JP6019517B2 - Eye movement analysis system, eye movement diagnosis device, and method of operating eye movement analysis system - Google Patents

Description

The present invention relates to an eye movement analysis system, an eye movement diagnosis apparatus, and an operation method of the eye movement analysis system , and more particularly to an eye movement analysis system, an eye movement diagnosis apparatus, and an eye movement analysis system that analyze eye movement data in a balance function test. Relates to the method of operation .

  In otolaryngology, neurology, neurosurgery, etc., in the treatment of dizziness and balance dysfunction, how the eyeball moves in response to eye stimulation, head stimulation, or ear stimulation Equilibrium function tests are widely conducted. This balanced function test detects, for example, various accelerations caused by the human body by comparing eye movements with a healthy person by stimulating the head horizontally, more specifically, by stimulating the neck to the left or right. Check for abnormalities in the balance function system such as the vestibule and the semicircular canal.

  For balance function tests, vestibular eye reflex (VOR: VESTIBULO-OCULAR REFLEX), natural vision vestibular reflex (Vis-VOR: VISUAL-VESTIBULO-OCULAR REFLEX), fixation vestibule reflex (VOR-FIX: FIXATION SUPPRESSION OF THE) Some test VESTIBULO-OCULAR REFLEX).

  As a method for recording and observing eye movements used for such an equilibrium function test, there are visual observation, observation under Frenzel glasses, chromography, movie shooting, video recording, electrical or optical recording method, electromagnetic recording method and the like. In recent years, the electro-hybridometer (ENG: ELECTRO-NYSTAGMOGRAPHY), which is an electrical recording method, the search coil method, which is an electromagnetic recording method, or the eyeball is imaged with a video camera, and the moving image is observed and recorded The method of doing is attracting attention. By using these methods, objective eye movement data can be obtained. A specific configuration of the balance function inspection apparatus is disclosed in Patent Document 1, for example.

  One of the methods for analyzing eye movements from data obtained from the balance function testing apparatus is an analysis method using vestibulo-ocular reflex. Vestibulo-oculomotor reflex is a reflection in which the eyeball moves in the opposite direction when the head is rotated. When acceleration stimulation in a certain direction continues, the eyeball is gradually displaced in the opposite direction and rapidly Repeat the regular movement to return to the original. Of the repetitive eye movements, the part where the eyeball position is gradually displaced is called the slow phase, and the part where the eyeball position returns rapidly to the original position is called the rapid phase. The phenomenon in which these two phases appear alternately is known as nystagmus, and the time series data of this nystagmus is called nystagmus data.

  When analyzing vestibulo-oculomotor reflexes from nystagmus data or for diagnosing dizziness, it can be divided into a rapid phase caused by a central action such as the cerebellum and a slow phase caused by vestibulo-ocular reflex. It was necessary to properly separate nystagmus data.

  Conventionally, various methods for separating nystagmus data into a rapid phase portion and a slow phase portion have been proposed. For example, in Patent Document 2, fuzzy set theory is applied to nystagmus data, and a membership value obtained from a difference of nystagmus data is compared with a threshold value so that the nystagmus data includes a rapid phase portion and a slow phase portion. A method for separating them is disclosed.

JP-A-9-285468 Japanese Patent Laid-Open No. 2007-20802

  However, in the conventional eye movement analysis system, as shown in Patent Document 2, when using a method of separating eye movement data (nystagmus data) into a rapid phase part and a slow phase part according to a threshold, There is a problem that an expected result cannot be obtained unless a proper threshold is set. Furthermore, in the conventional eye movement analysis system, it is not possible to easily confirm whether or not the eye movement data can be appropriately separated into the slow phase and the rapid phase immediately from the obtained results. was there.

  In addition, in the conventional eye movement analysis system, it is not possible to easily confirm how much the result obtained by changing the threshold value changes, and an operation for selecting an appropriate threshold value while changing the threshold value is performed. I could not. The eye movement analysis system cannot provide information necessary for diagnosing eye movement unless the eye movement data can be properly separated from the rapid phase part and the slow phase part. It was.

  Furthermore, in the diagnosis of eye movement so far, the slow phase and the rapid phase have been treated separately. However, since the slow phase and the rapid phase appear alternately in succession, it is expected that there is some correlation between the slow phase and the rapid phase. There is a possibility that information on the correlation has been overlooked in the conventional eye movement examination methods.

Therefore, the present invention has been made to solve the above problems, and it is easy to confirm whether or not eye movement data can be appropriately separated into a slow phase and a rapid phase. It is an object of the present invention to provide an eye movement analysis system, an eye movement diagnosis apparatus, and an operation method of an eye movement analysis system that can handle a slow phase and a rapid phase in an integrated manner.

  An eye movement analysis system according to the present invention is an eye movement analysis system for analyzing eye movement data in an equilibrium function test, and includes an input unit for inputting eye movement data measured in the balance function test, and an input from the input unit. A phase separation unit that separates the motion data into a slow phase and a rapid phase in eye movement based on a predetermined threshold, and a plurality of slow phases and a plurality of rapid phases separated by the phase separation unit, and an eyeball in the slow phase An angle detection unit that detects an angle formed by the first displacement vector of the first eye and the second displacement vector of the eyeball in the rapid phase next to the slow phase, and the first displacement vector and the second displacement vector detected by the angle detection unit A distribution calculation unit that calculates a frequency distribution of the angles formed; and an output unit that outputs a result including the frequency distribution calculated by the distribution calculation unit.

Preferably, the output unit includes a display unit that displays the frequency distribution calculated by the distribution calculation unit.
Preferably, the display unit displays the frequency distribution as a histogram.

  Preferably, the display unit displays the frequency distribution calculated by the distribution calculation unit and also displays exercise data corresponding to the frequency distribution.

  Preferably, the display unit displays the slow phase portion and the rapid phase portion of the exercise data to be displayed so as to be distinguishable.

