JP2021049312A - Visual function evaluation device - Google Patents

Abstract

To provide a visual function evaluation device capable of accurately evaluating a visual function of a subject eye using a retina potential.SOLUTION: The visual function evaluation device in one aspect of this invention comprises a detection unit, a generation unit, and an evaluation unit. The detection unit detects a potential signal generated in the retina of a subject eye due to visual stimulation. The generation unit generates a first potential signal in a first visual field and generates a second potential signal in a second visual field on the basis of the potential signal detected by the detection unit. The evaluation unit evaluates the visual function of the subject eye on the basis of the first potential signal and the second potential signal generated by the generation unit.SELECTED DRAWING: Figure 8

Description

The present invention relates to a visual function evaluation device for evaluating the visual function of an eye to be inspected.

Conventionally, it is known that a constant potential (retinal potential) exists in the human eyeball, particularly the retina, and the potential changes depending on the stimulation of light. And such a phenomenon is widely used for inspection, research and the like. For example, electrophysiological examination of the retina or vision is performed using a retinal potential map (ERG) in which fluctuations in the retinal potential are recorded with time as the horizontal axis (see, for example, Patent Document 1).

Japanese Unexamined Patent Publication No. 2011-87609

By the way, it is desired to accurately evaluate the visual function of the eye to be inspected using the retinal potential. Therefore, it is desirable to provide a visual function evaluation device capable of accurately evaluating the visual function of the eye to be inspected using the retinal potential.

The visual function evaluation device according to the first aspect of the present invention includes a detection unit, a generation unit, and a display unit. The detection unit detects the potential signal generated in the retina of the eye to be inspected by the visual stimulus. The generation unit generates the first potential signal in the first visual field and the second potential signal in the second visual field based on the potential signal detected by the detection unit. The display unit displays the result of the evaluation of the visual function of the eye to be inspected, which is performed based on the first potential signal and the second potential signal generated by the generation unit.

In the visual function evaluation device according to the first aspect of the present invention, the first potential signal in the first visual field is generated based on the potential signal generated in the retina of the eye to be inspected by the visual stimulus detected by the detection unit, and the first potential signal is generated. A second potential signal in two fields of view is generated. Here, the first potential signal and the second potential signal change according to the visual function of the eye to be inspected. For example, in the eyes of a healthy subject, the first potential signal and the second potential signal show an asymmetry in the amplitude ratio, and in the eyes of a glaucoma patient, the first potential signal and the second potential signal have an amplitude ratio. Significantly eliminates asymmetry. As a result, the visual function of the eye to be inspected can be evaluated based on the first potential signal and the second potential signal, and the result of the evaluation can be displayed on the display unit.

The visual function evaluation device according to the second aspect of the present invention includes a detection unit, a generation unit, and an evaluation unit. The detection unit detects the potential signal generated in the retina of the eye to be inspected by the visual stimulus. The generation unit generates the first potential signal in the first visual field and the second potential signal in the second visual field based on the potential signal detected by the detection unit. The evaluation unit evaluates the visual function of the eye to be inspected based on the first potential signal and the second potential signal generated by the generation unit.

In the visual function evaluation device according to the second aspect of the present invention, the first potential signal in the first visual field is generated based on the potential signal generated in the retina of the eye to be inspected by the visual stimulus detected by the detection unit, and the first potential signal is generated. A second potential signal in two fields of view is generated. Here, the first potential signal and the second potential signal change according to the visual function of the eye to be inspected. For example, in the eyes of a healthy subject, the first potential signal and the second potential signal show an asymmetry in the amplitude ratio, and in the eyes of a glaucoma patient, the first potential signal and the second potential signal have an amplitude ratio. Significantly eliminates asymmetry. Thereby, the visual function of the eye to be inspected can be evaluated based on the first potential signal and the second potential signal.

According to the visual function evaluation device in the first and second aspects of the present invention, the visual function of the eye to be inspected can be evaluated based on the first potential signal and the second potential signal, so that the retinal potential is used. It is possible to accurately evaluate the visual function of the eye to be inspected.

It is a figure which shows typically the visual stimulus by a binary m sequence. It is a figure which shows the fluctuation of the retinal potential for each channel. It is a figure which shows an example of the response signal of the primary nucleus. It is a figure which shows an example of the response signal of a secondary nucleus. It is a figure which shows typically the secondary nuclear nasal visual field signal and the secondary nuclear ear side visual field signal for each channel. It is a figure which shows an example of the secondary nuclear nasal visual field signal and the secondary nuclear ear side visual field signal of a healthy person. It is a figure which shows an example of the secondary nuclear nasal visual field signal and the secondary nuclear ear visual field signal of a glaucoma patient. It is a figure which shows the schematic configuration example of the visual function evaluation apparatus which concerns on 1st Embodiment of this invention. It is a figure which shows the schematic structure example of the retinal potential measuring part. It is a figure which shows an example of an electrode position. It is a figure which shows an example of an electrode position. It is a figure which shows an example of an electrode position. It is a figure which shows an example of an electrode position. It is a figure which shows the schematic structure example of a learning model. It is a figure which shows an example of the secondary nuclear nasal visual field signal. It is a figure which shows an example of the secondary nucleus ear side visual field signal. It is a figure which shows one modification of the schematic structure of the learning model. It is a figure which shows the schematic configuration example of the visual function evaluation system which concerns on the 2nd Embodiment of this invention.

