Menopause progress estimation system, menopause progress estimation device, menopause progress estimation method, and menopause progress estimation program

Abstract

This menopause progress estimation system comprises a control unit and a storage device. The storage device stores a plurality of menstrual cycles of a measured subject and a plurality of basal body temperatures of the measured subject. The control unit estimates the degree of progress of menopause of the measured subject on the basis of the plurality of menstrual cycles and the plurality of basal body temperatures.

Description

Menopausal progression estimation system, menopausal progression estimation device, menopausal progression estimation method, and menopausal progression estimation program

[0001] The present invention relates to a technique for estimating the stage of menopause in women.

[0002] Irregular menstruation can frequently occur in women due to factors such as stress, lifestyle habits, and hormonal imbalance. In particular, for women in their 40s and older, irregular menstruation is caused by hormonal imbalance due to the effects of menopause. Patent Document 1 describes a technology for estimating the expected onset date of menstruation. Patent Document 1 estimates the expected onset date of menstruation based on whether the menstrual cycle is stable and whether the number of days in the high temperature phase is stable.

[0003] JP 2014-212977 A

[0004] However, the technique in Patent Document 1 estimates the expected onset date of menstruation using only the menstrual cycle and the number of days in the high temperature phase. In other words, although it can predict the onset of menstruation, it is difficult to determine whether menstrual irregularities are due to menopause.

[0005] Generally, the menopausal period lasts for approximately 10 years, including the five years leading up to menopause and the five years following menopause. With the configuration of Patent Document 1, even if it is possible to predict the expected onset date of menopause while reflecting the effects of menopause, it is difficult to grasp the extent to which menopause has progressed.

[0006] Furthermore, if irregular menstruation in women in their 40s or older is not due to menopause, it may be due to diseases such as uterine fibroids, uterine cancer, cervical cancer, etc. In other words, understanding whether irregular menstruation is due to menopause and how far menopause has progressed (stage of progression) is necessary for living a healthy daily life.

[0007] Therefore, an object of the present invention is to provide a technique for objectively understanding the progression of menopause.

[0008] A menopausal progression estimation system according to an embodiment of the present invention includes a control unit and a storage device. The storage device stores a plurality of menstrual cycles and a plurality of basal body temperatures of the subject. The control unit estimates the subject's menopausal progression based on the plurality of menstrual cycles and the plurality of basal body temperatures.

[0009] In this configuration, the progress of menopause can be estimated based on multiple menstrual cycles and multiple basal body temperatures.

[0010] A menopausal progression estimation device according to an embodiment of the present invention includes a control unit, a storage device, and a display unit. The storage device stores a plurality of menstrual cycles and a plurality of basal body temperatures of the subject. The control unit estimates the subject's menopausal progression based on the plurality of menstrual cycles and the plurality of basal body temperatures. The control unit also causes the display unit to display the menopausal progression.

[0011] This configuration allows the stage of menopause to be estimated based on multiple menstrual cycles and multiple basal body temperatures.In addition, the stage of menopause can be displayed on the display unit, allowing the stage of menopause to be visually recognized.

[0012] A method for estimating the progression of menopause according to an embodiment of the present invention includes a step of storing a plurality of menstrual cycles and a plurality of basal body temperatures of the subject, and a step of estimating the progression of menopause of the subject based on the plurality of menstrual cycles and the plurality of basal body temperatures.

[0013] This method allows for the estimation of the progression of menopause based on multiple menstrual cycles and multiple basal body temperatures.

[0014] A menopausal progression estimation program according to an embodiment of the present invention causes a computer to execute the steps of storing a plurality of menstrual cycles and a plurality of basal body temperatures of the subject, and estimating the subject's menopausal progression based on the plurality of menstrual cycles and the plurality of basal body temperatures.

[0015] This program can estimate the progression of menopause based on multiple menstrual cycles and multiple basal body temperatures.

[0016] A menopausal progression estimation program according to an embodiment of the present invention causes a first computer to execute the following steps: storing a plurality of menstrual cycles and a plurality of basal body temperatures of the subject; transmitting the plurality of menstrual cycles and the plurality of basal body temperatures to a second computer; and receiving the subject's menopausal progression estimated by the second computer based on the plurality of menstrual cycles and the plurality of basal body temperatures.

