WO2016038937A1 - Mental disease determination device and mental disease determination method - Google Patents

Mental disease determination device and mental disease determination method Download PDF

Info

Publication number
WO2016038937A1
WO2016038937A1 PCT/JP2015/063868 JP2015063868W WO2016038937A1 WO 2016038937 A1 WO2016038937 A1 WO 2016038937A1 JP 2015063868 W JP2015063868 W JP 2015063868W WO 2016038937 A1 WO2016038937 A1 WO 2016038937A1
Authority
WO
WIPO (PCT)
Prior art keywords
eye movement
test
predetermined number
subject
patient
Prior art date
Application number
PCT/JP2015/063868
Other languages
French (fr)
Japanese (ja)
Inventor
亮太 橋本
美智子 藤本
健一郎 三浦
Original Assignee
国立大学法人大阪大学
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.)
Filing date
Publication date
Application filed by 国立大学法人大阪大学 filed Critical 国立大学法人大阪大学
Publication of WO2016038937A1 publication Critical patent/WO2016038937A1/en

Links

Images

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B10/00—Other methods or instruments for diagnosis, e.g. instruments for taking a cell sample, for biopsy, for vaccination diagnosis; Sex determination; Ovulation-period determination; Throat striking implements

Definitions

  • the present invention relates to a mental illness determination apparatus and a mental illness determination method for determining whether or not a patient has a mental illness.
  • a schizophrenia diagnostic apparatus for determining whether or not a patient has schizophrenia is known.
  • a schizophrenia diagnostic apparatus including a stimulus display unit, a viewpoint identification unit, a reactive search score calculation unit, an exercise number measurement unit, and a determination unit is disclosed (see Patent Document 1).
  • the stimulus display means presents a visual stimulus to the subject.
  • the viewpoint specifying means specifies the viewpoint of the subject with respect to the stimulus display means.
  • the reactive search score calculation means calculates a reactive search score.
  • the exercise number measuring means measures the exercise number.
  • the determination means determines whether or not the subject suffers from schizophrenia from the reactive search score and the number of exercises.
  • Patent Document 1 According to the schizophrenia diagnostic apparatus described in Patent Document 1, it is described in Patent Document 1 that it can be determined with high accuracy whether a subject is likely to suffer from schizophrenia or is a healthy person. ing.
  • the schizophrenia diagnostic apparatus described in Patent Document 1 has insufficient accuracy (70% to 80%) and is difficult to apply to clinical practice. Moreover, since the schizophrenia diagnostic apparatus described in Patent Document 1 has a complicated structure, there is a problem that the manufacturing cost is high.
  • the present invention has been made in view of the above problems, and an object of the present invention is to provide a mental disease determination apparatus and a mental disease determination method capable of accurately determining whether or not a patient has a mental disease. It is said.
  • the first mental illness determination apparatus of the present invention is a mental illness determination apparatus for determining a mental illness, and includes a detection means, an analysis means, and a determination means.
  • the detection means detects a movement of the eyeball of the subject when viewing a preselected eye movement test image.
  • the analysis unit analyzes the movement of the eyeball detected by the detection unit and obtains three or more first predetermined number of eye movement features.
  • the determination means determines the mental illness of the subject based on the first predetermined number of eye movement characteristics obtained by the analysis means.
  • the second mental illness determination device of the present invention is a mental illness determination device that determines whether or not a patient has a mental illness, and includes a detection means, an analysis means, and a determination means.
  • the detection means detects a movement of the eyeball of the subject when viewing a preselected eye movement test image.
  • the analysis unit analyzes the movement of the eyeball detected by the detection unit and obtains three or more first predetermined number of eye movement features.
  • the determination means determines whether the subject is a patient with the mental disease based on the first predetermined number of eye movement characteristics obtained by the analysis means.
  • a third mental illness determination device is the second mental illness determination device, wherein the determination means determines whether the first predetermined number of eye movement characteristics obtained by the analysis means are normal subjects and Two or more second predetermined number of eye movement features effective for discriminating from the mentally ill patient are selected. The determination means determines whether the subject is a patient with the mental illness based on the second predetermined number of eye movement characteristics.
  • the fourth mental illness determination apparatus of the present invention is the third mental illness determination apparatus, wherein the determination means is independent from the first predetermined number of eye movement characteristics obtained by the analysis means. The second predetermined number of eye movement features having strong strength are selected.
  • the fifth mental illness determination apparatus of the present invention is the fourth mental illness determination apparatus, wherein the determination means is the first predetermined number of eye movement characteristics obtained by the analysis means by a stepwise method. Then, the second predetermined number of eye movement features effective for discriminating between the healthy person and the patient with the mental illness are selected.
  • the sixth mental disease determination device of the present invention is any one of the third mental disease determination device to the fifth mental disease determination device, wherein the determination means includes the second mental disease determination device.
  • a function of a predetermined number of eye movement characteristics is obtained as a discriminant, and it is determined by the discriminant whether the subject is a patient with the mental illness.
  • the seventh mental disease determination device of the present invention is the sixth mental disease determination device, wherein the determination means obtains a linear equation relating to the second predetermined number of eye movement characteristics as the discriminant.
  • An eighth mental disease determination device is the mental disease determination device according to any one of the third mental disease determination device to the sixth mental disease determination device, wherein the eye movement test is performed based on the normal state. This is an eye movement test in which there is a significant difference in test results between a person and a patient with the mental illness.
  • the ninth mental illness determination device of the present invention is the eighth mental illness determination device, wherein the eye movement test includes at least one of a gaze test, a smooth spa shoot test, and a free viewing test. Including.
  • the tenth mental disease determination device of the present invention is any one of the third mental disease determination device to the ninth mental disease determination device, wherein the mental disease is schizophrenia.
  • the second predetermined number of eye movement features include a scan path distance in a free viewing test or other eye movement characteristics having a strong correlation with the scan path distance.
  • An eleventh mental disease determination device is the mental disease determination device according to any one of the third mental disease determination device to the ninth mental disease determination device, wherein the second predetermined number of eye movements.
  • Features include a vertical position gain in a quick lissajous of a smooth spout test, or other eye movement features that are highly correlated with the position gain.
  • the twelfth mental disease determination device of the present invention is a mental disease determination device that determines whether a subject is a schizophrenic patient based on two or more second predetermined number of eye movement characteristics.
  • the second predetermined number of eye movement features include a scan path distance in a free viewing test, a vertical position gain in a quick lissajous test, a number of gazes in a quick lissajous test Lissajous, a distant disturbance stimulus in a gaze test It includes at least one of the gaze period and the S / N ratio in the horizontal pursuit of the smooth spout test.
  • the first mental illness determination method of the present invention is a mental illness determination method for determining whether or not a mental illness includes a detection step, an analysis step, and a determination step.
  • the detection step detects the movement of the eyeball of the subject when viewing the image of the eye movement test.
  • the analyzing step the eye movement detected in the detecting step is analyzed to obtain three or more first predetermined number of eye movement features.
  • the determination step determines the mental illness of the subject based on the first predetermined number of eye movement characteristics obtained in the analysis step.
  • the second mental disease determination method of the present invention is a mental disease determination method for determining whether or not a patient has a mental disease, and includes a detection step, an analysis step, and a determination step.
  • the detection step detects the movement of the eyeball of the subject when viewing the image of the eye movement test.
  • the analyzing step the eye movement detected in the detecting step is analyzed to obtain three or more first predetermined number of eye movement features.
  • the determination step determines whether or not the subject is a patient with the mental illness based on the first predetermined number of eye movement characteristics obtained in the analysis step.
  • the third mental illness determination method of the present invention is the second mental illness determination method, wherein, in the determination step, from the first predetermined number of eye movement characteristics obtained in the analysis step, Two or more second predetermined number of eye movement features effective for distinguishing from the patient with the mental illness are selected, and the subject is the patient with the mental illness based on the second predetermined number of eye movement characteristics. It is determined whether or not there is.
  • the mental disease determination device and the mental disease determination method of the present invention it is possible to accurately determine whether or not the patient is a mental disease patient.
  • FIG. 1 It is a figure which shows an example of a structure of the mental disease determination apparatus which concerns on embodiment of this invention. It is a figure which shows an example of the result detected by the eye movement detection part shown in FIG. (A) is a figure which shows an example of a healthy person's eye movement, (b) is a figure which shows an example of the eye movement of a schizophrenia patient. It is a graph which shows an example of a structure of the healthy person and schizophrenia patient used for the discriminant formula production
  • FIG. 1 is a diagram illustrating an example of a configuration of a mental disease determination device 100 according to the present embodiment.
  • the mental illness determination device 100 includes a monitor 1, a video camera 2, and a control device 3.
  • a case where the mental disease determination device 100 determines whether or not schizophrenia is present will be described.
  • the monitor 1 includes an LCD (Liquid Crystal Display) or the like, and displays a still image or a moving image of the eye movement test.
  • the monitor 1 is, for example, an LCD having 19 inches and a resolution of 1280 ⁇ 1024 pixels. Further, the subject sits on the chair from the screen of the monitor 1 such that the viewing distance is 70 cm, for example.
  • the eye movement test is an eye movement test in which there is a significant difference in test results between healthy subjects and patients with mental disorders (schizophrenia in the present embodiment). Specifically, the eye movement test is a free viewing test, a smooth pursuit test, and a fixation stability test.
  • the gazing point is displayed on the entire black monitor 1 and moved. The subject is also instructed to follow the moving point of gaze with his eyes.
  • the gazing point is moved for 20 seconds by the following three types of movement methods.
  • First Trial Move the point of sight horizontally (horizontal pursuit)
  • Second Trial Slowly move the gazing point so that the locus draws a Lissajous figure (slow Lissajous: for example, horizontal direction 0.15 Hz, vertical direction 0.2 Hz)
  • Third Trial Move the point of interest quickly so that the trajectory draws a Lissajous figure (fast Lissajous: for example, horizontal 0.3 Hz, vertical 0.4 Hz)
  • a gaze point (white point) is displayed at the center of the black monitor 1 and a disturbing stimulus (white point) is displayed in the vicinity (or far).
  • the subject is instructed to watch the gaze point for 5 seconds even when the disturbing stimulus is displayed.
  • the nearby disturbing stimulus is displayed at a viewing angle of 1.5 degrees from the gazing point
  • the distant disturbing stimulus is displayed at a viewing angle of 2.5 degrees from the gazing point.
  • the video camera 2 includes, for example, a CCD (Charge Coupled Device), and detects the eye movement (movement of the eyeball EB) of the subject. Specifically, for example, the eye movement of the subject's left eye is detected using an EyeLink 1000 manufactured by SR Research Inc. of Canada as the video camera 2.
  • the video camera 2 corresponds to a part of “detection means”.
  • an eyeball EB indicates the eyeball of the subject.
  • the control device 3 is, for example, a personal computer, and includes a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), and an HDD (Hard Disk Drive).
  • a control program is stored in the ROM.
  • the CPU reads out and executes the control program stored in the ROM, thereby various functions including the test display unit 31, the eye movement detection unit 32, the analysis unit 33, the selection unit 34, and the evaluation unit 35. It functions as a part.
  • the CPU causes the HDD to function as the storage unit 36 by reading and executing a control program stored in the ROM.
  • the RAM is used as a work area when the CPU executes the control program.
  • the storage unit 36 stores still image data and moving image data to be displayed on the monitor 1 in the free viewing test, the smooth sweep test, and the gaze test, and the eye position data detected by the eye movement detection unit 32.
  • the storage unit 36 stores the value of each eye movement feature obtained by the analysis unit 33, discriminant data used by the evaluation unit 35, and the like.
  • the discriminant shown in the discriminant data is the following equation (1).
  • the test display unit 31, the eye movement detection unit 32, the analysis unit 33, the selection unit 34, and the evaluation unit 35 perform the discriminant generation process described with reference to FIG. 4 and the discrimination process described with reference to FIG. Execute.
  • the “discriminant generation process” is a process of generating a discriminant for determining whether or not the subject is a schizophrenic patient.
  • the “discriminating process” is a process of discriminating whether or not the subject is a schizophrenic patient based on the discriminant generated by the “discriminant generating process”.
  • the test display unit 31, the eye movement detection unit 32, the analysis unit 33, and the selection unit are distinguished from the operation when the discriminant generation process is executed and the operation when the discrimination process is executed. 34 and the function of the evaluation part 35 are demonstrated.
  • the test display unit 31 has an eye movement test in which there is a significant difference in test results between a healthy person and a patient with the mental illness (schizophrenia in the present embodiment). Is displayed on the monitor 1. Specifically, the test display unit 31 reads out still images or moving images corresponding to the free viewing test, the smooth spshoot test, and the gaze test from the storage unit 36 and displays them on the monitor 1.
  • the eye movement detection unit 32 detects the eye movement of the subject via the video camera 2 and records it in the storage unit 36 in the discriminant generation process and the discrimination process.
  • the eye movement detection unit 32 corresponds to a part of “detection means”.
  • the analysis unit 33 smoothes the eyeball position data of the subject detected through the video camera 2 with a digital FIR (Finite Impulse Response) filter in the discriminant generation process.
  • the analysis unit 33 classifies the smoothed eye movement data into three periods of a blinking period, a saccade (fine and rapid eye movement) period, and a gaze period. Store in the storage unit 36.
  • the analysis unit 33 analyzes the movement of the eyeball EB detected by the eyeball detection unit 32 to obtain three or more first predetermined number N1 of eyeball movement characteristics. Specifically, the analysis unit 33 obtains twelve eye movement features to be described later with reference to FIG. 5 as the eye movement features in the free viewing test.
  • the analysis part 33 calculates
  • requires 41 eye movement characteristics mentioned later using FIG.6 and FIG.7 as an eyeball movement characteristic in the case of a smooth spa chute test. Further, the analysis unit 33 obtains twelve eye movement features to be described later with reference to FIG. 8 as eye movement characteristics at the gaze test. In this way, the analysis unit 33 obtains 65 ( 12 + 41 + 12) eye movement characteristics.
  • the 65 eye movement features obtained by the analysis unit 33 correspond to the first predetermined number N1 of eye movement features.
  • the analysis unit 33 analyzes the movement of the eyeball EB detected by the eye movement detection unit 32 in the discrimination process, and two or more second predetermined number N2 of eye movement features (in the discrimination formula generation process ( Five first eye movement characteristics A to fifth eye movement characteristics E) to be described later are obtained.
  • the selection unit 34 discriminates between a healthy person and a schizophrenic patient from the first predetermined number N1 (65 in this embodiment) of eye movement characteristics obtained by the analysis unit 33. Two or more second predetermined number N2 of eye movement features effective for the purpose are selected. Specifically, the selection unit 34 selects an eye movement feature that is effective for discriminating between a healthy person and a patient with schizophrenia based on, for example, a significance probability (P value: P value). The selection unit 34 selects eye movement features that are highly independent from each other from 65 eye movement features. The selection unit 34 corresponds to a part of the “determination unit”.
  • the selection unit 34 is effective for discriminating a healthy person and a schizophrenic patient from 65 eye movement characteristics obtained by the analysis unit 33 by a stepwise method.
  • a second predetermined number N2 five in this embodiment
  • eye movement features are selected. In this way, the selection unit 34 selects five eye movement features (first eye movement feature A to fifth eye movement feature E) to be described later.
  • the evaluation unit 35 uses the second predetermined number N2 of eye movements selected by the selection unit 34 as a discriminant for discriminating whether or not the patient is a schizophrenic patient (equation (1) below) in the discriminant generation process.
  • the first eye movement feature A is a scan path distance that is an eye movement feature obtained in the free viewing test.
  • the second eye movement feature B is a position gain in the vertical direction, which is an eye movement feature obtained in Lissajous with a quick smooth shot test.
  • the third eye movement feature C is the number of gazes that is the eye movement feature obtained in the quick Lissajous of the smooth spa chute test.
  • the fourth eye movement feature D is a gaze time that is an eye movement feature obtained in a distant disturbing stimulus of the gaze test.
  • the fifth eye movement feature E is an S / N ratio that is an eye movement feature obtained in the horizontal pursuit of the smooth spa chute test.
  • the eye movement score Y is a value for determining whether or not the patient has schizophrenia.
  • the evaluation unit 35 substitutes the values of the five eye movement characteristics obtained by the analysis unit 33 in the discriminating process into the discriminant (the above formula (1)) generated in the discriminant generating process. Thus, it is determined whether or not the subject is a schizophrenic patient. Specifically, the evaluation unit 35 determines that the eye movement score Y is a healthy person when the eye movement score Y is equal to or greater than a threshold ( ⁇ 0.3 in this embodiment) determined by the posterior probability, and the eye movement score. When Y is less than the threshold value, it is determined that the patient is schizophrenic.
  • FIG. 2 is a diagram illustrating an example of a result detected by the eye movement detection unit 32 illustrated in FIG.
  • A is a figure which shows an example of the eye movement of the healthy subject in a free viewing test
  • (b) is a figure which shows an example of the eye movement of the schizophrenia patient in a free viewing test.
  • FIG. 2 a still image FV1 of an urban area where high-rise buildings are scattered is displayed as an example of a still image.
  • the locus NP of the healthy subject's viewpoint position moves in a wide range
  • the viewpoint position of the schizophrenia patient has stopped moving within a narrow range.
  • Such a feature is expressed as the first eye movement feature A (a scan path distance that is an eye movement feature obtained in the free viewing test) in the above equation (1).
  • the “scan path distance” is the sum of distances for moving the viewpoint.
  • a healthy person has a long scan path distance
  • a schizophrenic patient has a short scan path distance.
  • FIG. 3 is a chart showing an example of the configuration of a healthy person and a schizophrenic patient used in the discriminant generation process by the mental disease determination apparatus 100 shown in FIG.
  • the numerical values in FIG. 3 are (average value) ⁇ (standard deviation).
  • the P value is a significant probability.
  • the variable with a significant difference between a healthy subject and a schizophrenia patient has indicated the numerical value of P value in bold type, and has underlined.
  • the pre-disease intelligence quotient is data for 38 schizophrenic patients.
  • PANSS in the variable column indicating the degree of schizophrenia pathology is “Positive And Negative Synthetic Scale”, CPZ is “Chlorprozine”, and GAF is “Global Assessment of Fun”.
  • FIG. 4 is a flowchart showing an example of the discriminant generation process in the mental illness determination apparatus 100 shown in FIG.
  • the still image of the free viewing test is displayed on the monitor 1 by the test display unit 31 (step S101).
  • the eye movement detection unit 32 detects the eye movement of the subject through the video camera 2 (step S103).
  • the movement of the eyeball EB detected in step S103 is analyzed by the analysis unit 33, and twelve eye movement features shown in FIG. 5 are obtained (step S105).
  • step S107 the moving image of the smooth spat test is displayed on the monitor 1 by the test display unit 31 (step S107).
  • the eye movement detection unit 32 detects the eye movement of the subject via the video camera 2 (step S109).
  • the motion of the eyeball EB detected in step S109 is analyzed by the analysis unit 33, and 41 eye movement features shown in FIGS. 6 and 7 are obtained (step S111).
  • step S113 the still image of the gaze test is displayed on the monitor 1 by the test display unit 31 (step S113).
  • the eye movement detection unit 32 detects the eye movement of the subject through the video camera 2 (step S115).
  • the analysis unit 33 analyzes the movement of the eyeball EB detected in step S115, and obtains the twelve eye movement features shown in FIG. 8 (step S117).
  • the selection unit 34 obtains 65 eye movement characteristics corresponding to the three tests for all the subjects (69 healthy persons and 40 schizophrenia patients as shown in FIG. 3, total 109 persons). It is determined whether or not (step S119). If it is determined that there is a subject who has not finished the test (NO in step S119), the process returns to step S101, and the processing after step S101 is started for the subject who has not finished the test. If it is determined that the test has been completed for all the subjects (YES in step S119), the process proceeds to step S121.
  • the selection unit 34 uses the stepwise method to discriminate between a healthy person and a schizophrenic patient from the 65 eye movement characteristics obtained in step S105, step S111, and step S117.
  • a valid second predetermined number N2 here, 5
  • the linear equations (the above equation (1)) relating to the five eye movement features selected in step S121. Is obtained (step S123), and the process is terminated.
  • Step S103, step S109, and step S115 shown in FIG. 4 correspond to a part of the “detection step”.
  • Steps S105, S111, and S117 illustrated in FIG. 4 correspond to a part of the “analysis process”.
  • Steps S121 and S123 illustrated in FIG. 4 correspond to a part of the “determination step”.
  • the selection unit 34 selects the second predetermined number N2 of eye movement features that are effective for discriminating between a healthy person and a schizophrenic patient from the first predetermined number N1 of eye movement characteristics. Therefore, a healthy person and a schizophrenic patient can be distinguished by a simple process.
  • the second predetermined number N2 is five is described, but the second predetermined number N2 may be two or more.
  • the second predetermined number N2 is two, it is possible to discriminate between a healthy person and a patient with schizophrenia by a simpler process.
  • the selection unit 34 selects an appropriate number of appropriate eye movement features. You can choose. Therefore, it can be determined more accurately whether or not the patient has a mental illness. As a result of executing the stepwise method, the second predetermined number is determined. In the stepwise method, the second predetermined number is not predetermined.
  • the selection unit 34 selects an eye movement feature by the stepwise method.
  • the selection unit 34 may perform other methods (for example, genetic algorithm, principal component analysis, etc.)
  • determine a healthy person and the patient of schizophrenia may be sufficient.
  • the selection unit 34 selects the second predetermined number N2 of eye movement features that are highly independent from each other from the first predetermined number N1 of eye movement characteristics. This is because it is possible to more accurately determine whether or not the patient is a mentally ill patient by selecting the second predetermined number N2 of eye movement features that are highly independent of each other.
  • the evaluation unit 35 obtains a linear equation (the above equation (1)) regarding the second predetermined number N2 of eye movement characteristics as a discriminant for determining whether or not the subject is a schizophrenic patient, With a simple configuration, it is possible to accurately distinguish between a healthy person and a schizophrenic patient.
  • the evaluation unit 35 obtains a linear equation relating to the second predetermined number N2 of eye movement features as a discriminant, but the evaluation unit 35 uses the second predetermined number N2 of eyeballs as a discriminant. Any form may be used as long as the function relating to the motion feature is obtained.
  • the evaluation unit 35 may obtain a quadratic or higher-order linear equation regarding the second predetermined number N2 of eye movement features as a discriminant.
  • the free viewing test, the smooth spa shoot test, and the gaze test are eye movement tests in which there are marked differences in test results between healthy subjects and schizophrenic patients. Therefore, since the eye movement detection unit 32 detects the movement of the eyeball EB in the free viewing test, the smooth shoot test, and the gaze test, there is a significant difference between a healthy person and a schizophrenic patient. Results are obtained. Therefore, it becomes possible to accurately discriminate between a healthy person and a schizophrenic patient.
  • the eye movement detection unit 32 detects the movement of the eyeball EB in the free viewing test, the smooth spout test, and the gaze test is described. Any form may be used as long as it detects the movement of the eyeball EB in at least one of the inching test, the smooth spa chute test, and the gaze test.
  • the eye movement test includes at least one of a free viewing test using a moving image and a visual search test in addition to (or instead of) the free viewing test, the smooth shoot test, and the gaze test. Form may be sufficient.
  • the visual search test is a test in which, for example, a large number of characters are displayed on a monitor screen and an instructed character is searched for among them. In the visual search test, the number of saccades, the search time, etc. are obtained as eye movement features.
  • step S105 the 65 eye movement characteristics obtained in step S105, step S111, and step S117 in FIG. 4 will be described, and then selected in step S121 in FIG. Individual eye movement characteristics will be described.
  • FIG. 5 is a chart showing an example of eye movement characteristics obtained by the analysis unit 33 when a still image of the free viewing test is displayed on the monitor 1 shown in FIG.
  • the numerical values in FIG. 5 are (average value) ⁇ (standard deviation).
  • the P value is a significant probability.
  • Eye movement characteristics that are significantly different between healthy subjects and schizophrenia patients are indicated by the corresponding P value numerical values in bold and underlined.
  • Eye movement characteristics that are significantly different between healthy individuals and schizophrenic patients are specifically scan path distance (sum of distance to move the viewpoint), number of gazes (number of times the viewpoint is fixed), saccade Number (number of fine and rapid eye movements), gaze density, gaze time, etc.
  • the eye movement feature selected by the selection unit 34 among the 12 eye movement features shown in FIG. 5 is the scan path distance (first eye movement feature A).
  • FIG. 6 is a chart showing an example of eye movement characteristics obtained by the analysis unit 33 when a moving image (horizontal pursuit and slow Lissajous) of the smooth pursuit test is displayed on the monitor 1 shown in FIG.
  • FIG. 7 is a chart showing an example of eye movement characteristics obtained by the analysis unit 33 when a moving image (fast Lissajous) of a smooth spa chute test is displayed on the monitor 1 shown in FIG.
  • the numerical values in FIG. 6 and FIG. 7 are (average value) ⁇ (standard deviation).
  • the P value is a significant probability.
  • the eye movement characteristics that are significantly different between healthy subjects and schizophrenic patients are indicated by the corresponding P values in bold. Underlined.
  • eye movement characteristics that are significantly different between healthy subjects and schizophrenia patients are position gain (vertical), position gain (horizontal), number of gazes, number of saccades, etc. in fast Lissajous.
  • the eye movement feature selected by the selection unit 34 is the vertical position gain (second eye movement feature B) in the fast Lissajous, the number of gazes. (Third eye movement feature C) and S / N ratio (fifth eye movement feature E) in horizontal pursuit.
  • FIG. 8 is a chart showing an example of eye movement characteristics obtained by the analysis unit 33 when a still image of a gaze test is displayed on the monitor 1 shown in FIG.
  • the numerical values in FIG. 8 are (average value) ⁇ (standard deviation).
  • the P value is a significant probability.
  • the eye movement characteristics that are significantly different between healthy subjects and schizophrenic patients are indicated by the corresponding P values in bold and underlined. ing.
  • eye movement features that are significantly different between healthy and schizophrenic patients are: gaze time at distant disturbing stimuli, gaze time at near disturbing stimuli, gaze time without disturbing stimuli, no disturbing stimuli
  • the eye movement feature selected by the selection unit 34 among the twelve eye movement features shown in FIG. 8 is the gaze time (fourth eye movement feature D) in the far disturbing stimulus.
  • FIG. 9 is a chart showing an example of the eye movement feature selected by the selection unit 34 shown in FIG.
  • the numerical values in FIG. 9 are (average value) ⁇ (standard deviation).
  • the P value is a significant probability.
  • eye movement characteristics that are particularly significant between healthy subjects and schizophrenic patients are indicated by the corresponding P values in bold letters and underlined.
  • the first eye movement feature A is the scan path distance (the fifth eye movement feature from the bottom in FIG. 5) which is the eye movement feature obtained in the free viewing test.
  • the second eye movement feature B is a vertical position gain (fifth eye movement feature from the top in FIG. 7), which is an eye movement feature obtained in a quick Lissajous of a smooth spa chute test.
  • the third eye movement feature C is the number of gazes (the seventh eye movement feature from the top in FIG.
  • the fourth eye movement feature D is a gaze time (third eye movement feature from the bottom in FIG. 8) that is an eye movement feature obtained in a distant disturbing stimulus of the gaze test.
  • the fifth eye movement feature E is an S / N ratio (first eye movement feature from the top of FIG. 6) which is an eye movement feature obtained in the horizontal pursuit of the smooth spa chute test.
  • FIG. 10 is a flowchart illustrating an example of determination processing in the mental disease determination apparatus 100 illustrated in FIG.
  • the still image of the free viewing test is displayed on the monitor 1 by the test display unit 31 (step S201).
  • the eye movement detection unit 32 detects the eye movement of the subject through the video camera 2 (step S203).
  • the analysis unit 33 analyzes the movement of the eyeball EB detected in step S203, and obtains the first eye movement feature A (scan path distance) (step S205).
  • the test display unit 31 displays a moving image of the smooth shoot test on the monitor 1 (step S207).
  • the eye movement detection unit 32 detects the eye movement of the subject through the video camera 2 (step S209).
  • the motion of the eyeball EB detected in step S209 is analyzed by the analysis unit 33, and the second eye movement feature B (vertical position gain in the fast Lissajous) and the third eye movement feature C (in the fast Lissajous) The number of gazes) and the fifth eye movement feature E (S / N ratio in horizontal pursuit) are obtained (step S211).
  • the still image of the gaze test is displayed on the monitor 1 by the test display unit 31 (step S213).
  • the eye movement detection unit 32 detects the eye movement of the subject through the video camera 2 (step S215).
  • the analysis unit 33 analyzes the movement of the eyeball EB detected in step S215, and obtains a fourth eye movement feature D (gaze time in a distant disturbing stimulus) (step S217).
  • step S217 the values of the first eye movement feature A to the fifth eye movement feature E obtained by the evaluation unit 35 in step S205, step S211 and step S217 are expressed by the above equation (1).
  • step S219 the evaluation unit 35 determines whether or not the eye movement score Y obtained in step S219 is greater than or equal to zero (step S221).
  • the threshold in this embodiment, ⁇ 0.3
  • the evaluation unit 35 determines that the subject is a healthy person. It is determined that there is (step S223), and the process is terminated.
  • the evaluation unit 35 determines that the subject is a schizophrenic patient. Is determined (step S225), and the process is terminated.
  • Step S203, step S209, and step S215 shown in FIG. 10 correspond to a part of the “detection step”.
  • Steps S205, S211 and S217 shown in FIG. 10 correspond to a part of the “analysis process”.
  • Step S219, step S221, step S223, and step S225 shown in FIG. 10 correspond to a part of the “determination step”.
  • step S203, step S209, and step S215 of FIG. 10 the eye movement detection unit 32 performs a preselected eye movement test (in this embodiment, a free viewing test, a smooth shoot test, and a gaze test). The movement of the eyeball EB of the subject when viewing the image is detected.
  • the analysis unit 33 analyzes the movement of the eyeball EB detected by the eyeball movement detection unit 32.
  • step S219, step S221, step S223, and step S225 of FIG. 10 whether or not the subject is a schizophrenic patient based on the eye movement characteristics obtained by the analysis unit 33 by the evaluation unit 35. Is determined.
  • the subject is a schizophrenic patient based on the second predetermined number N2 of eye movement features selected by the selection unit 34 among the first predetermined number N1 of eye movement features obtained by the analysis unit 33.
  • the form which determines whether a test subject is a schizophrenic patient may be sufficient. In this case, the discriminant generation process and the discrimination process are simplified. Further, for example, it may be configured to determine whether or not the subject is a schizophrenic patient based on all eye movement characteristics of the first predetermined number N1.
  • the scan path distance (first eye movement feature A) in the free viewing test in which the second predetermined number N2 of eye movement features is an effective eye movement feature for distinguishing between healthy subjects and schizophrenia patients. Therefore, it can be accurately determined whether or not the subject is a schizophrenic patient.
  • the second predetermined number N2 of eye movement features may include other eye movement features having a strong correlation with the scan path distance instead of the scan path distance in the free viewing test.
  • the second predetermined number N2 of eye movement features is an effective eye movement feature for distinguishing between healthy subjects and schizophrenic patients, and a vertical position gain (second eyeball) in a quick lissajous of a smooth spshoot test. Since it includes the movement feature B), it can be accurately determined whether or not the subject is a schizophrenic patient.
  • the second predetermined number N2 of eye movement characteristics may include other eye movement characteristics having a strong correlation with the position gain, instead of the vertical position gain in the Lissajous test with a quick smooth spout test.
  • the second predetermined number N2 of eye movement features is the first eye movement feature A to the fifth eye movement feature E
  • the second predetermined number N2 of eye movement features is described.
  • any configuration including at least one of the first eye movement feature A to the fifth eye movement feature E may be used.
  • FIG. 11 is a chart showing an example of an evaluation result by the evaluation unit 35 shown in FIG.
  • the left side of FIG. 11 is “when all data is used”, and the right side is a case where “Leave-one-out cross-validation” is performed.
  • “when all data is used” means that a discriminant (the above formula (1)) is generated using the data of all the subjects shown in FIG. 3, and the generated discriminant is used in FIG. This is a case where the discrimination processing shown in FIG.
  • “Leave-one-out cross-validation” means that a discriminant is generated using data excluding one person (herein referred to as an excluder) among the target persons shown in FIG.
  • the number of persons determined to be healthy by the evaluation unit 35 is 65, and the correct answer rate is 94. 2%.
  • the number of persons determined to be schizophrenia patients by the evaluation unit 35 was 31, and the correct answer rate was 77.5%.
  • the overall correct answer rate was 88.1%.
  • the psychiatric disorder determination device 100 it is possible to accurately determine whether or not the patient is a psychiatric disorder (in this embodiment, schizophrenia).
  • a psychiatric disorder in this embodiment, schizophrenia
  • the mental illness may be another mental illness (for example, depression, manic depression, etc.).
  • FIG. 12 is a bar graph showing an example of an evaluation result by the evaluation unit 35 shown in FIG.
  • FIG. 13 is a ROC (Receiver Operating Characteristic) graph showing an example of an evaluation result by the evaluation unit 35 shown in FIG.
  • the horizontal axis indicates the eye movement score Y
  • the vertical axis indicates the ratio.
  • a dark shade is a patient with schizophrenia
  • a thin shade is a healthy person.
  • the evaluation unit 35 determines that the person is a healthy person, and the eye movement score.
  • Y is less than the threshold value, it is determined that the patient is schizophrenic.
  • a healthy person is determined very accurately.
  • the majority of schizophrenia patients who are misjudged as healthy individuals have a case where the eye movement score Y is close to zero, and further studies will indicate that the correct answer rate may be improved. .
  • the horizontal axis represents the false positive rate
  • the vertical axis represents the true positive rate.
  • the area of the shaded area below the ROC curve GR was 0.94 or more with respect to the maximum value (value in a case where perfect discrimination is possible) 1. This indicates that the schizophrenic patient can be clearly identified as a healthy person by the discriminant represented by the above formula (1).
  • the monitor 1 may include a functional unit corresponding to the test display unit 31.
  • the control device 3 includes the eye movement detection unit 32
  • the video camera 2 may include a functional unit corresponding to the eye movement detection unit 32.
  • the mental illness determination apparatus 100 that determines whether or not the patient is a mental illness has been described. It may be configured.
  • the mental disease determination system may include an eye movement test display device, an eye movement detection device, an analysis device, and a determination device.
  • the eye movement test display device includes a monitor and displays an image of the eye movement test on the monitor.
  • the eye movement detection device includes a video camera and detects the movement of the eyeball of the subject.
  • the analysis device analyzes the movement of the eyeball detected by the eyeball movement detection device and obtains the eyeball movement feature.
  • the determination device determines whether or not the subject is a mentally ill patient based on the eye movement characteristics obtained by the analysis device.
  • the evaluation unit 35 determines whether the eye movement score Y is a schizophrenic patient depending on whether or not the threshold (in this embodiment, ⁇ 0.3) is less than zero. Although the case of determining whether or not is described, the evaluation unit 35 may determine a possibility of being a schizophrenic patient. In other words, the evaluation unit 35 may determine that the greater the value of the eye movement score Y, the higher the possibility of being a healthy person, and the smaller the value, the higher the possibility of suffering from a mental illness. In this case, when the doctor makes a diagnosis, the magnitude of the eye movement score Y can be used as a reference for determining whether or not he is a healthy person.
  • the first predetermined number N1 is 65 has been described, but the first predetermined number N1 may be a number in the range of 50 to 100, for example.
  • the second predetermined number N2 is five has been described.
  • the second predetermined number N2 may be a number in the range of 5 to 15, for example.
  • the evaluation unit 35 determines whether or not the patient is a schizophrenic patient has been described.
  • the evaluation unit is a schizophrenic patient or an autistic patient. It may be a form for determining whether or not. Further, the evaluation unit may determine which mental disorder the subject has among a plurality of preset mental disorders (for example, schizophrenia, autism, depression).
  • the evaluation unit 35 determines whether or not the patient is a schizophrenic patient has been described, but the evaluation unit may determine the prognosis or degree of mental illness.
  • the present invention is applicable to a mental illness determination apparatus and a mental illness determination method for determining whether or not a patient has a mental illness.

