JP2023034756A - Secretion amount estimation system and secretion amount estimation program - Google Patents

Abstract

To make it possible to grasp the amount of secretion of a hormone by an easier method without collecting and examining a sample individually.SOLUTION: A secretion amount estimation system S includes: a frequency component detection unit 212 and an estimation unit 215. The frequency component detection unit 212 detects a frequency component of a brain wave in a specific region of a brain. An estimation unit 215 estimates the amount of secretion of a hormone as an estimation target of an estimation subject on the basis of the result of frequency between a frequency component detected by the frequency component detection unit 212 from the estimation subject and a frequency component as a reference for estimating the amount of secretion of the estimation target hormone.SELECTED DRAWING: Figure 3

Description

The present invention relates to a secretion amount estimation system and a secretion amount estimation program.

Conventionally, the amount of secretion of hormones secreted in the body has been measured for various purposes. By measuring the amount of hormone secretion, it becomes possible for a medical professional to select an appropriate medical treatment and for a person to be measured to properly grasp his or her physical condition.

An example of such a technique for measuring the amount of hormone secretion is disclosed in Patent Document 1. The technique disclosed in Patent Document 1 measures the amount of hormone secretion at a medical institution or a testing institution. By notifying the person to be measured of medical advice or the like corresponding to the measured hormone secretion amount, the measurement result can be used more effectively.

JP 2021-108177 A

In general techniques such as those disclosed in the above-mentioned Patent Literature 1, it is necessary to carry out specimen tests. That is, in order to measure the amount of hormone secretion, it is necessary to collect a specimen such as blood or saliva of a subject and perform a specimen test on this specimen.
However, in order to perform a sample test, it is necessary to receive a sample at a medical institution or use a predetermined test kit to collect the sample, which is very troublesome for the subject. Therefore, for example, it is difficult and unrealistic for a woman to routinely measure her hormone secretion in order to grasp her own menstrual condition.

The present invention has been made in view of such circumstances. Further, an object of the present invention is to make it possible to grasp the amount of hormone secretion by a simpler method without the need to collect a sample each time and perform a sample test.

In order to solve the above problems, a secretion amount estimation system according to an embodiment of the present invention includes:
detection means for detecting frequency components of electroencephalograms in specific brain regions;
Secretion of the presumed target hormone in the presumed target person based on the result of comparison between the frequency component detected by the detection means from the presumed target person and the frequency component serving as a reference for estimating the secretion amount of the presumed target hormone. an estimating means for estimating the quantity;
characterized by comprising

According to the present invention, it is possible to grasp the amount of hormone secretion by a simpler method without the need to collect a sample each time and perform a sample test.

BRIEF DESCRIPTION OF THE DRAWINGS It is a block diagram which shows an example of the whole structure of the secretion amount estimation system which concerns on one Embodiment of this invention. 1 is a block diagram showing an example of the configuration of an electroencephalogram measurement device according to an embodiment of the present invention; FIG. BRIEF DESCRIPTION OF THE DRAWINGS It is a block diagram which shows an example of a structure of the secretion amount estimation apparatus which concerns on one Embodiment of this invention. It is a table showing an example of subject information stored in the secretion amount estimation device according to one embodiment of the present invention. 4 is a flow chart showing the flow of measurement processing executed by an electroencephalogram determination device and a secretion amount estimation device according to an embodiment of the present invention. It is a flowchart which shows the flow of the reference data generation process which the secretion amount estimation apparatus which concerns on one Embodiment of this invention performs. It is a flowchart which shows the flow of the secretion amount estimation process which the secretion amount estimation apparatus which concerns on one Embodiment of this invention performs. 4 is a graph showing the results of verification according to an embodiment of the present invention, showing that the amount of female hormone secretion fluctuates with the menstrual cycle. 4 is a graph showing reference data corresponding to estradiol and reference data corresponding to progesterone, which are verification results according to an embodiment of the present invention.

An example of an embodiment of the present invention will be described below with reference to the accompanying drawings.

[System configuration]
FIG. 1 is a block diagram showing the overall configuration of a secretion amount estimation system S according to this embodiment. As shown in FIG. 1 , the secretion amount estimation system S includes an electroencephalogram measurement device 10 and a secretion amount estimation device 20 . FIG. 1 also shows a user who wants to know his/her own hormone secretion amount using the secretion amount estimation system S and a user who provides predetermined data for that purpose.

The electroencephalogram measuring device 10 and the secretion amount estimating device 20 are communicatively connected according to any communication method. This communication may be performed directly between the devices or via a network including relay devices. When communication is performed via a network, this network is realized by, for example, a network such as the Internet, a LAN (Local Area Network), or a network combining these.

Here, the secretion amount estimating system S is an example of an embodiment of the present invention, and makes it possible to ascertain the secretion amount of hormones in a simpler manner without the need to collect specimens each time for specimen testing.
The inventors of the present invention, as a result of repeated test research on the amount of hormone secretion, found that there is a correlation between the amount of hormone secretion and the frequency components of electroencephalograms. The inventors of the present invention conceived that it is possible to estimate the amount of hormone secretion based on the frequency components of brain waves, and have completed the present invention.
Therefore, the secretion amount estimation system S estimates the hormone secretion amount based on the frequency component of the electroencephalogram.

There are a wide variety of hormones, but in the following description, the target hormone to be estimated in this embodiment will be referred to as "estimated target hormone". The presumed target hormones may be, for example, so-called female hormones such as “estradiol” and “progesterone”, so-called male hormones such as “testtetron” and “androstenedione”. It may be "oxytocin" or "serotonin", which are hormones secreted inside.

The electroencephalogram measurement device 10 is a device that measures variations in potential in the user's head as electroencephalograms of the user. The electroencephalogram measurement device 10 is a headset type device that includes a pair of electrodes or a larger number of electrodes for measuring the electroencephalogram of the user, and each of these electrodes electrically contacts a predetermined part of the user. consists of an electroencephalograph.

