JP2017018420A - Tinnitus patient discrimination systems, tinnitus patient discrimination method, and tinnitus patient discrimination program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a tinnitus patient discrimination system, a tinnitus patient discrimination method, and a tinnitus patient discrimination program.SOLUTION: A tinnitus patient discrimination system is a system for discriminating a tinnitus patient from a non-tinnitus patient, and comprises: a storage part for storing brain wave data having a pattern unique to the tinnitus patient; an electroencephalograph for measuring a brain wave of a subject; and a determination part for determining whether or not the subject is the tinnitus patient on the basis of the brain wave data of the subject measured by the electroencephalograph, and the brain wave data stored in the storage part.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a tinnitus patient discrimination system, a tinnitus patient discrimination method, and a tinnitus patient discrimination program that can discriminate whether or not a subject is a tinnitus patient, particularly a subjective tinnitus patient that cannot be recognized by surrounding people.

  Tinnitus is a phenomenon in which sound can be heard in an environment where no sound source exists outside the body. In many cases, it occurs with some illness, but at present, the mechanism of tinnitus has not been elucidated. In order to cure tinnitus, it is necessary to accurately diagnose the disease or cause that causes tinnitus and to treat it according to each cause. In a clinical setting, a doctor examines the state of tinnitus (for example, the size and height of the tinnitus) of a tinnitus patient in order to diagnose a disease, determine a treatment policy, and grasp the course of treatment.

  In the conventional method, a pitch match test is performed to check the level of tinnitus, and a loudness balance test is performed to check the level of tinnitus. The pitch match test is a method in which a patient is made to listen to various sounds using an inspection device, and a sound having a height closest to his / her tinnitus is selected. In this inspection, generally about 11 kinds of sounds having different heights are used. In the loudness balance test, the pitch of the sound checked by the pitch match test is used. The volume of the sound emitted by the test device is changed with the pitch kept constant, and the patient is made to select a sound having a volume closest to his / her tinnitus.

  Such an inspection makes it possible to grasp the height and magnitude of the tinnitus. The reason why the pitch match inspection is performed first is to consider the nature of human sensitivity to sound. Human sensitivity to sound has the property that it feels as if the sound volume is different when listening to sounds of the same magnitude but different height. Therefore, in order to check the loudness of the tinnitus, it is necessary to check the pitch of the sound first. By performing pitch match inspection and loudness balance inspection, it is possible to more accurately capture how the tinnitus sounds.

  Conventionally, as a determination device using an electroencephalogram, an electroencephalograph that measures a human electroencephalogram, a calculation unit, and a CMAC classifier are provided, and the human mental state (for example, emotions and so on) is analyzed by electroencephalogram analysis. Has been proposed that can determine the feelings and comfort levels of three or more classes.

JP 2011-188961 A

  However, in the conventional method, there is a problem that if the patient cannot determine which sound his / her tinnitus sound is close to, how to hear the tinnitus sound cannot be grasped. In addition, it is troublesome for the patient and ambiguity due to the subjective evaluation of the patient is a problem. For this reason, it is required that tinnitus patients can be identified simply and objectively.

  An object of the present invention is to provide a tinnitus patient discrimination system, a tinnitus patient discrimination method, and a program that can easily and objectively discriminate a tinnitus patient.

  In order to solve the above problems, the tinnitus patient discrimination system according to the present invention is a tinnitus patient discrimination system for discriminating between tinnitus patients and non-tinnitus patients, in which electroencephalogram data having a pattern specific to the tinnitus patient is stored. Determining whether or not the subject is a tinnitus patient based on the electroencephalograph that measures the brain wave of the subject, the electroencephalogram data of the subject measured by the electroencephalograph, and the electroencephalogram data stored in the storage unit A part.

  According to the tinnitus patient discriminating system according to the present invention, since it is discriminated whether or not it is a tinnitus patient based on an electroencephalogram, it is possible to easily discriminate the tinnitus patient. In addition, since it is determined whether or not the subject is a tinnitus patient based on the electroencephalogram data having a pattern specific to the tinnitus patient stored in the storage unit and the electroencephalogram data of the subject measured by an electroencephalograph, the objective is It is possible to discriminate tinnitus patients.