[0017] This program can estimate the stage of menopause based on multiple menstrual cycles and multiple basal body temperatures. This program distributes processing, reducing the load on the computer that executes each step.

[0018] According to this invention, the progress of menopause can be objectively grasped.

[0019] FIG. 1 is a configuration diagram of a menopausal progression estimation system according to a first embodiment of the present invention. FIG. 2 is a configuration diagram of a menopausal progression estimation system according to a first embodiment of the present invention. FIG. 3(A) is a table showing the correlation between menstruation and basal body temperature according to a first embodiment of the present invention, and FIG. 3(B) is a table showing the correlation between menstrual cycle and average body temperature according to a first embodiment of the present invention. FIG. 4 is a flowchart showing an example of a method for determining the menopausal progression according to a first embodiment of the present invention. FIG. 5 is a table showing thresholds for grouping the menopausal progression according to a first embodiment of the present invention. FIG. 6 is a scatter plot (plot diagram) for grouping the menopausal progression according to a first embodiment of the present invention. FIG. 7 is a diagram showing an example of a display unit for displaying the menopausal progression according to a first embodiment of the present invention. FIG. 8(A) is a table showing the correlation between menstruation and basal body temperature according to a second embodiment of the present invention, and FIG. 8(B) is a table showing the correlation between menstruation and average body temperature according to a second embodiment of the present invention. FIG. 9 is a flowchart showing an example of a method for determining the menopausal progression according to a second embodiment of the present invention. Fig. 10 is a table showing thresholds for grouping the degree of menopausal progression according to the second embodiment of the present invention. Fig. 11 is a scatter diagram (plot diagram) for grouping the degree of menopausal progression according to the second embodiment of the present invention. Fig. 12 is a configuration diagram of a menopausal progression estimation system according to a third embodiment of the present invention. Fig. 13 is a flowchart showing an example of determining the degree of menopausal progression according to the third embodiment of the present invention. Fig. 14 is a tree diagram for determining the degree of menopausal progression according to the third embodiment of the present invention. Fig. 15 is a scatter diagram (plot diagram) for grouping the degree of menopausal progression according to a modified example of the present invention.

[0020] The terms "basal body temperature," "menstrual cycle," and "progression of menopause" explained in the following embodiments will be defined.

[0021] <Basal Body Temperature> Deep body temperature is the temperature inside the human body, such as the core, that keeps the brain and organs functioning normally. Of these deep body temperatures, basal body temperature is the temperature at rest when only the energy necessary to sustain life is used. Generally, sublingual temperature measured immediately after waking up is used as basal body temperature, but in the present invention, basal body temperature is also defined to include temperatures measured under certain conditions that can be linked to basal body temperature, such as temperature measured by attaching a device to the chest while sleeping. In other words, in the present invention, measuring basal body temperature includes both measuring basal body temperature itself and measuring deep body temperature or other temperatures that can be converted to basal body temperature.

[0022] <Basal Body Temperature and Menstrual Cycle of the Subject> Next, the basal body temperature and menstrual cycle of the subject will be defined.

[0023] - The basal body temperature measured once by one person is called the "first basal body temperature." - The average of the basal body temperatures measured multiple times by one person is called the "first average basal body temperature." - The multiple basal body temperatures measured once by multiple people are called the "second basal body temperature." - The average of the multiple basal body temperatures measured multiple times by multiple people is called the "second average basal body temperature." - The number of days defined as the period from the first day of one person's menstruation to the day before the first day of the next menstruation is called the "first menstrual cycle." - The number of days defined as the period from the first day of one person's menstruation to the day before the first day of the next menstruation is called the "second menstrual cycle." - The average of the multiple menstrual cycles of multiple people is called the "second average menstrual cycle."

[0024] Therefore, "plurality of basal body temperatures" in the present invention correspond to a plurality of first or second basal body temperatures, and may include both. "plurality of menstrual cycles" in the present invention correspond to a plurality of first or second menstrual cycles, and may include both.

[0025] <Progression of Menopause> Next, the progression of menopause will be defined.