The electroencephalogram measurement device 10 measures the electroencephalogram of the user using these electrodes, thereby generating data corresponding to the electroencephalogram of the user (hereinafter referred to as "electroencephalogram data"). The electroencephalogram measurement device 10 also transmits the generated electroencephalogram data to the secretion amount estimation device 20 .

The secretion amount estimation device 20 is a device that estimates the amount of hormone secretion based on the electroencephalogram data generated by the electroencephalogram measurement device 10 . The secretion amount estimation device 20 is configured by, for example, an information processing device such as a server device, a personal computer, or a smart phone.

The secretion amount estimation device 20 detects frequency components of electroencephalogram data (ie, electroencephalograms) in a specific brain region in order to estimate the amount of hormone secretion. Further, the secretion amount estimating device 20 compares the frequency component detected by the detecting means from the estimation target person with the frequency component serving as the reference for estimating the secretion amount of the estimation target hormone, based on the result of comparison. Estimate the secretion amount of the estimated target hormone in

In this way, the secretion amount estimation system S estimates the secretion amount of the presumed target hormone in the presumed subject based on the detected frequency components of the electroencephalogram. Therefore, according to the secretion amount estimation system S, although it is necessary to specify the reference frequency component by the sample test of the subject, after that, the estimation subject simply measures the electroencephalogram, and the secretion amount of the estimated target hormone is determined. can be grasped immediately. In addition, while a general technique would require sample testing, the secretion amount estimation system S eliminates the need for the person to be estimated to perform sample testing.
Therefore, according to the secretion amount estimation system S, it is possible to solve the problem of making it possible to grasp the secretion amount of hormones by a simpler method without the need to collect samples each time and perform a sample test.

Next, the configurations and functions of the electroencephalogram measuring device 10 and the secretion amount estimating device 20 for realizing such processing will be described in more detail. In order to clarify the explanation, each person involved in the secretion amount estimation system S will be distinguished as follows.

First, in order for the secretion amount estimation system S to specify a reference frequency component, a user who undergoes electroencephalogram data measurement is referred to as a “subject”. As a test subject, for example, an employee of a company that operates the secretion amount estimation system S and a cooperator who cooperates with this company are assumed.
A user whose secretion amount of an estimation target hormone is estimated based on the reference frequency component specified by the secretion amount estimation system S is referred to as an "estimation target person". As an estimated target person, for example, a woman who wants to grasp her own menstrual situation and the like is assumed.
Note that the subject and the person to be presumed may be different persons, or may be the same person. That is, a certain user may become a subject and specify a reference frequency component, and then the user may become an estimation subject and receive the estimation. Also, a third party such as a medical worker may refer to the estimation result of the amount of secretion and use the estimation result for medical measures.

[Configuration of electroencephalogram measuring device]
Next, the configuration of the electroencephalogram measurement device 10 will be described with reference to FIG. FIG. 2 is a block diagram showing an example of the configuration of the electroencephalogram measurement device 10. As shown in FIG.
As shown in FIG. 2, the electroencephalogram measurement apparatus 10 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a communication section 14, a storage section 15, An input section 16 , an output section 17 and a measurement section 18 are provided. These units are connected by signal lines and send and receive signals to each other.

The CPU 11 executes various processes (for example, measurement process described later) according to programs recorded in the ROM 12 or programs loaded from the storage unit 15 to the RAM 13 .
The RAM 13 also stores data necessary for the CPU 11 to execute various processes.

The communication unit 14 performs communication control for the CPU 11 to communicate with another device (for example, the secretion amount estimation device 20).
The storage unit 15 is composed of a semiconductor memory such as a DRAM (Dynamic Random Access Memory) and stores various data.

The input unit 16 is composed of various buttons and the like, and inputs various information according to user's operation.
The output unit 17 includes a display, a speaker, and the like, and outputs images and sounds.

The measurement unit 18 measures changes in the potential of the head of the user (here, the subject or the person to be estimated) as the user's electroencephalogram. In this embodiment, as an example of the measurement method, it is assumed that the measurement unit 18 measures electroencephalograms from a specific region of the brain by the reference electrode derivation method. In this case, one end of the pair of electrodes provided in the measurement unit 18 is brought into contact with a point where the potential is close to zero (for example, the earlobe of the user) to be used as a reference electrode. Also, the other end is brought into contact with a predetermined position on the user's head (for example, a position corresponding to Fp1 in the left anterior frontal cortex defined by the International 10-20 method) as an exploration electrode. Then, the measuring unit 18 measures changes in the potential difference between the reference electrode and the probe electrode over time as electroencephalograms in a predetermined region of the user's brain at a predetermined sampling frequency (eg, 512 [Hz]).

Here, as described above, the electroencephalogram measurement device 10 has a headset shape, and the pair of electrodes provided in the measurement unit 18 are located at positions suitable for measurement when the user wears the electroencephalogram measurement device 10 (for example, , the position that contacts the earlobe, and the position that contacts the site corresponding to Fp1). In this respect, when an electroencephalograph having a general shape in which an electrode net is placed over the user's head is used, the user feels oppressed, and noise resulting from tension is generated in the electroencephalogram. On the other hand, since the electroencephalogram measurement apparatus 10 has a headset shape, it is possible to perform measurement in a state in which the user's tension is suppressed without giving such a feeling of oppression. Therefore, according to the electroencephalogram measuring apparatus 10, it is possible to suppress the generation of noise caused by the tension of the user and perform accurate measurement.

In the electroencephalogram measurement device 10, these units cooperate to perform "measurement processing".
Here, the measurement process is a series of processes in which the electroencephalogram measuring device 10 and the secretion amount estimating device 20 measure the user's electroencephalogram and perform predetermined preprocessing and the like on the measured electroencephalogram.

When the measurement process is executed, as shown in FIG. 2, in the CPU 11, a measurement control section 111, a preprocessing section 112, and an electroencephalogram data transmission section 113 function.
Data necessary for realizing processing is appropriately transmitted and received between these functional blocks at appropriate timings, including cases not specifically mentioned below.