  Preferably, the display unit further includes a display range changing unit that changes a display range of the exercise data displayed on the display unit based on a user's input operation, and the distribution calculation unit is included in the display range changed by the display range changing unit. The frequency distribution of the angle formed by the first displacement vector and the second displacement vector detected from the motion data to be detected is calculated again, and the display unit displays the frequency distribution calculated again.

  Preferably, the apparatus further includes a threshold value changing unit that changes the threshold value of the phase separation unit, and the phase separation unit separates the motion data again into the slow phase and the rapid phase based on the threshold value changed by the threshold value changing unit, and the angle detection unit. Detects again the angle formed by the first displacement vector and the second displacement vector based on the slow phase and the rapid phase separated again, and the distribution calculation unit calculates the first displacement vector and the second displacement vector detected again. The frequency distribution of the angle formed is calculated again, and the display unit displays the frequency distribution calculated again.

  Preferably, a statistical calculation unit that calculates statistical data of an angle formed by the first displacement vector and the second displacement vector detected by the angle detection unit is further provided, and the display unit displays the statistical data calculated by the statistical calculation unit. .

  Preferably, the movement data is eyeball position data obtained by sampling the angle of the eyeball at the rotational movement center of the eyeball at a predetermined interval, and the phase separation unit calculates an angular velocity of the eyeball from a difference between adjacent eyeball position data, The eye position data in which the calculated angular velocity of the eyeball is equal to or greater than the threshold is separated into a rapid phase, and the angle detection unit includes first eye position data that changes from a rapid phase to a slow phase, A vector connecting the two eyeball position data is a first displacement vector, and a vector connecting the second eyeball position data and the third eyeball position data changing from the rapid phase to the slow phase is the second displacement vector.

  An eye movement diagnosis apparatus according to the present invention includes an equilibrium function inspection apparatus that measures eye movement data in an equilibrium function inspection, and any one of the eye movement analysis systems described above.

An operation method of an eye movement analysis system according to the present invention is an operation method of an eye movement analysis system for analyzing eye movement data in an equilibrium function test, and an input step for inputting the eye movement data measured in the balance function test. And a phase separation step for separating eye movement data input from the input step into a slow phase and a rapid phase in eye movement based on a predetermined threshold, and a plurality of slow phases and a plurality of rapid phases separated in the phase separation step In contrast, an angle detection step for detecting an angle between the first displacement vector of the eyeball in the slow phase and the second displacement vector of the eyeball in the rapid phase next to the slow phase, and the first displacement detected in the angle detection step A distribution calculating step for calculating the frequency distribution of the angle formed by the vector and the second displacement vector, and a result including the frequency distribution calculated by the distribution calculating step. And an output step of.

An eye movement analysis system, an eye movement diagnosis apparatus, and an eye movement analysis system operating method according to the present invention include a first displacement vector of an eyeball in a slow phase and a second displacement vector of an eyeball in a rapid phase next to the slow phase. By calculating the frequency distribution of the angles formed, it is possible to easily confirm whether or not the eye movement data can be appropriately separated into the slow phase and the rapid phase. Further, according to the present invention, it is possible to objectively evaluate whether or not an appropriate threshold is set from the frequency distribution of the angles formed by the first displacement vector and the second displacement vector. Furthermore, in the present invention, by analyzing the angle formed by the first displacement vector and the second displacement vector based on the appropriately separated slow phase and rapid phase, and the frequency distribution of the angle formed, the analysis and evaluation of eye movement can be performed. Information necessary for diagnosis can be provided.

It is the schematic which shows the basic composition of the eye movement analysis system which concerns on embodiment of this invention. It is a block diagram which shows the structure of the eye movement analysis system which concerns on embodiment of this invention. It is a flowchart for demonstrating operation | movement of the eye movement analysis system which concerns on embodiment of this invention. It is a figure for demonstrating an eyeball position. It is a figure which shows an example of the nystagmus data which arranges eyeball position data in time series, and two phases, a slow phase and a rapid phase, appear alternately. It is a figure for demonstrating the angular velocity of the eyeball calculated from the nystagmus data shown in FIG. It is a figure for demonstrating the angle | corner which the 1st displacement vector of a slow phase and the 2nd displacement vector of a rapid phase make. It is a figure which shows an example of the analysis result which the eye movement analysis system which concerns on embodiment of this invention outputs. It is a figure which shows another example of the analysis result which the eye movement analysis system which concerns on embodiment of this invention outputs. It is a figure which shows another example of the analysis result which the eye movement analysis system which concerns on embodiment of this invention outputs. It is a flowchart for demonstrating operation | movement of the eye movement analysis system which concerns on the modification of embodiment of this invention. It is a figure which shows an example of the scatter diagram which the eye movement analysis system which concerns on the modification of embodiment of this invention outputs.

Hereinafter, embodiments according to the present invention will be described with reference to the drawings.
(Embodiment)
FIG. 1 is a schematic diagram showing a basic configuration of an eye movement diagnosis apparatus according to an embodiment of the present invention. An eye movement diagnosis apparatus 100 shown in FIG. 1 analyzes an eye movement E motion data (hereinafter also referred to as nystagmus data) in an equilibrium function test, and an eye movement E motion data in an equilibrium function test. And an eye movement analysis system. The balanced function testing apparatus is a video that AD-converts a moving image captured by an imaging camera 1 configured with a CCD (Charge Coupled Device) camera, a computer 2 configured with a personal computer, a head motion sensor 3, and the imaging camera 1. An input board 4 and an A / D board 5 for AD converting the measurement signal Va output from the head movement sensor 3 are included.

  The balance function testing apparatus gives a predetermined stimulus to the head of the subject, observes the vestibular eye reflection, the natural vision vestibular eye reflection, and the fixation vestibular eye reflection, and the movement of the eyeball E at this time is captured by the imaging camera 1. The captured moving image is captured by the computer 2 via the video input board 4. As a configuration for imaging the movement of the eyeball, there is a balanced function inspection apparatus disclosed in Japanese Patent Laid-Open No. 9-285468 (Japanese Patent No. 3455638). The configuration proposed for the balance function testing apparatus is a goggle-type eyeball observation wearing device, and the subject wears this goggles and images the movement of the eyeball E by rotating the head. An image is taken with the camera 1.

