KR102349805B1 - System and method for diagnosis of stroke - Google Patents

Abstract

The present invention provides a stroke diagnosis system and method for accurately diagnosing a stroke through a quantitatively measured index. The present invention provides a quantitatively measured index to quickly and accurately diagnose a subject's stroke in an emergency room of a hospital, etc. By enabling diagnosis, there is an effect of promptly receiving diagnosis and treatment of stroke.

Description

Stroke diagnosis system and method

The present invention relates to a stroke diagnosis system and method, and more particularly, to a stroke diagnosis system and method capable of accurately diagnosing a stroke through a quantitatively measured index.

Stroke is a disease that causes irreversible neurological damage due to blood flow disturbance occurring in a local area of the brain, and is one of the chronic diseases that are increasing in social and economic importance in an aging society. Stroke has a high fatality rate and is accompanied by serious physical disability during survival, so there are many cases where there is a limit to returning to society or recovering functional status after acute recovery. In Korea, where the elderly population is rapidly increasing, the trend of increasing stroke prevalence among those in their 40s and 60s who have most of the responsibility for social and family support is expected to gradually increase the loss in social and economic aspects. do.

With regard to the prognosis of acute stroke patients, intravenous thrombolytic agent (IV-tPA) administration within a short time after symptom onset is a proven treatment. In addition, it is known that the shorter the time from symptom onset to treatment, the lower the in-hospital mortality and complications. Therefore, for effective treatment of stroke, it is important to arrive at a hospital that can receive professional treatment within 3 hours, and awareness of early symptoms of stroke is known to be a major factor influencing a patient's rapid arrival time to a medical institution. Therefore, in order to be treated within an appropriate time when stroke symptoms occur, a device capable of predicting and diagnosing stroke early in daily life or in an emergency room is needed.

Meanwhile, according to a recent study, about 9% of cerebrovascular diseases are initially misdiagnosed, and temporary nonspecific symptoms such as dizziness are closely related to the misdiagnosis. The reasons for the high stroke misdiagnosis rate in acute dizziness include palliative approaches according to the type of dizziness, excessive dependence on vascular risk factors, and incorrect perception of early brain CT and MRI. (Head Impulse test, Nystagmus, Test of Skew) Immature examination is identified as the biggest cause.

Among HINTS, the Head Impulse test (HI) has the patient look at the examiner's nose and then quickly turns the patient's head to the center to observe the eye movements. If the vestibular function is normal, the patient's eyes do not move. Continue to stare at the examiner's nose without it, but when the sedation function is abnormal, when the head is turned, the eyes move in the same direction as the head rotation, so it can be observed that rapid eye movements occur to look at the examiner's nose again. can Nystagmus (N) is an unconscious, rapid, rhythmic movement of the eye that attempts to restore the gaze point when the eyeball does not stay in the desired position due to an abnormality in the oculomotor system or an external factor and gradually deviates from the gaze point. It is an involuntary rapid movement of the eyeball. The Skew Test (Test of Skew, TS) measures changes in the vertical and horizontal position of the pupil in a dark environment and in a light environment for a certain period of time by configuring an environment without light in only one eye by alternating both eyes.

This HINTS examination is a very useful test for diagnosing stroke in acute vestibular syndrome, and it is known that the diagnosis rate is better than MRI images performed in the early stages of stroke. However, if the eye movement abnormality is mild, it is difficult to judge only by subjective clinical examination.

Therefore, there is a need for equipment capable of quantitatively measuring eye movement abnormalities in emergency rooms or stroke centers. Accordingly, the developed countries of the United States, Germany, and Australia are accelerating the development of portable stroke diagnosis systems to solve the misdiagnosis of stroke in acute dizziness and the resulting increase in medical expenses.

Domestic Registered Patent Publication No. 10-1905716 Domestic Patent Publication No. 10-2019-0061249

It is an object of the present invention to solve the problems of the prior art as described above to provide a stroke diagnosis system and method for accurately diagnosing a stroke through a quantitatively measured index.