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Medical Informatics (AREA)
  • Engineering & Computer Science (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Pathology (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
  • Eye Examination Apparatus (AREA)

Abstract

A mental disease determination device (100) is equipped with an eye movement detection unit (32), an analysis unit (33) and an evaluation unit (35). The eye movement detection unit (32) can detect the movement of an eye (EB) of a subject during the watching of an image of an eye movement test which is displayed on a monitor (1) through a video camera (2). The analysis unit (33) can analyze the movement of the eye (EB) which is detected by the eye movement detection unit (32). The evaluation unit (35) can determine as to whether or not the subject is a patient of a mental disease on the basis of at least two first predetermined numbers N1 of eye movement characteristics which are determined by the analysis unit (33).

Description

精神疾患判定装置、及び、精神疾患判定方法Mental disease determination device and mental disease determination method
　本発明は、精神疾患の患者であるか否かを判定する精神疾患判定装置、及び、精神疾患判定方法に関する。 The present invention relates to a mental illness determination apparatus and a mental illness determination method for determining whether or not a patient has a mental illness.
　従来、統合失調症に罹患しているか否かの判定を行う統合失調症診断装置が知られている。例えば、刺激表示手段、視点特定手段、反応的探索スコア算出手段、運動数計測手段、及び、判定手段を備える統合失調症診断装置が開示されている（特許文献１参照）。 Conventionally, a schizophrenia diagnostic apparatus for determining whether or not a patient has schizophrenia is known. For example, a schizophrenia diagnostic apparatus including a stimulus display unit, a viewpoint identification unit, a reactive search score calculation unit, an exercise number measurement unit, and a determination unit is disclosed (see Patent Document 1).
　上記刺激表示手段は、被験者に対して視覚的な刺激を提示する。上記視点特定手段は、上記刺激表示手段に対する被験者の視点を特定する。上記反応的探索スコア算出手段は、反応的探索スコアを算出する。上記運動数計測手段は、運動数を計測する。上記判定手段は、反応的探索スコア及び運動数から被験者が統合失調症に罹患しているか否かを判定する。 The stimulus display means presents a visual stimulus to the subject. The viewpoint specifying means specifies the viewpoint of the subject with respect to the stimulus display means. The reactive search score calculation means calculates a reactive search score. The exercise number measuring means measures the exercise number. The determination means determines whether or not the subject suffers from schizophrenia from the reactive search score and the number of exercises.
　特許文献１に記載の統合失調症診断装置によれば、被験者が統合失調症に罹患している可能性があるか、或いは健常者であるかを高精度で判定できると特許文献１に記載されている。 According to the schizophrenia diagnostic apparatus described in Patent Document 1, it is described in Patent Document 1 that it can be determined with high accuracy whether a subject is likely to suffer from schizophrenia or is a healthy person. ing.
特開２００４－２９８５２６号公報JP 2004-298526 A
　しかしながら、特許文献１に記載の統合失調症診断装置では、判定精度が充分ではない（７０％～８０％である）ため、臨床への適用が困難である。また、特許文献１に記載の統合失調症診断装置は、複雑な構造を備えるため製造コストが高いという問題もある。 However, the schizophrenia diagnostic apparatus described in Patent Document 1 has insufficient accuracy (70% to 80%) and is difficult to apply to clinical practice. Moreover, since the schizophrenia diagnostic apparatus described in Patent Document 1 has a complicated structure, there is a problem that the manufacturing cost is high.
　本発明は、上記課題に鑑みてなされたものであり、精神疾患の患者であるか否かを正確に判定することの可能な精神疾患判定装置、及び、精神疾患判定方法を提供することを目的としている。 The present invention has been made in view of the above problems, and an object of the present invention is to provide a mental disease determination apparatus and a mental disease determination method capable of accurately determining whether or not a patient has a mental disease. It is said.
　本発明の第１の精神疾患判定装置は、精神疾患を判定する精神疾患判定装置であって、検出手段、分析手段、及び、判定手段を備える。前記検出手段は、予め選定された眼球運動テストの画像を見る際の被験者の眼球の動きを検出する。前記分析手段は、前記検出手段によって検出された眼球の動きを分析し、３個以上の第１所定数の眼球運動特徴を求める。前記判定手段は、前記分析手段によって求められた前記第１所定数の眼球運動特徴に基づき、前記被験者の前記精神疾患を判定する。 The first mental illness determination apparatus of the present invention is a mental illness determination apparatus for determining a mental illness, and includes a detection means, an analysis means, and a determination means. The detection means detects a movement of the eyeball of the subject when viewing a preselected eye movement test image. The analysis unit analyzes the movement of the eyeball detected by the detection unit and obtains three or more first predetermined number of eye movement features. The determination means determines the mental illness of the subject based on the first predetermined number of eye movement characteristics obtained by the analysis means.
　本発明の第２の精神疾患判定装置は、精神疾患の患者であるか否かを判定する精神疾患判定装置であって、検出手段、分析手段、及び、判定手段を備える。前記検出手段は、予め選定された眼球運動テストの画像を見る際の被験者の眼球の動きを検出する。前記分析手段は、前記検出手段によって検出された眼球の動きを分析し、３個以上の第１所定数の眼球運動特徴を求める。前記判定手段は、前記分析手段によって求められた前記第１所定数の眼球運動特徴に基づき、前記被験者が前記精神疾患の患者であるか否かを判定する。 The second mental illness determination device of the present invention is a mental illness determination device that determines whether or not a patient has a mental illness, and includes a detection means, an analysis means, and a determination means. The detection means detects a movement of the eyeball of the subject when viewing a preselected eye movement test image. The analysis unit analyzes the movement of the eyeball detected by the detection unit and obtains three or more first predetermined number of eye movement features. The determination means determines whether the subject is a patient with the mental disease based on the first predetermined number of eye movement characteristics obtained by the analysis means.
　本発明の第３の精神疾患判定装置は、前記第２の精神疾患判定装置であって、前記判定手段は、前記分析手段によって求められた前記第１所定数の眼球運動特徴から、健常者と前記精神疾患の患者とを判別するために有効な２個以上の第２所定数の眼球運動特徴を選択する。また、前記判定手段は、前記第２所定数の眼球運動特徴に基づき、前記被験者が前記精神疾患の患者であるか否かを判定する。 A third mental illness determination device according to the present invention is the second mental illness determination device, wherein the determination means determines whether the first predetermined number of eye movement characteristics obtained by the analysis means are normal subjects and Two or more second predetermined number of eye movement features effective for discriminating from the mentally ill patient are selected. The determination means determines whether the subject is a patient with the mental illness based on the second predetermined number of eye movement characteristics.
　本発明の第４の精神疾患判定装置は、前記第３の精神疾患判定装置であって、前記判定手段は、前記分析手段によって求められた前記第１所定数の眼球運動特徴から、互いに独立性の強い前記第２所定数の眼球運動特徴を選択する。 The fourth mental illness determination apparatus of the present invention is the third mental illness determination apparatus, wherein the determination means is independent from the first predetermined number of eye movement characteristics obtained by the analysis means. The second predetermined number of eye movement features having strong strength are selected.
　本発明の第５の精神疾患判定装置は、前記第４の精神疾患判定装置であって、前記判定手段は、ステップワイズ法によって、前記分析手段によって求められた前記第１所定数の眼球運動特徴から、前記健常者と前記精神疾患の患者とを判別するために有効な前記第２所定数の眼球運動特徴を選択する。 The fifth mental illness determination apparatus of the present invention is the fourth mental illness determination apparatus, wherein the determination means is the first predetermined number of eye movement characteristics obtained by the analysis means by a stepwise method. Then, the second predetermined number of eye movement features effective for discriminating between the healthy person and the patient with the mental illness are selected.
　本発明の第６の精神疾患判定装置は、前記第３の精神疾患判定装置から前記第５の精神疾患判定装置のいずれか１つの精神疾患判定装置であって、前記判定手段は、前記第２所定数の眼球運動特徴の関数を判別式として求め、前記判別式によって、前記被験者が前記精神疾患の患者であるか否かを判定する。 The sixth mental disease determination device of the present invention is any one of the third mental disease determination device to the fifth mental disease determination device, wherein the determination means includes the second mental disease determination device. A function of a predetermined number of eye movement characteristics is obtained as a discriminant, and it is determined by the discriminant whether the subject is a patient with the mental illness.
　本発明の第７の精神疾患判定装置は、前記第６の精神疾患判定装置であって、前記判定手段は、前記判別式として、前記第２所定数の眼球運動特徴に関する線形方程式を求める。 The seventh mental disease determination device of the present invention is the sixth mental disease determination device, wherein the determination means obtains a linear equation relating to the second predetermined number of eye movement characteristics as the discriminant.
　本発明の第８の精神疾患判定装置は、前記第３の精神疾患判定装置から前記第６の精神疾患判定装置のいずれか１つの精神疾患判定装置であって、前記眼球運動テストは、前記健常者と前記精神疾患の患者との間でテスト結果に顕著な差異がある眼球運動テストである。 An eighth mental disease determination device according to the present invention is the mental disease determination device according to any one of the third mental disease determination device to the sixth mental disease determination device, wherein the eye movement test is performed based on the normal state. This is an eye movement test in which there is a significant difference in test results between a person and a patient with the mental illness.
　本発明の第９の精神疾患判定装置は、前記第８の精神疾患判定装置であって、前記眼球運動テストは、注視テスト、スムースパシュートテスト、及び、フリービューイングテストのうち、少なくとも１つを含む。 The ninth mental illness determination device of the present invention is the eighth mental illness determination device, wherein the eye movement test includes at least one of a gaze test, a smooth spa shoot test, and a free viewing test. Including.
　本発明の第１０の精神疾患判定装置は、前記第３の精神疾患判定装置から前記第９の精神疾患判定装置のいずれか１つの精神疾患判定装置であって、前記精神疾患は、統合失調症であり、前記第２所定数の眼球運動特徴は、フリービューイングテストにおけるスキャンパス距離、又は、前記スキャンパス距離と相関の強い他の眼球運動特徴を含む。 The tenth mental disease determination device of the present invention is any one of the third mental disease determination device to the ninth mental disease determination device, wherein the mental disease is schizophrenia. And the second predetermined number of eye movement features include a scan path distance in a free viewing test or other eye movement characteristics having a strong correlation with the scan path distance.
　本発明の第１１の精神疾患判定装置は、前記第３の精神疾患判定装置から前記第９の精神疾患判定装置のいずれか１つの精神疾患判定装置であって、前記第２所定数の眼球運動特徴は、スムースパシュートテストの速いリサージュにおける垂直方向の位置ゲイン、又は、前記位置ゲインと相関の強い他の眼球運動特徴を含む。 An eleventh mental disease determination device according to the present invention is the mental disease determination device according to any one of the third mental disease determination device to the ninth mental disease determination device, wherein the second predetermined number of eye movements. Features include a vertical position gain in a quick lissajous of a smooth spout test, or other eye movement features that are highly correlated with the position gain.
　本発明の第１２の精神疾患判定装置は、２個以上の第２所定数の眼球運動特徴に基づき、被験者が統合失調症の患者であるか否かを判定する精神疾患判定装置であって、前記第２所定数の眼球運動特徴は、フリービューイングテストにおけるスキャンパス距離、スムースパシュートテストの速いリサージュにおける垂直方向の位置ゲイン、スムースパシュートテストの速いリサージュにおける注視数、注視テストの遠い妨害刺激における注視期間、及び、スムースパシュートテストの水平パシュートにおけるＳ／Ｎ比のうち、少なくとも１つを含む。 The twelfth mental disease determination device of the present invention is a mental disease determination device that determines whether a subject is a schizophrenic patient based on two or more second predetermined number of eye movement characteristics. The second predetermined number of eye movement features include a scan path distance in a free viewing test, a vertical position gain in a quick lissajous test, a number of gazes in a quick lissajous test Lissajous, a distant disturbance stimulus in a gaze test It includes at least one of the gaze period and the S / N ratio in the horizontal pursuit of the smooth spout test.
　本発明の第１の精神疾患判定方法は、精神疾患かを判定する精神疾患判定方法であって、検出工程、分析工程、及び、判定工程を含む。前記検出工程は、眼球運動テストの画像を見る際の被験者の眼球の動きを検出する。前記分析工程は、前記検出工程において検出された眼球の動きを分析し、３個以上の第１所定数の眼球運動特徴を求める。前記判定工程は、前記分析工程において求められた前記第１所定数の眼球運動特徴に基づき、前記被験者の前記精神疾患を判定する。 The first mental illness determination method of the present invention is a mental illness determination method for determining whether or not a mental illness includes a detection step, an analysis step, and a determination step. The detection step detects the movement of the eyeball of the subject when viewing the image of the eye movement test. In the analyzing step, the eye movement detected in the detecting step is analyzed to obtain three or more first predetermined number of eye movement features. The determination step determines the mental illness of the subject based on the first predetermined number of eye movement characteristics obtained in the analysis step.
　本発明の第２の精神疾患判定方法は、精神疾患の患者であるか否かを判定する精神疾患判定方法であって、検出工程、分析工程、及び、判定工程を含む。前記検出工程は、眼球運動テストの画像を見る際の被験者の眼球の動きを検出する。前記分析工程は、前記検出工程において検出された眼球の動きを分析し、３個以上の第１所定数の眼球運動特徴を求める。前記判定工程は、前記分析工程において求められた前記第１所定数の眼球運動特徴に基づき、前記被験者が前記精神疾患の患者であるか否かを判定する。 The second mental disease determination method of the present invention is a mental disease determination method for determining whether or not a patient has a mental disease, and includes a detection step, an analysis step, and a determination step. The detection step detects the movement of the eyeball of the subject when viewing the image of the eye movement test. In the analyzing step, the eye movement detected in the detecting step is analyzed to obtain three or more first predetermined number of eye movement features. The determination step determines whether or not the subject is a patient with the mental illness based on the first predetermined number of eye movement characteristics obtained in the analysis step.
　本発明の第３の精神疾患判定方法は、前記第２の精神疾患判定方法であって、前記判定工程において、前記分析工程において求められた前記第１所定数の眼球運動特徴から、健常者と前記精神疾患の患者とを判別するために有効な２個以上の第２所定数の眼球運動特徴を選択し、前記第２所定数の眼球運動特徴に基づき、前記被験者が前記精神疾患の患者であるか否かを判定する。 The third mental illness determination method of the present invention is the second mental illness determination method, wherein, in the determination step, from the first predetermined number of eye movement characteristics obtained in the analysis step, Two or more second predetermined number of eye movement features effective for distinguishing from the patient with the mental illness are selected, and the subject is the patient with the mental illness based on the second predetermined number of eye movement characteristics. It is determined whether or not there is.
　本発明の精神疾患判定装置、及び、精神疾患判定方法によれば、精神疾患の患者であるか否かを正確に判定することができる。 According to the mental disease determination device and the mental disease determination method of the present invention, it is possible to accurately determine whether or not the patient is a mental disease patient.