  Since the moving image captured by the imaging camera 1 is output in the form of a video signal, the video signal is taken into the computer 2 via the video input board 4. The computer 2 samples the captured moving image of the eyeball E for each frame or field, binarizes the sampled image, and detects the motion center O (see FIG. 4) of the eyeball E by the ellipse approximation method. Furthermore, the computer 2 performs predetermined calculation processing, and calculates the angular position of the pupil center with respect to the movement center O of the eyeball E as eyeball position data. Note that the method of obtaining the eye movement center O from the eyeball image using the ellipse approximation method is disclosed in detail in Japanese Patent Laid-Open No. 8-145644, and therefore the description thereof will not be repeated.

  The computer 2 arranges the calculated eyeball position data in time series, and stores it in a storage unit (not shown) as nystagmus data in which two phases of a slow phase and a rapid phase appear alternately. The nystagmus data stored in the storage unit can be saved as a data file in an external storage medium, transmitted to the outside via a LAN, or analyzed by an eye movement analysis system described later. .

  The head movement sensor 3 uses an angular velocity sensor, an angle sensor, an angular acceleration sensor, or the like, and outputs a measurement signal Va corresponding to the movement of the subject's head. The computer 2 takes in the measurement signal Va via the AD board 5 and stores it in a storage unit (not shown) in synchronization with the eyeball position data. As disclosed in Japanese Patent Application Laid-Open No. 11-225967 (Patent No. 3730005), the computer 2 stores the eyeball position data stored in the storage unit and data such as the angular velocity of the head movement based on the measurement signal Va. By analyzing in combination, the data analyzed as more reliable diagnostic data can be used.

  Next, an eye movement analysis system for analyzing nystagmus data will be described. The eye movement analysis system will be described below as a system configured by software executed by the computer 2 shown in FIG. 1, but the present invention is not limited to this and is a system in which each unit is configured as dedicated hardware. There may be.

  FIG. 2 is a block diagram showing the configuration of the eye movement analysis system according to the embodiment of the present invention. The eye movement analysis system 22 illustrated in FIG. 2 includes an input unit 221, a phase separation unit 223, an angle detection unit 224, a distribution calculation unit 225, an output unit 226, a statistical calculation unit 227, a display range change unit 228, and a threshold value change unit 229. Is included.

  The input unit 221 inputs nystagmus data acquired by the balance function testing device. Specifically, the input unit 221 is directly connected to the video input board 4, reads nystagmus data from the video input board 4, and inputs it to the eye movement analysis system 22. Alternatively, the input unit 221 reads nystagmus data from a file already stored in the storage unit of the computer 2 and inputs it to the eye movement analysis system 22. Of course, the input unit 221 may read nystagmus data from a wired or wirelessly connected server (storage device in which nystagmus data is stored) and input it to the eye movement analysis system 22.

  The phase separation unit 223 separates the nystagmus data input from the input unit 221 into a slow phase and a rapid phase. In this embodiment, as will be described later, a method of separating eyeball position data in which the angular velocity of the eyeball E is equal to or greater than a threshold value into a rapid phase and the others into a slow phase will be described. However, the phase separation unit 223 is not limited to this method, and the nystagmus data may be separated into a slow phase and a rapid phase by another method described in Patent Document 2 and the like.

  For the plurality of slow phases and the plurality of rapid phases separated by the phase separation unit 223, the angle detection unit 224 includes the first displacement vector of the eyeball E in the slow phase and the first displacement vector of the eyeball E in the rapid phase next to the slow phase. An angle formed by the two displacement vectors (hereinafter, also simply referred to as an angle formed by the first displacement vector and the second displacement vector) is detected. In the angle detection unit 224, the slow phase measured by the equilibrium function testing apparatus and the rapid phase that appears next to the slow phase are handled as a set of information, so that the slow phase displacement vector and the rapid phase displacement vector are formed. It is detected as a corner. Here, the slow phase displacement vector is a vector indicating the position displacement from the eyeball position data at the time when the slow phase begins to the eyeball position data at the time when the slow phase ends, and the rapid phase displacement vector starts the rapid phase. It is a vector indicating the position displacement from the eyeball position data at the time point to the eyeball position data at the time point when the rapid phase ends.

  The distribution calculation unit 225 calculates a frequency distribution of angles formed by the first displacement vector and the second displacement vector detected by the angle detection unit 224. For example, the distribution calculation unit 225 may calculate the frequency distribution by fixing the number of classes to 13 and the class width to 30 degrees so that the frequency distribution is an appropriate distribution so that the frequency distribution becomes an appropriate distribution. The frequency distribution may be calculated by automatically setting the class width.

  The output unit 226 outputs a result including the frequency distribution calculated by the distribution calculation unit. Specifically, the output unit 226 is connected to the display 21 and displays the calculated frequency distribution on the display 21. Further, the output unit 226 may be connected to the printer 6 to print the calculated frequency distribution in the printer 6, or may store the calculated frequency distribution in the storage unit of the computer 2 as it is, or the eye movement analysis system You may export and memorize | store the file of the format which can be displayed with general-purpose software from 22 dedicated software. Of course, the output unit 226 may display the calculated frequency distribution on another display connected by wire or wireless.

  The statistical calculation unit 227 calculates statistical data of an angle formed by the first displacement vector and the second displacement vector detected by the angle detection unit 224. Here, as the statistical data of the angle formed by the first displacement vector and the second displacement vector, for example, the average value, median value, mode value, deviation, standard deviation, coefficient of variation, skewness, There is kurtosis.

  The display range changing unit 228 changes the display range of the nystagmus data displayed on the display 21 by a process based on information about the user's input operation. For example, in order for the user to enlarge and display a part of the nystagmus data displayed on the display 21 or to display a part of the nystagmus data that was not displayed by reducing the nystagmus data, The range changing unit 228 can change the display range of the nystagmus data displayed on the display 21 by performing processing based on input operation information such as a mouse.