Hereinafter, embodiments for carrying out the present invention will be described in detail with reference to the drawings. The following description is a specific example of the present invention, and the present invention is not limited to the following aspects. The description will be given in the following order.
1. 1. Overview of multi-local ERG (Figs. 1 to 8)
2. First Embodiment (FIGS. 8 to 13)
3. 3. Modification example (Fig. 14)
4. Second embodiment (FIG. 15)

<1. Overview of multi-local ERG>
The multi-local ERG is a recording of fluctuations in the retinal potential (1 output) obtained by visual stimulation (multi-input) by a binary m sequence, with time as the horizontal axis. Visual stimulation by the binary m sequence is performed by irradiating each channel ch with light in a time series in a sequence in which a plurality of hexagonal channel channels are arranged concentrically as shown in FIG. It is a stimulus given to the retina. Such visual stimuli cause local fluctuations in the retinal potential, for example, as shown in FIG.

In each channel ch, the response signal of the primary nucleus (1st orderer kernel) has, for example, as shown in FIG. 3, focusing on one time t1 and having a positive sign on the potential signal when light irradiation is performed. Is given, and when light irradiation is not performed, a negative sign is given to the potential signal, and these two potential signals are added together to obtain the potential signal. When generating the response signal of the primary nucleus, the sign of the potential signal is determined by the presence or absence of light irradiation at time t1, and does not depend on the presence or absence of light irradiation at a time after time t1. Further, in each channel ch, the response signal of the secondary nucleus (2nd order kener) is, for example, focused on the two times t1 and t2 and irradiated with light at both the two times t1 and t2, as shown in FIG. When is set, a positive sign is given to the potential signal, and when only one of the two times t1 and t2 is irradiated with light, a negative sign is given to the potential signal and the two times t1 and t2 are given. When no light irradiation is performed in both of the above, a positive sign is given to the potential signal, and these four potential signals are added together to obtain the potential signal. When generating the response signal of the secondary nucleus, the sign of the potential signal is determined by the presence or absence of light irradiation at time t1 and t2, and does not depend on the presence or absence of light irradiation at a time after time t2.

Here, in the multi-local ERG, the response signal of the secondary nucleus within a radius of α ° from the center is the amplitude ratio (N /) of the response signal of the secondary nucleus in the nasal visual field and the response signal of the secondary nucleus in the auditory visual field. In terms of T ratio), the asymmetry is present in the eyes of a healthy subject, and the asymmetry is significantly eliminated in the eyes of a patient with glaucoma deep sea disorder. Hereinafter, in the multi-local ERG, the response signal of the secondary nucleus of the nasal visual field within a radius of α ° from the center is referred to as a “secondary nuclear nasal visual field signal”. Further, in the multi-local ERG, the response signal of the secondary nucleus of the auditory visual field within a radius of α ° from the center is referred to as “secondary nuclear auditory visual field signal”. The radius α ° is, for example, 5 °.

The nasal visual field signal of the secondary nucleus is, for example, as shown in FIG. 5, three secondary nuclei obtained by irradiating three channels ch1 within a radius of 5 ° in the nasal visual field with light in chronological order. It is a signal generated based on the response signal of. The secondary nucleus ear side visual field signal is, for example, as shown in FIG. 5, three secondary nuclei obtained by irradiating three channels ch2 within a radius of 5 ° in the ear side visual field in chronological order. It is a signal generated based on the response signal of.

The secondary nuclear nasal visual field signal and the secondary nuclear ear visual field signal obtained from a healthy person have, for example, waveforms as shown in FIG. On the other hand, the secondary nuclear nasal visual field signal and the secondary nuclear ear visual field signal obtained from the glaucoma patient have waveforms as shown in FIG. 7, for example. It can be seen that there is a significant difference between the amplitude ratio of the two signals shown in FIG. 6 and the amplitude ratio of the two signals shown in FIG. 7. From FIGS. 6 and 7, it can be seen that by observing the secondary nuclear nasal visual field signal and the secondary nuclear auditory visual field signal, it is easy to grasp the functional change of the optic nerve due to glaucoma. Therefore, the visual function evaluation device and the visual function evaluation system according to the embodiment of the present invention utilize the secondary nuclear nasal visual field signal and the secondary nuclear ear visual field signal in the multi-local ERG to allow the eye to be inspected. We decided to evaluate whether or not we had glaucoma. In the following, a visual function evaluation device and a visual function evaluation system capable of performing such evaluation will be described.

<2. First Embodiment>
[Constitution]
FIG. 8 shows an example of a schematic configuration of the visual function evaluation device 1 according to the first embodiment of the present invention. The visual function evaluation device 1 utilizes the secondary nuclear nasal visual field signal and the secondary nuclear ear visual field signal in the multi-local ERG to evaluate the visual function (specifically, whether the eye to be inspected suffers from glaucoma). (Evaluation of whether or not) is performed. The visual function evaluation device 1 is a device provided with a non-invasive measurement unit that detects a retinal potential from an electrode in contact with the skin around the eye. As shown in FIG. 8, for example, the visual function evaluation device 1 includes a control unit 10, a memory 20, a retinal potential measurement unit 30, a learning model 40, a display unit 50, and an input unit 60. There is.

The control unit 10 includes a CPU (Central Processing Unit) and the like, and executes, for example, an operating system (not shown) stored in the memory 20 and a program 21. The program 21 causes the control unit 10 to execute a series of procedures for evaluating the visual function. A series of procedures to be executed by the program 21 to the control unit 10 will be described in detail later. The control unit 10 processes the potential signal generated by the retinal potential measuring unit 30, displays it on the display unit 50, and stores it in the memory 20. Further, the control unit 10 displays the evaluation result of the visual function of the eye to be inspected (for example, the determination result 43A described later) obtained by the learning model 40 on the display unit 50 or stores it in the memory 20.

