 prepared as shown in FIG. 2 may be equipped with an image acquisition device 200. The image acquiring device 200 of the present invention may be any device capable of acquiring an image of the test subject. However, since it is necessary to capture the motion of the subject and acquire an image, it is more preferable that the image acquiring apparatus of the present invention is a two-dimensional image acquiring apparatus capable of acquiring an image of Bi-Plane. In the figure, two image acquisition devices 210 and 220 are shown for acquiring an image of Bi-Plane in one embodiment.

The kinematic behavior data of the present invention refers to various kinesiological behaviors including movement speed of a joint measured by a marker 100 and measurement means, angular velocity, direction of movement of a joint, Data.

The physical properties of the present invention include all properties such as tensile strength, compressive strength, elastic modulus, Poisson's ratio, Young's modulus, yield stress, and ultimate strength.

In the present invention, the kinematic behavior data of the subject is obtained through motion capture, and the muscular strength is calculated. Ultimately, the physical properties of the living body are extracted by using the obtained motion data to perform patient-customized surgery, correction, and rehabilitation And to facilitate the construction of the system having the above-mentioned functions.

Next, a method of deriving muscular strength and a method of constructing a musculoskeletal model according to an embodiment of the present invention will be described in detail.

3 is a conceptual diagram illustrating a method of deriving muscular power according to an embodiment of the present invention. FIG. 4 is a conceptual diagram illustrating a method for performing in-vivo physical property optimization using a stochastic analysis technique according to an embodiment of the present invention.

According to one embodiment of the present invention, as shown in FIG. 3 (a), the motion of the subject is captured, and the muscle power of the subject is calculated from the collected motion data. During the calculation, a musculoskeletal-dynamics model as shown in Fig. 3 (b) can be constructed.

Here, the construction of the musculoskeletal-dynamics model can use commercially available commercial programs, and the kinetic behavior data of the subject can be visually expressed as shown in FIG. 3 (b) The muscular strength of the musculoskeletal system can be freely selected.

The inverse dynamics analysis using the calculated muscle power data can be used to derive muscle power for the region of interest.

More specifically, according to the in vivo physical property extraction method of a patient of the present invention, in the step (B), the calculated muscle force is calculated by using the kinematic behavior data of the musculoskeletal system obtained through motion capture of the subject and the ground reaction force, May be calculated by calculating the kinematics of the musculoskeletal system.

According to one embodiment, a mechanism for measuring the ground reaction force may additionally be provided under the leg or the studio 10 of the subject of the test subject. The kinematic behavior data due to the movement of the marker 100 and the ground reaction force are calculated, It is possible to calculate the muscle force of a specific value when taking a specific movement.

Further, in the method of extracting in vivo physical characteristics of a patient using motion capture according to an embodiment of the present invention, the muscle power calculated in the step (B) is compared with the EMG data obtained using the EMG sensor at the time of motion capture of the test subject And verifying the previously calculated muscle force.

The reliability of the in-vivo property extraction method of the present invention can be ensured by verifying the muscle force calculated through the EMG sensor attached to the subject.

Once the musculoskeletal model is acquired and the muscular strength can be calculated, the in vivo physical properties of a particular subject can be calculated by the following process.

Next, a method for extracting in vivo physical characteristics of a patient using motion capture according to an embodiment of the present invention includes (C) constructing a model of a musculoskeletal system of a target subject to be applied with the calculated muscle power , Which is to apply the calculated muscle power to the model of the established musculoskeletal system. Once the model of the musculoskeletal system is constructed, it is possible to optimize the physical properties while adjusting the behavior against the calculated muscle force.

For example, when the vertebra is taken as an example, the vertebral FE model to which the muscle force of the subject is applied can be constructed as shown in FIG.

Here, a model of a musculoskeletal system of a specific subject is constructed. However, the basic data for constructing the model of the musculoskeletal system may be obtained from the specific person according to an embodiment, but it is also possible to use a plurality of Or may be acquired from the subject to be examined.

For example, in the construction of a musculoskeletal model, when the data necessary for model construction is acquired from a specific individual (a specific person), a 3D model is directly constructed from the image of the specific person. In this case, a 3D image acquiring device such as CT or MRI may be used or a 2D image acquiring device such as a tomography device may be used.

On the other hand, in the case of acquiring data necessary for model construction in the construction of a musculoskeletal model from a plurality of subjects, a statistical 3D model is obtained on the basis of image information obtained by photographing a plurality of subjects, and a musculoskeletal model It can be constructed indirectly. At this time, it is possible to construct a musculoskeletal model of the test subject by using only a 2D image acquisition device such as a tomographic imaging apparatus.

Next, a method of constructing a musculoskeletal model will be described in more detail.

First, the musculoskeletal image of the region of interest is obtained.

A three-dimensional image can be obtained by successively photographing and attaching two-dimensional images to the musculoskeletal system of a region of interest, and the obtained image is restored into three-dimensional data. A 3D model of the musculoskeletal system of the region of interest is generated through the process of reconstructing the obtained image into three-dimensional data.