  In the present embodiment, the frequency distribution is calculated by the distribution calculation unit 225 for all of the nystagmus data, and the frequency distribution is displayed on the display 21. On the other hand, only the display range designated based on the user's input operation is displayed as nystagmus data. That is, in the present embodiment, the distribution calculation unit 225 does not calculate the frequency distribution in conjunction with the range of the nystagmus data displayed on the display 21, but the display range of the nystagmus data based on the user's input operation. Is just changing.

  However, the display range changing unit 228 outputs the result of changing the display range of the nystagmus data to the distribution calculating unit 225, and the frequency distribution is calculated again with the nystagmus data included in the display range changed by the distribution calculating unit 225. It may be configured to. That is, the frequency distribution may be calculated in conjunction with the nystagmus data displayed on the display 21 and the display on the display 21 may be updated with the calculated frequency distribution. Details will be described in a modification.

  The threshold value changing unit 229 changes the threshold value of the phase separation unit 223. Even if the threshold value changing unit 229 changes the threshold value of the phase separating unit 223 based on a user's input operation, the phase separating unit 223 has a frequency distribution calculated by the distribution calculating unit 225 so that the distribution is within a predetermined range. The threshold value may be changed. Note that when the threshold value of the phase separation unit 223 is changed, the threshold value changing unit 229 outputs the result to the phase separation unit 223. The phase separation unit 223 separates the nystagmus data again into the slow phase and the rapid phase based on the threshold value changed by the threshold value changing unit 229.

  Next, the operation of the eye movement analysis system 22 will be described in detail using a flowchart. FIG. 3 is a flowchart for explaining the operation of the eye movement analysis system 22 according to the embodiment of the present invention. First, the input unit 221 reads a file including nystagmus data acquired by the balanced function testing device (step S301).

  Here, the nystagmus data will be described in detail. The nystagmus data is data in which eyeball position data are arranged in time series, and two phases of a slow phase and a rapid phase appear alternately. FIG. 4 is a diagram for explaining the eyeball position. FIG. 5 is a diagram illustrating an example of nystagmus data in which eyeball position data is arranged in time series and two phases of a slow phase and a rapid phase appear alternately.

  In FIG. 4, an eyeball E viewed in the xy plane or the yz plane is shown. The position where the y-axis direction is the front and the eyeball E faces the front is the reference position e0. The angle between the reference position e0 and the position e1 where the eyeball E has moved around the movement center O is the eyeball position θ. The eyeball position θ has a component of an angle θxy on the xy plane and a component of an angle θyz on the yz plane. Therefore, in the present embodiment, the eyeball position θ is expressed as a root mean square (RMS) or a mean square deviation value between the angle θxy and the angle θyz. In addition, although the root mean square of the angle θxy and the angle θyz is the eyeball position θ, the analysis may be performed by separately using each angle as the eyeball position.

  The nystagmus data shown in FIG. 5 shows the time change of the eyeball position θ, and is data in which two phases of a slow phase and a rapid phase appear alternately. That is, the nystagmus data shown in FIG. 5 repeats a change in which the eyeball position θ gradually increases in the slow phase and rapidly decreases in the rapid phase.

  Returning to FIG. 3, the phase separation unit 223 obtains the angular velocity (angle / second) of the eyeball E by taking the difference between the data of the adjacent eyeball positions θ in order to separate the nystagmus data into the slow phase and the rapid phase. Calculate (step S302). FIG. 6 is a diagram for explaining the angular velocity of the eyeball E calculated from the nystagmus data shown in FIG. The graph of the angular velocity of the eyeball E shown in FIG. 6 shows that the movement of the eyeball E, which was a slow angular velocity during the slow phase period, suddenly changes to a fast angular velocity in the rapid phase. Therefore, as can be seen from FIG. 6, if a threshold is set between the angular velocity of the slow phase and the angular velocity of the rapid phase, the nystagmus data can be separated into the slow phase and the rapid phase.

  Returning to FIG. 3, the phase separation unit 223 separates the nystagmus data into a slow phase and a rapid phase, for example, with a threshold specified by an input operation (step S303). That is, the phase separation unit 223 sets the data of the eyeball position θ corresponding to the angular velocity equal to or higher than the specified threshold as the rapid phase, and sets the data of the eyeball position θ corresponding to the angular velocity slower than the specified threshold as the slow phase.

  Next, the angle detection unit 224 detects an angle formed by the slow phase and the rapid phase separated by the phase separation unit 223 (step S304). The angle formed between the slow phase and the rapid phase is the angle formed between the first displacement vector in the slow phase and the second displacement vector in the rapid phase. The first slow displacement vector can be obtained, for example, from the position displacement from the eyeball position θ changed from the rapid phase to the slow phase shown in FIG. 5 to the eyeball position θ changed from the slow phase to the rapid phase. Further, the second displacement vector in the rapid phase is obtained from, for example, the position displacement from the eyeball position θ changed from the slow phase to the rapid phase to the eyeball position θ changed from the rapid phase to the slow phase as shown in FIG. Can do.

  FIG. 7 is a diagram for explaining an angle formed by the first displacement vector in the slow phase and the second displacement vector in the rapid phase. As shown in FIG. 7, the first displacement vector and the second displacement vector obtained as described above are aligned with the origin of the xy coordinates as shown in FIG. 7, and the respective angles from the x axis are obtained. When the angle of the first displacement vector is the angle α and the angle of the second displacement vector is the angle β, the angle formed by the slow phase and the rapid phase (the angle formed by the first displacement vector and the second displacement vector) is an angle. It can be determined by β−angle α.