本発明の実施形態に係る精神疾患判定装置の構成の一例を示す図である。It is a figure which shows an example of a structure of the mental disease determination apparatus which concerns on embodiment of this invention. 図１に示す眼球運動検出部によって検出された結果の一例を示す図である。（ａ）は、健常者の眼球運動の一例を示す図であり、（ｂ）は、統合失調症患者の眼球運動の一例を示す図である。It is a figure which shows an example of the result detected by the eye movement detection part shown in FIG. (A) is a figure which shows an example of a healthy person's eye movement, (b) is a figure which shows an example of the eye movement of a schizophrenia patient. 図１に示す精神疾患判定装置による判別式生成処理に用いられる健常者及び統合失調症患者の構成の一例を示す図表である。It is a graph which shows an example of a structure of the healthy person and schizophrenia patient used for the discriminant formula production | generation process by the psychiatric disorder determination apparatus shown in FIG. 図１に示す精神疾患判定装置における判別式生成処理の一例を示すフローチャートである。It is a flowchart which shows an example of the discriminant formula production | generation process in the mental disease determination apparatus shown in FIG. 図１に示すモニタにフリービューイングテストの画像を表示した場合に、分析部によって得られる眼球運動特徴の一例を示す図表である。It is a graph which shows an example of the eye movement characteristic obtained by an analysis part, when the image of a free viewing test is displayed on the monitor shown in FIG. 図１に示すモニタにスムースパシュートテストの画像（水平パシュート及び遅いリサージュ）を表示した場合に、分析部によって得られる眼球運動特徴の一例を示す図表である。6 is a chart showing an example of eye movement characteristics obtained by an analysis unit when a smooth pursuit test image (horizontal pursuit and slow Lissajous) is displayed on the monitor shown in FIG. 1. 図１に示すモニタにスムースパシュートテストの画像（速いリサージュ）を表示した場合に、分析部によって得られる眼球運動特徴の一例を示す図表である。It is a chart which shows an example of the eye movement feature obtained by an analysis part, when the image (fast Lissajous) of a smooth spa chute test is displayed on the monitor shown in FIG. 図１に示すモニタに注視テストの画像を表示した場合に、分析部によって得られる眼球運動特徴の一例を示す図表である。7 is a chart showing an example of eye movement characteristics obtained by an analysis unit when an image of a gaze test is displayed on the monitor shown in FIG. 1. 図１に示す選択部によって選択された眼球運動特徴の一例を示す図表である。It is a graph which shows an example of the eye movement feature selected by the selection part shown in FIG. 図１に示す精神疾患判定装置における判別処理の一例を示すフローチャートである。It is a flowchart which shows an example of the discrimination | determination process in the mental disease determination apparatus shown in FIG. 図１に示す評価部による評価結果の一例を示す図表である。It is a graph which shows an example of the evaluation result by the evaluation part shown in FIG. 図１に示す評価部による評価結果の一例を示す棒グラフである。It is a bar graph which shows an example of the evaluation result by the evaluation part shown in FIG. 図１に示す評価部による評価結果の一例を示すＲＯＣグラフである。It is a ROC graph which shows an example of the evaluation result by the evaluation part shown in FIG.
　以下、本発明の実施形態について、図面（図１～図１３）を参照しながら説明する。なお、図中、同一又は相当部分については同一の参照符号を付して説明を繰り返さない。 Hereinafter, embodiments of the present invention will be described with reference to the drawings (FIGS. 1 to 13). In the drawings, the same or corresponding parts are denoted by the same reference numerals and description thereof is not repeated.
　まず、図１を参照して、本実施形態に係る精神疾患判定装置１００について説明する。図１は、本実施形態に係る精神疾患判定装置１００の構成の一例を示す図である。精神疾患判定装置１００は、モニタ１、ビデオカメラ２、及び、制御装置３を備えている。なお、本実施形態では、精神疾患判定装置１００が、統合失調症であるか否かを判定する場合について説明する。 First, a mental illness determination apparatus 100 according to the present embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of a configuration of a mental disease determination device 100 according to the present embodiment. The mental illness determination device 100 includes a monitor 1, a video camera 2, and a control device 3. In the present embodiment, a case where the mental disease determination device 100 determines whether or not schizophrenia is present will be described.
　モニタ１は、ＬＣＤ（Ｌｉｑｕｉｄ　Ｃｒｙｓｔａｌ　Ｄｉｓｐｌａｙ）等からなり、眼球運動テストの静止画像又は動画像を表示する。本実施形態では、モニタ１は、例えば、１９インチ、解像度１２８０×１０２４ピクセルのＬＣＤである。また、被験者は、モニタ１の画面から、例えば、視距離７０ｃｍの位置になるように椅子に座る。本実施形態では、眼球運動テストは、健常者と精神疾患（本実施形態では、統合失調症）の患者との間でテスト結果に顕著な差異がある眼球運動テストである。具体的には、眼球運動テストは、フリービューイング（ｆｒｅｅ　ｖｉｅｗｉｎｇ）テスト、スムースパシュート（ｓｍｏｏｔｈ　ｐｕｒｓｕｉｔ）テスト、及び、注視（ｆｉｘａｔｉｏｎ　ｓｔａｂｉｌｉｔｙ）テストである。 The monitor 1 includes an LCD (Liquid Crystal Display) or the like, and displays a still image or a moving image of the eye movement test. In the present embodiment, the monitor 1 is, for example, an LCD having 19 inches and a resolution of 1280 × 1024 pixels. Further, the subject sits on the chair from the screen of the monitor 1 such that the viewing distance is 70 cm, for example. In the present embodiment, the eye movement test is an eye movement test in which there is a significant difference in test results between healthy subjects and patients with mental disorders (schizophrenia in the present embodiment). Specifically, the eye movement test is a free viewing test, a smooth pursuit test, and a fixation stability test.
　フリービューイングテストでは、例えば、５６種類の静止画像が８秒ずつモニタ１に表示される。また、被験者にはモニタ１に表示された静止画像を自由に見るように指示される。 In the free viewing test, for example, 56 types of still images are displayed on the monitor 1 every 8 seconds. Further, the subject is instructed to freely view the still image displayed on the monitor 1.
　スムースパシュートテストでは、例えば、全面黒色のモニタ１上に注視点が表示されて動かされる。また、被験者は、動く注視点を目で追うように指示される。注視点は、本実施形態では、下記の３種類の移動方法で、それぞれ、２０秒間動かされる。
第１トライアル：注視点を水平方向に移動する（水平パシュート）
第２トライアル：軌跡がリサージュ図形を描くように注視点を遅く動かす（遅いリサージュ：例えば、水平方向０．１５Ｈｚ、垂直方向０．２Ｈｚ）
第３トライアル：軌跡がリサージュ図形を描くように注視点を速く動かす（速いリサージュ：例えば、水平方向０．３Ｈｚ、垂直方向０．４Ｈｚ） In the smooth spout test, for example, the gazing point is displayed on the entire black monitor 1 and moved. The subject is also instructed to follow the moving point of gaze with his eyes. In this embodiment, the gazing point is moved for 20 seconds by the following three types of movement methods.
First Trial: Move the point of sight horizontally (horizontal pursuit)
Second Trial: Slowly move the gazing point so that the locus draws a Lissajous figure (slow Lissajous: for example, horizontal direction 0.15 Hz, vertical direction 0.2 Hz)
Third Trial: Move the point of interest quickly so that the trajectory draws a Lissajous figure (fast Lissajous: for example, horizontal 0.3 Hz, vertical 0.4 Hz)
　注視テストでは、全面黒色のモニタ１の中央に注視点（白点）が表示され、その近傍（又は、遠方）に妨害刺激（白点）が表示される。また、被験者は妨害刺激が表示されても５秒間は上記注視点を注視するよう指示される。本実施形態では、上記近傍の妨害刺激は、上記注視点から視野角１．５度の位置に表示され、上記遠方の妨害刺激は、上記注視点から視野角２．５度の位置に表示される。 In the gaze test, a gaze point (white point) is displayed at the center of the black monitor 1 and a disturbing stimulus (white point) is displayed in the vicinity (or far). In addition, the subject is instructed to watch the gaze point for 5 seconds even when the disturbing stimulus is displayed. In the present embodiment, the nearby disturbing stimulus is displayed at a viewing angle of 1.5 degrees from the gazing point, and the distant disturbing stimulus is displayed at a viewing angle of 2.5 degrees from the gazing point. The
　ビデオカメラ２は、例えば、ＣＣＤ（Ｃｈａｒｇｅ　Ｃｏｕｐｌｅｄ　Ｄｅｖｉｃｅ）を備え、被験者の眼球運動（眼球ＥＢの動き）を検出する。具体的には、例えば、ビデオカメラ２として、カナダのＳＲリサーチ社製のアイリンク（ＥｙｅＬｉｎｋ）１０００を用いて、被験者の左目の眼球運動を検出する。ここで、ビデオカメラ２は、「検出手段」の一部に相当する。図１において、眼球ＥＢは、被験者の眼球を示す。 The video camera 2 includes, for example, a CCD (Charge Coupled Device), and detects the eye movement (movement of the eyeball EB) of the subject. Specifically, for example, the eye movement of the subject's left eye is detected using an EyeLink 1000 manufactured by SR Research Inc. of Canada as the video camera 2. Here, the video camera 2 corresponds to a part of “detection means”. In FIG. 1, an eyeball EB indicates the eyeball of the subject.
　制御装置３は、例えば、パーソナルコンピュータであって、ＣＰＵ（Ｃｅｎｔｒａｌ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）、ＲＯＭ（Ｒｅａｄ　Ｏｎｌｙ　Ｍｅｍｏｒｙ）、ＲＡＭ（Ｒａｎｄｏｍ　Ａｃｃｅｓｓ　Ｍｅｍｏｒｙ）、及び、ＨＤＤ（Ｈａｒｄ　Ｄｉｓｋ　Ｄｒｉｖｅ）を備える。上記ＲＯＭには、制御プログラムが格納されている。そして、上記ＣＰＵは、上記ＲＯＭに格納された制御プログラムを読み出して実行することによって、テスト表示部３１、眼球運動検出部３２、分析部３３、選択部３４、及び、評価部３５を含む各種機能部として機能する。また、上記ＣＰＵは、上記ＲＯＭに格納された制御プログラムを読み出して実行することによって、上記ＨＤＤを、記憶部３６として機能させる。上記ＲＡＭは、上記ＣＰＵが、上記制御プログラムを実行する際の作業領域として用いられる。 The control device 3 is, for example, a personal computer, and includes a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), and an HDD (Hard Disk Drive). A control program is stored in the ROM. The CPU reads out and executes the control program stored in the ROM, thereby various functions including the test display unit 31, the eye movement detection unit 32, the analysis unit 33, the selection unit 34, and the evaluation unit 35. It functions as a part. The CPU causes the HDD to function as the storage unit 36 by reading and executing a control program stored in the ROM. The RAM is used as a work area when the CPU executes the control program.
　記憶部３６は、フリービューイングテスト、スムースパシュートテスト、及び、注視テストにおいてモニタ１に表示する静止画像データ及び動画像データ、並びに、眼球運動検出部３２によって検出された眼球位置データを記憶する。また、記憶部３６は、分析部３３によって求められた各眼球運動特徴の値、及び、評価部３５によって用いられる判別式データ等を記憶する。なお、判別式データにおいて示される判別式は、下記の（１）式である。 The storage unit 36 stores still image data and moving image data to be displayed on the monitor 1 in the free viewing test, the smooth sweep test, and the gaze test, and the eye position data detected by the eye movement detection unit 32. In addition, the storage unit 36 stores the value of each eye movement feature obtained by the analysis unit 33, discriminant data used by the evaluation unit 35, and the like. The discriminant shown in the discriminant data is the following equation (1).
　テスト表示部３１、眼球運動検出部３２、分析部３３、選択部３４、及び、評価部３５は、図４を用いて説明する判別式生成処理、及び、図１０を用いて説明する判別処理を実行する。ここで、「判別式生成処理」とは、被験者が統合失調症患者であるか否かを判別する判別式を生成する処理である。また、「判別処理」とは、「判別式生成処理」によって生成された判別式によって、被験者が統合失調症患者であるか否かを判別する処理である。以下の説明においては、上記判別式生成処理を実行する場合の動作と、上記判別処理を実行する場合の動作とを区別して、テスト表示部３１、眼球運動検出部３２、分析部３３、選択部３４、及び、評価部３５の機能を説明する。 The test display unit 31, the eye movement detection unit 32, the analysis unit 33, the selection unit 34, and the evaluation unit 35 perform the discriminant generation process described with reference to FIG. 4 and the discrimination process described with reference to FIG. Execute. Here, the “discriminant generation process” is a process of generating a discriminant for determining whether or not the subject is a schizophrenic patient. The “discriminating process” is a process of discriminating whether or not the subject is a schizophrenic patient based on the discriminant generated by the “discriminant generating process”. In the following description, the test display unit 31, the eye movement detection unit 32, the analysis unit 33, and the selection unit are distinguished from the operation when the discriminant generation process is executed and the operation when the discrimination process is executed. 34 and the function of the evaluation part 35 are demonstrated.
　テスト表示部３１は、上記判別式生成処理及び上記判別処理において、健常者と上記精神疾患（本実施形態では、統合失調症）の患者との間でテスト結果に顕著な差異がある眼球運動テストをモニタ１に表示する。具体的には、テスト表示部３１は、フリービューイングテスト、スムースパシュートテスト、及び、注視テストにそれぞれ対応する静止画像又は動画像を記憶部３６から読み出して、モニタ１に表示する。 In the discriminant generation process and the discrimination process, the test display unit 31 has an eye movement test in which there is a significant difference in test results between a healthy person and a patient with the mental illness (schizophrenia in the present embodiment). Is displayed on the monitor 1. Specifically, the test display unit 31 reads out still images or moving images corresponding to the free viewing test, the smooth spshoot test, and the gaze test from the storage unit 36 and displays them on the monitor 1.
　眼球運動検出部３２は、上記判別式生成処理及び上記判別処理において、ビデオカメラ２を介して、被験者の眼球運動を検出し、記憶部３６に記録する。ここで、眼球運動検出部３２は、「検出手段」の一部に相当する。 The eye movement detection unit 32 detects the eye movement of the subject via the video camera 2 and records it in the storage unit 36 in the discriminant generation process and the discrimination process. Here, the eye movement detection unit 32 corresponds to a part of “detection means”.
　分析部３３は、上記判別式生成処理において、ビデオカメラ２を介して検出した被験者の眼球位置データをデジタルＦＩＲ（Ｆｉｎｉｔｅ　Ｉｍｐｕｌｓｅ　Ｒｅｓｐｏｎｓｅ）フィルタで平滑化する。また、分析部３３は、上記判別式生成処理において、平滑化された眼球運動データを、瞬き期間、サッケード（ｓａｃｃａｄｅ：細かく急速な眼球運動）期間、及び、注視期間の３つの期間に分類して記憶部３６に記憶する。更に、分析部３３は、上記判別式生成処理において、眼球運動検出部３２によって検出された眼球ＥＢの動きを分析し、３個以上の第１所定数Ｎ１の眼球運動特徴を求める。具体的には、分析部３３は、フリービューイングテストの際の眼球運動特徴として、図５を用いて後述する１２個の眼球運動特徴を求める。また、分析部３３は、スムースパシュートテストの際の眼球運動特徴として、図６、及び、図７を用いて後述する４１個の眼球運動特徴を求める。更に、分析部３３は、注視テストの際の眼球運動特徴として、図８を用いて後述する１２個の眼球運動特徴を求める。このようにして、分析部３３は、６５個（＝１２＋４１＋１２）の眼球運動特徴を求める。分析部３３によって求められた６５個の眼球運動特徴は、第１所定数Ｎ１の眼球運動特徴に相当する。 The analysis unit 33 smoothes the eyeball position data of the subject detected through the video camera 2 with a digital FIR (Finite Impulse Response) filter in the discriminant generation process. In the discriminant generation process, the analysis unit 33 classifies the smoothed eye movement data into three periods of a blinking period, a saccade (fine and rapid eye movement) period, and a gaze period. Store in the storage unit 36. Further, in the discriminant generation process, the analysis unit 33 analyzes the movement of the eyeball EB detected by the eyeball detection unit 32 to obtain three or more first predetermined number N1 of eyeball movement characteristics. Specifically, the analysis unit 33 obtains twelve eye movement features to be described later with reference to FIG. 5 as the eye movement features in the free viewing test. Moreover, the analysis part 33 calculates | requires 41 eye movement characteristics mentioned later using FIG.6 and FIG.7 as an eyeball movement characteristic in the case of a smooth spa chute test. Further, the analysis unit 33 obtains twelve eye movement features to be described later with reference to FIG. 8 as eye movement characteristics at the gaze test. In this way, the analysis unit 33 obtains 65 (= 12 + 41 + 12) eye movement characteristics. The 65 eye movement features obtained by the analysis unit 33 correspond to the first predetermined number N1 of eye movement features.
　分析部３３は、上記判別処理において、眼球運動検出部３２によって検出された眼球ＥＢの動きを分析し、上記判別式生成処理において選択された２個以上の第２所定数Ｎ２の眼球運動特徴（後述する５個の第１の眼球運動特徴Ａ～第５の眼球運動特徴Ｅ）を求める。 The analysis unit 33 analyzes the movement of the eyeball EB detected by the eye movement detection unit 32 in the discrimination process, and two or more second predetermined number N2 of eye movement features (in the discrimination formula generation process ( Five first eye movement characteristics A to fifth eye movement characteristics E) to be described later are obtained.
　選択部３４は、上記判別式生成処理において、分析部３３によって求められた第１所定数Ｎ１（本実施形態では、６５個）の眼球運動特徴から、健常者と統合失調症の患者とを判別するために有効な２個以上の第２所定数Ｎ２の眼球運動特徴を選択する。具体的には、選択部３４は、例えば、有意確率（Ｐ値：Ｐ　ｖａｌｕｅ）に基づいて、健常者と統合失調症の患者とを判別するために有効な眼球運動特徴を選択する。また、選択部３４は、６５個の眼球運動特徴から互いに独立性の強い眼球運動特徴を選択する。なお、選択部３４は、「判定手段」の一部に相当する。 In the discriminant generation process, the selection unit 34 discriminates between a healthy person and a schizophrenic patient from the first predetermined number N1 (65 in this embodiment) of eye movement characteristics obtained by the analysis unit 33. Two or more second predetermined number N2 of eye movement features effective for the purpose are selected. Specifically, the selection unit 34 selects an eye movement feature that is effective for discriminating between a healthy person and a patient with schizophrenia based on, for example, a significance probability (P value: P value). The selection unit 34 selects eye movement features that are highly independent from each other from 65 eye movement features. The selection unit 34 corresponds to a part of the “determination unit”.
　更に具体的には、選択部３４は、ステップワイズ（ｓｔｅｐｗｉｓｅ）法によって、分析部３３によって求められた６５個の眼球運動特徴から、健常者と統合失調症の患者とを判別するために有効な第２所定数Ｎ２（本実施形態では、５個）の眼球運動特徴を選択する。このようにして、選択部３４は、後述する５個の眼球運動特徴（第１の眼球運動特徴Ａ～第５の眼球運動特徴Ｅ）を選択する。 More specifically, the selection unit 34 is effective for discriminating a healthy person and a schizophrenic patient from 65 eye movement characteristics obtained by the analysis unit 33 by a stepwise method. A second predetermined number N2 (five in this embodiment) eye movement features are selected. In this way, the selection unit 34 selects five eye movement features (first eye movement feature A to fifth eye movement feature E) to be described later.
　評価部３５は、判別式生成処理において、統合失調症の患者であるか否かを判別する判別式（下記（１）式）として、選択部３４によって選択された第２所定数Ｎ２の眼球運動特徴の関数（本実施形態では、一次方程式）を求める。
Ｙ＝０．０３×Ａ＋２．０１×Ｂ＋０．０３×Ｃ＋０．３７×Ｄ
　　　－１．５３×Ｅ－４．９２　　（１） The evaluation unit 35 uses the second predetermined number N2 of eye movements selected by the selection unit 34 as a discriminant for discriminating whether or not the patient is a schizophrenic patient (equation (1) below) in the discriminant generation process. A feature function (in this embodiment, a linear equation) is obtained.