The memory 20 stores a program (for example, an operating system, a program 21) executed by the control unit 10. The memory 20 is composed of, for example, a RAM (Random Access Memory), a ROM (Read Only Memory), an auxiliary storage device (hard disk, etc.), and the like. The memory 20 stores, for example, a retinal potential map (ERG) generated by the retinal potential measuring unit 30, data input to the input unit 60 as a result of visual function evaluation obtained by the learning model 40, and the like. ..

The display unit 50 includes, for example, a display device such as a liquid crystal panel or an organic EL (Electroluminescence) panel. The display unit 50 displays an image based on the video signal from the control unit 10. The display unit 50 is, for example, a retinal potential diagram (ERG) generated by the retinal potential measuring unit 30 or a result of evaluation of the visual function of the eye to be inspected obtained by the learning model 40 (for example, evaluation of glaucoma in the eye to be inspected). Result) is displayed. The input unit 60 receives an input from the user and outputs the received input to the control unit 10. The input unit 60 may be, for example, a mechanical input interface including buttons, dials, or the like, or may be a touch panel provided on the display surface of the display unit 50.

As shown in FIG. 9, the retinal potential measuring unit 30 includes, for example, a light stimulating unit 31, a Seki electrode 32, a non-seki electrode 33, and a calculation unit 34. The Seki electrode 32 and the Seki electrode 33 correspond to a specific example of the "detection unit" of the present invention. The calculation unit 34 corresponds to a specific example of the "generation unit" of the present invention.

The light stimulating unit 31 gives a visual stimulus (light stimulus) to the retina of the eye to be inspected according to the control by the control unit 10. For example, in a series in which a plurality of hexagonal channels are arranged concentrically, the light stimulating unit 31 lights each channel in a time series and irradiates the retina of the eye to be inspected with the light flux obtained thereby. The light stimulating unit 31 drives, for example, a light emitting diode array in which one light emitting diode is provided for each of the above channels, a microlens array in which one microlens is provided for each light emitting diode, and a light emitting diode array. It has a drive circuit to operate. The microlens diffuses the light from the light emitting diode to form a substantially uniform luminance distribution. The drive circuit controls the light emission of the light emitting diode array so as to give a visual stimulus by a binary m sequence to the retina of the eye to be inspected, for example. In the drive circuit, for example, under the control of the control unit 10, the light stimulation unit 31 sequentially performs four types of light irradiation (light stimulation) as shown in FIG. 4 on a predetermined channel ch. 31 is controlled.

The Seki electrode 32 and the Seki electrode 33 detect the potential fluctuation generated in the retina of the eye to be inspected as a potential signal by the visual stimulus (light stimulus) by the light stimulating unit 31. The Seki electrode 32 and the Seki electrode 33 have a structure in which, for example, a disk-shaped electrode plate made of a material such as silver is integrally provided on the lower surface of a disk-shaped support portion. At this time, the lead wire is electrically connected to the electrode plate, and the potential signal detected by the electrode plate is taken out to the calculation unit 34 through the lead wire. The Seki electrode 32 and the Seki electrode 33 are arranged in contact with the skin around the eye. The Seki electrode 32 (electrode plate) is arranged in contact with the lower eyelid, for example, as shown in FIGS. 10 (A) to 10 (D). The irrelevant electrode 33 (electrode plate) is arranged in contact with the eyes, for example, as shown in FIG. 10 (A). As shown in FIG. 10A, the Seki electrode 32 and the Seki electrode 33 may be arranged in contact with the skin around the left eye, or may be arranged in contact with the skin around the right eye. Good.

The indifferent electrode 33 may be arranged so as to be in contact with the eyes, for example, as shown in FIG. 10 (B). At this time, the Seki electrode 32 and the Seki electrode 33 may be arranged in contact with the skin around the left eye or in contact with the skin around the right eye, as shown in FIG. 10 (B). May be done.

For example, as shown in FIG. 10C, the unrelated electrode 33 may be arranged in contact with the lower eyelid of the eye 100, which is different from the eye 100 adjacent to the barrier electrode 32. At this time, as shown in FIG. 10C, even if the Seki electrode 32 is arranged in contact with the skin around the left eye and the indifferent electrode 33 is arranged in contact with the skin around the right eye. Good. Further, the Seki electrode 32 may be arranged in contact with the skin around the right eye, and the Seki electrode 33 may be arranged in contact with the skin around the left eye.

The retinal potential measuring unit 30 may have two indifferent electrodes 33, for example, as shown in FIG. 10 (D). In this case, one unrelated electrode 33 is placed in contact with the lower eyelid of one eye 100, and the other unrelated electrode 33 is in contact with the lower eyelid of the eye 100 different from the eye 100 adjacent to the seki electrode 32. May be arranged. At this time, the Seki electrode 32 and the two dissimilar electrodes 33 may be arranged in contact with the skin around the left eye or in contact with the skin around the right eye, as shown in FIG. 10 (D). May be arranged.

Based on the potential signal 32A taken out from the Seki electrode 32 and the potential signal 33A taken out from the indifferent electrode 33, the calculation unit 34 determines the potential fluctuation generated in the retina of the eye to be inspected by the visual stimulus (light stimulus). A skin potential signal 34G having a correlation with the above is generated and output to the control unit 10. The calculation unit 34 outputs, for example, a difference between the potential signal 32A and the potential signal 33A (for example, difference = potential signal 32A-potential signal 33A) to the control unit 10 as a skin potential signal 34G. The skin potential signal 34G is a signal having a predetermined correlation with the potential signal of the retina of the eye to be examined, and is a signal corresponding to a so-called retinal potential map (ERG).