  Returning to FIG. 3, the distribution calculation unit 225 calculates the frequency distribution of the angle formed by the slow phase and the rapid phase (step S305). Specifically, the distribution calculation unit 225 distributes the angle formed by the slow phase and the rapid phase detected by the angle detection unit 224 for each class, and calculates the frequency distribution by obtaining the number included in each class. The statistical calculation unit 227 calculates a statistical amount (statistical data) of an angle formed by the slow phase and the rapid phase (step S306). Here, the processing in the distribution calculation unit 225 and the processing in the statistical calculation unit 227 may be performed sequentially as shown in the flowchart of FIG. 3 or in parallel as shown in FIG. Further, as will be described later, the distribution is not performed in the statistical calculation unit 227 so long as it is confirmed whether or not the nystagmus data can be appropriately separated into the slow phase and the rapid phase. Only the processing in the calculation unit 225 may be performed. That is, the eye movement analysis system 22 may be a process of a flowchart that skips step S306.

  Next, the output unit 226 displays the results of the distribution calculation unit 225 and the statistics calculation unit 227 on the display 21 (step S307). FIG. 8 is a diagram illustrating an example of an analysis result output by the eye movement analysis system 22 according to the embodiment of the present invention. In the display shown in FIG. 8, the nystagmus data is shown in the upper part, and the histogram of the frequency distribution calculated by the distribution calculating unit 225 is shown in the lower part.

  In the nystagmus data shown in the upper part, a part of the sampled data of the eyeball position θ (for 10 seconds from a certain time point) is shown. The display range changing unit 228 can change the range of the nystagmus data displayed on the display 21 by processing the information on the slide bar 228a operated by the user. Specifically, the display range changing unit 228 does not change a period (10 seconds) that can be displayed by processing information of an operation in which the user moves the slide bar 228a left and right, and changes the user among the sampled data. Can be displayed on the display 21.

  In addition, the display range changing unit 228 can lengthen the display period (10 seconds) by processing information of an operation for the user to lengthen the slide bar 228a itself (for example, 20 seconds). However, it is possible to shorten the display period (10 seconds) (for example, 5 seconds) by processing the operation information for shortening the slide bar 228a itself. In other words, the display range changing unit 228 processes information of an input operation such as a mouse, and thereby enlarges and displays a part of the nystagmus data displayed on the display 21 or reduces and displays the nystagmus data. A portion that has not been displayed can be displayed on the display 21.

  In the nystagmus data shown in the upper row, sampled data of the eyeball position θ is displayed as dots. Further, the dot at the eyeball position θ that is equal to or greater than the threshold value (threshold value = 5.0 in FIG. 8) shown in the upper right column of the display 21 is identified as white, and the dot at the eyeball position θ that is less than the threshold value is identified as black. . The black dots are the slow phase, and the white dots are the rapid phase. Furthermore, the slow phase and the rapid phase can be distinguished by connecting the black dots with a solid line and connecting the white dots with a broken line. As a result, the user displays the slow phase portion and the rapid phase portion so as to be distinguishable only by looking at the nystagmus data displayed on the display 21. It can be visually confirmed whether the rapid phase is properly separated. The slow phase portion and the rapid phase portion may be identified by different colors. For example, the slow phase may be represented by a blue solid line or a dot, and the rapid phase may be represented by a red solid line or a dot. .

  The histogram shown at the bottom shows the frequency distribution of the angle between the slow phase and the rapid phase. The number of classes is 13 and the class width is 30 degrees (however, the class of 0 degrees and 360 degrees are Except). Specifically, each class has a 0 degree class (0 degrees to less than 15 degrees), a 30 degree class (15 degrees to less than 45 degrees), a 60 degree class (45 degrees to less than 75 degrees), 90 degree class (75 degrees to less than 105 degrees), 120 degree class (105 degrees to less than 135 degrees), 150 degree class (135 degrees to less than 165 degrees), 180 degree class (165 degrees or more) ~ 195 degrees), 210 degrees class (195 degrees to less than 225 degrees), 240 degrees class (225 degrees to less than 255 degrees), 270 degrees class (255 degrees to less than 285 degrees), 300 degrees Class (285 degrees to less than 315 degrees), 330 degrees (315 degrees to less than 345 degrees), and 360 degrees (345 degrees to less than 360 degrees).

  The histogram shown in the lower row has 287 angles between the slow phase and the rapid phase, 6 in the 0 degree class, 3 in the 30 degree class, 6 in the 60 degree class, and 90 degrees. 3 in the class, 6 in the 120 degree class, 24 in the 150 degree class, 218 in the 180 degree class, 15 in the 210 degree class, and 6 in the 240 degree class, The angle with the rapid phase is distributed.

  In the balanced function test, a regular movement in which the eyeball E is gradually displaced in the reverse direction and rapidly returns to the original direction when an acceleration stimulus in a certain direction continues is inspected. Therefore, the angle formed by the first displacement vector in the slow phase in which the eyeball E is gradually displaced in the reverse direction and the second displacement vector in the rapid phase in which the eyeball E rapidly returns to the normal phase is 180 degrees for normal subjects. Many will be distributed. Therefore, the user can confirm the angle between the slow phase and the rapid phase based on the appropriately separated slow phase and the rapid phase, and the frequency distribution of the angle, making it easy to determine whether the frequency distribution is normal or not. It can be confirmed, and information necessary for the diagnosis of eye movement can be provided. Furthermore, by comparing the histograms, comparison with normal eye movement is further facilitated.

  The histogram shown in the lower row is an example, and the format for displaying the calculated frequency distribution on the display 21 may be a frequency distribution table in which the numbers for each class are tabulated. Furthermore, the format displayed on the display 21 is not limited to this, and may be a format in which the number for each class is represented by a line graph, a pie chart, or the like.

  Further, the statistics calculated by the statistics calculator 227 are displayed in the lower right column of the display 21. Specifically, the average, standard deviation, coefficient of variation, skewness, and kurtosis are displayed in the same column as statistics. In the same column, the number of angles formed between the slow phase and the rapid phase is also displayed. As described above, the eye movement analysis system 22 can provide the user with quantitative data necessary for diagnosing eye movement by calculating the statistic of the angle between the slow phase and the rapid phase.