The measurement control unit 111 controls the electroencephalogram measurement by the measurement unit 18 based on the user's instruction operation received by the input unit 16 (or the user's instruction operation received via the communication unit 14). For example, based on these instructions, the measurement control unit 111 controls the timing of starting and ending the measurement by the measurement unit 18, and controls the sampling period and the like in the measurement. Then, the measurement control unit 111 outputs the user's electroencephalogram obtained by the measurement by the measurement unit 18 to the preprocessing unit 112 .

The electroencephalogram measurement by the measurement control unit 111 may be performed in any scene, but is preferably performed in a steady scene. For example, it may be performed every day when the user wakes up.
In addition, if the user is given a task during measurement, it is considered that imaging of the normal state of the brain is hindered. Therefore, measurement is performed in a state in which no task is given, such as a resting state with eyes closed.
Furthermore, the length of one measurement time is also arbitrary, but for example, the measurement time is about 15 minutes.

The preprocessing unit 112 generates electroencephalogram data by performing preprocessing such as noise component removal on the electroencephalogram input from the measurement control unit 111 .

For example, the preprocessing unit 112 normalizes the amplitude of the electroencephalogram in order to absorb the individual difference in consideration of the individual difference in amplitude of the electroencephalogram data. In this case, for example, the preprocessing unit 112 normalizes the measured electroencephalogram so that the average amplitude value is 0 and the standard deviation is 1.

Also, for example, the preprocessing unit 112 uses a bandpass filter to transmit only a predetermined frequency band (eg, 1 to 40 [Hz]) from the normalized electroencephalogram. In this case, if only the frequency band of 4 to 24 [Hz], which has a particularly high correlation with the secretion amount of the target hormone to be estimated, is transmitted, it is possible to estimate the secretion amount of the target hormone to be estimated with higher accuracy. Become. As a result, the preprocessing unit 112 realizes removal of noise (artifact) corresponding to the user's body movement during electroencephalogram measurement.

Furthermore, for example, the preprocessing unit 112 may perform noise (artifact ) is removed.

The preprocessing unit 112 thus performs normalization and removal of various noises (artifacts) as preprocessing, thereby generating electroencephalogram data from the measured electroencephalograms of the user. The preprocessing unit 112 then outputs the generated electroencephalogram data to the electroencephalogram data transmission unit 113 .
Part or all of the preprocessing described as being performed by the preprocessing unit 112 may be performed by the frequency component detection unit 212 of the secretion amount estimation device 20 instead of the preprocessing unit 112 .

The electroencephalogram data transmission unit 113 transmits the electroencephalogram data input from the preprocessing unit 112 to the secretion amount estimation device 20 . In this case, the electroencephalogram data generated in parallel with the measurement is temporarily stored (that is, buffered) in the storage unit 15, and the electroencephalogram data stored in the storage unit 15 is retrieved at the timing such as when the measurement ends. The data may be transmitted all at once, or may be transmitted in real time each time the preprocessing unit 112 generates electroencephalogram data.

[Configuration of secretion amount estimation device]
Next, the configuration of the secretion amount estimation device 20 will be described with reference to FIG. FIG. 3 is a block diagram showing an example of the configuration of the secretion amount estimation device 20. As shown in FIG. As shown in FIG. 3, the secretion amount estimation device 20 includes a CPU 21, a ROM 22, a RAM 23, a communication section 24, a storage section 25, an input section 26, an output section 27, and a drive 28. there is These units are connected by signal lines and send and receive signals to each other.

The CPU 21 executes various processes (for example, a reference data generation process and a secretion amount estimation process, which will be described later) according to programs recorded in the ROM 22 or programs loaded from the storage unit 25 to the RAM 23 .
The RAM 23 also stores data necessary for the CPU 21 to execute various processes.

The communication unit 24 performs communication control for the CPU 21 to communicate with another device (for example, the electroencephalogram measurement device 10).
The storage unit 25 is composed of a semiconductor memory such as a DRAM (Dynamic Random Access Memory) and stores various data.

The input unit 26 is composed of external input devices such as various buttons and a touch panel, or a mouse and keyboard, and inputs various information according to user's instruction operations.
The output unit 27 includes a display, a speaker, and the like, and outputs images and sounds.

The drive 28 is loaded with a removable medium (not shown) such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory. A program read from the removable medium by the drive 28 is installed in the storage unit 25 as required.

In the secretion amount estimation device 20, these units cooperate to perform a "measurement process", a "reference data generation process", and a "secretion amount estimation process".

As described above, the measurement process is a series of processes in which the electroencephalogram measuring device 10 and the secretion amount estimating device 20 measure the user's electroencephalogram and perform predetermined preprocessing and the like on the measured electroencephalogram.
Further, in the reference data generation process, the secretion amount estimation device 20 specifies a frequency component that serves as a reference for estimating the secretion amount of the target hormone to be estimated based on the electroencephalogram data of the subject measured by the electroencephalogram measurement device 10. , and a series of processes for generating the data of the frequency component (hereinafter referred to as "reference data") that serves as the reference.
Furthermore, the reference data generation process is a series of processes in which the secretion amount estimation device 20 estimates the secretion amount of the target hormone to be estimated based on the electroencephalogram data of the subject measured by the electroencephalogram measurement device 10 and the reference data. is.
That is, in the present embodiment, the secretion amount estimation device 20 generates reference data, and uses the generated reference data to estimate the secretion amount of the estimation target hormone.

When the reference data generation process and the secretion amount estimation process are executed, as shown in FIG. A generation unit 214 and an estimation unit 215 function.
A subject data storage unit 251 and a reference data storage unit 252 are provided in one area of the storage unit 25 .
Data necessary for realizing processing is appropriately transmitted and received between these functional blocks at appropriate timings, including cases not specifically mentioned below.