[0026] - Menopause has not yet begun. This is when the menstrual cycle for the past year is between 25 and 38 days.

[0027] Early menopause: A condition in which the menstrual cycle gradually shortens, and includes menstrual cycles of 24 days or less in the past year.

[0028] - Early to mid-menopause: Anovulatory menstruation is included in some menstrual periods. There have been two or more cycles in the past year in which menstruation began without reaching the high temperature phase. Or, there has been a menstrual cycle of 39 to 60 days in the past year.

[0029] - After mid-menopause: A condition in which menstruation occurs once every two to three months (oligomenorrhea), and the menstrual cycle has been 61 days or more in the past year.

[0030] [First Embodiment] A menopausal progression estimation system, a menopausal progression estimation device, a menopausal progression estimation method, and a menopausal progression estimation program according to a first embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a configuration diagram of a menopausal progression estimation system according to a first embodiment of the present invention. FIG. 2 is a configuration diagram of a menopausal progression estimation system according to a first embodiment of the present invention. FIG. 3(A) is a table showing the correlation between menstruation and basal body temperature according to a first embodiment of the present invention, and FIG. 3(B) is a table showing the correlation between menstrual cycle and average body temperature according to a first embodiment of the present invention. FIG. 4 is a flowchart showing an example of determining the menopausal progression according to a first embodiment of the present invention. FIG. 5 is a table showing thresholds for grouping the menopausal progression according to a first embodiment of the present invention. FIG. 6 is a scatter diagram (plot diagram) for grouping the menopausal progression according to a first embodiment of the present invention. FIG. 7 is a diagram showing an example of a display unit for displaying the menopausal progression according to a first embodiment of the present invention.

[0031] In the first embodiment, the first basal body temperature, the first average basal body temperature, and the first menstrual cycle are used as examples. That is, in the first embodiment, the results of measurements taken by one subject are used.

[0032] 1 and 2, the menopausal progression estimation system 10 includes a sensor device 100, a first arithmetic device 200, and a second arithmetic device 300. The first arithmetic device 200 corresponds to the "computer" and the "first computer" of the present invention, and the second arithmetic device 300 corresponds to the "second computer" of the present invention.

[0033] The sensor device 100 is, for example, a core thermometer that measures the core body temperature of a woman. The sensor device 100 includes a network interface (hereinafter referred to as network IF) 101, a sensing unit 102, a storage unit 103, a control unit 104, and a power supply unit 105.

[0034] The first arithmetic device 200 is an information device such as a smartphone or tablet terminal. The first arithmetic device 200 performs calculations using the woman's basal body temperature measured by the sensor device 100. The first arithmetic device 200 includes a network IF 201, a display unit 202, a storage unit 203, a control unit 204, a power supply unit 205, and an input unit 206. The storage unit 203 corresponds to the "storage device" of the present invention.

[0035] The second arithmetic device 300 is a server, a virtual server, a cloud computing service, or the like constructed on the Internet. The second arithmetic device 300 stores the woman's basal body temperature measured by the sensor device 100 and the results of calculations performed by the first arithmetic device 200. The second arithmetic device 300 includes a network IF 301, a storage unit 302, a control unit 303, and a power supply unit 304. The storage unit 302 corresponds to the "storage device" of the present invention. It is to be noted that the storage unit 103 of the sensor device 100 can also be used as the "storage device" of the present invention.

[0036] [Sensor Device] First, the configuration of the sensor device 100 will be described. The sensor device 100 is configured to measure deep body temperature by, for example, contacting and fixing it to the abdomen, subclavian region, or the like while the user is asleep. The sensor device 100 outputs the maximum value of the deep body temperature as the measurement result (basal body temperature). Note that the sensor device 100 is not limited to the maximum value, and may output the average, maximum, minimum, extreme value, median, or other value of the body temperature while sleeping as the measurement result. Note that the sensor device 100 may also be configured to measure basal body temperature under the armpit or under the tongue.

[0037] The network IF 101 communicates with the network IF 201 of the first arithmetic device 200. The network IF 101 and the network IF 201 transmit and receive data via wireless communication that exchanges data over short distances, such as Bluetooth (registered trademark) or Wi-Fi (registered trademark).