  Next, returning to FIG. 3, when it is determined that the user needs to change the threshold based on the result displayed on the display 21, an input operation is performed on the threshold changing unit 229. When it is determined that there is no need to change the threshold value changing unit 229, no input operation is performed. That is, the threshold value changing unit 229 determines whether or not an input operation for changing the threshold value has been performed by the user (step S308). When the threshold value changing unit 229 determines that an input operation for changing the threshold value has been performed by the user (step S308: YES), the process returns to step S303, and the phase separation unit 223 performs the slow phase with the threshold value specified by the input operation. And the rapid phase are separated again. On the other hand, when the threshold value changing unit 229 determines that the input operation for changing the threshold value by the user has not been performed (step S308: NO), the output unit 226 outputs the nystagmus data with the slow phase and the rapid phase with the set threshold value. And the result processed by the distribution calculation unit 225 and the statistical calculation unit 227 is output to the storage unit of the computer 2 (step S309). Thereafter, the eye movement analysis system 22 ends the process.

  As described above, the eye movement analysis system 22 displays the nystagmus data displayed by identifying the slow phase and the rapid phase each time the threshold value is changed, and the display of the histogram of the angle formed by the slow phase and the rapid phase. Since the update is performed, it is possible to easily and visually confirm how much the result obtained by changing the threshold value changes, and it is possible to perform an operation of selecting an appropriate threshold value while changing the threshold value.

  Note that the output destination of the results processed by the distribution calculation unit 225 and the statistical calculation unit 227 is not limited to the storage unit of the computer 2, but a printer 6 connected to the computer 2 or a server connected by wire or wirelessly. Etc. In addition to the results processed by the distribution calculation unit 225 and the statistical calculation unit 227, the results output by the output unit 226 include the results of separation into a slow phase and a rapid phase by the phase separation unit 223, and detection by the angle detection unit 224. The result of the angle formed by the slow phase and the rapid phase, or the image data of the screen displayed on the display 21 may be included.

  The user can change the threshold value by operating the slider 229a below the threshold value displayed in the upper right column of the display 21 with the mouse or the like. The user can also change the threshold value by directly entering a number in the displayed threshold value field. An analysis result when the threshold value is changed by the input operation as described above will be described.

  FIG. 9 is a diagram illustrating another example of the analysis result output by the eye movement analysis system 22 according to the embodiment of the present invention. FIG. 10 is a diagram showing still another example of the analysis result output by the eye movement analysis system 22 according to the embodiment of the present invention. Note that the nystagmus data displayed in FIGS. 9 and 10 is the nystagmus data in the same display range displayed in FIG. Further, the histograms displayed in FIGS. 9 and 10 are the same number of classes displayed in FIG. 8 and the same class width.

  The analysis result shown in FIG. 9 is when the threshold value is changed to 0.1 by an input operation. For this reason, in the nystagmus data shown in the upper stage, substantially all of the dots at the eyeball position θ are equal to or greater than the threshold value, and all the dots are displayed in black. In FIG. 8, the dot (rapid phase dot) at the eyeball position θ that is equal to or greater than the threshold value is displayed in white. However, if all the dots are displayed in white as shown in FIG. 9, it is difficult to visually recognize the display. Therefore, all dots are displayed in black.

  In FIG. 8, the slow phase and the rapid phase are identified by connecting the dots of the slow phase with solid lines and connecting the dots of the rapid phase with broken lines. However, in the nystagmus data shown in FIG. 9, since all dots are determined to be in a rapid phase, a solid line and a broken line cannot be drawn correctly, and a meaningless broken line is displayed. Therefore, the eye movement analysis system 22 can visually confirm that the slow phase and the rapid phase are not properly separated in the nystagmus data.

  Since almost all of the nystagmus data is based on the separation result that the rapid phase is extremely slow and the slow phase is extremely small, the histogram shown in FIG. 9 has four angles between the slow phase and the rapid phase, There are three angles in the class of 180 degrees and one in the class of 330 degrees, and the angle between the slow phase and the rapid phase is distributed. Therefore, the eye movement analysis system 22 can visually confirm that the slow phase and the rapid phase are not properly separated even in the histogram.

  On the other hand, the analysis result shown in FIG. 10 is when the threshold value is changed to 8.0 by an input operation. Therefore, in the nystagmus data shown in the upper part, some of the dots at the eyeball position θ separated from the rapid phase in FIG. 8 are separated from the slow phase, and some of the white dots are changed to black dots. . However, unlike the nystagmus data shown in FIG. 9, the nystagmus data shown in FIG. 10 can connect the black dots with solid lines and the white dots with broken lines. Can be identified. As a result, the user displays the slow phase portion and the rapid phase portion so as to be distinguishable only by looking at the nystagmus data displayed on the display 21. It can be visually confirmed whether or not the rapid phase is properly separated.

  The histogram shown in FIG. 10 has 254 angles between the slow phase and the rapid phase, 3 in the 0 degree class, 3 in the 60 degree class, 3 in the 90 degree class, and 120 degrees. 9 in class, 24 in 150 degree class, 194 in 180 degree class, 9 in 210 degree class, 6 in 240 degree class, and 3 in 270 degree class, slow phase and rapid The angles formed with the phases are distributed. Therefore, the eye movement analysis system 22 can visually confirm that the slow phase and the rapid phase are appropriately separated even in the histogram.

  As described above, the eye movement analysis system 22 according to the present embodiment appropriately separates the nystagmus data into the slow phase and the rapid phase by calculating the frequency distribution of the angles formed by the slow phase and the rapid phase. It can be easily confirmed whether or not it is possible. Furthermore, by outputting the angle formed by the appropriately separated slow phase and the rapid phase and the frequency distribution of the formed angle, information necessary for diagnosing eye movement can be provided. In addition, since the eye movement analysis system 22 displays the frequency distribution as a histogram, it is possible to visually confirm whether or not the nystagmus data can be appropriately separated into the slow phase and the rapid phase. By comparing the histograms, comparison with normal eye movement is facilitated.