According to an embodiment of the present invention, it is possible to generate a statistical 3D model by editing a plurality of images obtained through two-dimensional tomography of the body, and combining the edited images into a surface.

For example, when the spine is set as the target musculoskeletal system, an image of noise such as other living tissues around the vertebra, ribs, backbone, or other bone fragments can be obtained together. This noise can be excluded from the editing process because it becomes a factor that delays the computation speed and lowers the precision in constructing the statistical 3D model. It can also be excluded when combining plural images and making them into a surface.

Here, the combination of the plurality of edited images may mean that the images taken tomographically in the specific direction, that is, the coordinate reference of the obtained image, are connected successively.

According to an embodiment of the present invention, a boundary for the target musculoskeletal system can be set for each image in order to continuously attach the tomographic images. Here, the task of setting the boundary for the target musculoskeletal system can be performed simultaneously with the process of removing the noise.

A 3D modeling is formed by combining a plurality of edited images into a surface, where the 3D modeling can be expressed as a mesh model. Then, the process of dataizing the 3D modeling is performed.

On the other hand, when a model of a musculoskeletal system is constructed on the basis of data provided from a plurality of subjects, (C-1) a plurality of images of a musculoskeletal system of a region of interest are acquired from a plurality of subjects, (C-2) constructing a statistical 3D model for a plurality of subjects to be inspected; (C-3) extracting a two-dimensional image from a specific object to be examined; (C-4) forming a customized biometric model for a specific subject by matching statistical 3D models of the plurality of subjects with the extracted two-dimensional image.

For example, a statistical musculoskeletal model can be obtained for about 100 subjects. Steps up to constructing a statistical 3D model for a plurality of test subjects are performed in the same manner as the above-described method for constructing a 3D model for a single test subject. However, if the number of subjects is 100, 100 3D models are acquired and then constructed in advance using statistical 3D models.

Thereafter, a two-dimensional image extracted from a specific subject is matched with a statistical 3D model obtained here, so that a model of a target musculoskeletal system for a specific subject can be constructed.

By constructing a target musculoskeletal model using a pre-constructed statistical 3D model, it is possible to construct a musculoskeletal model for a specific subject in a faster and more accurate manner without having to generate a 3D model for each individual subject, .

As described above, once the model for the target musculoskeletal system is constructed for a specific subject, the muscular force calculated through motion capture is applied to the constructed model, and the physical properties of a subject to be inspected ultimately used in the present invention . ≪ / RTI >

However, the present invention has a different meaning from the prior art in that it presents a non-invasive method for extracting a biological property of a patient by an in-vivo method, unlike a conventional method of extracting a biological material, which is dependent on an in-vitro method .

Hereinafter, a method for deriving in vivo physical properties of a living body will be described in detail with reference to FIG.

5 is a diagram showing a process of deriving in vivo physical properties in vivo.

Specifically, FIG. 5 (a) shows a real image obtained with respect to a musculoskeletal system of a region of interest, and FIG. 5 (b) is a diagram showing a model constructed for a musculoskeletal system of interest.

According to an embodiment of the present invention, (D) applying the muscle force calculated from a plurality of subjects to the constructed musculoskeletal model, and comparing the kinematic behavior of the musculoskeletal model with images of the acquired musculoskeletal system .

The image of the target musculoskeletal system acquired in the step (D) may be acquired together with the motion capturing process.

In addition, the image extracted in the present invention may be a Bi-Plane image extracted from a specific subject. Here, the Bi-Plane image can be, for example, an image of two planes obtained around the musculoskeletal system of a region of interest of the subject to be examined using X-ray.

Here, the Bi-Plane of the present invention does not mean any specific angular plane, but may preferably mean a coronal plane or a sagittal plane spaced apart from each other by 90 degrees. For reference, the coronal plane may refer to an anatomical plane cut from the object in a vertical direction while looking at the object from the front, and the sagittal plane is a plane that extends from the front to the back It may mean cut anatomy.

A specific angle of the musculoskeletal system is expressed in a real image obtained when the subject to be inspected wears the marker 100 on the studio 10 in any motion and the angle corresponds to the angle of the musculoskeletal model according to the calculated muscle force .

5 (a) shows the knee cartilage when the muscular force acts at 50 Mpa. In the model constructed as shown in Fig. 5 (b) The image of the cartilaginous portion is projected, and whether or not it matches with the cartilage model produced by the muscular force of 50 Mpa matches the angles.

If the kinematic behavior of the musculoskeletal model is matched with the actual image obtained here, various physical data such as tensile strength, compressive strength, elastic modulus, Poisson's ratio, Young's modulus, Yield stress, Extraction can be performed.

If the kinematic behavior of the musculoskeletal system is not matched with the actual image obtained according to an embodiment of the present invention, the step of optimizing in vivo physical properties may be performed.