  The tinnitus patient discrimination system according to the present invention includes an estimation unit that estimates the frequency of the tinnitus of the subject based on the brain wave data of the subject measured by an electroencephalograph and the electroencephalogram data stored in the storage unit. According to the tinnitus patient discrimination system according to the present invention, the frequency of tinnitus of a tinnitus patient can be estimated.

  The estimation unit of the tinnitus patient discrimination system according to the present invention estimates the frequency of the tinnitus of the subject by comparing the electroencephalogram data measured by an electroencephalograph with the electroencephalogram data stored in the storage unit by pattern matching. For this reason, the frequency of the subject's tinnitus can be estimated more accurately.

  The electroencephalogram data stored in the storage unit of the tinnitus patient discrimination system according to the present invention allows a plurality of tinnitus patients and a plurality of non-tinnitus patients to hear a single frequency sound while changing the frequency step by step. This is a result of extracting electroencephalogram data of a pattern peculiar to tinnitus patients from the electroencephalogram measured each time it is changed.

  According to the tinnitus patient discrimination system according to the present invention, the electroencephalogram data having a pattern specific to the tinnitus patient is extracted from the electroencephalogram data of the plurality of tinnitus patients and the plurality of non-tinnitus patients, and stored in the storage unit. It is possible to discriminate typical tinnitus patients and estimate the frequency of tinnitus.

  In the storage unit of the tinnitus patient discrimination system according to the present invention, the frequency of tinnitus and brain wave data having a pattern specific to the frequency are stored in association with each other. Therefore, it is possible to easily and objectively estimate the frequency of tinnitus of a tinnitus patient.

  The tinnitus patient discrimination system according to the present invention further includes a Fourier transform unit that Fourier transforms an electroencephalogram measured by an electroencephalograph, and the electroencephalogram data stored in the storage unit is electroencephalogram data after Fourier transform.

  According to the tinnitus patient discrimination system according to the present invention, since the brain wave is Fourier-transformed, it is easy to detect the characteristics of the electroencephalogram data of the tinnitus patient. Therefore, it is possible to objectively discriminate tinnitus patients and estimate the frequency of tinnitus.

  In order to solve the above problems, the tinnitus patient discrimination method of the present invention is a tinnitus patient discrimination method for discriminating between tinnitus patients and non-tinnitus patients, the step of measuring the subject's brain waves with an electroencephalograph, And determining whether or not the subject is a tinnitus patient based on the electroencephalogram data of the tinnitus patient and the non-tinnitus patient stored in the storage unit and the electroencephalogram data of the subject measured by an electroencephalograph.

  In order to solve the above problems, the tinnitus patient discrimination program of the present invention causes a computer to execute each step in the above-described method.

1 is a schematic diagram of a tinnitus patient identification system according to an embodiment. It is a figure which shows the measurement position of the electroencephalogram defined by the international 10-20 method. It is a block diagram of a data processor. It is a figure which shows an example of electroencephalogram data (frequency spectrum). It is a flowchart which shows operation | movement of the tinnitus patient discrimination system which concerns on embodiment. It is a flowchart which shows operation | movement of the tinnitus patient discrimination system which concerns on embodiment.

  Tinnitus can be classified into two types depending on whether or not the surrounding person can recognize it. Tinnitus that can be recognized by the surrounding people is called objective tinnitus, and tinnitus that cannot be recognized is called subjective tinnitus. In objective tinnitus, the sound of blood and muscle spasms are recognized. In subjective tinnitus, continuous single-frequency sounds and noise are perceived. In the present embodiment, among the two types of tinnitus, subjective tinnitus is handled, and in particular, single-frequency sound tinnitus is handled. Hereinafter, embodiments of the present invention will be described with reference to the drawings.