  In addition, the eye movement diagnosis apparatus 100 according to the present embodiment calculates the frequency distribution of the angle formed by the slow phase and the rapid phase in the eye movement analysis system 22 so that the nystagmus data is appropriate for the slow phase and the rapid phase. It can be easily confirmed whether or not it can be separated. The eye movement diagnosis apparatus 100 outputs the angle formed by the slow phase and the rapid phase appropriately separated in the eye movement analysis system 22 and the frequency distribution of the formed angle, and is necessary for the analysis evaluation and diagnosis of the eye movement. Information can be provided.

(Modification)
(1) In the present embodiment, the distribution calculation unit 225 does not calculate the frequency distribution in conjunction with the range of the nystagmus data displayed on the display 21, but displays the nystagmus data based on the user's input operation. The configuration for simply changing the range has been described. Therefore, in the first modification, a configuration in which the frequency distribution is calculated in conjunction with the nystagmus data displayed on the display 21 and the display on the display 21 is updated with the calculated frequency distribution will be described.

  When the display range changing unit 228 according to the first modification changes the display range of the nystagmus data, the result is output to the distribution calculating unit 225. Therefore, the distribution calculation unit 225 recalculates the frequency distribution with the nystagmus data included in the changed display range. Specifically, the processing of the display range changing operation will be described in detail using a flowchart. FIG. 11 is a flowchart for explaining the operation of the eye movement analysis system 22 according to the first modification of the embodiment of the present invention.

  First, the display range changing unit 228 reads information in which the user specifies a display range of nystagmus data such as a mouse (step S101). Specifically, information that the user has performed an operation such as moving the slide bar 228a to the left or right is read into the display range changing unit 228 as information specifying the display range.

  Next, the display range changing unit 228 checks whether or not the display range based on the read information is the same as the currently displayed display range (step S102). When the display range based on the read information is different from the currently displayed display range (step S102: NO), the display range changing unit 228 sends the information on the display range of the nystagmus data to be changed to the distribution calculating unit 225. Output. When the information on the display range of the nystagmus data to be changed is input, the distribution calculation unit 225 recalculates the frequency distribution of the angle formed by the slow phase and the rapid phase included in the newly specified display range (step S103). ).

  Next, the statistical calculation unit 227 calculates again the statistical amount (statistical data) of the angle formed by the slow phase and the rapid phase included in the newly designated display range (step S104). Thereafter, the output unit 226 updates the display 21 on the histogram of the frequency distribution calculated again by the distribution calculation unit 225 and updates the display 21 on the result of the statistics calculated again by the statistics calculation unit 227 (step S105).

  On the other hand, when the display range based on the read information is the same as the currently displayed display range (step S102: YES), the display range changing unit 228 skips the processing from step S103 to step S105, The display of the histogram and statistics currently displayed on the display 21 is maintained.

  As described above, when the display range of the nystagmus data is changed, the eye movement analysis system 22 according to the first modification calculates the frequency distribution of the changed display range of the nystagmus data again and displays it on the display 21. Therefore, the frequency distribution of the display range of the nystagmus data desired by the user can be easily confirmed.

  (2) In the present embodiment, the threshold value is changed by operating the slider 229a by looking at the nystagmus data displayed on the display 21 by the user and the histogram, and the distribution calculation unit 225 is based on the changed threshold value. The configuration for calculating the frequency distribution again has been described. Therefore, in the second modification, based on the frequency distribution calculated by the distribution calculation unit 225 and the statistics calculated by the statistical calculation unit 227, it is determined whether or not the threshold value changing unit 229 is set to an appropriate threshold value. A configuration for changing the threshold will be described.

  In step S308 shown in FIG. 3, the threshold value changing unit 229 does not determine whether or not an input operation for changing the threshold value is performed, but, for example, the frequency distribution result calculated from the distribution calculating unit 225 is input. It is determined whether the result of the frequency distribution is within a predetermined frequency distribution range. Then, when the result of the frequency distribution does not fall within the predetermined frequency distribution range (step S308: YES), the threshold value changing unit 229 changes the threshold value to increase by, for example, “1.0”, and If the result is within the predetermined frequency distribution range, it is determined that there is no problem with the threshold (step S308: NO), and the process proceeds to step S309 without changing the threshold.

  As described above, in the eye movement analysis system 22 according to the second modification, the threshold value changing unit 229 changes the threshold value change so that the result of the frequency distribution falls within the predetermined frequency distribution range. It is possible to automatically set a threshold value that can be appropriately separated into a phase and a rapid phase.

  Note that the threshold value changing unit 229 determines whether the statistical result calculated by the statistical calculation unit 227 is within the predetermined statistical range, not the frequency distribution result calculated from the distribution calculating unit 225. The threshold value may be changed. For example, the threshold value changing unit 229 may change the threshold value by determining whether or not the skewness and kurtosis calculated by the statistical calculation unit 227 are within a predetermined range.

  (3) In this embodiment, when the threshold value is changed, the configuration in which the histogram of the frequency distribution calculated based on the changed threshold value is displayed on the display 21 and the display is updated has been described. However, the present invention is not limited to this. For example, in the third modification, the histogram of the frequency distribution calculated based on the changed threshold value is displayed so that it can be compared with the histogram before the change. For example, the output unit 226 may tile the display areas of a plurality of histograms having different threshold values and display them on the display 21, or display the plurality of histograms in order of the threshold values and three-dimensionally display them on the display 21.