The calculation unit 34 generates a secondary nuclear nasal visual field signal 34A (first potential signal) by using the potential signal in the nasal visual field (first visual field) of the generated skin potential signal 34G. For example, as shown in FIG. 5, the calculation unit 34 uses the skin potential signal 34G obtained by irradiating three channels ch1 within a radius of 5 ° in the nasal visual field with light in time series. Secondary nuclear nasal visual field signal 34A is generated. The calculation unit 34 is obtained by, for example, the light stimulation unit 31 sequentially performing four types of light irradiation (light stimulation) as shown in FIG. 4 on the channel ch corresponding to the nasal visual field (first visual field). The secondary nuclear nasal visual field signal 34A is generated using the four types of skin potential signals 34G. For example, the calculation unit 34 includes a first signal in which a positive sign is added to the skin potential signal 34G generated when light irradiation is performed at both times t1 and t2, and light irradiation is performed at time t1 and at time t2. A second signal with a negative sign added to the skin potential signal 34G generated when light irradiation is not performed, and generated when light irradiation is not performed at time t1 and light irradiation is performed at time t2. The third signal with a negative sign added to the skin potential signal 34G and the first signal with a positive sign added to the skin potential signal 34G generated when no light irradiation was performed at both times t1 and t2 are added. By combining, a secondary nuclear nasal visual field signal 34A is generated.

The calculation unit 34 generates a secondary nuclear ear-side visual field signal 34B (second potential signal) by using the potential signal in the ear-side visual field (second visual field) of the generated skin potential signal 34G. For example, as shown in FIG. 5, the calculation unit 34 uses the skin potential signal 34G obtained by irradiating three channels ch2 within a radius of 5 ° in the ear side visual field with light in time series. The secondary nucleus ear side visual field signal 34B is generated. The calculation unit 34 is obtained by, for example, the light stimulation unit 31 sequentially performing four types of light irradiation (light stimulation) as shown in FIG. 4 on the channel ch corresponding to the ear side visual field (second visual field). The secondary nuclear auditory visual field signal 34B is generated using the four types of cutaneous potential signals 34G. For example, the calculation unit 34 includes a first signal in which a positive sign is added to the skin potential signal 34G generated when light irradiation is performed at both times t1 and t2, and light irradiation is performed at time t1 and at time t2. A second signal with a negative sign added to the skin potential signal 34G generated when light irradiation is not performed, and generated when light irradiation is not performed at time t1 and light irradiation is performed at time t2. The third signal with a negative sign added to the skin potential signal 34G and the first signal with a positive sign added to the skin potential signal 34G generated when no light irradiation was performed at both times t1 and t2 are added. By combining, the secondary nucleus ear side visual field signal 34B is generated.

The calculation unit 34 outputs the generated secondary nuclear nasal visual field signal 34A and secondary nuclear ear visual field signal 34B to the control unit 10.

The learning model 40 has, for example, neural networks 41 and 42 and a similarity determination unit 43, as shown in FIG. The neural networks 41 and 42 correspond to a specific example of the learning model.

Both the neural networks 41 and 42 have the same parameters. In this case, when the secondary nuclear nasal visual field signal 34A is input, the neural network 41 abstracts the input secondary nuclear nasal visual field signal 34A, and determines the similarity of the abstracted data 41A obtained thereby. Output to unit 43. When the secondary nuclear ear side visual field signal 34B is input, the neural network 42 abstracts the input secondary nuclear ear side visual field signal 34B, and the abstracted data 42A obtained thereby is used in the similarity determination unit 43. Output.

The similarity determination unit 43 calculates the similarity of the abstract data 41A and 42A input from the neural networks 41 and 42. Based on the calculation result (similarity), the similarity determination unit 43 receives two secondary nuclear signals (secondary nuclear nasal visual field signal 34A, secondary nuclear ear visual field signal) input to the neural networks 41 and 42. It is determined whether or not 34B) are similar to each other. When the similarity is expressed numerically, the similarity determination unit 43 determines whether or not the similarity exceeds a predetermined threshold value, thereby inputting two secondary nuclear signals input to the neural networks 41 and 42. It is determined whether or not (secondary nuclear nasal visual field signal 34A, secondary nuclear ear side visual field signal 34B) is similar to each other. When the similarity determination unit 43 determines that the two secondary nuclear signals (secondary nuclear nasal visual field signal 34A and secondary nuclear ear visual field signal 34B) input to the neural networks 41 and 42 are similar to each other. To determine that the eye to be inspected suffers from glaucoma. When the similarity determination unit 43 determines that the two secondary nuclear signals (secondary nuclear nasal visual field signal 34A and secondary nuclear ear visual field signal 34B) input to the neural networks 41 and 42 are not similar to each other. To determine that the eye to be inspected does not suffer from glaucoma. The similarity determination unit 43 outputs the determination result 43A obtained by the above determination to the control unit 10.

The similarity determination unit 43 executes the above-mentioned calculation of similarity every time abstract data 41A, 42A is input from the neural networks 41, 42.

In this case, it is assumed that there is some correlation between the plurality of secondary nuclear nasal visual field signals 34A input to the neural network 41. The plurality of secondary nuclear nasal visual field signals 34A input to the neural network 41 are, for example, a time axis extracted from the secondary nuclear signal D1 having a predetermined correlation with the potential fluctuation generated in the retina of the eye to be inspected by visual stimulation. Corresponds to a plurality of secondary nuclear section signals that are different from each other in (section). The plurality of secondary nuclear nasal visual field signals 34A have, for example, a secondary nuclear signal D1 having a predetermined correlation with the potential fluctuation generated in the retina of the eye to be inspected by visual stimulation while sliding a window of a predetermined size on the time axis. Corresponds to a plurality of secondary nuclear section signals having different time axes (sections) obtained by cutting out the above in a window. In each secondary nuclear section signal, the lengths of the time axes (sections) are equal to each other, and the start time and end time of the time axes (sections) are different from each other.