  FIG. 1 is a configuration diagram showing an outline of a tinnitus patient discrimination system 1 according to an embodiment of the present invention. The tinnitus patient discrimination system 1 includes a headset device 10 and a data processing device 20. The headset device 10 includes an electroencephalograph and is set on the head of the subject U to acquire the brain wave data of the subject U. The data processing device 20 processes the electroencephalogram data acquired by the headset device 10 and determines whether or not the subject U is a tinnitus patient. Further, the data processing device 20 estimates the frequency of the tinnitus of the subject U. The headset device 10 and the data processing device 20 are connected by a wireless or wired network.

  The headset device 10 includes a pair or a plurality of electrodes 11. The electrode 11 is attached to the head or ear of the subject U and detects the potential of the head of the subject U. In addition, although an electroencephalogram shows a different waveform depending on a part in the brain, in this embodiment, it is preferable to install an electrode so as to measure the electroencephalogram of the part of Fp1 defined by the international 10-20 method (FIG. 2 shows an international 10- The measurement position of the electroencephalogram determined by the 20 method is shown). The headset device 10 amplifies the potential of the head of the subject U detected by the electrodes and outputs it in time series.

  In this headset device 10, since the electrode 11 is attached to the ear and forehead of the subject U, it is not necessary to apply a conductive gel to the hair like an electroencephalograph used by covering the head with the electrode net, Can be easily installed. For this reason, it has the advantage that the subject U can wear it in a relaxed state, and it is difficult for noise to enter an immediately determined brain wave.

  The data processing device 20 includes an input / output device such as a keyboard, a mouse, and a touch panel, a calculation unit such as a CPU (Central Processing Unit), and a storage device such as a RAM (Random Access Memory) and a ROM (read only memory), The computer system includes a display device such as an LCD (Liquid Crystal Display), a speaker that outputs sound, and the like.

  The data processing device 20 can be realized by executing a program stored in a storage device of a computer system by an arithmetic unit. The storage device and the calculation unit may be incorporated in a physically separated device such as a server or a cloud connected via a communication line.

  FIG. 3 is a configuration diagram of the data processing device 20. The data processing device 20 includes a storage unit 21, a reception unit 22, a filter unit 23, a Fourier transform unit 24, a determination unit 25, an estimation unit 26, an operation reception unit 27, and a display unit 28.

  The storage unit 21 is a storage medium such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive). The storage unit 21 may be an external server. The storage unit 21 stores electroencephalogram data (electroencephalogram pattern) for discriminating tinnitus patients and electroencephalogram data (electroencephalogram patterns) for estimating the frequency (height) of tinnitus sounds of tinnitus patients.

More specifically, the storage unit 21 stores brain wave data extracted by the following method.
(1) A plurality of tinnitus patients and a plurality of non-tinnitus patients are made to listen to a single frequency sound while changing the frequency stepwise, and the brain waves are measured each time the frequency is changed.
(2) After removing the noise component from the acquired electroencephalogram data with a filter, Fourier transform is performed to obtain a frequency spectrum indicating the relationship between frequency and intensity. In order to improve the accuracy of discrimination and estimation, the average of the frequency spectrum for each patient And calculate the standard deviation.
(3) Electroencephalogram data showing a pattern peculiar to the tinnitus patient is extracted from the electroencephalogram data for which the average and standard deviation are calculated.

  FIG. 4 is an example of frequency spectrum data extracted for discrimination between tinnitus patients and non-tinnitus patients stored in the storage unit 21. 4A shows a case where the vertical axis is an average amplitude spectrum, and FIG. 4B shows a case where the vertical axis is a standard deviation spectrum. As shown in FIG. 4, it can be seen that there is a difference in the vicinity of 10 Hz (5 to 15 Hz) between the brain waves (frequency spectrum) of the tinnitus patient and the non-tinnitus patient.