In order to achieve the above object, the present invention is mounted on one side of the device worn on the face including the eyes of the subject, the camera for photographing the eyes of the subject; a position sensor mounted on the other side of the device and sensing the position of the subject's face; And detecting the movement of the pupil from the image taken by the camera, detecting the movement of the face from the position information of the face detected by the position sensor, and analyzing the movement of the pupil and the movement of the face to determine whether a stroke It provides a stroke diagnosis system comprising a control module.

In addition, the control module includes: a pupil extraction unit for extracting the position of the pupil from the image taken by the camera; a first movement detection unit for detecting movement information of the pupil by tracking the coordinates of the position information of the pupil extracted by the pupil extraction unit; a second movement detection unit for detecting movement information of the face by tracking the position information of the face detected by the position sensor; and a determination unit configured to determine whether a stroke has occurred by analyzing the pupil motion information detected by the first movement detection unit and the facial movement information detected by the second movement detection unit.

In addition, the camera is configured as an infrared camera, and the pupil extraction unit provides a stroke diagnosis system, characterized in that it extracts the position of the pupil by removing noise from the image of the eye received from the camera.

In addition, the first movement detection unit provides a stroke diagnosis system, characterized in that it detects the movement information of the pupil by extracting the movement distance, movement angle, and movement direction of the pupil according to the duration based on a preset reference point.

In addition, the first movement detection unit determines that it is a fast phase signal when the amplitude of the pupil according to the duration is shorter than the preset amplitude, and determines that it is a slow phase signal when the amplitude of the pupil according to the duration is longer than the preset amplitude, but , when it is determined that the signal is a slow phase, provides a stroke diagnosis system characterized in that the movement distance, movement angle, and movement direction of the pupil according to time are extracted.

In addition, the second movement detection unit provides a stroke diagnosis system, characterized in that it detects the movement information of the face by extracting the rotation direction, rotation speed, and inclination of the face according to time based on a preset reference point.

In addition, the determination unit, a head impulse test, a nystagmus test, and a skew deviation test from the pupil movement information detected by the first movement detection unit and the facial movement information detected by the second movement detection unit (Test of Skew) to determine whether there is an abnormality in either the peripheral nervous system or the central nervous system, and as a result of the judgment, abnormalities in the central nervous system during any one of the examinations selected from the head impulse test, nystagmus test, and skew deviation test To provide a stroke diagnosis system, characterized in that the diagnosis of stroke when it is determined that there is.

In addition, the present invention is a photographing process of controlling the camera mounted on one side of the device worn on the face including the eyes of the subject to photograph the eyes of the subject; a sensing process of controlling a position sensor mounted on the other side of the device to detect the position of the subject's face; and detecting the movement of the pupil from the image taken by the camera, detecting the movement of the face from the position information of the face detected by the position sensor, and analyzing the movement of the pupil and the movement of the face to determine whether a stroke It provides a stroke diagnosis method comprising a judgment process.

In addition, the determination process may include an acquiring step of acquiring location information of the pupil from the image captured by the camera; a pupil movement detection step of detecting movement information of the pupil by tracking movement coordinates for the position information of the pupil; a face motion detection step of detecting face motion information by tracking the face location information detected by the location sensor; and analyzing the motion information of the pupil and the motion information of the face to determine whether or not there is a stroke.

In addition, the acquiring step provides a stroke diagnosis method, characterized in that the acquisition of the location information of the pupil by removing noise from the infrared image taken by the camera.

In addition, the step of detecting the pupil movement provides a stroke diagnosis method, characterized in that the movement information of the pupil is detected by extracting the movement distance, movement angle, and movement direction of the pupil according to time based on a preset reference point.

In addition, in the step of detecting the pupil movement, if the amplitude of the pupil according to the duration is shorter than the preset amplitude, it is determined as a fast phase signal, and if the amplitude of the pupil according to the duration is longer than the preset amplitude, it is determined as a slow phase signal step; and detecting the pupil movement information by extracting the movement distance, movement angle, and movement direction of the pupil according to time when it is determined that it is the slow phase signal.

In addition, the detecting of the face motion provides a stroke diagnosis method, characterized in that the face motion information is detected by extracting the rotation direction, rotation speed, and inclination of the face according to time based on a preset reference point.