Y = 0.03 × A + 2.01 × B + 0.03 × C + 0.37 × D
-1.53 × E-4.92 (1)
　ここで、第１の眼球運動特徴Ａは、フリービューイングテストにおいて求められた眼球運動特徴であるスキャンパス距離（ｓｃａｎｐａｔｈ　ｌｅｎｇｔｈ）である。第２の眼球運動特徴Ｂは、スムースパシュートテストの速いリサージュ（Ｌｉｓｓａｊｏｕｓ）において求められた眼球運動特徴である垂直方向の位置ゲインである。第３の眼球運動特徴Ｃは、スムースパシュートテストの速いリサージュにおいて求められた眼球運動特徴である注視数である。第４の眼球運動特徴Ｄは、注視テストの遠い妨害刺激において求められた眼球運動特徴である注視時間である。第５の眼球運動特徴Ｅは、スムースパシュートテストの水平パシュートにおいて求められた眼球運動特徴であるＳ／Ｎ比である。眼球運動スコアＹは、統合失調症の患者であるか否かを判定する値である。 Here, the first eye movement feature A is a scan path distance that is an eye movement feature obtained in the free viewing test. The second eye movement feature B is a position gain in the vertical direction, which is an eye movement feature obtained in Lissajous with a quick smooth shot test. The third eye movement feature C is the number of gazes that is the eye movement feature obtained in the quick Lissajous of the smooth spa chute test. The fourth eye movement feature D is a gaze time that is an eye movement feature obtained in a distant disturbing stimulus of the gaze test. The fifth eye movement feature E is an S / N ratio that is an eye movement feature obtained in the horizontal pursuit of the smooth spa chute test. The eye movement score Y is a value for determining whether or not the patient has schizophrenia.
　また、評価部３５は、上記判別処理において、分析部３３によって求められた５個の眼球運動特徴の値を、上記判別式生成処理において生成された判別式（上記（１）式）に代入することによって、被験者が統合失調症の患者であるか否かを判定する。具体的には、評価部３５は、眼球運動スコアＹが、事後確率によって定められる閾値（本実施形態では、－０．３）以上である場合に、健常者であると判定し、眼球運動スコアＹが上記閾値未満である場合に、統合失調症の患者であると判定する。 Further, the evaluation unit 35 substitutes the values of the five eye movement characteristics obtained by the analysis unit 33 in the discriminating process into the discriminant (the above formula (1)) generated in the discriminant generating process. Thus, it is determined whether or not the subject is a schizophrenic patient. Specifically, the evaluation unit 35 determines that the eye movement score Y is a healthy person when the eye movement score Y is equal to or greater than a threshold (−0.3 in this embodiment) determined by the posterior probability, and the eye movement score. When Y is less than the threshold value, it is determined that the patient is schizophrenic.
　次に、図２を参照して、眼球運動テストについて説明する。図２は、図１に示す眼球運動検出部３２によって検出された結果の一例を示す図である。（ａ）は、フリービューイングテストにおける健常者の眼球運動の一例を示す図であり、（ｂ）は、フリービューイングテストにおける統合失調症患者の眼球運動の一例を示す図である。 Next, the eye movement test will be described with reference to FIG. FIG. 2 is a diagram illustrating an example of a result detected by the eye movement detection unit 32 illustrated in FIG. (A) is a figure which shows an example of the eye movement of the healthy subject in a free viewing test, (b) is a figure which shows an example of the eye movement of the schizophrenia patient in a free viewing test.
　上述のように、フリービューイングテストでは、５６種類の静止画像が８秒ずつモニタ１に表示される。図２では、静止画像の一例として、高層ビルが散在する市街地の静止画像ＦＶ１が表示されている。また、図２（ａ）に示すように、健常者の視点位置の軌跡ＮＰが、広範囲に移動しているのに対して、図２（ｂ）に示すように、統合失調症患者の視点位置の軌跡ＰＰは、狭い範囲内での移動に止まっている。このような特徴は、上記（１）式において、第１の眼球運動特徴Ａ（フリービューイングテストにおいて求められた眼球運動特徴であるスキャンパス距離）として表される。ここで、「スキャンパス距離」とは、視点を移動する距離の総和である。健常者は、スキャンパス距離が長く、統合失調症患者はスキャンパス距離が短い。 As described above, in the free viewing test, 56 types of still images are displayed on the monitor 1 every 8 seconds. In FIG. 2, a still image FV1 of an urban area where high-rise buildings are scattered is displayed as an example of a still image. In addition, as shown in FIG. 2 (a), the locus NP of the healthy subject's viewpoint position moves in a wide range, whereas as shown in FIG. 2 (b), the viewpoint position of the schizophrenia patient. The trajectory PP has stopped moving within a narrow range. Such a feature is expressed as the first eye movement feature A (a scan path distance that is an eye movement feature obtained in the free viewing test) in the above equation (1). Here, the “scan path distance” is the sum of distances for moving the viewpoint. A healthy person has a long scan path distance, and a schizophrenic patient has a short scan path distance.
　次に、図３を参照して、図１に示す精神疾患判定装置１００の被験者について説明する。図３は、図１に示す精神疾患判定装置１００による判別式生成処理に用いられる健常者及び統合失調症患者の構成の一例を示す図表である。図３中の数値は、（平均値）±（標準偏差）である。なお、Ｐ値は、有意確率である。また、健常者と統合失調症患者との間で有意な差異のある変数は、Ｐ値の数値を太字で記載し下線を施している。病前の知能指数は、３８人の統合失調症患者のデータである。統合失調症の病状の程度を示す変数の欄のＰＡＮＳＳは、「Ｐｏｓｉｔｉｖｅ　Ａｎｄ　Ｎｅｇａｔｉｖｅ　Ｓｙｎｄｒｏｍｅ　Ｓｃａｌｅ」であり、ＣＰＺは、「ｃｈｌｏｒｐｒｏｍａｚｉｎｅ」であり、ＧＡＦは、「Ｇｌｏｂａｌ　Ａｓｓｅｓｓｍｅｎｔ　ｏｆ　Ｆｕｎｃｔｉｏｎｉｎｇ」である。 Next, the subject of the mental illness determination apparatus 100 shown in FIG. 1 will be described with reference to FIG. FIG. 3 is a chart showing an example of the configuration of a healthy person and a schizophrenic patient used in the discriminant generation process by the mental disease determination apparatus 100 shown in FIG. The numerical values in FIG. 3 are (average value) ± (standard deviation). The P value is a significant probability. Moreover, the variable with a significant difference between a healthy subject and a schizophrenia patient has indicated the numerical value of P value in bold type, and has underlined. The pre-disease intelligence quotient is data for 38 schizophrenic patients. PANSS in the variable column indicating the degree of schizophrenia pathology is “Positive And Negative Synthetic Scale”, CPZ is “Chlorprozine”, and GAF is “Global Assessment of Fun”.
　図３に示すように、統合失調症患者は、４０名であり、健常者は６９名であった。また、年齢、性別、及び、利き手に関しては、健常者と統合失調症患者との間で有意な差はなかった。一方、教育歴、現在の知能指数、及び、病前の知能指数は、健常者と比較して、統合失調症患者がかなり低かった。 As shown in FIG. 3, there were 40 schizophrenia patients and 69 healthy individuals. There were no significant differences between healthy subjects and schizophrenic patients regarding age, gender, and dominant hand. On the other hand, educational history, current intelligence quotient, and pre-disease intelligence quotient were significantly lower in schizophrenic patients compared to healthy individuals.
　次に、図４を参照して、精神疾患判定装置１００における判別式の生成処理について説明する。図４は、図１に示す精神疾患判定装置１００における判別式生成処理の一例を示すフローチャートである。まず、テスト表示部３１によって、モニタ１にフリービューイングテストの静止画像が表示される（ステップＳ１０１）。次に、眼球運動検出部３２によって、ビデオカメラ２を介して、被験者の眼球運動が検出される（ステップＳ１０３）。そして、分析部３３によって、ステップＳ１０３において検出された眼球ＥＢの動きが分析され、図５に示す１２個の眼球運動特徴が求められる（ステップＳ１０５）。 Next, the discriminant generation process in the mental illness determination apparatus 100 will be described with reference to FIG. FIG. 4 is a flowchart showing an example of the discriminant generation process in the mental illness determination apparatus 100 shown in FIG. First, the still image of the free viewing test is displayed on the monitor 1 by the test display unit 31 (step S101). Next, the eye movement detection unit 32 detects the eye movement of the subject through the video camera 2 (step S103). Then, the movement of the eyeball EB detected in step S103 is analyzed by the analysis unit 33, and twelve eye movement features shown in FIG. 5 are obtained (step S105).
　次いで、テスト表示部３１によって、モニタ１にスムースパシュートテストの動画像が表示される（ステップＳ１０７）。次に、眼球運動検出部３２によって、ビデオカメラ２を介して、被験者の眼球運動が検出される（ステップＳ１０９）。そして、分析部３３によって、ステップＳ１０９において検出された眼球ＥＢの動きが分析され、図６及び図７に示す４１個の眼球運動特徴が求められる（ステップＳ１１１）。 Next, the moving image of the smooth spat test is displayed on the monitor 1 by the test display unit 31 (step S107). Next, the eye movement detection unit 32 detects the eye movement of the subject via the video camera 2 (step S109). Then, the motion of the eyeball EB detected in step S109 is analyzed by the analysis unit 33, and 41 eye movement features shown in FIGS. 6 and 7 are obtained (step S111).
　次いで、テスト表示部３１によって、モニタ１に注視テストの静止画像が表示される（ステップＳ１１３）。次に、眼球運動検出部３２によって、ビデオカメラ２を介して、被験者の眼球運動が検出される（ステップＳ１１５）。そして、分析部３３によって、ステップＳ１１５において検出された眼球ＥＢの動きが分析され、図８に示す１２個の眼球運動特徴が求められる（ステップＳ１１７）。 Next, the still image of the gaze test is displayed on the monitor 1 by the test display unit 31 (step S113). Next, the eye movement detection unit 32 detects the eye movement of the subject through the video camera 2 (step S115). Then, the analysis unit 33 analyzes the movement of the eyeball EB detected in step S115, and obtains the twelve eye movement features shown in FIG. 8 (step S117).
　次に、選択部３４によって、全ての対象者（図３に示す健常者６９名及び統合失調症患者４０名、合計１０９名）について、３つのテストに対応する６５個の眼球運動特徴が求められたか否かの判定が行われる（ステップＳ１１９）。テストが終わっていない対象者がいる（ステップＳ１１９でＮＯ）と判定された場合には、処理がステップＳ１０１に戻され、テストが終わっていない対象者についてステップＳ１０１以降の処理が開始される。全ての対象者についてテストが終了した（ステップＳ１１９でＹＥＳ）と判定された場合には、ステップＳ１２１に進められる。 Next, the selection unit 34 obtains 65 eye movement characteristics corresponding to the three tests for all the subjects (69 healthy persons and 40 schizophrenia patients as shown in FIG. 3, total 109 persons). It is determined whether or not (step S119). If it is determined that there is a subject who has not finished the test (NO in step S119), the process returns to step S101, and the processing after step S101 is started for the subject who has not finished the test. If it is determined that the test has been completed for all the subjects (YES in step S119), the process proceeds to step S121.
　そして、選択部３４によって、ステップワイズ法を用いて、ステップＳ１０５、ステップＳ１１１、及び、ステップＳ１１７において求められた６５個の眼球運動特徴から、健常者と統合失調症の患者とを判別するために有効な第２所定数Ｎ２（ここでは、５個）の眼球運動特徴が選択される（ステップＳ１２１）。次に、評価部３５によって、被験者が統合失調症の患者であるか否かを判定する判別式として、ステップＳ１２１において選択された５個の眼球運動特徴に関する一次方程式（上記（１）式）が求められ（ステップＳ１２３）、処理が終了される。 Then, the selection unit 34 uses the stepwise method to discriminate between a healthy person and a schizophrenic patient from the 65 eye movement characteristics obtained in step S105, step S111, and step S117. A valid second predetermined number N2 (here, 5) of eye movement features are selected (step S121). Next, as a discriminant for determining whether or not the subject is a schizophrenic patient by the evaluation unit 35, the linear equations (the above equation (1)) relating to the five eye movement features selected in step S121. Is obtained (step S123), and the process is terminated.
　図４に示すステップＳ１０３、ステップＳ１０９、及び、ステップＳ１１５は、「検出工程」の一部に相当する。図４に示すステップＳ１０５、ステップＳ１１１、及び、ステップＳ１１７は、「分析工程」の一部に相当する。図４に示すステップＳ１２１、及び、ステップＳ１２３は、「判定工程」の一部に相当する。 Step S103, step S109, and step S115 shown in FIG. 4 correspond to a part of the “detection step”. Steps S105, S111, and S117 illustrated in FIG. 4 correspond to a part of the “analysis process”. Steps S121 and S123 illustrated in FIG. 4 correspond to a part of the “determination step”.
　上述のように、選択部３４によって、第１所定数Ｎ１の眼球運動特徴から、健常者と統合失調症の患者とを判別するために有効な第２所定数Ｎ２の眼球運動特徴が選択されるため、健常者と統合失調症の患者とを単純な処理で判別することができる。 As described above, the selection unit 34 selects the second predetermined number N2 of eye movement features that are effective for discriminating between a healthy person and a schizophrenic patient from the first predetermined number N1 of eye movement characteristics. Therefore, a healthy person and a schizophrenic patient can be distinguished by a simple process.
　本実施形態では、第２所定数Ｎ２が５個である場合について説明しているが、第２所定数Ｎ２は２個以上であればよい。第２所定数Ｎ２が２個である場合には、健常者と統合失調症の患者とを更に単純な処理で判別することができる。 In the present embodiment, the case where the second predetermined number N2 is five is described, but the second predetermined number N2 may be two or more. When the second predetermined number N2 is two, it is possible to discriminate between a healthy person and a patient with schizophrenia by a simpler process.
　また、選択部３４によって、ステップワイズ法を用いて、第１所定数Ｎ１の眼球運動特徴から、第２所定数Ｎ２の眼球運動特徴が選択されるため、適正な個数の適正な眼球運動特徴を選択することができる。したがって、精神疾患の患者であるか否かを更に正確に判定することができる。なお、ステップワイズ法を実行した結果、上記第２所定数が定まるのであって、ステップワイズ法では、上記第２所定数を予め定めることはない。 In addition, since the second predetermined number N2 of eye movement features are selected from the first predetermined number N1 of eye movement features by using the stepwise method, the selection unit 34 selects an appropriate number of appropriate eye movement features. You can choose. Therefore, it can be determined more accurately whether or not the patient has a mental illness. As a result of executing the stepwise method, the second predetermined number is determined. In the stepwise method, the second predetermined number is not predetermined.
　本実施形態では、選択部３４が、ステップワイズ法によって眼球運動特徴を選択する場合について説明しているが、選択部３４が、その他の方法（例えば、遺伝的アルゴリズム、主成分分析等）によって、健常者と統合失調症の患者とを判別するために有効な眼球運動特徴を選択する形態でもよい。ただし、選択部３４は、第１所定数Ｎ１の眼球運動特徴から、互いに独立性の強い第２所定数Ｎ２の眼球運動特徴を選択することが好ましい。なぜなら、互いに独立性の強い第２所定数Ｎ２の眼球運動特徴を選択することによって、精神疾患の患者であるか否かを更に正確に判定することができるからである。 In the present embodiment, the case where the selection unit 34 selects an eye movement feature by the stepwise method is described. However, the selection unit 34 may perform other methods (for example, genetic algorithm, principal component analysis, etc.) The form which selects the effective eye movement feature in order to discriminate | determine a healthy person and the patient of schizophrenia may be sufficient. However, it is preferable that the selection unit 34 selects the second predetermined number N2 of eye movement features that are highly independent from each other from the first predetermined number N1 of eye movement characteristics. This is because it is possible to more accurately determine whether or not the patient is a mentally ill patient by selecting the second predetermined number N2 of eye movement features that are highly independent of each other.
　また、評価部３５によって、被験者が統合失調症の患者であるか否かを判定する判別式として、第２所定数Ｎ２の眼球運動特徴に関する一次方程式（上記（１）式）が求められるため、簡素な構成で健常者と統合失調症の患者とを正確に判別することができる。 In addition, since the evaluation unit 35 obtains a linear equation (the above equation (1)) regarding the second predetermined number N2 of eye movement characteristics as a discriminant for determining whether or not the subject is a schizophrenic patient, With a simple configuration, it is possible to accurately distinguish between a healthy person and a schizophrenic patient.
　本実施形態では、評価部３５が、判別式として第２所定数Ｎ２の眼球運動特徴に関する一次方程式を求める場合について説明しているが、評価部３５が、判別式として第２所定数Ｎ２の眼球運動特徴に関する関数を求める形態であればよい。例えば、評価部３５が、判別式として第２所定数Ｎ２の眼球運動特徴に関する２次以上の線形方程式を求める形態でもよい。 In the present embodiment, a case has been described in which the evaluation unit 35 obtains a linear equation relating to the second predetermined number N2 of eye movement features as a discriminant, but the evaluation unit 35 uses the second predetermined number N2 of eyeballs as a discriminant. Any form may be used as long as the function relating to the motion feature is obtained. For example, the evaluation unit 35 may obtain a quadratic or higher-order linear equation regarding the second predetermined number N2 of eye movement features as a discriminant.
　また、フリービューイングテスト、スムースパシュートテスト、及び、注視テストは、健常者と統合失調症患者との間でテスト結果に顕著な差異がある眼球運動テストである。よって、眼球運動検出部３２によって、フリービューイングテスト、スムースパシュートテスト、及び、注視テストにおける眼球ＥＢの動きが検出されるため、健常者と統合失調症患者との間で顕著な差異があるテスト結果が得られる。したがって、健常者と統合失調症患者とを正確に判別することが可能になる。 In addition, the free viewing test, the smooth spa shoot test, and the gaze test are eye movement tests in which there are marked differences in test results between healthy subjects and schizophrenic patients. Therefore, since the eye movement detection unit 32 detects the movement of the eyeball EB in the free viewing test, the smooth shoot test, and the gaze test, there is a significant difference between a healthy person and a schizophrenic patient. Results are obtained. Therefore, it becomes possible to accurately discriminate between a healthy person and a schizophrenic patient.