The electroencephalogram data acquisition unit 211 acquires the electroencephalogram data transmitted from the electroencephalogram measurement device 10 by receiving the electroencephalogram data. Then, the electroencephalogram data acquisition section 211 outputs the acquired electroencephalogram data to the frequency component detection section 212 .

The electroencephalogram measurement apparatus 10 may be provided with a drive similar to the drive 28 so that the electroencephalogram measurement apparatus 10 stores the electroencephalogram data in a removable medium. Then, the electroencephalogram data acquisition unit 211 may acquire the electroencephalogram data from the removable medium via the drive 28 instead of acquiring the electroencephalogram data through communication.

The frequency component detection unit 212 detects frequency components of each of a plurality of frequencies from the electroencephalogram data of the subject and the electroencephalogram data of the person to be estimated obtained by the electroencephalogram data acquisition unit 211 . In this case, the frequency component detector 212 divides the electroencephalogram data into predetermined time units (eg, 30 seconds).
Further, the frequency component detection unit 212 detects frequency components of each of the plurality of frequencies from each of the divided electroencephalogram data. For example, the frequency component detection unit 212 applies a Fourier transform (for example, a 512-point Hamming window and a 50% overlap processing, FFT: Fast Fourier transform T )) and averaging to generate a power spectrum indicating power values of a plurality of frequencies (for example, 1 to 40 [Hz]) as frequency components in the electroencephalogram data.
Then, the frequency component detection unit 212 detects, as frequency components, the power values of each of the plurality of frequencies in the power spectrum thus generated.

When the frequency component detection unit 212 detects the frequency component from the electroencephalogram data of the subject, the frequency component detection unit 212 stores the frequency component of the subject in the subject data storage unit 251 . On the other hand, when the frequency component detection unit 212 detects the frequency component from the brain wave data of the estimation target person, the frequency component detection unit 212 outputs the frequency component of the estimation target person to the estimation unit 215 .

The measured secretion amount acquisition unit 213 acquires the secretion amount of the estimated target hormone for each subject. In this case, the secretion amount of the target hormone to be estimated acquired by the measured secretion acquisition unit 213 is not estimated by the secretion amount estimation device 20, but is measured by an existing method involving sample testing. That is, in the present embodiment, a specimen test is performed on a subject in order to generate reference data. However, after creating the reference data, it is possible to estimate the secretion amount of the presumed target hormone without performing a sample test on the presumed target person. In order to clarify the explanation, instead of the secretion amount of the presumed target hormone estimated by the present embodiment, the secretion of the presumed target hormone measured by the sample test for the subject obtained by the measured secretion amount acquisition unit 213 The amount is hereinafter referred to as "measured secretion amount".

The measured secretion amount acquisition unit 213 obtains the estimated secretion amount for each subject, for example, according to the input operation from the user accepted by the input unit 26 (or the input operation from the user received via the communication unit 14). Based on, get. Then, the measured secretion amount acquisition unit 213 causes the subject data storage unit 251 to store the acquired measured secretion amount.

The subject data storage unit 251 stores subject data. The subject data is data in which the frequency component and the measured secretion amount are associated with each measurement of each subject.
FIG. 4 is a table showing an example of subject data stored in the subject data storage unit 251. As shown in FIG. As shown in FIG. 4, the subject data storage unit 251 stores, for example, subject data in a table format. In this table, columns (rows) are provided for each measurement for each subject. Also, for each measurement of each subject, a record (column) is provided for subject ID, date of measurement, frequency component, and measured secretion volume. Corresponding information is stored in fields (cells) where columns and records intersect.

Here, the subject ID is unique information that differs for each subject assigned to the subject, and for example, an identifier that combines information such as numbers and alphabets can be used.
The date of measurement is the date on which the electroencephalogram data was measured by the electroencephalogram measurement device 10 .
Furthermore, the frequency component is the power value of each of a plurality of frequencies (eg, 1 to 40 [Hz]) in the power spectrum generated by the measured secretion amount acquisition unit 213 as described above. In the figure, the value of power, which is a frequency component, is shown as "***".
Furthermore, the measured secretion amount is the measured secretion amount obtained by the frequency component detection unit 212 as described above when each measurement of each subject is performed, and corresponds to a unit such as [pmol/L], for example. It is expressed as a numerical value.
By storing the subject data in such a format, the frequency component and the measured secretion amount of which subject and which day of measurement are stored in an identifiable manner.

Returning to FIG. 3, the reference data generation unit 214 generates reference data that is used as a reference for the estimation unit 215, which will be described later, to estimate the secretion amount of the estimation target hormone. The reference data is the frequency component detected by the frequency component detection unit 212 from the subject whose secretion amount of the estimation target hormone is in a predetermined state. In the following, as an example for explanation, the state in which the secretion amount of the presumed target hormone is predetermined is a state in which the secretion amount of the presumed target hormone is relatively large when the secretion amount of the presumed target hormone fluctuates periodically. Assume there is.

As described above, the secretion amount of the estimated target hormone in the subject is stored in the subject data storage unit 251 as the measured secretion amount in the subject data. Therefore, the reference data generator 214 reads the measured secretion amount in the subject data, and specifies the measurement day with the highest measured secretion amount for each subject. In addition, the reference data generation unit 214 extracts the frequency component of the measurement day when the measured secretion amount is the largest from the subject data. That is, the frequency component of the measurement day with the highest measured secretion amount for the first subject, . component, and the frequency components of N subjects are extracted.

Then, the reference data generator 214 calculates the average value of the power values of the frequency components of the N subjects for each frequency. As a result, the average value of the power values is calculated for each frequency when the secretion amount of the estimated target hormone is relatively large.

The reference data generation unit 214 causes the reference data storage unit 252 to store the calculated average value of the power of each frequency as reference data. That is, the reference data storage unit 252 functions as a storage unit that stores reference data. Thereby, the reference data is generated by the reference data generation unit 214 .