In addition, the determining step includes a head impulse test, a nystagmus test, and a skew deviation from the pupil movement information detected by the first movement detection unit and the face movement information detected by the second movement detection unit. Determining whether there is an abnormality in which nervous system of the peripheral nervous system and the central nervous system by performing a test (Test of Skew); And as a result of the determination, if it is determined that there is an abnormality in the central nervous system in any one examination process selected from the head impulse test, the nystagmus test and the skew deviation test, it provides a stroke diagnosis method, characterized in that the diagnosis of stroke is provided.

The present invention has the effect of rapidly and accurately diagnosing the stroke of a subject in an emergency room of a hospital, etc. using quantitatively measured indicators, so that the diagnosis and treatment of stroke can be quickly received.

1 is a diagram schematically illustrating the overall configuration of a stroke diagnosis system according to a preferred embodiment of the present invention.
2 is a block diagram illustrating a stroke diagnosis system according to a preferred embodiment of the present invention.
3 is a diagram schematically illustrating a control module of a stroke diagnosis system according to a preferred embodiment of the present invention.
4 is a view showing eye images processed by the pupil extraction unit of the stroke diagnosis system according to a preferred embodiment of the present invention.
5 is a view showing a BPPV test result for monitoring nystagmus in a stroke diagnosis system according to a preferred embodiment of the present invention.
6 is a graph showing the movement of the pupil in nystagmus in order to apply the stroke diagnosis system according to the preferred embodiment of the present invention.
7 is a flowchart illustrating a stroke diagnosis method according to a preferred embodiment of the present invention.

Hereinafter, a stroke diagnosis system and method according to a preferred embodiment of the present invention will be described in more detail with reference to the accompanying drawings.

1 is a diagram schematically illustrating the overall configuration of a stroke diagnosis system according to a preferred embodiment of the present invention, and FIG. 2 is a block diagram illustrating a stroke diagnosis system according to a preferred embodiment of the present invention.

1 and 2 , a stroke diagnosis system 100 according to a preferred embodiment of the present invention includes a device 110 , a camera 120 , a position sensor 130 , a control module 140 , and an output unit 150 . ) is included.

The device 110 is worn on the face including the eyes of the examinee, and may be configured in various forms such as, for example, a head mounted display (HMD), glasses, or helmet, for convenience of handling. It is preferable to be manufactured in the form of glasses for this purpose.

The camera 120 is mounted on one side of the device 110 to photograph the eyes of the examinee, and may be configured to photograph one eye of the examinee, or may be configured to photograph both eyes of the examinee. Such a camera 120 may be configured as an infrared camera, for example.

The position sensor 130 is mounted on the other side of the device 110 to detect the position of the subject's face, and may include, for example, any one or more selected from a gyro sensor, an acceleration sensor, and a geomagnetic sensor. The gyro sensor may measure the azimuth of the face, the acceleration sensor may measure the tilt and acceleration of the face, and the geomagnetic sensor may measure the east, west, south, north, and south directions of the face. Using the position information detected by the position sensor 130, it is possible to know the movement of the face, such as the rotation direction, rotation speed, and inclination of the face.

The control module 140 detects the movement of the pupil from the image captured by the camera 120, detects the movement of the face from the position information of the face detected by the position sensor 130, and controls the movement of the pupil and the movement of the face. It is analyzed to determine whether or not a stroke is present, which will be described later.

The output unit 150 receives various control signals from the control module 140 and outputs them as sounds, texts, images, etc. to the outside. For example, the output unit 150 may be configured as a speaker provided in the device 110 to output sound, or may be provided in an external terminal such as a smartphone, PC, or notebook to output text. It may also be configured as a display unit. When the output unit 150 is configured as a display unit, the output unit 150 and the terminal may be connected by short-range wireless communication such as Bluetooth or wired communication.

3 is a diagram schematically illustrating a control module of a stroke diagnosis system according to a preferred embodiment of the present invention, and FIG. 4 is a step-by-step eye processed by the pupil extraction unit of the stroke diagnosis system according to a preferred embodiment of the present invention. It is a view showing an image, and FIG. 5 is a view showing a BPPV test result for tracking nystagmus in a stroke diagnosis system according to a preferred embodiment of the present invention, and FIG. 6 is a stroke diagnosis system according to a preferred embodiment of the present invention. It is a diagram showing the movement of the pupil in nystagmus in a graph for application.