At this time, when the control unit 10 acquires the secondary nuclear nasal visual field signal 34A (first potential signal) corresponding to the above-mentioned secondary nuclear signal D1 from the arithmetic unit 34, the acquired secondary nuclear nasal visual field signal A plurality of secondary nuclear section signals (first section signals) different from each other on the time axis (section) are extracted from 34A and output to the learning model 40. The control unit 10 cuts out the secondary nuclear nasal visual field signal 34A in the window while sliding a window of a predetermined size on the time axis, so that the control unit 10 has a plurality of secondary nuclear sections having different time axes (sections). Get the signal. The control unit 10 corresponds to a specific example of the "extraction unit" of the present invention.

Further, it is assumed that there is some correlation between the plurality of secondary nucleus ear side visual field signals 34B input to the neural network 42. At this time, the plurality of secondary nuclear ear side visual field signals 34B are extracted from the secondary nuclear signal D2 having a predetermined correlation with the potential fluctuation generated in the retina of the eye to be inspected by visual stimulation, for example, on the time axis (section). It corresponds to a plurality of secondary nuclear section signals that are different from each other. The plurality of secondary nuclear visual field signals 34B have, for example, a secondary nuclear signal D2 having a predetermined correlation with the potential fluctuation generated in the retina of the eye to be inspected by visual stimulation while sliding a window of a predetermined size on the time axis. Corresponds to a plurality of secondary nuclear section signals having different time axes (sections) obtained by cutting out the above in a window. In each secondary nuclear section signal, the lengths of the time axes (sections) are equal to each other, and the start time and end time of the time axes (sections) are different from each other.

At this time, when the control unit 10 acquires the secondary nuclear ear side visual field signal 34B (second potential signal) corresponding to the above-mentioned secondary nuclear signal D2 from the calculation unit 34, the control unit 10 obtains the acquired secondary nuclear ear side visual field signal. A plurality of secondary nuclear section signals (second section signals) having different time axes (sections) from each other are extracted from 34B and output to the learning model 40. For example, the control unit 10 slides a window of a predetermined size on the time axis and cuts out the secondary nucleus ear side visual field signal 34B in the window, so that a plurality of secondary nuclear sections having different time axes (sections) are used. Get the signal. The control unit 10 corresponds to a specific example of the "extraction unit" of the present invention.

The similarity determination unit 43 derives the similarity between the plurality of first section signals extracted by the control unit 10 and the plurality of second section signals extracted by the control unit 10 for each same section, and derives the derived sections. The visual function of the eye to be examined is evaluated based on the degree of similarity for each. The similarity determination unit 43 determines whether or not the secondary nuclear nasal visual field signal 34A and the secondary nuclear ear visual field signal 34B are similar to each other based on a plurality of similarities derived by the number of sections. When the number of sections is n, the similarity determination unit 43, for example, when a predetermined number of n similarity exceeds a predetermined threshold value, the secondary nucleus nasal visual field signal 34A and the secondary nucleus. It is determined that the visual field signals 34B on the ear side are similar to each other, and it is determined that the eye to be inspected has glaucoma. In the similarity determination unit 43, for example, when a predetermined number of n similarity is equal to or less than a predetermined threshold value, the secondary nuclear nasal visual field signal 34A and the secondary nuclear ear visual field signal 34B are similar to each other. It is judged that there is no glaucoma, and the eye to be examined is not suffering from glaucoma.

In the learning mode, a plurality of secondary nuclear nasal visual field signals 34A when the eye to be inspected is normal are sequentially input to the neural network 41 as explanatory variables, and when the eye to be inspected is normal to the neural network 42. The plurality of secondary nuclear auditory visual field signals 34B of the above are sequentially input as explanatory variables. At this time, a plurality of abstract data 41A for which low similarity is output by the similarity determination unit 43 are sequentially input to the neural network 41 as objective variables, and the similarity determination unit 43 is input to the neural network 42. A plurality of abstract data 42A for which a low degree of similarity is output in the above are sequentially input as objective variables.

In the learning mode, a plurality of secondary nuclear nasal visual field signals 34A when the eye to be inspected suffers from glaucoma are sequentially input to the neural network 41 as explanatory variables, and the eye to be inspected has glaucoma in the neural network 42. A plurality of secondary nuclear auditory visual field signals 34B when suffering from glaucoma are sequentially input as explanatory variables. At this time, a plurality of abstract data 41A for which high similarity is output by the similarity determination unit 43 are sequentially input to the neural network 41 as objective variables, and the similarity determination unit 43 is input to the neural network 42. A plurality of abstract data 42A for which a high degree of similarity is output in the above are sequentially input as objective variables.

Next, a specific method for acquiring a plurality of secondary nuclear section signals (first section signals) from the secondary nuclear nasal visual field signal 34A and a plurality of secondary nuclear section signals from the secondary nuclear ear side visual field signal 34B. A specific method for acquiring (second section signal) will be described.

First, in the two secondary nuclear signals (secondary nuclear nasal visual field signal 34A, secondary nuclear ear visual field signal 34B), the value of the waveform data for 80 ms is normalized so as to be in the range of -1 to 1. Cut out the section from 7.5 ms to 63.3 ms. This is because it is considered that meaningful waveform data of the biological reaction is obtained only in the range of 7.5 ms to 63.3 ms based on the reaction rate of the living body.