　本実施形態では、眼球運動検出部３２が、フリービューイングテスト、スムースパシュートテスト、及び、注視テストにおける眼球ＥＢの動きを検出する場合について説明しているが、眼球運動検出部３２が、フリービューイングテスト、スムースパシュートテスト、及び、注視テストのうち、少なくとも１つのテストにおける眼球ＥＢの動きを検出する形態であればよい。 In the present embodiment, the case where the eye movement detection unit 32 detects the movement of the eyeball EB in the free viewing test, the smooth spout test, and the gaze test is described. Any form may be used as long as it detects the movement of the eyeball EB in at least one of the inching test, the smooth spa chute test, and the gaze test.
　また、眼球運動テストが、フリービューイングテスト、スムースパシュートテスト、及び、注視テストに加えて（又は、替えて）、動画像を用いたフリービューイングテスト、及び、視覚探索テストの少なくとも一方を含む形態でもよい。 Further, the eye movement test includes at least one of a free viewing test using a moving image and a visual search test in addition to (or instead of) the free viewing test, the smooth shoot test, and the gaze test. Form may be sufficient.
　上記動画像を用いたフリービューイングテストでは、眼球運動特徴として、サッケード回数、サッケード頻度等が得られる。また、上記視覚探索テストとは、モニタ画面に、例えば、多くの文字を表示して、その中から指示された文字を探すテストである。上記視覚探索テストでは、眼球運動特徴として、サッケード回数、探索時間等が得られる。 In the free viewing test using the above moving image, the number of saccades, the saccade frequency, etc. are obtained as eye movement characteristics. The visual search test is a test in which, for example, a large number of characters are displayed on a monitor screen and an instructed character is searched for among them. In the visual search test, the number of saccades, the search time, etc. are obtained as eye movement features.
　ここで、図５～図８を参照して、図４のステップＳ１０５、ステップＳ１１１、及び、ステップＳ１１７において求められる６５個の眼球運動特徴について説明した後、図４のステップＳ１２１で選択される５個の眼球運動特徴について説明する。 Here, with reference to FIGS. 5 to 8, the 65 eye movement characteristics obtained in step S105, step S111, and step S117 in FIG. 4 will be described, and then selected in step S121 in FIG. Individual eye movement characteristics will be described.
　図５は、図１に示すモニタ１にフリービューイングテストの静止画像を表示した場合に、分析部３３によって得られる眼球運動特徴の一例を示す図表である。図５中の数値は、（平均値）±（標準偏差）である。なお、Ｐ値は、有意確率である。 FIG. 5 is a chart showing an example of eye movement characteristics obtained by the analysis unit 33 when a still image of the free viewing test is displayed on the monitor 1 shown in FIG. The numerical values in FIG. 5 are (average value) ± (standard deviation). The P value is a significant probability.
　また、図５に示す１２個の眼球運動特徴のうち、健常者と統合失調症患者との間で有意な差異のある眼球運動特徴は、対応するＰ値の数値を太字で記載し下線を施している。健常者と統合失調症患者との間で有意な差異のある眼球運動特徴は、具体的には、スキャンパス距離（視点を移動する距離の総和）、注視数（視点を固定する回数）、サッケード数（細かく急速な眼球運動の回数）、注視密度、注視時間等である。また、図５に示す１２個の眼球運動特徴のうち、選択部３４によって選択される眼球運動特徴は、スキャンパス距離（第１の眼球運動特徴Ａ）である。 In addition, among the 12 eye movement characteristics shown in FIG. 5, the eye movement characteristics that are significantly different between healthy subjects and schizophrenia patients are indicated by the corresponding P value numerical values in bold and underlined. ing. Eye movement characteristics that are significantly different between healthy individuals and schizophrenic patients are specifically scan path distance (sum of distance to move the viewpoint), number of gazes (number of times the viewpoint is fixed), saccade Number (number of fine and rapid eye movements), gaze density, gaze time, etc. Also, the eye movement feature selected by the selection unit 34 among the 12 eye movement features shown in FIG. 5 is the scan path distance (first eye movement feature A).
　図６は、図１に示すモニタ１にスムースパシュートテストの動画像（水平パシュート及び遅いリサージュ）を表示した場合に、分析部３３によって得られる眼球運動特徴の一例を示す図表である。図７は、図１に示すモニタ１にスムースパシュートテストの動画像（速いリサージュ）を表示した場合に、分析部３３によって得られる眼球運動特徴の一例を示す図表である。 FIG. 6 is a chart showing an example of eye movement characteristics obtained by the analysis unit 33 when a moving image (horizontal pursuit and slow Lissajous) of the smooth pursuit test is displayed on the monitor 1 shown in FIG. FIG. 7 is a chart showing an example of eye movement characteristics obtained by the analysis unit 33 when a moving image (fast Lissajous) of a smooth spa chute test is displayed on the monitor 1 shown in FIG.
　図６中、及び、図７中の数値は、（平均値）±（標準偏差）である。なお、Ｐ値は、有意確率である。また、図６及び図７に示す４１個の眼球運動特徴のうち、健常者と統合失調症患者との間で有意な差異のある眼球運動特徴は、対応するＰ値の数値を太字で記載し下線を施している。 The numerical values in FIG. 6 and FIG. 7 are (average value) ± (standard deviation). The P value is a significant probability. Among the 41 eye movement characteristics shown in FIGS. 6 and 7, the eye movement characteristics that are significantly different between healthy subjects and schizophrenic patients are indicated by the corresponding P values in bold. Underlined.
具体的には、健常者と統合失調症患者との間で有意な差異のある眼球運動特徴は、速いリサージュにおける位置ゲイン（垂直）、位置ゲイン（水平）、注視数、サッケード数等である。また、図６及び図７に示す４１個の眼球運動特徴のうち、選択部３４によって選択される眼球運動特徴は、速いリサージュにおける垂直方向の位置ゲイン（第２の眼球運動特徴Ｂ）、注視数（第３の眼球運動特徴Ｃ）、及び、水平パシュートにおけるＳ／Ｎ比（第５の眼球運動特徴Ｅ）である。 Specifically, eye movement characteristics that are significantly different between healthy subjects and schizophrenia patients are position gain (vertical), position gain (horizontal), number of gazes, number of saccades, etc. in fast Lissajous. Of the 41 eye movement features shown in FIGS. 6 and 7, the eye movement feature selected by the selection unit 34 is the vertical position gain (second eye movement feature B) in the fast Lissajous, the number of gazes. (Third eye movement feature C) and S / N ratio (fifth eye movement feature E) in horizontal pursuit.
　図８は、図１に示すモニタ１に注視テストの静止画像を表示した場合に、分析部３３によって得られる眼球運動特徴の一例を示す図表である。図８中の数値は、（平均値）±（標準偏差）である。なお、Ｐ値は、有意確率である。また、図８に示す１２個の眼球運動特徴のうち、健常者と統合失調症患者との間で有意な差異のある眼球運動特徴は、対応するＰ値の数値を太字で記載し下線を施している。 FIG. 8 is a chart showing an example of eye movement characteristics obtained by the analysis unit 33 when a still image of a gaze test is displayed on the monitor 1 shown in FIG. The numerical values in FIG. 8 are (average value) ± (standard deviation). The P value is a significant probability. Of the twelve eye movement characteristics shown in FIG. 8, the eye movement characteristics that are significantly different between healthy subjects and schizophrenic patients are indicated by the corresponding P values in bold and underlined. ing.
　具体的には、健常者と統合失調症患者との間で有意な差異のある眼球運動特徴は、遠い妨害刺激における注視時間、近い妨害刺激における注視時間、妨害刺激なしにおける注視時間、妨害刺激なしにおけるスキャンパス距離等である。また、図８に示す１２個の眼球運動特徴のうち、選択部３４によって選択される眼球運動特徴は、遠い妨害刺激における注視時間（第４の眼球運動特徴Ｄ）である。 Specifically, eye movement features that are significantly different between healthy and schizophrenic patients are: gaze time at distant disturbing stimuli, gaze time at near disturbing stimuli, gaze time without disturbing stimuli, no disturbing stimuli The scan path distance at. In addition, the eye movement feature selected by the selection unit 34 among the twelve eye movement features shown in FIG. 8 is the gaze time (fourth eye movement feature D) in the far disturbing stimulus.
　図９は、図１に示す選択部３４によって選択された眼球運動特徴の一例を示す図表である。図９中の数値は、（平均値）±（標準偏差）である。なお、Ｐ値は、有意確率である。また、健常者と統合失調症患者との間で特に有意な差異のある眼球運動特徴は、対応するＰ値の数値を太字で記載し下線を施している。 FIG. 9 is a chart showing an example of the eye movement feature selected by the selection unit 34 shown in FIG. The numerical values in FIG. 9 are (average value) ± (standard deviation). The P value is a significant probability. In addition, eye movement characteristics that are particularly significant between healthy subjects and schizophrenic patients are indicated by the corresponding P values in bold letters and underlined.
　図９に示すように、図５～図８に示す６５個の眼球運動特徴から選択部３４によって、健常者と統合失調症の患者とを判別するために有効な眼球運動特徴として、下記の５つの眼球運動特徴が選択される。第１の眼球運動特徴Ａは、フリービューイングテストにおいて求められた眼球運動特徴であるスキャンパス距離（図５の下から５個目の眼球運動特徴）である。第２の眼球運動特徴Ｂは、スムースパシュートテストの速いリサージュにおいて求められた眼球運動特徴である垂直方向の位置ゲイン（図７の上から５個目の眼球運動特徴）である。第３の眼球運動特徴Ｃは、スムースパシュートテストの速いリサージュにおいて求められた眼球運動特徴である注視数（図７の上から７個目の眼球運動特徴）である。第４の眼球運動特徴Ｄは、注視テストの遠い妨害刺激において求められた眼球運動特徴である注視時間（図８の下から３個目の眼球運動特徴）である。第５の眼球運動特徴Ｅは、スムースパシュートテストの水平パシュートにおいて求められた眼球運動特徴であるＳ／Ｎ比（図６の上から１個目の眼球運動特徴）である。 As shown in FIG. 9, the following 5 types of eye movement features effective for discriminating a healthy person from a schizophrenic patient by the selection unit 34 from the 65 eye movement features shown in FIGS. Two eye movement features are selected. The first eye movement feature A is the scan path distance (the fifth eye movement feature from the bottom in FIG. 5) which is the eye movement feature obtained in the free viewing test. The second eye movement feature B is a vertical position gain (fifth eye movement feature from the top in FIG. 7), which is an eye movement feature obtained in a quick Lissajous of a smooth spa chute test. The third eye movement feature C is the number of gazes (the seventh eye movement feature from the top in FIG. 7), which is the eye movement feature obtained in the quick Lissajous of the smooth spa chute test. The fourth eye movement feature D is a gaze time (third eye movement feature from the bottom in FIG. 8) that is an eye movement feature obtained in a distant disturbing stimulus of the gaze test. The fifth eye movement feature E is an S / N ratio (first eye movement feature from the top of FIG. 6) which is an eye movement feature obtained in the horizontal pursuit of the smooth spa chute test.
　次に、図１０を参照して、被験者が統合失調症の患者であるか否かを判定する判別処理について説明する。図１０は、図１に示す精神疾患判定装置１００における判別処理の一例を示すフローチャートである。 Next, with reference to FIG. 10, a determination process for determining whether or not the subject is a schizophrenic patient will be described. FIG. 10 is a flowchart illustrating an example of determination processing in the mental disease determination apparatus 100 illustrated in FIG.
　まず、テスト表示部３１によって、モニタ１にフリービューイングテストの静止画像が表示される（ステップＳ２０１）。次に、眼球運動検出部３２によって、ビデオカメラ２を介して、被験者の眼球運動が検出される（ステップＳ２０３）。そして、分析部３３によって、ステップＳ２０３において検出された眼球ＥＢの動きが分析され、第１の眼球運動特徴Ａ（スキャンパス距離）が求められる（ステップＳ２０５）。 First, the still image of the free viewing test is displayed on the monitor 1 by the test display unit 31 (step S201). Next, the eye movement detection unit 32 detects the eye movement of the subject through the video camera 2 (step S203). Then, the analysis unit 33 analyzes the movement of the eyeball EB detected in step S203, and obtains the first eye movement feature A (scan path distance) (step S205).
　次いで、テスト表示部３１によって、モニタ１にスムースパシュートテストの動画像が表示される（ステップＳ２０７）。次に、眼球運動検出部３２によって、ビデオカメラ２を介して、被験者の眼球運動が検出される（ステップＳ２０９）。そして、分析部３３によって、ステップＳ２０９において検出された眼球ＥＢの動きが分析され、第２の眼球運動特徴Ｂ（速いリサージュにおける垂直方向の位置ゲイン）、第３の眼球運動特徴Ｃ（速いリサージュにおける注視数）、及び、第５の眼球運動特徴Ｅ（水平パシュートにおけるＳ／Ｎ比）が求められる（ステップＳ２１１）。 Next, the test display unit 31 displays a moving image of the smooth shoot test on the monitor 1 (step S207). Next, the eye movement detection unit 32 detects the eye movement of the subject through the video camera 2 (step S209). Then, the motion of the eyeball EB detected in step S209 is analyzed by the analysis unit 33, and the second eye movement feature B (vertical position gain in the fast Lissajous) and the third eye movement feature C (in the fast Lissajous) The number of gazes) and the fifth eye movement feature E (S / N ratio in horizontal pursuit) are obtained (step S211).
　次いで、テスト表示部３１によって、モニタ１に注視テストの静止画像が表示される（ステップＳ２１３）。次に、眼球運動検出部３２によって、ビデオカメラ２を介して、被験者の眼球運動が検出される（ステップＳ２１５）。そして、分析部３３によって、ステップＳ２１５において検出された眼球ＥＢの動きが分析され、第４の眼球運動特徴Ｄ（遠い妨害刺激における注視時間）が求められる（ステップＳ２１７）。 Next, the still image of the gaze test is displayed on the monitor 1 by the test display unit 31 (step S213). Next, the eye movement detection unit 32 detects the eye movement of the subject through the video camera 2 (step S215). Then, the analysis unit 33 analyzes the movement of the eyeball EB detected in step S215, and obtains a fourth eye movement feature D (gaze time in a distant disturbing stimulus) (step S217).
　そして、評価部３５によって、ステップＳ２０５、ステップＳ２１１、及び、ステップＳ２１７で求められた第１の眼球運動特徴Ａ～第５の眼球運動特徴Ｅの値が、判別式である上記（１）式に代入され、眼球運動スコアＹが求められる（ステップＳ２１９）。次に、評価部３５によって、ステップＳ２１９で求められた眼球運動スコアＹが零以上であるか否かの判定が行われる（ステップＳ２２１）。眼球運動スコアＹが、事後確率によって定められる閾値（本実施形態では、－０．３）以上である（ステップＳ２２１でＹＥＳ）と判定された場合には、評価部３５によって、被験者は健常者であると判定され（ステップＳ２２３）、処理が終了される。眼球運動スコアＹが、上記閾値（本実施形態では、－０．３）未満である（ステップＳ２２１でＮＯ）と判定された場合には、評価部３５によって、被験者は統合失調症の患者であると判定され（ステップＳ２２５）、処理が終了される。 Then, the values of the first eye movement feature A to the fifth eye movement feature E obtained by the evaluation unit 35 in step S205, step S211 and step S217 are expressed by the above equation (1). Substituted and an eye movement score Y is obtained (step S219). Next, the evaluation unit 35 determines whether or not the eye movement score Y obtained in step S219 is greater than or equal to zero (step S221). When it is determined that the eye movement score Y is equal to or greater than the threshold (in this embodiment, −0.3) determined by the posterior probability (YES in step S221), the evaluation unit 35 determines that the subject is a healthy person. It is determined that there is (step S223), and the process is terminated. When it is determined that the eye movement score Y is less than the threshold value (−0.3 in this embodiment) (NO in step S221), the evaluation unit 35 determines that the subject is a schizophrenic patient. Is determined (step S225), and the process is terminated.
　図１０に示すステップＳ２０３、ステップＳ２０９、及び、ステップＳ２１５は、「検出工程」の一部に相当する。図１０に示すステップＳ２０５、ステップＳ２１１、及び、ステップＳ２１７は、「分析工程」の一部に相当する。図１０に示すステップＳ２１９、ステップＳ２２１、ステップＳ２２３、及び、ステップＳ２２５は、「判定工程」の一部に相当する。 Step S203, step S209, and step S215 shown in FIG. 10 correspond to a part of the “detection step”. Steps S205, S211 and S217 shown in FIG. 10 correspond to a part of the “analysis process”. Step S219, step S221, step S223, and step S225 shown in FIG. 10 correspond to a part of the “determination step”.
　図１０のステップＳ２０３、ステップＳ２０９、及び、ステップＳ２１５において、眼球運動検出部３２によって、予め選定された眼球運動テスト（本実施形態では、フリービューイングテスト、スムースパシュートテスト、及び、注視テスト）の画像を見る際の被験者の眼球ＥＢの動きが検出される。そして、図１０のステップＳ２０５、ステップＳ２１１、及び、ステップＳ２１７において、分析部３３によって、眼球運動検出部３２によって検出された眼球ＥＢの動きが分析される。また、図１０のステップＳ２１９、ステップＳ２２１、ステップＳ２２３、及び、ステップＳ２２５において、評価部３５によって、分析部３３によって求められた眼球運動特徴に基づき、被験者が統合失調症の患者であるか否かが判定される。 In step S203, step S209, and step S215 of FIG. 10, the eye movement detection unit 32 performs a preselected eye movement test (in this embodiment, a free viewing test, a smooth shoot test, and a gaze test). The movement of the eyeball EB of the subject when viewing the image is detected. Then, in step S205, step S211 and step S217 of FIG. 10, the analysis unit 33 analyzes the movement of the eyeball EB detected by the eyeball movement detection unit 32. Further, in step S219, step S221, step S223, and step S225 of FIG. 10, whether or not the subject is a schizophrenic patient based on the eye movement characteristics obtained by the analysis unit 33 by the evaluation unit 35. Is determined.
　このようにして、分析部３３によって求められた眼球運動特徴に基づき、被験者が統合失調症の患者であるか否かが判定されるため、統合失調症の患者であるか否かを正確に判定することができる。 Thus, since it is determined whether or not the subject is a schizophrenic patient based on the eye movement characteristics obtained by the analysis unit 33, it is accurately determined whether or not the subject is a schizophrenic patient. can do.
　本実施形態では、分析部３３によって求められた第１所定数Ｎ１の眼球運動特徴のうち、選択部３４によって選択された第２所定数Ｎ２の眼球運動特徴に基づき被験者が統合失調症の患者であるか否かを判定する場合について説明したが、第１所定数Ｎ１の眼球運動特徴に基づき被験者が統合失調症の患者であるか否かを判定する形態であればよい。例えば、第１所定数Ｎ１の眼球運動特徴のうち健常者と統合失調症の患者とを判別するために最も有効な１個の眼球運動特徴（例えば、第１の眼球運動特徴Ａ）に基づき、被験者が統合失調症の患者であるか否かを判定する形態でもよい。この場合には、判別式生成処理及び判別処理が簡略化される。また、例えば、第１所定数Ｎ１全ての眼球運動特徴基づき、被験者が統合失調症の患者であるか否かを判定する形態でもよい。 In this embodiment, the subject is a schizophrenic patient based on the second predetermined number N2 of eye movement features selected by the selection unit 34 among the first predetermined number N1 of eye movement features obtained by the analysis unit 33. Although the case where it is determined whether it exists is demonstrated, what is necessary is just a form which determines whether a test subject is a schizophrenic patient based on the 1st predetermined number N1 eye movement characteristic. For example, based on one eye movement feature (for example, the first eye movement feature A) that is most effective for discriminating between healthy subjects and schizophrenic patients among the first predetermined number N1 of eye movement features, The form which determines whether a test subject is a schizophrenic patient may be sufficient. In this case, the discriminant generation process and the discrimination process are simplified. Further, for example, it may be configured to determine whether or not the subject is a schizophrenic patient based on all eye movement characteristics of the first predetermined number N1.