3 to 6 , the control module 140 includes a pupil extraction unit 142 , a first movement detection unit 144 , a second movement detection unit 146 , and a determination unit 148 .

The pupil extractor 142 removes noise from the image of the eye received from the camera 120 to accurately extract the position of the pupil. To explain this in detail, first, the infrared camera 120 receives the image of the eye photographed, converts it to gray, performs binarization based on a preset reference value, and outputs the binarized image 142a. In the binarized image 142a, noise is removed by filtering erosion and dilate using a morphology operation. Erosion is to replace the minimum pixel value among neighboring pixels with the current pixel value, and can cause objects of small noise (small chunks) to disappear. And the expansion is to replace the maximum pixel value among the neighboring pixels with the current pixel value, and serves to make small holes inside the object disappear. That is, noise is removed through an erosion operation (142b), an empty space in an object is removed through an expansion operation (142c), and a filtered image 142d is generated by applying these erosion and expansion. Then, the circle 142e is detected from the filtered image 142d, the center point of the circle is calculated so that the detected circle 142e matches the pupil, and the calculated center point is the actual pupil in consideration of the 3D structure and curve of the pupil. The pupil position is extracted by estimating the moving distance and angle in units of pixels.

The first movement detection unit 144 detects pupil movement information by tracking the coordinates of the pupil position information extracted by the pupil extraction unit 142 . In addition, the first movement detection unit 144 may perform a Benign Paroxysmal Positional Vertigo (BPPV) Head-Rolling Test to track and observe the position of the pupil. BPPV is a test for observing nystagmus after lying down with the subject's head turned 45° to the affected side in a sitting position and keeping the head lowered by about 20°. In the BPPV test result, as shown in FIG. 5 , the highest point and the lowest point of the pupil coordinates appear periodically. And the movement of the pupil in nystagmus appears as shown in FIG. 6 . The movement of the pupil in FIG. 6 is divided into a fast phase (fp) and a slow phase (slow phase, sp), and can be distinguished using a slope. The first movement detection unit 144 calculates the slope using Equation 1 below, and when the amplitude (amplitude, a) of the pupil according to the duration (d) is shorter than the preset amplitude, the fast phase (fast phase, fp) signal, and if the amplitude of the pupil according to the duration is longer than the preset amplitude, it is determined as a slow phase signal (slow phase, sp) Extract the distance, movement angle and movement direction. Also, the first movement detection unit 144 may detect movement information of the pupil by analyzing a pattern through horizontal and vertical components.

[Equation 1]

(In Equation 1, s is the slope, d is the duration, a is the amplitude, spd is the duration of the slow phase, and fpd is the duration of the fast phase.)

The second movement detection unit 146 detects facial movement information by tracking the position information of the face detected by the position sensor 130, and the azimuth, tilt, acceleration, azimuth, etc. of the face detected by the position sensor 130 is used to detect the rotation direction, rotation speed, and inclination of the face.

The determination unit 148, the HINTS, that is, the head impulse test (Head Impulse test, HI) from the movement information of the pupil detected by the first movement detection unit 144 and the movement information of the face detected by the second movement detection unit 146 ), nystagmus (Nystagmus, N), and skewness test (Test of Skew, TS) to determine whether the cause of dizziness is the central nervous system or the peripheral nervous system. These head impulse tests, nystagmus tests, and skew deviation tests are common tests performed in the hospital emergency room to diagnose stroke.

On the other hand, if there is an abnormality in the central nervous system, objects appear in two with dizziness, speech becomes dull, or food is swallowed in many cases, and consciousness may deteriorate. If these symptoms occur after middle age, stroke disease may be suspected. On the other hand, if there is an abnormality in the peripheral nervous system, along with dizziness, otolithiasis, Meniere's disease, vestibular neuritis, etc. may be suspected. Accordingly, when dizziness occurs, HINTS is performed to determine whether the cause of the dizziness is the central nervous system (stroke) or the peripheral nervous system. As a result of the judgment, if it is determined that there is an abnormality in the central nervous system in any one of the tests selected from the head impulse test, the nystagmus test, and the skew deviation test, the occurrence of a stroke is predicted, so prepare and treat it. The criteria for diagnosing stroke using HINTS are shown in Table 1 below.