Next, 32.5 ms, which is about 58% of the obtained section (55.8 ms), is set as the window size, and while sliding a window of this size on the time axis, the obtained section (55.8 ms) of the obtained section (55.8 ms) By cutting out the waveform data 34K obtained by normalizing the secondary nuclear nasal visual field signal 34A with a window, 29 waveform data Dais (i = 1 to 29) are obtained. The 29 waveform data Dais are, for example, as shown in FIG. 12, the waveform data Da1 of the section S1 of 7.5 ms to 40.0 ms, the waveform data Da2 of the section S2 of 8.3 ms to 40.8 ms, and so on. This is the waveform data Da29 in the section S29 from 30.8 ms to 63.3 ms.

Similarly, 32.5 ms, which is about 58% of the obtained section (55.8 ms), is set as the window size, and while sliding a window of this size on the time axis, the obtained section (55.8 ms) of the obtained section (55.8 ms) By cutting out the waveform data 34L obtained by normalizing the secondary nuclear ear side visual field signal 34B with a window, 29 waveform data Dbi (i = 1 to 29) are obtained. The 29 waveform data Dbi are, for example, as shown in FIG. 13, the waveform data Db1 of the section S1 of 7.5 ms to 40.0 ms, the waveform data Db2 of the section S2 of 8.3 ms to 40.8 ms, and so on. ... It is the waveform data Db29 of the section S29 of 30.8 ms to 63.3 ms.

The maximum slide amount ΔT (that is, the amount of deviation between the section Si and the section Si + 1 on the time axis) is 7.5 ms. The smaller the slide amount ΔT, the more versatile the neural networks 41 and 42 can be.

In the learning mode, two waveform data Dai and Dbi with the same time axis (section Si) obtained from the same eye are input to the neural networks 41 and 42 as explanatory variables, and correspond to the two waveform data Dai and Dbi. Two abstract data 41Ai and 42Ai are input as objective variables. At this time, in the learning mode, two waveform data Dai and Dbi when the eye to be examined is normal are input to the neural networks 41 and 42 as explanatory variables, and two waveform data Dai when the eye to be examined is normal. , Two abstract data 41Ai and 42Ai corresponding to Dbi are input as objective variables.

[effect]
Next, the effect of the visual function evaluation device 1 according to the present embodiment will be described.

In the present embodiment, the secondary nuclear nasal visual field signal 34A (first potential signal) in the nasal visual field (first visual field) is generated based on the detected potential signal generated in the retina of the eye to be inspected by the visual stimulus. At the same time, a secondary nuclear ear-side visual field signal 34B (second potential signal) in the auditory visual field (second visual field) is generated. Here, the secondary nuclear nasal visual field signal 34A and the secondary nuclear ear visual field signal 34B change according to the visual function of the eye to be inspected. For example, in the eye of a healthy subject, the secondary nuclear nasal visual field signal 34A and the secondary nuclear auditory visual field signal 34B show asymmetry in amplitude ratio, and in the eye of a glaucoma patient, the secondary nuclear nasal side. The visual field signal 34A and the secondary nuclear auditory visual field signal 34B significantly eliminate asymmetry in amplitude ratio. As a result, the visual function of the eye to be inspected (for example, evaluation of glaucoma in the eye to be inspected) can be evaluated based on the visual field signal 34A on the nasal side of the secondary nucleus and the visual field signal 34B on the ear side of the secondary nucleus. For example, the result of the evaluation of glaucoma of the eye to be inspected) can be displayed on the display unit 50. Therefore, it is possible to accurately evaluate the visual function of the eye to be examined (for example, the evaluation of glaucoma of the eye to be inspected) using the retinal potential.

In the present embodiment, the secondary nuclear nasal visual field signal 34A (first potential signal) in the nasal visual field (first visual field) is generated based on the detected potential signal generated in the retina of the eye to be inspected by the visual stimulus. At the same time, a secondary nuclear ear-side visual field signal 34B (second potential signal) in the auditory visual field (second visual field) is generated. Here, the secondary nuclear nasal visual field signal 34A and the secondary nuclear ear visual field signal 34B change according to the visual function of the eye to be inspected. For example, in the eye of a healthy subject, the secondary nuclear nasal visual field signal 34A and the secondary nuclear auditory visual field signal 34B show asymmetry in amplitude ratio, and in the eye of a glaucoma patient, the secondary nuclear nasal side. The visual field signal 34A and the secondary nuclear auditory visual field signal 34B significantly eliminate asymmetry in amplitude ratio. Thereby, the visual function of the eye to be inspected can be evaluated (for example, the evaluation of glaucoma in the eye to be inspected) based on the visual field signal 34A on the nasal side of the secondary nucleus and the visual field signal 34B on the ear side of the secondary nucleus. Therefore, it is possible to accurately evaluate the visual function of the eye to be inspected (for example, the result of evaluation of glaucoma in the eye to be inspected) using the retinal potential.

In the present embodiment, a plurality of secondary nuclear section signals (first section signals) having different time axes (sections) are extracted from the secondary nuclear nasal visual field signal 34A, and are extracted from the secondary nuclear ear side visual field signal 34B. , Multiple secondary nuclear section signals (second section signals) different from each other on the time axis (section) are extracted, and the extracted multiple secondary nuclear section signals (first section signals) and a number of secondary nuclear section signals The result of the evaluation of the visual function of the eye to be inspected based on (the second section signal) is displayed on the display unit 50. As a result, the visual function of the eye to be inspected can be evaluated based on the secondary nuclear nasal visual field signal 34A and the secondary nuclear ear-side visual field signal 34B. ) Can be displayed on the display unit 50. Therefore, it is possible to accurately evaluate the visual function of the eye to be examined (for example, the evaluation of glaucoma of the eye to be inspected) using the retinal potential.