  That is, the spectral intensity of tinnitus patients near 10 Hz (5 to 15 Hz) decreases almost monotonously as the frequency (horizontal axis) increases and does not have a peak near 9 to 10 Hz. ) Has a peak in the vicinity of 9 to 10 Hz. From this, the subject is a tinnitus patient by comparing the pattern of the electroencephalogram data (frequency spectrum) in the vicinity of 10 Hz (5 to 15 Hz) of the obtained subject U with the pattern of the electroencephalogram data (frequency spectrum) shown in FIG. It can be determined whether there is.

  In addition, in the storage unit 21, for estimating the frequency (height) of the tinnitus of the tinnitus patient, for each frequency of the tinnitus, an electroencephalogram pattern that appears specifically in the tinnitus patient who can hear the tinnitus of the frequency is associated. It is remembered. The frequency (height) of the tinnitus of the tinnitus patient can be estimated by comparing the brain wave pattern stored for each frequency of the tinnitus and the brain wave pattern of the subject. It should be noted that when extracting electroencephalogram data, the electroencephalogram data is extracted so that the frequency of tinnitus and the electroencephalogram pattern correspond one-to-one.

  The receiving unit 22 receives the electroencephalogram data transmitted from the headset device 10 in time series.

  The filter unit 23 removes a noise component by passing only a specific frequency component of the electroencephalogram data transmitted from the headset device 10 in time series.

  The Fourier transform unit 24 Fourier transforms the brain wave data that has passed through the filter unit 23 to obtain a frequency spectrum.

  The determination unit 25 determines whether or not the subject U is a tinnitus patient based on the brain wave data (frequency spectrum) Fourier-transformed by the Fourier transform unit 24 and the brain wave data (frequency spectrum) stored in the storage unit 21. judge. Specifically, the determination unit 25 stores the pattern of the brain wave data (frequency spectrum) of the subject U subjected to the Fourier transform by the Fourier transform unit 24 in the brain unit (frequency spectrum) shown in FIG. Is compared with this pattern to determine whether or not the subject U is a tinnitus patient.

  The estimation unit 26 compares the brain wave data of the subject U measured by the electroencephalograph of the headset device 10 with the brain wave data stored in the storage unit 21 to estimate the frequency of the tinnitus sound of the subject U. Specifically, the estimation unit 26 uses the electroencephalogram data (frequency spectrum) pattern measured by the electroencephalograph of the headset device 10 and the electroencephalogram data pattern for each frequency of tinnitus stored in the storage unit 21. The matching is performed to estimate the frequency (height) of the subject's tinnitus.

  The operation receiving unit 27 receives user operation input. Specifically, operations such as ON / OFF of the tinnitus patient discrimination system 1 and start of discrimination are accepted.

  The display unit 28 displays data stored in the storage unit 21 on a display device such as an LCD in accordance with the operation content received by the operation receiving unit 27.

  FIG. 5 is a flowchart showing an operation of determining whether or not the subject of the tinnitus patient discrimination system 1 is a tinnitus patient. Hereinafter, the operation of the tinnitus patient discrimination system 1 will be described with reference to FIGS.

  First, the headset device 10 is worn on the subject. Next, when the input device is operated to start the tinnitus patient determination process, the electroencephalograph of the headset device 10 acquires the electroencephalogram data, and the acquired electroencephalogram data is transmitted to the data processing device 20 in time series. (S101). The receiving unit 22 of the data processing device 20 receives the electroencephalogram data transmitted from the headset device 10 (S102), and the filter unit 23 removes noise components from the received electroencephalogram data (S103).

  Next, the Fourier transform unit 24 performs Fourier transform on the electroencephalogram data that has passed through the filter unit 23 to obtain a frequency spectrum (S104).

  Next, the determination unit 25 determines whether the subject U is a tinnitus patient based on the brain wave data (frequency spectrum) Fourier-transformed by the Fourier transform unit 24 and the brain wave data (frequency spectrum) stored in the storage unit 21. It is determined whether or not (S105).

  Specifically, the discriminating unit 25 uses the brain wave data (frequency spectrum) pattern Fourier transformed by the Fourier transform unit 24 as the brain wave data (frequency spectrum) pattern shown in FIG. A comparison is made to determine whether subject U is a tinnitus patient.