[Table 1]

Head impulse test (HI) is a test that evaluates whether both eyes can fix their gaze on the tip of the examiner's nose by quickly turning the subject's head to one side with the subject's eyes facing the tip of the examiner's nose. way. The determination unit 148 determines if the subject properly performs the head impulse test through the pupil movement information detected by the first movement detection unit 144 and the face movement information detected by the second movement detection unit 146 (positive test result). observed), it is judged that there is an abnormality in the peripheral nervous system. If the subject cannot properly perform the head impulse test (a negative reaction is observed), it is judged that there is an abnormality in the central nervous system.

Nystagmus (N) test is an unconscious, rapid, rhythmic movement of the eyes, which attempts to restore the gaze point when the eyeball does not remain in the desired position due to abnormalities in the oculomotor system or due to external factors. It is an involuntary rapid movement of the eyeball. For this nystagmus test, the determination unit 148 extracts gain, asymmetry, and phase characteristics from the slow phase signal and outputs pupil motion characteristic information.

Gain is the ratio of the amplitude of eye movements to the amplitude of head stimulation. It is calculated by dividing the maximum velocity of the slow phase pupil movement by the maximum velocity of the facial movement. This may be expressed by Equation 2 below.

[Equation 2]

For example, patients with bilateral vestibular weakness will have reduced gain at lower frequencies of rotation.

Symmetry/Asymmetry is represented by comparing the left and right equally slow phase components as they rotate left and right for each frequency. The asymmetry may be calculated by Equation 3 below.

[Equation 3]

Here, b2 denotes the ipsilesional saccade amplitude (height of the instantaneous movement signal of the eye on the injured side), and b1 denotes the contraleisonal saccade amplitude (the height of the instantaneous movement signal of the eye opposite to the injured side).

In general, the normal range of symmetry is 15-20%.

Phase is the temporal relationship between the onset of head movement and the reflex eye response. If the head and eyes move in opposite directions at exactly the same speed, the phase is considered 180°. A phase lead appears when a head movement triggers an eye reaction reflex, and a phase lag appears when the corrective eye movement proceeds. Abnormally long leads and short leads can be considered peripheral lesions and cerebellar lesions, respectively. The phase angle θ is calculated by Equation 4 below, and when perfect electrostatic reflection occurs, the phase is 0°.

[Equation 4]

(Where f denotes the frequency of the eye movement signal, and Δt denotes the time difference between the maximum velocity of the eye movement and the maximum velocity of the face movement in the slow phase.)

The determination unit 148 determines whether the vestibular function loss acts unidirectionally or in both directions when the gain is reduced or asymmetry occurs through the analysis of gain, phase difference, and symmetry. If it acts unidirectionally, it is judged that there is an abnormality in the peripheral nervous system, and if it acts in both directions, it is judged as a central nervous system, that is, a stroke.

The Skew Test (Test of Skew, TS) measures changes in the vertical and horizontal position of the pupil in a dark environment and in a light environment for a certain period of time by configuring an environment without light in only one eye by alternating both eyes. When a change is detected in the vertical and horizontal positions of the pupil through the skew test, the determination unit 148 determines that there is an abnormality in the central nervous system and diagnoses a stroke. If no change is detected, it is determined that there is an abnormality in the peripheral nervous system. .

As such, the determination unit 148 performs a head impulse test, a nystagmus test and a skew deviation test from the pupil movement information detected by the first movement detection unit 144 and the face movement information detected by the second movement detection unit 146, and , by substituting the progress results in Table 1, it is determined whether there is an abnormality in either the peripheral nervous system or the central nervous system. As a result of the determination, the determination unit 148 determines that there is an abnormality in the central nervous system in any one examination process selected from the head impulse test, the nystagmus test, and the skew deviation test, or that there is an abnormality in the central nervous system in two or more examination processes. It is diagnosed as having a stroke.

7 is a flowchart illustrating a stroke diagnosis method according to a preferred embodiment of the present invention.

Referring to the drawings, in the stroke diagnosis method according to the preferred embodiment of the present invention, first, the device 110 is worn on the face including the eyes of the subject. Thereafter, the control module 140 controls the camera 120 mounted on the device 110 to photograph the subject's eyes (S100), and then controls the position sensor 130 to detect the position of the subject's face ( S110).