Note that the method of generating the reference data described above is only an example, and the reference data generation unit 214 may also calculate other values such as the median value and the mode value instead of the average value to generate the reference data. may be generated. Alternatively, the reference data generation unit 214 may generate reference data by extracting the frequency component on a measurement day when the estimated target hormone secretion amount is relatively low, rather than on a measurement day when the estimation target hormone secretion amount is relatively high. can be Furthermore, in addition to this, the reference data generation unit 214, for example, sets a threshold based on an absolute value for the secretion amount of the target hormone to be estimated, and the frequency of measurement days when the measured secretion amount is equal to or higher than this threshold (or measurement days below the threshold). A component may be extracted to generate reference data.

The estimation unit 215 compares the frequency components of the person to be estimated input from the frequency component detection unit 212 with the reference data stored in the reference data storage unit 252, based on the result of the comparison. Estimate the amount of secretion. The comparison by the estimating unit 215 is realized, for example, by calculating the degree of similarity between the frequency component of the person to be estimated and the reference data. In this case, the degree of similarity can be calculated by any method. For example, it is possible to compare power values (that is, frequency components) to calculate a difference value, or to use existing techniques such as pattern matching.

In this case, the similarity may be calculated by comparing the power values for all frequencies included in each data, but depending on the type of target hormone to be estimated, only the power values for a predetermined frequency may be compared. may be used to calculate the degree of similarity. For example, based on past estimation results, if a predetermined frequency that causes a particular difference in the type of target hormone to be estimated is known, the degree of similarity is calculated by comparing only the power value of this predetermined frequency. You may make it Alternatively, the power values of all frequencies are compared, but the power value of this predetermined frequency is given priority as a judgment criterion by being weighted, and the similarity is calculated by comparison. good too.

Then, the estimation unit 215 estimates that the higher the calculated similarity is, the closer the secretion amount of the estimation target hormone corresponding to the reference data is to the predetermined state. Here, it is assumed that the predetermined state is a state in which the amount of the estimated target hormone secreted is relatively large. Estimate that the amount is large.
For this purpose, the estimating unit 215 further sets the average value, median value, or mode value of the measured secretion amount of each subject on the measurement day when the measured secretion amount is the largest, which is specified to generate the reference data, as the “reference value”. Calculate as
Then, the estimation unit 215 estimates the value obtained by multiplying the degree of similarity by the reference value as the secretion amount of the estimation target hormone in the estimation target person. For example, if the degree of similarity is 100%, it will be "reference value x 1.00", so the value itself of the reference value is estimated to be the secretion amount of the estimated target hormone in the target person. Alternatively, if the degree of similarity is 50%, then "reference value×0.50" is obtained, so half the reference value is estimated to be the secretion amount of the estimated target hormone in the target person.

Then, the estimation unit 215 presents the estimation result (that is, the estimated value) to the user (here, the estimation subject, the subject, or a third party such as a medical worker). This presentation is, for example, display on a display included in the output unit 27, audio output from a speaker included in the output unit 27, printing on a paper medium from a printing device via the communication unit 24, 24 to another device (not shown) used by the user.

As described above, in the secretion amount estimation system S, the electroencephalogram measurement device 10 measures electroencephalogram data. In addition, in the secretion amount estimation system S, the secretion amount estimation device 20 estimates the secretion amount of the estimation target hormone in the estimation target person based on the detected frequency component of the electroencephalogram.
Therefore, according to the secretion amount estimation system S, it is possible to solve the problem of making it possible to grasp the secretion amount of hormones by a simpler method without the need to collect samples each time and perform a sample test.

Note that, of course, the relationship between the estimated target hormone and the frequency component differs depending on the type of the estimated target hormone to be estimated. It differs from target hormones (eg, progesterone). Therefore, the reference data generator 214 generates reference data for each type of estimation target hormone. In addition, the estimation unit 215 estimates the secretion amount of the estimation target hormone using the reference data corresponding to the type of the estimation target hormone to be estimated.

[Measurement processing]
Next, with reference to FIG. 5, the flow of measurement processing executed by the electroencephalogram measuring device 10 and the secretion amount estimating device 20 will be described. FIG. 5 is a flowchart for explaining the flow of measurement processing executed by the electroencephalogram measurement device 10 and the secretion amount estimation device 20. As shown in FIG. The measurement process is executed in response to a user's instruction to start measurement.

First, the flow of processing on the side of the electroencephalogram measurement device 10 will be described.
In step S<b>11 , the measurement control unit 111 starts the measurement of brain waves by the measurement unit 18 by controlling the measurement of the user's brain waves by the measurement unit 18 . Then, the measurement control unit 111 outputs the user's electroencephalogram obtained by the measurement by the measurement unit 18 to the preprocessing unit 112 .

In step S<b>12 , the preprocessing unit 112 generates electroencephalogram data by preprocessing the electroencephalogram input from the measurement control unit 111 . Then, the preprocessing unit 112 causes the storage unit 15 to temporarily store (that is, buffer) the generated electroencephalogram data.

In step S<b>13 , the measurement control unit 111 determines whether or not to end the electroencephalogram measurement by the measurement unit 18 . For example, the measurement control unit 111 determines to end the electroencephalogram measurement when a predetermined time has passed since the start of the measurement, or when the user instructs to end the measurement. If the electroencephalogram measurement is to be ended, the determination in step S13 is Yes, and the process proceeds to step S14. On the other hand, if the electroencephalogram measurement is not to be ended, it is determined No in step S13, and the process is repeated again from step S11.

In step S<b>14 , the electroencephalogram data transmission unit 113 transmits all electroencephalogram data temporarily stored in the storage unit 15 by the preprocessing unit 112 to the secretion amount estimation device 20 . This completes the processing on the electroencephalogram measurement device 10 side.

In this flowchart, the electroencephalogram data is temporarily stored (that is, buffered) in the storage unit 15, and the electroencephalogram data stored in the storage unit 15 is transmitted all at once at the timing such as the end of measurement. However, as described above, transmission may be performed in real time each time electroencephalogram data is generated.