  FIG. 6 is a flowchart showing an operation of estimating the frequency of tinnitus of the subject in the tinnitus patient discrimination system 1. Hereinafter, the operation of the tinnitus patient discrimination system 1 will be described with reference to FIGS. 1 to 4 and 6.

  First, the headset device 10 is worn on the subject. Next, when the input device is operated to start the tinnitus patient determination process, the electroencephalograph of the headset device 10 acquires the electroencephalogram data, and the acquired electroencephalogram data is transmitted to the data processing device 20 in time series. (S201). The receiving unit 22 of the data processing device 20 receives the electroencephalogram data transmitted from the headset device 10 (S202), and the filter unit 23 removes noise components from the received electroencephalogram data (S203).

  Next, the Fourier transform unit 24 performs Fourier transform on the electroencephalogram data that has passed through the filter unit 23 to obtain a frequency spectrum (S204).

  Next, the estimation unit 26 compares the brain wave data of the subject U measured by the electroencephalograph of the headset device 10 with the brain wave data stored in the storage unit 21 to estimate the frequency of the tinnitus sound of the subject U. (S205). Specifically, the estimation unit 26 uses the electroencephalogram data (frequency spectrum) pattern measured by the electroencephalograph of the headset device 10 and the electroencephalogram data pattern for each frequency of tinnitus stored in the storage unit 21. The matching is performed to estimate the frequency (height) of the subject's tinnitus.

  As described above, the tinnitus patient discrimination system 1 according to the present embodiment is a tinnitus patient discrimination system that discriminates between tinnitus patients and non-tinnitus patients, and stores electroencephalogram data having a pattern unique to the tinnitus patient. The subject is a tinnitus patient based on the storage unit 21, the headset device 10 including an electroencephalograph that measures the subject's electroencephalogram, the electroencephalogram data of the subject measured by the electroencephalograph, and the electroencephalogram data stored in the storage unit 21. And a determination unit 25 for determining whether or not.

  Moreover, according to the tinnitus patient discrimination system 1 according to the present embodiment, it is discriminated whether or not it is a tinnitus patient based on an electroencephalogram, so that the tinnitus patient can be easily discriminated. Further, since it is determined whether or not the subject is a tinnitus patient based on the electroencephalogram data having a pattern specific to the tinnitus patient stored in the storage unit 21 and the subject's electroencephalogram data measured by an electroencephalograph. It is possible to objectively identify tinnitus patients.

  Moreover, the tinnitus patient discrimination system 1 according to the present embodiment is an estimation unit that estimates the frequency of the tinnitus of the subject based on the brain wave data of the subject measured by an electroencephalograph and the electroencephalogram data stored in the storage unit 21. 26. For this reason, the frequency of tinnitus of a tinnitus patient can be estimated.

  In addition, the electroencephalogram data stored in the storage unit 21 of the tinnitus patient discrimination system 1 according to the present embodiment outputs a single frequency sound while changing the frequency step by step to a plurality of tinnitus patients and a plurality of non-tinnitus patients. EEG data of a pattern peculiar to tinnitus patients is extracted from the EEG measured each time the frequency is changed. By extracting the electroencephalogram data of a pattern specific to the tinnitus patient from the electroencephalogram data of a plurality of tinnitus patients and a plurality of non-tinnitus patients, it is possible to more objectively identify the tinnitus patient and estimate the frequency of the tinnitus.

  The tinnitus patient discrimination system 1 according to the present embodiment stores the frequency (height) of tinnitus and electroencephalogram data having a pattern peculiar to this frequency in association with each other. Therefore, it is possible to easily and objectively estimate the frequency of tinnitus of a tinnitus patient.

  The tinnitus patient discrimination system 1 according to the present embodiment further includes a Fourier transform unit 24 that Fourier transforms the electroencephalogram measured by the electroencephalograph of the headset device 10, and the electroencephalogram data stored in the storage unit 21 is Fourier transform. It is the electroencephalogram data after conversion. Therefore, it is easy to detect the characteristic amount of the electroencephalogram of the tinnitus patient, and it is possible to objectively determine the tinnitus patient and estimate the frequency of the tinnitus.