Thereafter, the pupil extraction unit 142 of the control module 140 extracts the position of the pupil by removing noise from the image of the eye received from the camera 120 ( S120 ).

Next, the first movement detection unit 144 of the control module 140 detects the pupil movement information by tracking the coordinates of the pupil position information extracted by the pupil extraction unit 142 . At this time, the first movement detection unit 144 detects the movement information of the pupil by extracting the movement distance, movement angle, and movement direction of the pupil according to time based on a preset reference point. Here, when the amplitude of the pupil according to the duration is shorter than the preset amplitude, the first movement detection unit 144 determines that it is a fast phase signal, and when the amplitude of the pupil according to the duration is longer than the preset amplitude, it is determined that it is a slow phase signal. . Thereafter, when it is determined that the signal is a slow phase, the first movement detection unit 144 extracts the movement distance, movement angle, and movement direction of the pupil according to time to detect movement information of the pupil ( S130 ).

Next, the second movement detection unit 146 of the control module 140 detects the movement information of the face by tracking the position information of the face detected by the position sensor 130 . Here, the second movement detecting unit 146 extracts the rotation direction, rotation speed, and inclination of the face according to time based on a preset reference point to detect movement information of the face ( S140 ).

Next, the determination unit 148 of the control module 140 performs a nystagmus test, a head impulse test, and a test of skew from the pupil movement information and the facial movement information. For example, the determination unit 148 outputs to the output unit 150 a guide message for allowing the doctor of the emergency room to perform a nystagmus examination on the subject. And when the doctor proceeds with the nystagmus examination, the determination unit 148 determines whether there is an abnormality in which of the peripheral nervous system and the central nervous system has pupil movement information and facial movement information. Next, the determination unit 148 outputs a guide message for the doctor to proceed with the head impulse test to the output unit 150 . And when the doctor proceeds with the head impulse test, the determination unit 148 determines whether there is an abnormality in which of the peripheral nervous system and the central nervous system has pupil movement information and facial movement information. Next, the determination unit 148 outputs a guide message for the doctor to proceed with the skew deviation test to the output unit 150 . And, when the doctor proceeds with the skew deviation test, the determination unit 148 determines whether there is an abnormality in which one of the peripheral nervous system and the central nervous system has pupil movement information and face movement information. Finally, if the determination unit 148 determines that there is an abnormality in the central nervous system in any one examination process selected from the nystagmus test, the head impulse test, and the skew deviation test, the determination unit 148 diagnoses a stroke, and the output unit 150 outputs the diagnosis result. to control to do so (S150).

As such, the present invention is configured to diagnose a stroke when it is determined that there is an abnormality in the central nervous system during any of the HINTS tests using indicators quantitatively measured from the subject, that is, pupil movement information and face movement information. It is possible to quickly and accurately diagnose a stroke by using the phosphorus index, which has the effect of promptly receiving diagnosis and treatment of stroke.

In addition, the present invention can reduce the misdiagnosis rate for stroke diagnosis, thereby reducing unnecessary medical costs.

Although the present invention has been described in detail in the above embodiments, it goes without saying that the present invention is not limited thereto, and it is apparent to those skilled in the art that various changes and modifications can be made within the scope of the technical spirit of the present invention. If it falls within the scope of the claims, the technical idea should also be regarded as belonging to the present invention.

100: stroke diagnosis system
110: device 120: camera
130: position sensor 140: control module
142: pupil extraction unit 144: first movement detection unit
146: second movement detection unit 148: determination unit
150: output unit