Next, the flow of processing on the side of the secretion amount estimation device 20 will be described.
In step S<b>21 , the electroencephalogram data acquisition unit 211 acquires the electroencephalogram data transmitted from the electroencephalogram measurement device 10 by receiving the electroencephalogram data.
In step S22, the frequency component detection unit 212 detects frequency components of each of a plurality of frequencies from the electroencephalogram data.

In step S23, the frequency component detection unit 212 determines whether or not frequency components have been detected from the electroencephalogram data of the subject in step S22. If the frequency component is detected from the electroencephalogram data of the subject, a determination of Yes is made in step S23, and this process ends on the secretion amount estimation device 20 side. On the other hand, if no frequency component is detected from the electroencephalogram data of the subject (that is, if the frequency component is detected from the electroencephalogram data of the subject to be estimated), it is determined No in step S23, and the process proceeds to step S24.

In step S24, the measured secretion amount acquisition unit 213 acquires the secretion amount of the estimation target hormone for the subject from whom the frequency component was detected in step S22.
In step S25, the frequency component detection unit 212 and the measured secretion amount acquisition unit 213 cause the subject data storage unit 251 to store the subject data of the subject from which the frequency component was detected in step S22. This completes the processing on the side of the secretion amount estimation device 20 .

By the measurement processing described above, the electroencephalogram measurement device 10 can measure electroencephalograms from the user and transmit electroencephalogram data generated based on the measured electroencephalograms to the secretion amount estimation device 20 . In addition, the secretion amount estimation device 20 can detect frequency components and store subject data about the subject.

[Reference data generation processing]
Next, with reference to FIG. 6, the flow of the reference data generation process executed by the secretion amount estimation device 20 will be described. FIG. 6 is a flowchart for explaining the flow of reference data generation processing executed by the secretion amount estimation device 20. As shown in FIG. The reference data generation process is executed in response to a user's instruction to start generating reference data.
As a premise of the processing, it is assumed that the subject data storage unit 251 stores the subject data generated by the measurement processing.

In step S31, the reference data generation unit 214 reads subject data stored in the subject data storage unit 251. FIG.
In step S32, the reference data generator 214 generates reference data based on the subject data read in step S31.
In step S33, the reference data generation unit 214 causes the reference data storage unit 252 to store the reference data generated in step S32. This completes the processing.

Through the reference data generation process described above, the secretion amount estimation device 20 can generate reference data as a reference for estimating the secretion amount of the estimation target hormone.

[Secretion Estimation Processing]
Next, with reference to FIG. 7, the flow of secretion amount estimation processing executed by the secretion amount estimation device 20 will be described. FIG. 7 is a flowchart for explaining the flow of the secretion amount estimation process executed by the secretion amount estimation device 20. As shown in FIG. The secretion amount estimation process is executed in accordance with an instruction operation from the user to start secretion amount estimation. As a premise of the processing, it is assumed that the electroencephalogram data of the person to be estimated has been detected by the measurement processing. Also, it is assumed that the reference data storage unit 252 stores the reference data generated by the reference data generation process.

In step S41, the estimation unit 215 acquires the electroencephalogram data of the person to be estimated detected by the measurement process.
In step S<b>42 , the estimation unit 215 reads the reference data stored in the reference data storage unit 252 .

In step S43, the estimating unit 215 estimates the secretion amount of the estimation target hormone in the estimation target based on the result of comparison between the electroencephalogram data of the estimation target acquired in step S41 and the reference data read in step S42. do.
In step S44, the estimation unit 215 presents the estimation result of the estimation in step S43 to the user.

With the secretion amount estimation processing described above, the secretion amount estimation system S solves the problem that the secretion amount of the hormone can be grasped by a simpler method without the need to collect a specimen each time and perform a specimen test. be able to.

[Verification example]
The embodiments of the present invention have been described above. Next, with reference to FIGS. 8 and 9, the results of the verification of the correlation between the amount of hormone secretion and the frequency component of the electroencephalogram actually performed on subjects will be described. do. FIG. 8 is a graph showing that the amount of female hormone secretion (here, estradiol and progesterone) fluctuates with the menstrual cycle. FIG. 9 is a graph showing baseline data for estradiol and baseline data for progesterone.

As a premise, the menstrual cycle is classified into four phases: the luteal phase, the menstrual phase, the follicular phase, and the ovulatory phase, and it is generally known that the amount of female hormones secreted changes periodically along with this. . In particular, the amount of estradiol secreted varies greatly during the four phases of the menstrual cycle. During the menstrual period, estradiol and progesterone levels are the lowest among the four periods. During the subsequent follicular phase, estradiol secretion gradually increases while progesterone secretion decreases. During ovulation, estradiol secretion decreases temporarily and progesterone secretion increases gradually. During the first half of the ovulation period, the amount of estradiol, which has the function of lowering body temperature, is highest. During the luteal phase, both estradiol and progesterone secretion increase. In particular, progesterone is secreted most during the luteal phase. At the end of the luteal phase, both estradiol and progesterone secretion decrease and menstruation begins again. Thus, during the menstrual cycle, the amount of hormone secretion fluctuates from period to period.

FIG. 8 (A) is a graph showing changes in the amount of estradiol secreted, the horizontal axis indicates the number of days from the start of menstruation, and the vertical axis indicates the amount of estradiol secreted (here, the concentration in the sample saliva [ pmol/L]). The amount of estradiol secreted was actually measured by a specimen test using the subject's saliva as a sample, and corresponds to the measured amount of secretion in the above-described embodiment. FIG. 8(B) is a graph similar to FIG. 8(A), and is a graph showing changes in the amount of progesterone secreted instead of the amount of estradiol secreted.
As shown in FIGS. 8(A) and (B), the amount of estradiol and progesterone actually secreted by the subject varies with the menstrual cycle.

In parallel with the measurement of the measured secretion amount shown in FIGS. 8A and 8B, the measurement process shown in FIG. 5 was performed by actually measuring the electroencephalogram of the subject. Also, based on these measurement results, the reference data generation process shown in FIG. 6 was performed to generate reference data with estradiol and progesterone as estimated target hormones. The reference data are shown in FIG.