In the present embodiment, a plurality of secondary nuclear section signals (first section signals) having different time axes (sections) are extracted from the secondary nuclear nasal visual field signal 34A, and are extracted from the secondary nuclear ear side visual field signal 34B. , Multiple secondary nuclear section signals (second section signals) different from each other on the time axis (section) are extracted, and the extracted multiple secondary nuclear section signals (first section signals) and a number of secondary nuclear section signals The visual function of the eye to be inspected is evaluated based on (second section signal). Therefore, it is possible to accurately evaluate the visual function of the eye to be inspected using the retinal potential.

In the present embodiment, a plurality of secondary nuclear section signals (first section signals) having different time axes (sections) are extracted from the secondary nuclear nasal visual field signal 34A, and are extracted from the secondary nuclear ear side visual field signal 34B. , Multiple secondary nuclear section signals (second section signals) different from each other on the time axis (section) are extracted, and the extracted multiple secondary nuclear section signals (first section signals) and a number of secondary nuclear section signals The result of the evaluation of the visual function of the eye to be inspected based on (the second section signal) is displayed on the display unit 50. As a result, the visual function of the eye to be inspected can be evaluated based on the secondary nuclear nasal visual field signal 34A and the secondary nuclear ear visual field signal 34B, and the evaluation result can be displayed on the display unit 50. Therefore, it is possible to accurately evaluate the visual function of the eye to be inspected using the retinal potential.

In the present embodiment, a plurality of secondary nuclear section signals (first section signals) having different time axes (sections) extracted from the secondary nuclear nasal visual field signal 34A and the secondary nuclear ear side visual field signal 34B are used. The degree of similarity with the extracted plurality of secondary nuclear section signals (second section signals) having different time axes (sections) is derived for each section of the same time, and based on the degree of similarity for each derived section, the subject is covered. The visual function of the optometry is evaluated. Such an evaluation method is particularly effective in evaluating waveform data obtained by using a measurement method in which the signal level and signal displacement can be reduced, and has an affinity for machine learning. In the present embodiment, a measurement method using skin contact electrodes, which can reduce the signal level and signal displacement, is adopted, and the above-mentioned plurality of secondary nuclear section signals (first section signals) are applied to the learning model 40. ) And the above-mentioned plurality of secondary nuclear section signals (second section signals) are input to evaluate the visual function of the eye to be inspected. Therefore, even when the measurement method using the electrodes of skin contact is used, the visual function of the eye to be inspected can be accurately evaluated.

<3. Modification example>
[Modification example A]
In the above embodiment, the parameters of the neural networks 41 and 42 may be different from each other. At this time, not only the secondary nuclear nasal visual field signal 34A but also the maximum value 34C and the minimum value 34D of the waveform in the secondary nuclear nasal visual field signal 34A may be input to the neural network 41. Not only the secondary nuclear ear side visual field signal 34B but also the maximum value 34E and the minimum value 34F of the waveform in the secondary nuclear ear side visual field signal 34B may be input to the neural network 42.

When the secondary nuclear nasal visual field signal 34A, the maximum value 34C and the minimum value 34D are input, the neural network 41 uses the input secondary nuclear nasal visual field signal 34A, the maximum value 34C and the minimum value 34D. The secondary nuclear nasal visual field signal 34A is abstracted, and the abstracted data 41A obtained thereby is output. When the secondary nuclear ear side visual field signal 34B, the maximum value 34E and the minimum value 34F are input, the neural network 42 uses the input secondary nuclear ear side visual field signal 34B, the maximum value 34E and the minimum value 34F. The secondary nuclear ear side visual field signal 34B is abstracted, and the abstracted data 42A obtained thereby is output. In this case, even if the characteristics of the two secondary nuclear signals (secondary nuclear nasal visual field signal 34A, secondary nuclear ear visual field signal 34B) are not the same as each other, the visual field of the eye to be inspected It is possible to evaluate the function.

Further, in this modification, the neural network 45 may be provided instead of the similarity determination unit 43. The neural network 45 corresponds to a specific example of the learning model. When the two abstract data 41A and 42A are input, the neural network 45 discriminates whether or not the eye to be inspected suffers from glaucoma, and outputs the discrimination result 45A to the control unit 10. Even in this case, it is possible to evaluate the visual function of the eye to be inspected as in the above embodiment.

[Modification B]
In the above embodiment and its modifications, the learning model 40 determines or discriminates whether or not the eye to be inspected suffers from glaucoma. However, in the above-described embodiment and its modification, the learning model 40 determines or discriminates not only the presence or absence of glaucoma but also the degree of glaucoma (for example, before visual field abnormality, mild, moderate, severe). It may be. However, in this case, it is necessary to learn about the degree of glaucoma (for example, before the visual field, mild, moderate, and severe) with respect to the learning model 40. Further, in the above-described embodiment and its modification, the learning model 40 may be adapted to determine or discriminate an eye disease different from glaucoma. However, in this case, it is necessary for the learning model 40 to also learn about eye diseases different from glaucoma.

[Modification C]
In the above embodiment and its modifications, the Seki electrode 32 and the Seki electrode 33 are in contact with the skin around the eye. However, in the above-described embodiment and its modifications, the Seki electrode 32 and the Seki electrode 33 may be provided in the contact lens and configured to come into direct contact with the eyeball. Even in this case, the same effect as that of the above-described embodiment and its modification can be obtained.

<4. Second Embodiment>
[Constitution]
FIG. 15 shows an example of a schematic configuration of the visual function evaluation system 2 according to the second embodiment of the present invention. The visual function evaluation system 2 includes, for example, a visual function evaluation device 1 and a server device 3, as shown in FIG. The visual function evaluation device 1 and the server device 3 are connected via an external network 4. The visual function evaluation device 1 has a communication unit 70 that communicates with the server device 3 via the external network 4. In the present embodiment, the learning model 40 is deleted from the visual function evaluation device 1, and the server device 3 has the learning model 40.

