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WO2018164361A1 - Dispositif de test vidéo de nystagmus et procédé utilisant une caméra infrarouge - Google Patents

Dispositif de test vidéo de nystagmus et procédé utilisant une caméra infrarouge Download PDF

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Publication number
WO2018164361A1
WO2018164361A1 PCT/KR2018/000114 KR2018000114W WO2018164361A1 WO 2018164361 A1 WO2018164361 A1 WO 2018164361A1 KR 2018000114 W KR2018000114 W KR 2018000114W WO 2018164361 A1 WO2018164361 A1 WO 2018164361A1
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WO
WIPO (PCT)
Prior art keywords
image
pupil
infrared
eye
outputting
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Application number
PCT/KR2018/000114
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English (en)
Korean (ko)
Inventor
남윤영
공영선
Original Assignee
순천향대학교 산학협력단
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Priority to CN201880009670.6A priority Critical patent/CN110325104B/zh
Publication of WO2018164361A1 publication Critical patent/WO2018164361A1/fr

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4863—Measuring or inducing nystagmus
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
    • A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
    • A61B3/113—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions for determining or recording eye movement
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/18—Eye characteristics, e.g. of the iris
    • G06V40/193—Preprocessing; Feature extraction

Definitions

  • the present invention relates to a video nystagmus testing apparatus and method, and more particularly, to rotate the patient from side to side to affect the vestibular organ of the patient and analyze the infrared pupil image taken by the infrared camera based on the rotation conditions of the patient.
  • the present invention relates to a video nystagmus test apparatus and method using an infrared camera to perform a nystagmus test on a patient.
  • Dizziness is so common that there are statistics that one in five adults experienced more than once a year.
  • Dizziness usually occurs when an abnormality occurs in the ear (peripheral), brain (central), heart, eyes, and the like.
  • VOR Vestibular-Ocular Reflex
  • Vestibular reflection helps to fix the eye by moving the eye in the opposite direction of the head's rotation.
  • Compensatory Eye Movement is induced by sensing angular acceleration in the semicircular vestibular system and called nystagmus.
  • Vestibular dysfunction or nystagmus, is a disorder in which the target escapes from the center and causes shaking of the field of vision.
  • ENG electro-nystagmography
  • SSCS sclera search coil system
  • electrostable recording method is sensitive to changes in electrode attachment state or changes in skin resistance due to sweat, etc. according to the movement of the patient, and thus requires frequent calibration of the device. There was a problem that the difficulty in the examination in patients not good.
  • the sclera search coil system is a method of three-dimensionally graphing the intensity change of the magnetic field of the muscle generated during eye movement after contacting the sclera with a contact lens-type device with a wire embedded therein.
  • the sclera search coil system has the advantage of receiving more accurate signals and capturing minute eye movements compared to electrospinography.
  • an object of the present invention is to rotate the patient from side to side affects the vestibular organ of the patient and based on the rotation conditions of the infrared camera to analyze the infrared pupil images taken by the infrared camera to perform a nystagmus test for the patient
  • An apparatus and method for testing video nystagmus are provided.
  • the nystagmus inspection unit the rotation control unit for controlling the rotation of the rotary chair according to the rotation control information preset for the nystagmus test;
  • An infrared image acquisition unit configured to control and drive the infrared image capture unit, and to acquire and output the infrared eye image through the infrared image capture unit;
  • An image processor configured to detect the pupil after binarizing the obtained infrared eye image and output image data of the detected pupil;
  • a pupil motion detector for receiving and analyzing the image data and outputting pupil motion characteristic information on pupil movement;
  • an nystagmus determination unit that performs an nystagmus test and analyzes nystagmus by analyzing the detected pupil movement characteristic information based on the rotation control information.
  • the image processing step may include: an ROI designation step of outputting an infrared front eye part image including only the front eye part from the infrared eye image; An image conversion step of binarizing the infrared eyepiece image and outputting a binarized eyeball image; An edge detection step of detecting an outline of an anterior eye part from the binarized anterior eye part image and outputting an anterior eye image; And a circle detection step of detecting a pupil from the frontal image of the front part, detecting a center point of the pupil, and outputting image data of the pupil according to the movement to the detected center point.