　また、第２所定数Ｎ２の眼球運動特徴が、健常者と統合失調症患者とを判別するために有効な眼球運動特徴であるフリービューイングテストにおけるスキャンパス距離（第１の眼球運動特徴Ａ）を含むため、被験者が統合失調症の患者であるか否かを正確に判定することができる。なお、第２所定数Ｎ２の眼球運動特徴が、フリービューイングテストにおけるスキャンパス距離に替えて、上記スキャンパス距離と相関の強い他の眼球運動特徴を含む形態でもよい。 The scan path distance (first eye movement feature A) in the free viewing test, in which the second predetermined number N2 of eye movement features is an effective eye movement feature for distinguishing between healthy subjects and schizophrenia patients. Therefore, it can be accurately determined whether or not the subject is a schizophrenic patient. The second predetermined number N2 of eye movement features may include other eye movement features having a strong correlation with the scan path distance instead of the scan path distance in the free viewing test.
　また、第２所定数Ｎ２の眼球運動特徴が、健常者と統合失調症患者とを判別するために有効な眼球運動特徴であるスムースパシュートテストの速いリサージュにおける垂直方向の位置ゲイン（第２の眼球運動特徴Ｂ）を含むため、被験者が統合失調症の患者であるか否かを正確に判定することができる。なお、第２所定数Ｎ２の眼球運動特徴が、スムースパシュートテストの速いリサージュにおける垂直方向の位置ゲインに替えて、上記位置ゲインと相関の強い他の眼球運動特徴を含む形態でもよい。 In addition, the second predetermined number N2 of eye movement features is an effective eye movement feature for distinguishing between healthy subjects and schizophrenic patients, and a vertical position gain (second eyeball) in a quick lissajous of a smooth spshoot test. Since it includes the movement feature B), it can be accurately determined whether or not the subject is a schizophrenic patient. Note that the second predetermined number N2 of eye movement characteristics may include other eye movement characteristics having a strong correlation with the position gain, instead of the vertical position gain in the Lissajous test with a quick smooth spout test.
　また、本実施形態では、第２所定数Ｎ２の眼球運動特徴が、第１の眼球運動特徴Ａ～第５の眼球運動特徴Ｅである場合について説明したが、第２所定数Ｎ２の眼球運動特徴が、第１の眼球運動特徴Ａ～第５の眼球運動特徴Ｅのうち、少なくとも１つを含む形態であればよい。 In the present embodiment, the case where the second predetermined number N2 of eye movement features is the first eye movement feature A to the fifth eye movement feature E has been described. However, the second predetermined number N2 of eye movement features is described. However, any configuration including at least one of the first eye movement feature A to the fifth eye movement feature E may be used.
　次に、図１１を参照して、上記（１）式による判別結果について説明する。図１１は、図１に示す評価部３５による評価結果の一例を示す図表である。図１１の左側は、「全データを使った場合」であり、右側は、「Ｌｅａｖｅ－ｏｎｅ－ｏｕｔ交差検証」を行った場合である。ここで、「全データを使った場合」とは、図３に示す対象者全員のデータを用いて判別式（上記（１）式）を生成し、生成された判別式を用いて図３に示す対象者全員について図１０に示す判別処理を行う場合である。また、「Ｌｅａｖｅ－ｏｎｅ－ｏｕｔ交差検証」とは、図３に示す対象者のうち１名（ここでは、除外者という）を除いたデータを用いて判別式を生成し、生成された判別式を用いて上記除外者について図１０に示す判別処理を行う場合である。なお、上記除外者としては、図３に示す対象者である１０９名から、順次１名を選定する。その結果、上記除外者が選定される度に、残りの１０８名に関するデータを用いて判別式が生成されるため、判別式が１０９回生成される。 Next, with reference to FIG. 11, the determination result by the above equation (1) will be described. FIG. 11 is a chart showing an example of an evaluation result by the evaluation unit 35 shown in FIG. The left side of FIG. 11 is “when all data is used”, and the right side is a case where “Leave-one-out cross-validation” is performed. Here, “when all data is used” means that a discriminant (the above formula (1)) is generated using the data of all the subjects shown in FIG. 3, and the generated discriminant is used in FIG. This is a case where the discrimination processing shown in FIG. In addition, “Leave-one-out cross-validation” means that a discriminant is generated using data excluding one person (herein referred to as an excluder) among the target persons shown in FIG. 10 is used to perform the discrimination processing shown in FIG. In addition, as the above-mentioned exclusion person, one person is sequentially selected from 109 persons who are the target persons shown in FIG. As a result, every time the above-mentioned excluder is selected, a discriminant is generated using data on the remaining 108 people, and thus the discriminant is generated 109 times.
　図１１の左側に示すように、「全データを使った場合」には、健常者６９名のうち、評価部３５によって健常者であると判定された人数は６５名であり、正答率は９４．２％であった。また、統合失調症患者４０名のうち、評価部３５によって統合失調症患者であると判定された人数は３３名であり、正答率は８２．５％であった。その結果、全体の正答率は、８９．９％であった。 As shown on the left side of FIG. 11, in “when all data is used”, of the 69 healthy persons, the number of persons determined to be healthy by the evaluation unit 35 is 65, and the correct answer rate is 94. 2%. Moreover, out of 40 schizophrenia patients, the number of persons determined to be schizophrenia patients by the evaluation unit 35 was 33, and the correct answer rate was 82.5%. As a result, the overall correct answer rate was 89.9%.
　図１１の右側に示すように、「Ｌｅａｖｅ－ｏｎｅ－ｏｕｔ交差検証」では、健常者６９名のうち、評価部３５によって健常者であると判定された人数は６５名であり、正答率は９４．２％であった。また、統合失調症患者４０名のうち、評価部３５によって統合失調症患者であると判定された人数は３１名であり、正答率は７７．５％であった。その結果、全体の正答率は、８８．１％であった。 As shown on the right side of FIG. 11, in the “Leave-one-out cross-validation”, out of 69 healthy persons, the number of persons determined to be healthy by the evaluation unit 35 is 65, and the correct answer rate is 94. 2%. Moreover, among the 40 schizophrenia patients, the number of persons determined to be schizophrenia patients by the evaluation unit 35 was 31, and the correct answer rate was 77.5%. As a result, the overall correct answer rate was 88.1%.
　このように、精神疾患判定装置１００によれば、精神疾患（本実施形態では、統合失調症）の患者であるか否かを正確に判定することができる。なお、本実施形態では、精神疾患が統合失調症である場合について説明したが、精神疾患がその他の精神疾患（例えば、うつ病、躁うつ病等）である形態でもよい。 Thus, according to the psychiatric disorder determination device 100, it is possible to accurately determine whether or not the patient is a psychiatric disorder (in this embodiment, schizophrenia). In the present embodiment, the case where the mental illness is schizophrenia has been described. However, the mental illness may be another mental illness (for example, depression, manic depression, etc.).
　次に、図１２及び図１３を用いて、図１１における「Ｌｅａｖｅ－ｏｎｅ－ｏｕｔ交差検証」での評価部３５による評価結果を示す。図１２は、図１に示す評価部３５による評価結果の一例を示す棒グラフである。図１３は、図１に示す評価部３５による評価結果の一例を示すＲＯＣ（Ｒｅｃｅｉｖｅｒ　Ｏｐｅｒａｔｉｎｇ　Ｃｈａｒａｃｔｅｒｉｓｔｉｃ）グラフである。 Next, an evaluation result by the evaluation unit 35 in “Leave-one-out cross verification” in FIG. 11 will be shown using FIG. 12 and FIG. FIG. 12 is a bar graph showing an example of an evaluation result by the evaluation unit 35 shown in FIG. FIG. 13 is a ROC (Receiver Operating Characteristic) graph showing an example of an evaluation result by the evaluation unit 35 shown in FIG.
　図１２において、横軸は、眼球運動スコアＹを示し、縦軸は割合を示す。濃い網掛けが統合失調症の患者であり、薄い網掛けが健常者である。上述のように、評価部３５によって、眼球運動スコアＹが、事後確率によって定められる閾値（本実施形態では、－０．３）以上である場合に、健常者であると判定され、眼球運動スコアＹが上記閾値未満である場合に、統合失調症の患者であると判定する。図１２に示すように、健常者に関しては、極めて正確に判定されている。また、健常者であると誤判定された統合失調症患者は、眼球運動スコアＹが零に近いケースが大半であり、今後の更なる研究により、正答率を向上できる可能性があることが判る。 In FIG. 12, the horizontal axis indicates the eye movement score Y, and the vertical axis indicates the ratio. A dark shade is a patient with schizophrenia, and a thin shade is a healthy person. As described above, when the eye movement score Y is equal to or greater than the threshold (−0.3 in this embodiment) determined by the posterior probability, the evaluation unit 35 determines that the person is a healthy person, and the eye movement score. When Y is less than the threshold value, it is determined that the patient is schizophrenic. As shown in FIG. 12, a healthy person is determined very accurately. In addition, the majority of schizophrenia patients who are misjudged as healthy individuals have a case where the eye movement score Y is close to zero, and further studies will indicate that the correct answer rate may be improved. .
　図１３において、横軸は、偽陽性率を示し、縦軸は、真陽性率を示す。ＲＯＣ曲線ＧＲの下側の網掛けを施した領域の面積は、最大値（完璧に判別できる場合の値）１に対して０．９４以上であった。これは、上記（１）式に示す判別式によって、統合失調症患者を健常者と明確に識別することができることを示している。 In FIG. 13, the horizontal axis represents the false positive rate, and the vertical axis represents the true positive rate. The area of the shaded area below the ROC curve GR was 0.94 or more with respect to the maximum value (value in a case where perfect discrimination is possible) 1. This indicates that the schizophrenic patient can be clearly identified as a healthy person by the discriminant represented by the above formula (1).
　以上、図面を参照しながら本発明の実施形態について説明した。ただし、本発明は、上記の実施形態に限られるものではなく、その要旨を逸脱しない範囲で種々の態様において実施することが可能である（例えば、下記に示す（１）～（９））。図面は、理解しやすくするために、それぞれの構成要素を主体に模式的に示しており、図示された各構成要素の厚み、長さ、個数等は、図面作成の都合上から実際とは異なる。また、上記の実施形態で示す各構成要素の形状、寸法等は一例であって、特に限定されるものではなく、本発明の構成から実質的に逸脱しない範囲で種々の変更が可能である。 The embodiments of the present invention have been described above with reference to the drawings. However, the present invention is not limited to the above-described embodiment, and can be implemented in various modes without departing from the gist thereof (for example, (1) to (9) shown below). In order to facilitate understanding, the drawings schematically show each component as a main component, and the thickness, length, number, and the like of each component shown in the drawings are different from the actual for convenience of drawing. . Moreover, the shape, dimension, etc. of each component shown by said embodiment are an example, Comprising: It does not specifically limit, A various change is possible in the range which does not deviate substantially from the structure of this invention.
　（１）本実施形態では、制御装置３がテスト表示部３１を備える場合について説明したが、モニタ１がテスト表示部３１に相当する機能部を備える形態でもよい。 (1) In the present embodiment, the case where the control device 3 includes the test display unit 31 has been described. However, the monitor 1 may include a functional unit corresponding to the test display unit 31.
　（２）本実施形態では、制御装置３が眼球運動検出部３２を備える場合について説明したが、ビデオカメラ２が眼球運動検出部３２に相当する機能部を備える形態でもよい。 (2) In the present embodiment, the case where the control device 3 includes the eye movement detection unit 32 has been described. However, the video camera 2 may include a functional unit corresponding to the eye movement detection unit 32.
　（３）本実施形態では、精神疾患の患者であるか否かを判定する精神疾患判定装置１００について説明したが、精神疾患判定装置１００の有する機能を複数の装置で実現した精神疾患判定システムとして構成してもよい。例えば、精神疾患判定システムが、眼球運動テスト表示装置、眼球運動検出装置、分析装置、及び、判定装置を備える形態でもよい。上記眼球運動テスト表示装置は、モニタを備え、眼球運動テストの画像をモニタに表示する。上記眼球運動検出装置は、ビデオカメラを備え、被験者の眼球の動きを検出する。上記分析装置は、上記眼球運動検出装置によって検出された眼球の動きを分析し、眼球運動特徴を求める。上記判定装置は、上記分析装置によって求められた眼球運動特徴に基づき、被験者が精神疾患の患者であるか否かを判定する。 (3) In this embodiment, the mental illness determination apparatus 100 that determines whether or not the patient is a mental illness has been described. It may be configured. For example, the mental disease determination system may include an eye movement test display device, an eye movement detection device, an analysis device, and a determination device. The eye movement test display device includes a monitor and displays an image of the eye movement test on the monitor. The eye movement detection device includes a video camera and detects the movement of the eyeball of the subject. The analysis device analyzes the movement of the eyeball detected by the eyeball movement detection device and obtains the eyeball movement feature. The determination device determines whether or not the subject is a mentally ill patient based on the eye movement characteristics obtained by the analysis device.
　（４）本実施形態では、ビデオカメラ２を介して被験者の眼球の動きを検出する場合について説明したが、その他の方法（例えば、赤外線を用いた強膜反射法）を用いて被験者の眼球の動きを検出する形態でもよい。 (4) In the present embodiment, the case where the movement of the eyeball of the subject is detected via the video camera 2 has been described. However, other methods (for example, scleral reflection method using infrared rays) are used to detect the eyeball of the subject. The form which detects a motion may be sufficient.
　（５）本実施形態では、評価部３５が、眼球運動スコアＹが上記閾値（本実施形態では、－０．３）零未満であるか否かに応じて、統合失調症の患者であるか否かを判定する場合について説明したが、評価部３５が、統合失調症の患者である可能性を判定する形態でもよい。換言すれば、評価部３５が、眼球運動スコアＹの値が大きいほど健常者である可能性が高く、小さいほど精神疾患に罹患している可能性が高いと判定する形態でもよい。この場合には、医師が診断をする際に、眼球運動スコアＹの値の大きさを、健常者であるかどうかの判断の参考とすることができる。 (5) In the present embodiment, the evaluation unit 35 determines whether the eye movement score Y is a schizophrenic patient depending on whether or not the threshold (in this embodiment, −0.3) is less than zero. Although the case of determining whether or not is described, the evaluation unit 35 may determine a possibility of being a schizophrenic patient. In other words, the evaluation unit 35 may determine that the greater the value of the eye movement score Y, the higher the possibility of being a healthy person, and the smaller the value, the higher the possibility of suffering from a mental illness. In this case, when the doctor makes a diagnosis, the magnitude of the eye movement score Y can be used as a reference for determining whether or not he is a healthy person.
　（６）本実施形態では、第１所定数Ｎ１が６５個の場合について説明したが、第１所定数Ｎ１は、例えば、５０個～１００個の範囲内の個数でもよい。 (6) In the present embodiment, the case where the first predetermined number N1 is 65 has been described, but the first predetermined number N1 may be a number in the range of 50 to 100, for example.
　（７）本実施形態では、第２所定数Ｎ２が５個の場合について説明したが、第２所定数Ｎ２は、例えば、５個～１５個の範囲内の個数でもよい。 (7) In the present embodiment, the case where the second predetermined number N2 is five has been described. However, the second predetermined number N2 may be a number in the range of 5 to 15, for example.
　（８）本実施形態では、評価部３５が、統合失調症の患者であるか否かを判定する場合について説明したが、評価部が、統合失調症の患者であるか、自閉症の患者であるかを判定する形態でもよい。更には、評価部が、被験者が、予め設定された複数の精神疾患（例えば、統合失調症、自閉症、うつ病）のうち、どの精神疾患であるかを判定する形態でもよい。 (8) In the present embodiment, the case where the evaluation unit 35 determines whether or not the patient is a schizophrenic patient has been described. However, the evaluation unit is a schizophrenic patient or an autistic patient. It may be a form for determining whether or not. Further, the evaluation unit may determine which mental disorder the subject has among a plurality of preset mental disorders (for example, schizophrenia, autism, depression).
　（９）本実施形態では、評価部３５が、統合失調症の患者であるか否かを判定する場合について説明したが、評価部が、精神疾患の予後や程度を判定する形態でもよい。 (9) In the present embodiment, the case where the evaluation unit 35 determines whether or not the patient is a schizophrenic patient has been described, but the evaluation unit may determine the prognosis or degree of mental illness.
　本発明は、精神疾患の患者であるか否かを判定する精神疾患判定装置、及び、精神疾患判定方法に利用可能である。 The present invention is applicable to a mental illness determination apparatus and a mental illness determination method for determining whether or not a patient has a mental illness.
　１００　　精神疾患判定装置
　１　　モニタ
　２　　ビデオカメラ（検出手段の一部）
　３　　制御装置
　３１　　テスト表示部
　３２　　眼球運動検出部（検出手段の一部）
　３３　　分析部（分析手段）
　３４　　選択部（判定手段の一部）
　３５　　評価部（判定手段の一部）
　３６　　記憶部 100 Mental illness determination device 1 Monitor 2 Video camera (part of detection means)
3 Control device 31 Test display unit 32 Eye movement detection unit (part of detection means)
33 Analysis unit (analysis means)
34 Selection unit (part of determination means)
35 Evaluation part (part of the judging means)
36 Memory unit