Claims (14)

a camera mounted on one side of a device worn on a face including the eyes of the examinee and photographing the eyes of the subject;
a position sensor mounted on the other side of the device and configured to detect the position of the subject's face; and
Control for detecting the movement of the pupil from the image taken by the camera, detecting the movement of the face from the position information of the face detected by the position sensor, and analyzing the movement of the pupil and the movement of the face to determine whether a stroke module; includes;
The control module includes:
a pupil extraction unit for extracting the position of the pupil from the image captured by the camera; and
Includes; a first movement detection unit for detecting the movement information of the pupil by tracking the coordinates for the position of the pupil extracted by the pupil extraction unit;
The first movement detection unit determines that it is a fast phase signal when the amplitude of the pupil according to the duration is shorter than a preset amplitude, and determines that it is a slow phase signal when the amplitude of the pupil according to the duration is longer than the preset amplitude , when it is determined that the slow phase signal is the stroke diagnosis system, characterized in that extracting the movement distance, movement angle, and movement direction of the pupil according to time.
The method of claim 1,
The control module includes:
a second movement detection unit for detecting movement information of the face by tracking the position information of the face detected by the position sensor; and
The stroke diagnosis system further comprising: a determination unit that determines whether a stroke occurs by analyzing the pupil motion information detected by the first movement detection unit and the facial movement information detected by the second movement detection unit.
The method of claim 1,
The camera is composed of an infrared camera,
The pupil extraction unit removes noise from the image of the eye received from the camera to extract the position of the pupil.
The method of claim 1,
The first movement detector extracts the movement distance, movement angle, and movement direction of the pupil according to the duration based on a preset reference point to detect movement information of the pupil.
delete 3. The method of claim 2,
The second movement detection unit extracts the rotation direction, rotation speed, and inclination of the face according to time based on a preset reference point to detect the movement information of the face.
3. The method of claim 2,
The determination unit, from the movement information of the pupil detected by the first movement detection unit and the face movement information detected by the second movement detection unit, a head impulse test, a nystagmus test, and a skew deviation test (Test) of Skew) to determine whether there is an abnormality in either the peripheral nervous system or the central nervous system. A stroke diagnosis system, characterized in that it is diagnosed as a stroke if judged to be.
a photographing step in which the control module controls a camera mounted on one side of a device worn on a face including the eyes of the examinee so that the camera captures the eyes of the examinee;
a sensing step in which the control module controls a position sensor mounted on the other side of the device so that the position sensor detects a position of the subject's face; and
The control module detects the movement of the pupil from the image captured by the camera, detects the movement of the face from the position of the face sensed by the position sensor, and analyzes the movement of the pupil and the movement of the face for a stroke A judgment step of determining whether
In the judgment step,
The control module obtains the location information of the pupil from the image taken by the camera,
The control module detects the movement information of the pupil by tracking the movement coordinates for the position information of the pupil,
In the pupil motion information detection,
If the amplitude of the pupil according to the duration is shorter than the preset amplitude, it is determined as a fast phase signal, and if the amplitude of the pupil according to the duration is longer than the preset amplitude, it is determined as a slow phase signal, but a slow phase signal Stroke diagnosis method, characterized in that extracting the movement distance, movement angle, and movement direction of the pupil according to time when it is determined that the
9. The method of claim 8,
In the judgment step,
a second movement detection unit of the control module tracks the position of the face detected by the position sensor to detect movement information of the face; and
Stroke diagnosis method, characterized in that the determination unit of the control module analyzes the motion information of the pupil and the motion information of the face to determine whether or not a stroke is present.
9. The method of claim 8,
In the judgment step,
Stroke diagnosis method, characterized in that the pupil extraction unit of the control module obtains the position of the pupil by removing noise from the infrared image taken by the camera.
9. The method of claim 8,
In the pupil motion information detection,
The first movement detection unit of the control module extracts the movement distance, movement angle, and movement direction of the pupil according to time based on a preset reference point to detect movement information of the pupil.
delete 9. The method of claim 8,
In the face motion detection,
Stroke diagnosis method, characterized in that the second movement detection unit of the control module detects movement information of the face by extracting the rotation direction, rotation speed, and inclination of the face according to time based on a preset reference point.
9. The method of claim 8,
In the judgment step,
The determination unit of the control module performs a head impulse test, a nystagmus test, and a skew deviation test from the pupil movement information detected by the first movement detection unit and the face movement information detected by the second movement detection unit. (Test of Skew) to determine whether there is an abnormality in either the peripheral nervous system or the central nervous system;
The determination unit of the control module, when it is determined that there is an abnormality in the central nervous system in any one test selected from the head impulse test, the nystagmus test, and the skew deviation test, it is diagnosed as a stroke.

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