FIG. 9A is a graph showing reference data generated when the hormone to be estimated is estradiol, where the horizontal axis indicates the frequency and the vertical axis indicates the frequency component (that is, power value) of each frequency. show. Here, the reference data is the average value of a plurality of subjects in the frequency component (that is, power value) on the measurement day when the measured secretion amount of the target hormone to be estimated is the largest. Therefore, for example, in the examples of FIGS. 8(A) and (B), the measured secretion of estradiol is the highest and the measured secretion of progesterone is the highest in the menstrual cycle at about one week after the start of menstruation. , is the reference data corresponding to the measurement date.

On the other hand, FIG. 9(B) is a graph similar to FIG. 9(A), showing reference data generated when progesterone, instead of estradiol, is the estimated target hormone. For example, in the examples of FIGS. 8A and 8B, the measured secretion of progesterone is the highest and the measured secretion of estradiol is normal in the menstrual cycle at about two weeks after the onset of menstruation. It becomes reference data corresponding to the measurement date.

A comparison of FIGS. 9A and 9B reveals the strength and weakness relationships of the frequency components (that is, power values) of each frequency in each reference data, and the degree of strength and weakness, depending on the hormone to be estimated. differ. Therefore, it is clear that there is a correlation between the secretion amount of the estimated target hormone and the frequency component of the electroencephalogram.
Therefore, it can be said that the secretion amount of the presumed target hormone in the presumed subject can be estimated by generating the reference data from the subject's electroencephalogram as in the embodiment described above and based on this.

[Modification]
Although the embodiment of the present invention has been described above, this embodiment is merely an example and does not limit the technical scope of the present invention. The present invention can take various other embodiments and can be modified in various ways such as omission and replacement without departing from the gist of the present invention. In this case, these embodiments and their modifications are included in the scope and gist of the invention described in this specification and the like, and are included in the scope of the invention described in the claims and equivalents thereof.
As an example, the embodiments of the present invention described above may be modified as illustrated below.

<First modification>
The device configuration of the secretion amount estimation system S in the above-described embodiment is merely an example, and can be changed as appropriate. For example, in the above-described embodiment, the electroencephalogram measuring device 10 and the secretion amount estimating device 20 are implemented as separate devices. Not limited to this, for example, the electroencephalogram measurement device 10 and the secretion amount estimation device 20 may be implemented as an integrated device.

Besides, in the above-described embodiment, the electroencephalogram measuring device 10 and the secretion amount estimating device 20 are each realized by a single device. Not limited to this, each of the electroencephalogram measuring device 10 and the secretion amount estimating device 20 may be realized by a plurality of devices by using technology such as cloud computing.

In addition, in the embodiment described above, it was assumed that the electroencephalogram measurement device 10 was used by a plurality of subjects. Alternatively, for example, an electroencephalogram measurement device 10 may be provided for each subject, and each subject may use the electroencephalogram measurement device 10 on a daily basis in a private environment such as at home.

Besides, in the above-described embodiment, the electroencephalogram measurement device 10 measures the electroencephalogram of Fp1 using a pair of electrodes. Not limited to this, the electroencephalogram measurement device 10 may measure electroencephalograms at locations other than Fp1. Alternatively, the electroencephalogram measurement device 10 may be provided with a larger number of electrodes to measure electroencephalograms at multiple locations. Then, a series of the above-described processes may be performed based on each of the electroencephalograms at a plurality of locations.

<Second modification>
In the above-described embodiment, the estimation unit 215 presents the estimated value of the secretion amount of the estimated target hormone as the estimation result. You may make it present not only this but other information relevant to an estimation result. For example, as described above in the description of the verification example, the menstrual cycle and the increase and decrease in the secretion amount of estradiol and progesterone have a predetermined regularity. Therefore, based on the estimation result of the secretion amount of estradiol and progesterone, it is possible to determine which phase included in the menstrual cycle the estimation subject is approaching. Therefore, the estimating unit 215 may also present a determination result indicating which period included in the menstrual cycle the estimation target person is approaching. For example, by presenting to the user that the user is in the luteal phase, the cause of the user's mental or physical unwell condition can be easily known from the electroencephalogram without a hormone test. As a result, for example, it can be expected to avoid many cases in which people in the luteal phase, whose symptoms are similar to those of depression, mistakenly assume that they are suffering from depression and visit a psychiatrist.

In addition, for example, it is known that the amount of noradrenaline and adrenaline secreted increases when one feels anger. Therefore, the estimation unit 215 estimates the amount of secretion of noradrenaline and adrenaline as hormones to be estimated. Then, based on the results of estimating the amount of secretion of noradrenaline and adrenaline, it is also possible to present the determination result of how angry the user is.

<Third Modification>
In the above-described embodiment, the electroencephalogram measurement device 10 measures electroencephalograms, and a series of processing is performed based on the electroencephalogram data of the electroencephalograms thus measured. Alternatively, other biological information may be measured, an electroencephalogram may be estimated from the other measurement information, and a series of processing may be performed based on the estimated electroencephalogram data. In other words, brain waves may be estimated values from other biological information instead of measured values.

As a technique for estimating brain waves without using an electroencephalograph worn on the head, for example, the technique disclosed in "Japanese Patent Application Laid-Open No. 2015-109964", which is partly shared by the present invention and the inventor, is used. be able to.
As a result, the series of processes in the above-described embodiment can be realized based on other biological information without actually measuring electroencephalograms.