Claims (15)

  1. 　精神疾患を判定する精神疾患判定装置であって、
    　予め選定された眼球運動テストの画像を見る際の被験者の眼球の動きを検出する検出手段と、
    　前記検出手段によって検出された眼球の動きを分析し、３個以上の第１所定数の眼球運動特徴を求める分析手段と、
    　前記分析手段によって求められた前記第１所定数の眼球運動特徴に基づき、前記被験者の前記精神疾患を判定する判定手段と
    　を備える、精神疾患判定装置。     A mental illness determination device for determining a mental illness,
    Detection means for detecting the movement of the eyeball of the subject when viewing a preselected eye movement test image;
    Analyzing the movement of the eyeball detected by the detection means, and obtaining three or more first predetermined number of eye movement features;
    A mental disease determination device comprising: determination means for determining the mental disease of the subject based on the first predetermined number of eye movement characteristics obtained by the analysis means.
  2. 　精神疾患の患者であるか否かを判定する精神疾患判定装置であって、
    　予め選定された眼球運動テストの画像を見る際の被験者の眼球の動きを検出する検出手段と、
    　前記検出手段によって検出された眼球の動きを分析し、３個以上の第１所定数の眼球運動特徴を求める分析手段と、
    　前記分析手段によって求められた前記第１所定数の眼球運動特徴に基づき、前記被験者が前記精神疾患の患者であるか否かを判定する判定手段と
    　を備える、精神疾患判定装置。     A mental illness determination device for determining whether or not a patient has a mental illness,
    Detection means for detecting the movement of the eyeball of the subject when viewing a preselected eye movement test image;
    Analyzing the movement of the eyeball detected by the detection means, and obtaining three or more first predetermined number of eye movement features;
    A mental disease determination device comprising: determination means for determining whether or not the subject is a patient with the mental disease based on the first predetermined number of eye movement characteristics obtained by the analysis means.
  3. 　前記判定手段は、前記分析手段によって求められた前記第１所定数の眼球運動特徴から、健常者と前記精神疾患の患者とを判別するために有効な２個以上の第２所定数の眼球運動特徴を選択し、前記第２所定数の眼球運動特徴に基づき、前記被験者が前記精神疾患の患者であるか否かを判定する、請求項２に記載の精神疾患判定装置。 The determination means includes two or more second predetermined number of eye movements effective for discriminating a healthy person and the patient with the mental illness from the first predetermined number of eye movement characteristics obtained by the analysis means. The mental disease determination device according to claim 2, wherein a feature is selected and whether or not the subject is the patient with the mental disease is determined based on the second predetermined number of eye movement features.
  4. 　前記判定手段は、前記分析手段によって求められた前記第１所定数の眼球運動特徴から、互いに独立性の強い前記第２所定数の眼球運動特徴を選択する、請求項３に記載の精神疾患判定装置。 4. The mental disease determination according to claim 3, wherein the determination unit selects the second predetermined number of eye movement features having strong independence from the first predetermined number of eye movement features obtained by the analysis unit. 5. apparatus.
  5. 　前記判定手段は、ステップワイズ法によって、前記分析手段によって求められた前記第１所定数の眼球運動特徴から、前記健常者と前記精神疾患の患者とを判別するために有効な前記第２所定数の眼球運動特徴を選択する、請求項４に記載の精神疾患判定装置。 The determination means is the second predetermined number effective for discriminating between the healthy person and the mentally ill patient from the first predetermined number of eye movement characteristics obtained by the analysis means by a stepwise method. The psychiatric disorder determination device according to claim 4, wherein the eye movement characteristics of the psychiatric disorder are selected.
  6. 　前記判定手段は、前記第２所定数の眼球運動特徴の関数を判別式として求め、前記判別式によって、前記被験者が前記精神疾患の患者であるか否かを判定する、請求項３から請求項５のいずれか１項に記載の精神疾患判定装置。 The determination unit obtains a function of the second predetermined number of eye movement characteristics as a discriminant and determines whether or not the subject is a patient with the mental disease based on the discriminant. The mental disease determination apparatus according to any one of 5.
  7. 　前記判定手段は、前記判別式として、前記第２所定数の眼球運動特徴に関する線形方程式を求める、請求項６に記載の精神疾患判定装置。 The mental disease determination device according to claim 6, wherein the determination means obtains a linear equation relating to the second predetermined number of eye movement characteristics as the discriminant.
  8. 　前記眼球運動テストは、前記健常者と前記精神疾患の患者との間でテスト結果に顕著な差異がある眼球運動テストである、請求項３から請求項７のいずれか１項に記載の精神疾患判定装置。 The psychiatric disorder according to any one of claims 3 to 7, wherein the eye movement test is an eye movement test in which there is a significant difference in test results between the healthy subject and the patient with the psychiatric disorder. Judgment device.
  9. 　前記眼球運動テストは、フリービューイングテスト、スムースパシュートテスト、及び、注視テストのうち、少なくとも１つを含む、請求項８に記載の精神疾患判定装置。 The psychiatric disorder determination device according to claim 8, wherein the eye movement test includes at least one of a free viewing test, a smooth spa chute test, and a gaze test.
  10. 　前記精神疾患は、統合失調症であって、
    　前記第２所定数の眼球運動特徴は、フリービューイングテストにおけるスキャンパス距離、又は、前記スキャンパス距離と相関の強い他の眼球運動特徴を含む、請求項３から請求項９のいずれか１項に記載の精神疾患判定装置。     The mental illness is schizophrenia,
    The second predetermined number of eye movement characteristics includes a scan path distance in a free viewing test or another eye movement characteristic having a strong correlation with the scan path distance. The psychiatric disorder determination device described in 1.
  11. 　前記精神疾患は、統合失調症であって、
    　前記第２所定数の眼球運動特徴は、スムースパシュートテストの速いリサージュにおける垂直方向の位置ゲイン、又は、前記位置ゲインと相関の強い他の眼球運動特徴を含む、請求項３から請求項１０のいずれか１項に記載の精神疾患判定装置。     The mental illness is schizophrenia,
    The second predetermined number of eye movement characteristics includes a vertical position gain in a quick Lissajous of a smooth spur test, or another eye movement characteristic having a strong correlation with the position gain. The psychiatric disorder determination device according to claim 1.
  12. 　２個以上の第２所定数の眼球運動特徴に基づき、被験者が統合失調症の患者であるか否かを判定する精神疾患判定装置であって、
    　前記第２所定数の眼球運動特徴は、フリービューイングテストにおけるスキャンパス距離、スムースパシュートテストの速いリサージュにおける垂直方向の位置ゲイン、スムースパシュートテストの速いリサージュにおける注視数、注視テストの遠い妨害刺激における注視期間、及び、スムースパシュートテストの水平パシュートにおけるＳ／Ｎ比のうち、少なくとも１つを含む、精神疾患判定装置。     A psychiatric disorder determination device that determines whether a subject is a schizophrenic patient based on two or more second predetermined number of eye movement characteristics,
    The second predetermined number of eye movement features include a scan path distance in a free viewing test, a vertical position gain in a quick lissajous test, a number of gazes in a quick lissajous test Lissajous, a distant disturbance stimulus in a gaze test A psychiatric disorder determination device including at least one of a gaze period and an S / N ratio in a horizontal pursuit of a smooth pursuit test.
  13. 　精神疾患を判定する精神疾患判定方法であって、
    　眼球運動テストの画像を見る際の被験者の眼球の動きを検出する検出工程と、
    　前記検出工程において検出された眼球の動きを分析する分析工程と、
    　前記分析工程において求められた３個以上の第１所定数の眼球運動特徴に基づき、前記被験者の前記精神疾患を判定する判定工程と
    　を含む、精神疾患判定方法。     A method for determining mental illness, comprising:
    A detection step of detecting the movement of the eyeball of the subject when viewing the image of the eye movement test;
    An analysis step of analyzing the movement of the eyeball detected in the detection step;
    A determination step of determining the mental illness of the subject based on three or more first predetermined number of eye movement characteristics obtained in the analysis step.
  14. 　精神疾患の患者であるか否かを判定する精神疾患判定方法であって、
    　眼球運動テストの画像を見る際の被験者の眼球の動きを検出する検出工程と、
    　前記検出工程において検出された眼球の動きを分析する分析工程と、
    　前記分析工程において求められた２個以上の第１所定数の眼球運動特徴に基づき、前記被験者が前記精神疾患の患者であるか否かを判定する判定工程と
    　を含む、精神疾患判定方法。     A mental disease determination method for determining whether or not a patient has a mental illness,
    A detection step of detecting the movement of the eyeball of the subject when viewing the image of the eye movement test;
    An analysis step of analyzing the movement of the eyeball detected in the detection step;
    A determination step of determining whether or not the subject is a patient with the mental disease based on two or more first predetermined number of eye movement characteristics obtained in the analysis step.
  15. 　前記判定工程において、前記分析工程において求められた前記第１所定数の眼球運動特徴から、健常者と前記精神疾患の患者とを判別するために有効な２個以上の第２所定数の眼球運動特徴を選択し、前記第２所定数の眼球運動特徴に基づき、前記被験者が前記精神疾患の患者であるか否かを判定する、請求項１４に記載の精神疾患判定方法。 In the determination step, two or more second predetermined number of eye movements effective for discriminating a healthy person and the patient with the mental disease from the first predetermined number of eye movement characteristics obtained in the analysis step. The mental disease determination method according to claim 14, wherein a feature is selected and whether or not the subject is the patient with the mental disease is determined based on the second predetermined number of eye movement features.
PCT/JP2015/063868 2014-09-08 2015-05-14 Mental disease determination device and mental disease determination method WO2016038937A1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2014-182369 2014-09-08
JP2014182369A JP6455656B2 (en) 2014-09-08 2014-09-08 Mental disease determination device and mental disease determination method