In addition, according to an embodiment of the present invention, the method may further include optimizing the in-vivo physical property in vivo using (E) stochastic analysis technique. It means that the kinematic behavior obtained by motion capture using the acquisition device 200 is optimized until the same behavior as the behavior seen through the image acquisition device 200 is seen.

Meanwhile, the in-vivo property optimization in vivo can be performed using the probabilistic analysis technique in the step (E). The Monte Carlo method can be used as an example of the probabilistic analysis technique. The Monte Carlo method is a probabilistic analysis technique which means a method of numerically repeating an experiment using a random number and obtaining an ultimate solution through the experiment. it means. However, this is according to one example, and any other probabilistic analysis techniques capable of performing optimization for in vivo physical properties in vivo may be included in the scope of the present invention.

According to the present invention, the sensitivity analysis of the model is carried out using the probabilistic method to the established model, and a more accurate musculoskeletal model is established by setting the most reliable factor obtained by the probabilistic method as a main factor of the musculoskeletal model .

Next, as the motion equation is optimized for the main factors based on the kinematic behavior obtained above, when the movement of the musculoskeletal model based on the obtained image and the kinetic behavior data becomes similar, And the resulting properties are derived.

For reference, in the present invention, a series of processes including calculation of muscle power, construction of a musculoskeletal model, and optimization of physical properties can be performed using CAE (Computer Aided Engineering).

Specifically, the method of extracting in vivo physical characteristics of a patient using motion capture described above can be implemented in the form of program instructions that can be executed through various computer components and recorded on a computer-readable medium. The computer readable medium may be any medium accessible by the processor. Such media can include both volatile and nonvolatile media, removable and non-removable media, storage media, and computer storage media. (ROM), an electrically erasable read only memory ("EEPROM"), a register, a hard disk, a removable disk, a compact disk read-only memory ("CD- ROM"), Lt; RTI ID = 0.0 > a < / RTI > storage medium. The computer storage media discussed include removable and non-removable, nonvolatile, and volatile storage media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, And non-volatile media. Such computer storage media may be embodied as program instructions, such as RAM, ROM, EPROM, EEPROM, flash memory, other solid state memory technology, CDROMs, digital versatile disks (DVDs) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage, Lt; RTI ID = 0.0 > and / or < / RTI > Examples of the mentioned program instructions may include machine language code such as those generated by the compiler, as well as high-level language code that may be executed by a computer using an interpreter or the like.

The foregoing description is merely illustrative of the technical idea of the present invention, and various changes and modifications may be made by those skilled in the art without departing from the essential characteristics of the present invention. Therefore, the embodiments disclosed in the present invention are intended to illustrate rather than limit the scope of the present invention, and the scope of the technical idea of the present invention is not limited by these embodiments. The scope of protection of the present invention should be construed according to the following claims, and all technical ideas within the scope of equivalents should be construed as falling within the scope of the present invention.

10: studio
100: Marker
200: Image acquisition device

Claims (7)

(A) collecting kinematic behavior data through motion capture of the subject;
(B) calculating muscle power of the subject from the collected behavior data;
(C) constructing a model of the target musculoskeletal system for a specific subject to be applied with the calculated muscle power;
(D) applying the muscle force calculated from the subject to the constructed musculoskeletal model and comparing the kinematic behavior of the musculoskeletal model with the image of the acquired musculoskeletal system; And
(E) optimizing in-vivo physical properties in vivo using a stochastic analysis technique.
The method according to claim 1,
Wherein the motion capture is extracted by a marker attached to an object to be examined.
The method according to claim 1,
In the step (B)
A method for extracting in vivo physical properties of a patient using motion capture, characterized by constructing a musculoskeletal-dynamics model in the process of calculating muscle power from the subject.
The method according to claim 1,
In the step (B), the calculated muscle power is
A method for extracting a biological in vivo physical property of a patient using motion capture, characterized by calculating the kinematics of a musculoskeletal system using kinematic behavior data of a musculoskeletal system obtained through motion capture of a subject and ground reaction force.
The method according to claim 1,
In the step (B)
And comparing the calculated muscle force with the EMG data obtained by using the EMG sensor at the time of motion capture of the subject to be inspected.
The method according to claim 1,
In the step (C)
The step of constructing a model of the object musculoskeletal system for a specific subject to be applied with the calculated muscle force,
(C-1) obtaining a plurality of images of a musculoskeletal system of a region of interest from a plurality of subjects to construct a statistical 3D model for a plurality of subjects;
(C-2) extracting a two-dimensional image from a specific object to be examined;
(C-3) In-vivo physical properties of a patient using motion capture, including a step of matching a statistical 3D model of the plurality of subjects with the extracted two-dimensional image to form a customized biometric model for a specific subject Extraction method.
The method according to claim 1,
In the step (D)
Wherein the acquired image of the target musculoskeletal system is acquired together with the motion capturing process.

Images