  • the circle detection step may be input from an anterior eye region outline image detection unit for at least two or more binarized anterior eye segment images converted based on a plurality of changed reference values, and detect a circle from each anterior eye segment outline image.
  • An optimal circle detection step of selecting and outputting an image of an anterior part of the eye where the circle corresponds to the pupil; And calculating a center point of the circle for the selected anterior eyelid image, and outputting the pupil image data by estimating the distance and angle of the actual pupil movement in pixel units in consideration of the three-dimensional structure and curve of the pupil.
  • an image calibration step may be input from an anterior eye region outline image detection unit for at least two or more binarized anterior eye segment images converted based on a plurality of changed reference values, and detect a circle from each anterior eye segment outline image.
  • the pupil motion detecting step may include: a first interpolation step of receiving the image data and applying a linear spline algorithm to interpolate a signal missing due to blinking to output a first interpolated image signal; A derivative step of obtaining a slope from the first interpolated image signal and outputting a differential image signal obtained by squaring the slope; A fast phase removing step of applying a differential video signal to the first interpolated video signal and outputting a slow phase signal from which a fast phase signal is removed from the first interpolated video signal; A second interpolation step of interpolating and outputting the slow phase signal by applying a linear spline algorithm; A filtering step of filtering and outputting the interpolated slow phase signal; And extracting gain, asymmetry and phase characteristics from the slow phase signal to output the pupil motion characteristic information.
  • FIG. 7 is a diagram illustrating a horizontal pupil signal for horizontal pupil data according to an embodiment of the present invention.
  • FIG. 9 is a view illustrating a signal processing process of a slow phase signal in the pupil motion detector according to the present invention.
  • Rotating chair 300 is configured in the form of a chair that the patient can sit and rotates the chair by adjusting the direction and speed under the control of the nystagmus test unit 400.
  • FIG. 2 is a diagram illustrating a detailed configuration of a nystagmus testing unit of a video nystagmus test apparatus according to the present invention.
  • the nystagmus checker 400 includes a rotation controller 410, an infrared image acquisition unit 420, an image processor 430, a pupil motion detector 440, and an nystagmus determination unit 450.
  • the rotation controller 410 controls the rotation direction and the rotation speed of the swivel chair 300 according to the rotation control information preset for the nystagmus test.
  • the pupil motion detector 440 receives the image data and analyzes the image data, and outputs pupil movement characteristic information on the movement of the pupil to the nystagmus determination unit 450.
  • the nystagmus determination unit 450 receives the rotation control information from the rotation control unit 410, analyzes the pupil movement characteristic information detected based on the rotation control information, performs an nystagmus test, and determines whether or not nystagmus is determined. It is displayed through the display unit 100.
  • FIG. 3 is a view showing the detailed configuration of the image processing unit of the nystagmus test unit according to the present invention
  • Figure 4 is a view showing the eye image step-by-step processed by the image processing unit according to the present invention
  • Figure 5 is an image applied according to the present invention
  • the detailed configuration and operation of the image processor 430 will be described with reference to FIGS. 3 to 5.
  • the ROI designator 431 outputs to the image converting unit 432 the infrared front eye region image 502 obtained by extracting only the front eye portion from the infrared eye image 501 of FIG. 4 input from the infrared image acquisition unit 420.
  • the eyepiece portion may be selected by an administrator through the input unit 500 or may be configured to be automatically detected by eye pattern detection.
  • the image converter 432 binarizes the infrared ray eyepiece image obtained through the ROI designator 431 and outputs the binarized eyeball image 503.
  • the binarization is performed by converting a pixel value of a gray front eye image converted into a gray channel exceeding a preset reference value to 255, and converting the following values to zero.
  • the preset reference value may be one, or may be two or more.
  • the second image converter 434 performs binarization corresponding to each reference value and binarization pre-image part 504 for each reference value.