[Configuration example]
As described above, the secretion amount estimation system S according to this embodiment includes the frequency component detection unit 212 and the estimation unit 215 .
The frequency component detection unit 212 detects frequency components of electroencephalograms in specific brain regions.
The estimating unit 215 compares the frequency component detected by the frequency component detecting unit 212 from the subject to be estimated with the frequency component serving as a reference for estimating the secretion amount of the target hormone to be estimated, based on the result of comparison. Estimate the secretion amount of the estimated target hormone.
In this way, the secretion amount estimation system S estimates the secretion amount of the presumed target hormone in the presumed subject based on the detected frequency components of the electroencephalogram. Therefore, according to the secretion amount estimation system S, although it is necessary to specify the reference frequency component by the sample test of the subject, after that, the estimation subject simply measures the electroencephalogram, and the secretion amount of the estimated target hormone is determined. can be grasped immediately. In addition, while a general technique would require sample testing, the secretion amount estimation system S eliminates the need for the person to be estimated to perform sample testing.
Therefore, according to the secretion amount estimation system S, it is possible to solve the problem of making it possible to grasp the secretion amount of hormones by a simpler method without the need to collect samples each time and perform a sample test.

The estimating unit 215 uses the frequency component detected by the frequency component detecting unit 212 from the subject whose secretion amount of the hormone to be estimated is in a predetermined state as a reference frequency component.
Thereby, the reference frequency component can be specified based on the objective index of the frequency component of the electroencephalogram of the subject.

A state in which the secretion amount of the estimated target hormone is predetermined is a state in which the secreted amount of the estimated target hormone is relatively large when the amount of the estimated target hormone secreted fluctuates periodically,
The estimating unit 215 estimates that the higher the similarity between the frequency component detected by the frequency component detecting unit 212 from the subject of estimation and the reference frequency component, the greater the secretion amount of the target hormone of the subject of estimation.
As a result, the secretion amount of the target hormone to be estimated can be estimated based on the objective index of the degree of similarity with the reference frequency component.

The frequency component detection unit 212 detects, as frequency components, power values of each of a plurality of frequencies when an electroencephalogram is represented as a power spectrum.
Thereby, the frequency component can be detected by information processing called calculation.

[Realization of functions by hardware and software]
A function for executing a series of processes according to the above-described embodiment can be realized by hardware, software, or a combination thereof. In other words, it suffices if the function of executing the series of processes described above is implemented in any of the secretion amount estimation systems S, and there are no particular limitations on how this function is implemented.

For example, when the function of executing the series of processes described above is realized by a processor that executes arithmetic processing, the processor that executes this arithmetic processing is composed of various single processing units such as a single processor, a multiprocessor, and a multicore processor. In addition to these, it also includes a combination of these various processing devices and a processing circuit such as ASIC (Application Specific Integrated Circuit) or FPGA (Field-Programmable Gate Array).

Further, for example, when the function of executing the series of processes described above is implemented by software, programs that constitute the software are installed in a computer via a network or a recording medium. In this case, the computer may be a computer in which dedicated hardware is installed, or a general-purpose computer capable of executing a predetermined function by installing a program (for example, a general-purpose personal computer, etc.). general electronic equipment). Also, the steps of writing the program may include only processes that are performed in chronological order, but may also include processes that are performed in parallel or individually. Also, the steps of writing the program may be executed in any order without departing from the gist of the present invention.

A recording medium recording such a program may be provided to the user by being distributed separately from the computer main body, or may be provided to the user while being pre-installed in the computer main body. In this case, the storage medium distributed separately from the computer main body is composed of a magnetic disk (including a floppy disk), an optical disk, a magneto-optical disk, or the like. Optical discs are composed of, for example, CD-ROMs (Compact Disc-Read Only Memory), DVDs (Digital Versatile Discs), Blu-ray (registered trademark) Discs, and the like. The magneto-optical disc is composed of, for example, an MD (Mini Disc) or the like. These storage media are installed in the drive 28 shown in FIG. 3, for example, and incorporated into the computer main body. 2, the ROM 22 of FIG. 3, the storage section 15 of FIG. 2, or the storage medium of FIG. It is configured by an SSD (Solid State Drive), a hard disk, etc. included in the unit 25 .

10 electroencephalogram measurement device, 20 secretion amount estimation device, 11, 21 CPU, 12, 22 ROM, 13, 23 RAM, 14, 24 communication unit, 15, 25 storage unit, 16, 26 input unit, 17, 27 output unit, 18 measurement unit, 28 drive, 111 measurement control unit, 112 preprocessing unit, 113 electroencephalogram data transmission unit, 211 electroencephalogram data acquisition unit, 212 frequency component detection unit, 213 measurement secretion amount acquisition unit, 214 reference data generation unit, 215 estimation Unit, 251 subject data storage unit, 252 reference data storage unit, S secretion amount estimation system

Claims (5)

detection means for detecting frequency components of electroencephalograms in specific brain regions;
Secretion of the presumed target hormone in the presumed target person based on the result of comparison between the frequency component detected by the detection means from the presumed target person and the frequency component serving as a reference for estimating the secretion amount of the presumed target hormone. an estimating means for estimating the quantity;
A secretion amount estimation system comprising: The estimating means uses, as the reference frequency component, the frequency component detected by the detecting means from a subject whose secretion amount of the target hormone to be estimated is in a predetermined state.
The system for estimating the amount of secretion according to claim 1, characterized in that: The state in which the secretion amount of the presumed target hormone is predetermined is a state in which the secretion amount of the presumed target hormone is relatively large when the secretion amount of the presumed target hormone fluctuates periodically,
The estimation means estimates that the higher the degree of similarity between the frequency component detected by the detection means from the estimation target and the reference frequency component, the higher the amount of the estimation target hormone secreted by the estimation target. do,
The system for estimating the amount of secretion according to claim 2, characterized in that: wherein the detecting means detects, as frequency components, power values of each of a plurality of frequencies when the electroencephalogram is represented as a power spectrum;
The system for estimating the amount of secretion according to any one of claims 1 to 3, characterized in that: a detection function that detects the frequency components of electroencephalograms in a specific brain region;
Secretion of the presumed target hormone in the presumed target person based on a comparison result between the frequency component detected by the detection function from the presumed target person and the frequency component serving as a reference for estimating the secretion amount of the presumed target hormone. an estimation function for estimating the quantity;
A program characterized by realizing on a computer.

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