Publications (1)

Publication Number Publication Date
WO2016038937A1 true WO2016038937A1 (en) 2016-03-17

Family

ID=55458700

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2015/063868 WO2016038937A1 (en) 2014-09-08 2015-05-14 Mental disease determination device and mental disease determination method

Country Status (2)

Country Link
JP (1) JP6455656B2 (en)
WO (1) WO2016038937A1 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108829246B (en) * 2018-05-31 2021-12-07 歌尔股份有限公司 Eyeball tracking function detection method and system

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012165602A1 (en) * 2011-05-31 2012-12-06 国立大学法人名古屋工業大学 Cognitive dysfunction-determining equipment, cognitive dysfunction-determining system, and program
WO2013102768A1 (en) * 2012-01-05 2013-07-11 University Court Of The University Of Aberdeen An apparatus and a method for psychiatric evaluation

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012165602A1 (en) * 2011-05-31 2012-12-06 国立大学法人名古屋工業大学 Cognitive dysfunction-determining equipment, cognitive dysfunction-determining system, and program
WO2013102768A1 (en) * 2012-01-05 2013-07-11 University Court Of The University Of Aberdeen An apparatus and a method for psychiatric evaluation

Also Published As

Publication number Publication date
JP2016054839A (en) 2016-04-21
JP6455656B2 (en) 2019-01-23

Similar Documents

Publication Publication Date Title
JP6251412B2 (en) Careless measuring device, system, and method
EP2829221B1 (en) Asperger's diagnosis assistance device
CN107713984B (en) Objective assessment method for facial paralysis
Wiecek et al. Effects of peripheral visual field loss on eye movements during visual search
JP5421146B2 (en) Visual field inspection system
de Almeida et al. Computational methodology for automatic detection of strabismus in digital images through Hirschberg test
KR102560069B1 (en) Stimulation and eye tracking system
JP2015503414A (en) Apparatus and method for psychiatric evaluation
EP2827758A1 (en) Method for assessing function of the visual system and apparatus thereof
CN111933275A (en) Depression evaluation system based on eye movement and facial expression
JPH08105B2 (en) Fixation and microtremor inspection device
KR20150036395A (en) Strabismus Detection
CN110772218A (en) Vision screening device and method
KR102344493B1 (en) A smart inspecting system, method and program for nystagmus using artificial intelligence
CN111067474B (en) Apparatus and method for objective visual acuity measurement using dynamic velocity threshold filter
Ruengkitpinyo et al. An automatic glaucoma screening algorithm using cup-to-disc ratio and ISNT rule with support vector machine
Atabaki et al. Assessing the precision of gaze following using a stereoscopic 3D virtual reality setting
JP6455656B2 (en) Mental disease determination device and mental disease determination method
US20210068650A1 (en) Assessing visual function
CN108495584B (en) Apparatus and method for determining eye movement through a haptic interface
Tong et al. Automated measuring method based on Machine learning for optomotor response in mice
KR20220053209A (en) Apparatus and Method for Measuring The Angel Of Strabismus for Supporting Diagnosis Of Strabismus
KR101643744B1 (en) Device and method for detecting user fixation pupillary response
Quang et al. Mobile traumatic brain injury assessment system
WO2024095261A1 (en) System and method for diagnosis and treatment of various movement disorders and diseases of the eye

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 15839375

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 15839375

Country of ref document: EP

Kind code of ref document: A1