  • the filtering unit 435 transmits the binarized eyeball image 504 from which the noise included in the binarized eyepiece image 503 input from the second image converter 434 is removed to the outline detector 436.
  • the outline detector 436 detects the outline of the anterior eye part from the binarized anterior eye part image 504 filtered by the filtering part 435, and transmits the front eye part outline image 505 to the original detector 437.
  • the circle detector 437 detects a circle corresponding to the pupil from the voltage portion outline image 505 input from the outline detector 436, and outputs the detected circle, that is, the image data of the pupil according to the movement of the pupil.
  • the original detector 437 may convert at least two or more binarization conversions based on a plurality of changed reference values.
  • An anterior eye image (505) for the ocular image (503) is received from the outline detector (436), a circle (506) is detected from each anterior eye image (505), and the detected circle (506) is applied to the pupil.
  • An optimal circle detector 438 that selects and outputs a matching anterior eye image 505 and calculates a center point of a circle for the selected anterior eye image, and considers the calculated center point in consideration of the three-dimensional structure and curve of the pupil.
  • the image calibrator 439 may output an image data of the pupil by estimating the distance and angle of the actual pupil in pixels.
  • the optimal circle detector 438 acquires binarized frontal eye contour images 505-1, 505-2, 505-3, and 505-4 by applying different reference values as shown in FIG. 5.
  • the circle 506 is detected from the eyeball outline images, the circle will be detected as shown in FIGS. 511-1 to 511-4 of FIG. 5.
  • 505-1 is a case where 262 is applied as a reference value
  • 505-2 is a case where 270 is applied as a reference value
  • 505-3 is a case where 275 is applied as a reference value
  • 505-4 is a case where 285 is applied as a reference value. It is shown.
  • the optimal circle detector 438 selects and outputs an anterior eye region outline image 505-3 for 511-3 in which the pupil and the detected circle 506 coincide among the 511-1 to 511-4.
  • the image calibration unit 439 needs to convert an eye movement unit to an angle in an image.
  • the angle is 0.49 ms per pixel.
  • FIG. 6 is a view showing a detailed configuration of the pupil motion detection unit of the nystagmus test unit according to the present invention
  • Figure 7 is a view showing a horizontal pupil signal for the horizontal pupil data according to an embodiment of the present invention
  • Figure 8 is a present invention 9 is a view illustrating a signal waveform for each step of image processing in a pupil motion detector according to an embodiment of the present invention
  • FIG. 9 is a view for explaining a signal processing process of a slow phase signal in a pupil motion detector according to the present invention
  • FIG. FIG. 11 is a diagram illustrating a gain curve according to a stimulus frequency
  • FIG. 11 is a diagram illustrating a phase curve according to a rotational stimulation frequency of the present invention.
  • the pupil motion detector 440 includes a first interpolator 441, a differentiator 442, a fast phase remover 443, a second interpolator 444, a filter 445, a slow phase signal detector 446, and Feature extraction unit 447 is included.
  • the first interpolator 441 receives the image data from the image processor 430 and applies a linear spline algorithm to interpolate the missing signal due to blinking to output the first interpolated image signal.
  • a frame in which no pupil is detected due to blinking may be set to a negative value.
  • the fast phase remover 443 applies the differential image signal to the first interpolated image signal, and thus, a fast phase signal corresponding to the dotted rectangle as shown at 804 of FIG. 8 in the first interpolated image signal illustrated at 801 of FIG. 8. Outputs a slow phase signal such as 901 of FIG.
  • Phase is the time relationship between the onset of head movement and the reflex eye reaction. If the head and eyes move in opposite directions at exactly the same speed, the phase is assumed to be 180 Hz. A phase lead appears when the movement of the head causes an eye response reflection, and a phase lag appears when the correction eye movement proceeds. Abnormally long leads and short leads can be considered peripheral and cerebellar lesions, respectively.
  • f represents the frequency of the eye movement signal
  • ⁇ t represents the time difference between the maximum velocity of slow phase eye movement and head (chair) movement.
  • the pupil motion detector 440 interpolates in a second order by applying a linear spline algorithm and outputs the second interpolated signal (S317).
  • the second interpolated slow phase signal is filtered using a low pass filter (S319), and motion feature information including gain, asymmetry, and phase information is extracted from the low pass filtered slow phase signal and output to the nystagmus determination unit 450. do.