The external network 4 is, for example, a network that communicates using a communication protocol (TCP / IP) that is standardly used on the Internet. The external network 4 may be, for example, a secure network that communicates using a communication protocol unique to the network. The connection between the external network 4 and the visual function evaluation device 1 and the server device 3 may be, for example, a wired LAN (Local Area Network) such as Ethernet, a wireless LAN such as Wi-Fi, or a mobile phone line. And so on.

In this embodiment, the learning model 40 is provided in the server device 3 on the external network 4. As a result, by connecting the plurality of visual function evaluation devices 1 to the external network 4, the individual visual function evaluation devices 1 can share the learning model 40. Therefore, as compared with the case where the learning model 40 is provided in each visual function evaluation device 1, the time and effort required for learning the learning model 40 can be reduced.

Although the present invention has been described above with reference to a plurality of embodiments and modifications thereof, the present invention is not limited to the embodiments and the like, and various modifications are possible. The effects described in this specification are merely examples. The effects of the present invention are not limited to the effects described herein. The present invention may have effects other than those described herein.

1 ... Visual function evaluation device, 2 ... Visual function evaluation system, 3 ... Server device, 4 ... External network, 10 ... Control unit, 20 ... Memory, 21 ... Program, 30 ... Retinal potential measurement unit, 31 ... Light stimulation unit, 32 ... Seki electrode, 32A, 33A ... Potential signal, 33 ... Unrelated electrode, 34 ... Calculation unit, 34A ... Secondary nuclear nasal visual field signal, 34B ... Secondary nuclear ear side visual field signal, 34C, 34E ... Maximum value, 34D, 34F ... Minimum value, 34G ... Skin potential signal, 34K, 34L ... Waveform data, 40 ... Learning model, 41, 42, 45 ... Neural network, 41A, 41Ai, 42A, 42Ai ... Abstract data, 50 ... Display unit , 60 ... Input unit, 100 ... Eye, ch, ch1, ch2 ... Channel, Da1, Da2, Dai, Da29, Db1, Db2, Dbi, Db29 ... Wave data, S1, S2, Si, Si + 1, S29 ... Section, t1 , T2 ... time, ΔT ... slide amount.

Claims (13)

A detector that detects the potential signal generated in the retina of the eye to be inspected by visual stimulation,
Based on the potential signal detected by the detection unit, a generation unit that generates a first potential signal in the first visual field and a second potential signal in the second visual field, and a generation unit.
A visual function evaluation device including a display unit that displays the result of evaluation of the visual function of the eye to be inspected based on the first potential signal and the second potential signal generated by the generation unit. A plurality of first section signals different from each other in the section are extracted from the first potential signal generated by the generation unit, and a plurality of second sections different from each other in the section are extracted from the second potential signal generated by the generation unit. It also has an extraction unit that extracts signals.
The display unit evaluates the visual function of the eye to be inspected based on the plurality of first section signals extracted by the extraction unit and the plurality of second section signals extracted by the extraction unit. The visual function evaluation device according to claim 1, wherein the result is displayed. The first visual field is the nasal visual field.
The visual function evaluation device according to claim 2, wherein the second visual field is an ear-side visual field. The visual function evaluation device according to claim 2 or 3, wherein the display unit displays the result of the evaluation of glaucoma of the eye to be inspected as a result of the evaluation of the visual function of the eye to be inspected. An evaluation unit for evaluating the visual function of the eye to be inspected is further provided based on the plurality of first section signals extracted by the extraction unit and the plurality of second section signals extracted by the extraction unit.
The visual function evaluation device according to any one of claims 2 to 4, wherein the display unit displays the result of evaluation by the evaluation unit. The evaluation unit derives and derives the similarity between the plurality of first section signals extracted by the extraction unit and the plurality of second section signals extracted by the extraction unit for each of the same sections. The visual function evaluation device according to claim 5, which evaluates the visual function of the eye to be inspected based on the similarity for each section. The visual function evaluation device according to claim 5 or 6, wherein the evaluation unit includes a learning model. A detector that detects the potential signal generated in the retina of the eye to be inspected by visual stimulation,
Based on the potential signal detected by the detection unit, a generation unit that generates a first potential signal in the first visual field and a second potential signal in the second visual field, and a generation unit.
An evaluation unit for evaluating the visual function of the eye to be inspected based on the first potential signal and the second potential signal generated by the generation unit is provided.
Visual function evaluation device. A plurality of first section signals different from each other in the section are extracted from the first potential signal generated by the generation unit, and a plurality of second sections different from each other in the section are extracted from the second potential signal generated by the generation unit. It also has an extraction unit that extracts signals.
Claim that the evaluation unit evaluates the visual function of the eye to be inspected based on the plurality of first section signals extracted by the extraction unit and the plurality of second section signals extracted by the extraction unit. 8. The visual function evaluation device according to 8. The evaluation unit derives and derives the similarity between the plurality of first section signals extracted by the extraction unit and the plurality of second section signals extracted by the extraction unit for each of the same sections. The visual function evaluation device according to claim 9, which evaluates the visual function of the eye to be inspected based on the similarity for each section. The first visual field is the nasal visual field.
The visual function evaluation device according to any one of claims 8 to 10, wherein the second visual field is an ear-side visual field. The visual function evaluation device according to any one of claims 8 to 11, wherein the evaluation unit evaluates glaucoma of the eye to be inspected as an evaluation of the visual function of the eye to be inspected. The visual function evaluation device according to any one of claims 8 to 12, wherein the evaluation unit includes a learning model.

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