  (4) Furthermore, in the fourth modification, a scatter of nystagmus data plotted with the angular velocity of the slow phase as the X axis and the angle between the slow phase and the rapid phase appropriately separated in the eye movement analysis system 22 as the Y axis. The figure may be displayed on the display 21. FIG. 12 is a diagram illustrating an example of a scatter diagram output by the eye movement analysis system 22 according to a modification of the embodiment of the present invention. The scatter diagram shown in FIG. 12 is obtained by taking an angular velocity of a slow phase of 0 degrees / second to 20 degrees / second on the X axis and an angle formed by a slow phase and a rapid phase of 0 degrees to 360 degrees on the Y axis. The angle variation between the slow phase and the rapid phase is displayed for each angular velocity of the slow phase. From this scatter diagram, when the angular velocity of the slow phase is slow, the angle variation between the slow phase and the rapid phase tends to increase, and conversely, when the angular velocity of the slow phase is high, the angle between the slow phase and the rapid phase It can be seen that the variation tends to be small. In addition, as shown in FIG. 12, in the case of a distribution in which the angle formed by the slow phase and the rapid phase is concentrated around 180 degrees for each angular velocity of the slow phase, it is considered to be a scatter diagram of a normal subject.

  Further, in the scatter diagram shown in FIG. 12, a histogram of the angle formed by the slow phase and the rapid phase can be created by projecting the plotted nystagmus data onto the Y axis. In the scatter diagram shown in FIG. 12, a histogram of the slow-phase angular velocity can be created by projecting the plotted nystagmus data onto the X axis.

  Note that the statistic calculated by the statistic calculation unit 227 from the scatter diagram may be displayed on the display 21 displaying the scatter diagram. Further, when the threshold value is changed, the output unit 226 may update the display of the display 21 with a scatter diagram and a histogram calculated based on the changed threshold value.

  The embodiment disclosed this time should be considered as illustrative in all points and not restrictive. The scope of the present invention is defined by the terms of the claims, rather than the description above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

  1 imaging camera, 2 computer, 3 head movement sensor, 4 video input board, 5 A / D board, 6 printer, 21 display, 22 eye movement analysis system, 100 eye movement diagnosis device, 221 input section, 223 phase separation section 224 Angle detection unit, 225 distribution calculation unit, 226 output unit, 227 statistical calculation unit, 228 display range change unit, 228a slide bar, 229 threshold change unit, 229a slider.

Claims (11)

An eye movement analysis system for analyzing eye movement data in a balance function test,
An input unit for inputting the movement data of the eyeball measured by the balance function test;
A phase separation unit that separates the movement data input from the input unit into a slow phase and a rapid phase in eye movement based on a predetermined threshold;
The first displacement vector of the eyeball in the slow phase and the second displacement vector of the eyeball in the rapid phase next to the slow phase with respect to the plurality of slow phases and the plurality of rapid phases separated by the phase separation unit An angle detector for detecting an angle formed by
A distribution calculator that calculates a frequency distribution of angles formed by the first displacement vector and the second displacement vector detected by the angle detector;
An eye movement analysis system comprising: an output unit that outputs a result including the frequency distribution calculated by the distribution calculation unit.   The eye movement analysis system according to claim 1, wherein the output unit includes a display unit that displays the frequency distribution calculated by the distribution calculation unit.   The eye movement analysis system according to claim 2, wherein the display unit displays the frequency distribution as a histogram.   The eye movement analysis system according to claim 2, wherein the display unit displays the frequency distribution calculated by the distribution calculation unit and displays the movement data corresponding to the frequency distribution.   The eye movement analysis system according to claim 4, wherein the display unit displays the slow phase portion and the rapid phase portion of the motion data to be displayed so as to be distinguishable. Further comprising a display range changing unit for changing a display range of the exercise data displayed on the display unit based on a user's input operation;
The distribution calculation unit recalculates the frequency distribution of the angle formed by the first displacement vector and the second displacement vector detected from the motion data included in the display range changed by the display range change unit,
The eye movement analysis system according to claim 4, wherein the display unit displays the frequency distribution calculated again. A threshold value changing unit for changing the threshold value of the phase separation unit;
The phase separation unit separates the motion data again into the slow phase and the rapid phase based on the threshold value changed by the threshold value changing unit,
The angle detection unit detects again an angle formed by the first displacement vector and the second displacement vector based on the slow phase and the rapid phase separated again;
The distribution calculation unit calculates again the frequency distribution of the angle formed between the first displacement vector and the second displacement vector detected again;
The eye movement analysis system according to any one of claims 2 to 6, wherein the display unit displays the frequency distribution calculated again. A statistical calculation unit that calculates statistical data of an angle formed by the first displacement vector and the second displacement vector detected by the angle detection unit;
The eye movement analysis system according to claim 2, wherein the display unit displays the statistical data calculated by the statistical calculation unit. The movement data is eyeball position data obtained by sampling the angle of the eyeball at the center of rotational movement of the eyeball at predetermined intervals,
The phase separation unit calculates an angular velocity of the eyeball from a difference between the adjacent eyeball position data, and separates the eyeball position data in which the calculated angular velocity of the eyeball is equal to or greater than the threshold into the rapid phase,
The angle detector includes a first displacement vector obtained by connecting a vector connecting the first eyeball position data changing from the rapid phase to the slow phase and the second eyeball position data changing from the slow phase to the rapid phase. The vector connecting the second eyeball position data and the third eyeball position data changing from the rapid phase to the slow phase is defined as the second displacement vector. The eye movement analysis system according to Item 1. An equilibrium function testing device for measuring eye movement data in the balance function testing;
An eye movement diagnosis apparatus comprising the eye movement analysis system according to claim 1. An operation method of an eye movement analysis system for analyzing eye movement data in a balance function test,
An input step of inputting the movement data of the eyeball measured by the balance function test;
A phase separation step of separating the movement data input from the input step into a slow phase and a rapid phase in eye movement based on a predetermined threshold;
A first displacement vector of the eyeball in the slow phase and a second displacement vector of the eyeball in the rapid phase next to the slow phase with respect to the plurality of slow phases and the plurality of rapid phases separated in the phase separation step. An angle detection step for detecting an angle formed by
A distribution calculating step for calculating a frequency distribution of angles formed by the first displacement vector and the second displacement vector detected in the angle detecting step; and an output step for outputting a result including the frequency distribution calculated in the distribution calculating step. A method of operating an eye movement analysis system comprising :

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