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Abstract

La présente invention concerne un dispositif et un procédé de test vidéo de nystagmus et, plus spécifiquement, un dispositif et un procédé de test vidéo de nystagmus utilisant une caméra infrarouge, le dispositif et le procédé faisant tourner un patient vers la gauche et vers la droite de façon à influer sur un organe vestibulaire du patient, et analyser, sur la base de l'état de rotation du patient, une image de pupille infrarouge capturée par la caméra infrarouge, de façon à effectuer un test de nystagmus sur le patient.
PCT/KR2018/000114 2017-03-06 2018-01-03 Dispositif de test vidéo de nystagmus et procédé utilisant une caméra infrarouge WO2018164361A1 (fr)

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CN201880009670.6A CN110325104B (zh) 2017-03-06 2018-01-03 利用红外摄像机的影像眼震颤检查装置及方法

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KR1020170028235A KR101905716B1 (ko) 2017-03-06 2017-03-06 적외선 카메라를 이용한 비디오 안진 검사 장치 및 방법

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CN114170192A (zh) * 2021-12-10 2022-03-11 武汉工程大学 星载光学相机焦面震颤精细检测方法
CN114617529A (zh) * 2022-05-12 2022-06-14 上海志听医疗科技有限公司 一种用于眼罩设备的眼球眩晕数据识别方法及系统
EP3991705A4 (fr) * 2019-06-25 2023-07-05 Korea University Research and Business Foundation Appareil d'évaluation et de rééducation du réflexe vestibulo-oculaire reposant sur un capteur de signal biologique et d'un jeu de réalité virtuelle

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KR102198356B1 (ko) * 2018-11-28 2021-01-04 연세대학교 원주산학협력단 휴대용 안진기 및 이의 캘리브레이션 방법
KR102293430B1 (ko) * 2019-09-23 2021-08-27 고려대학교 산학협력단 가상현실 및 생체신호 센서 기반의 전정-안반사 기능 평가 장치
KR102305387B1 (ko) * 2019-07-05 2021-09-27 순천향대학교 산학협력단 양성돌발성 두위 현훈 진단을 위한 안진 검사 장치 및 검사 방법
KR102349805B1 (ko) * 2019-12-20 2022-01-11 순천향대학교 산학협력단 뇌졸중 진단 시스템 및 방법
CN113065398B (zh) * 2021-03-04 2022-10-11 武汉大学 一种眼球震颤监测方法及系统
KR20240172006A (ko) 2023-05-30 2024-12-09 연세대학교 원주산학협력단 비디오 안진 검사를 위한 동공 트래킹 방법 및 장치
KR102748232B1 (ko) 2023-08-29 2024-12-31 주식회사 뉴로이어즈 비디오 영상의 안구 및 두위 변화를 추적하는 초고속 경량 딥러닝 모델을 이용한 어지럼증 진단 장치, 방법, 이를 구현하기 위한 프로그램이 저장된 기록매체 및 기록매체에 저장된 컴퓨터 프로그램

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CN114617529A (zh) * 2022-05-12 2022-06-14 上海志听医疗科技有限公司 一种用于眼罩设备的眼球眩晕数据识别方法及系统
CN114617529B (zh) * 2022-05-12 2022-08-26 上海志听医疗科技有限公司 一种用于眼罩设备的眼球眩晕数据识别方法及系统

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