  Furthermore, the estimation unit 26 of the tinnitus patient discrimination system 1 according to the present embodiment compares the electroencephalogram data measured by the electroencephalograph with the electroencephalogram data stored in the storage unit by pattern matching, and thereby the frequency of the tinnitus sound of the subject. Is estimated. For this reason, the frequency of the subject's tinnitus can be estimated more accurately.

  Although the present invention has been described by taking the tinnitus patient discrimination system 1 which is an embodiment of the present invention as an example, the present invention is not limited to the above-described embodiment and is within a range where the object of the present invention can be achieved. Such modifications and improvements are included in the present invention. For example, in the above embodiment, the estimation unit 26 of the data processing device 20 estimates the frequency (height) of the tinnitus by pattern matching. However, the frequency (height) of the tinnitus is determined by classification of the electroencephalogram data. You may comprise so that it may estimate. Here, various methods such as support vector machine, Fisher's linear discriminant analysis, and Mahalanobis distance classification can be used for the classification of the electroencephalogram.

  As described above, the tinnitus patient discrimination system, tinnitus patient discrimination method, and tinnitus patient discrimination program of the present invention can easily and objectively determine whether or not a subject is a tinnitus patient. In addition, the frequency (height) of tinnitus can be estimated easily and objectively.

DESCRIPTION OF SYMBOLS 1 Tinnitus patient discrimination system 10 Headset apparatus 20 Data processing apparatus 21 Storage part 22 Reception part 23 Filter 24 Fourier transform part 25 Discrimination part 26 Estimation part 27 Operation reception part 28 Display part

Claims (8)

A tinnitus patient discrimination system for discriminating between tinnitus patients and non-tinnitus patients,
A storage unit in which brain wave data having a pattern specific to the tinnitus patient is stored;
An electroencephalograph that measures the subject's electroencephalogram,
A tinnitus patient discrimination system comprising: a determination unit that determines whether the subject is a tinnitus patient based on the electroencephalogram data of the subject measured by the electroencephalograph and the electroencephalogram data stored in the storage unit.   The tinnitus patient determination according to claim 1, further comprising an estimation unit that estimates a frequency of tinnitus of the subject based on the electroencephalogram data of the subject measured by the electroencephalograph and the electroencephalogram data stored in the storage unit. system. The estimation unit includes
The tinnitus patient discrimination system according to claim 2, wherein the electroencephalogram data measured by the electroencephalograph is compared with the electroencephalogram data stored in the storage unit by pattern matching to estimate the frequency of tinnitus of the subject. The electroencephalogram data stored in the storage unit is
A plurality of the tinnitus patients and a plurality of the non-tinnitus patients are allowed to listen to a single frequency sound while changing the frequency stepwise, and an electroencephalogram having a pattern peculiar to the tinnitus patient is measured from an electroencephalogram measured each time the frequency is changed. The tinnitus patient discrimination system according to any one of claims 1 to 3, wherein the data is extracted.   The tinnitus patient discrimination system according to claim 4, wherein the storage unit stores a frequency of tinnitus and brain wave data having a pattern peculiar to the frequency in association with each other. A Fourier transform unit for Fourier transforming the electroencephalogram measured by the electroencephalograph;
The tinnitus patient discrimination system according to any one of claims 1 to 5, wherein the electroencephalogram data stored in the storage unit is electroencephalogram data after Fourier transform. A method for discriminating tinnitus from a tinnitus patient and a non-tinnitus patient,
Measuring a subject's brain waves with an electroencephalograph;
The determination unit determines whether or not the subject is a tinnitus patient based on the electroencephalogram data having a pattern specific to the tinnitus patient stored in the storage unit and the electroencephalogram data of the subject measured by the electroencephalograph And a method for discriminating tinnitus patients. A tinnitus patient discrimination program for causing a computer to execute each step according to claim 7.

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