[0038] The sensing unit 102 measures the subject's first basal body temperature. More specifically, the sensing unit 102 converts heat transmitted from the subject's skin surface into an electrical signal and detects it. The sensing unit 102 generates the first basal body temperature by processing this electrical signal.

[0039] The storage unit 103 stores the first basal body temperature measured by the sensing unit 102 .

[0040] The control unit 104 controls the calculations in the sensor device 100 , the storage of the first basal body temperature, and the input and output of data to and from the first calculation device 200 .

[0041] The power supply unit 105 supplies power to the sensor device 100. The power supply unit 105 may be a battery, a general household power supply, a commercial power supply, or the like.

[0042] [First Calculation Device] Next, the configuration of the first calculation device 200 will be described. The network IF 201 communicates with the network IF 101 of the sensor device 100 and the network IF 301 of the second calculation device 300. As described above, the network IF 201 and the network IF 101 transmit and receive data via wireless communication that exchanges data over short distances, such as Bluetooth (registered trademark) or Wi-Fi (registered trademark). The network IF 201 and the network IF 301 transmit and receive data via a network that uses Wi-Fi (registered trademark), a cellular line, or the like.

[0043] The display unit 202 displays information about the first basal body temperature, information about the first menstrual cycle, and the progression of menopause, which will be described later. The display unit 202 displays text, graphs, images, etc., making it easy for the user to visually recognize the information.

[0044] The storage unit 203 stores the first basal body temperature output from the sensor device 100. The storage unit 203 also stores grouping information. The grouping information is information for grouping (classifying) the degree of menopausal progression, which will be described later.

[0045] The control unit 204 controls the calculations in the first calculation device 200 , the storage of the first basal body temperature, and the input and output of data between the sensor device 100 and the second calculation device 300 .

[0046] The power supply unit 205 supplies power to the first arithmetic unit 200. The power supply unit 205 is, for example, a battery.

[0047] The input unit 206 is, for example, a software keyboard, command buttons, and the like.

[0048] [Second Calculation Unit] Next, a description will be given of the configuration of the second arithmetic unit 300. The network IF 301 communicates with the network IF 201 of the first arithmetic unit 200. As described above, the network IF 301 and the network IF 201 transmit and receive data using a cellular line or the like.

[0049] The storage unit 302 stores the first basal body temperature and the measurement date output from the first calculation device 200. Similarly to the storage unit 203, the storage unit 302 also stores grouping information for grouping (classifying) the degree of menopausal progression.

[0050] The control unit 303 controls the calculations in the second calculation device 300 , the storage of the first basal body temperature, and the input and output of data to and from the second calculation device 300 .

[0051] The power supply unit 304 supplies power to the second calculation unit 300 .

[0052] Using the above-described configuration, a more specific processing flow of the menopausal progression estimation system 10 will be described.

[0053] The subject measures their first basal body temperature using the sensor device 100. The control unit 104 acquires the subject's first basal body temperature measured by the sensing unit 102. The control unit 104 associates the first basal body temperature with the measurement date and stores them in the storage unit 103. The measurement date is acquired by a timing unit (not shown). The control unit 104 transmits the first basal body temperature, the measurement date, and an ID (e.g., a user ID) that can identify the subject to the first calculation unit 200 via the network IF 101.

[0054] The control unit 104 transmits the first basal body temperature and the measurement date immediately after measuring the first basal body temperature. The control unit 104 may also transmit the first basal body temperature and the measurement date at regular intervals (for example, about one week). This reduces the frequency of communication with the network IF 101. Furthermore, if the measured value of the first basal body temperature indicates an abnormal value, it is possible to manually transmit a re-measured first basal body temperature.

[0055] The first arithmetic device 200 acquires the user ID, the first basal body temperature, and the measurement date. As shown in FIG. 3A, the first arithmetic device 200 associates the user ID, the first basal body temperature, and the measurement date and stores them. If the sensor device 100 does not have a clock unit, the measurement date may be set to the date on which the first arithmetic device 200 received the first basal body temperature. Instead of the user ID, the sensor device ID may be acquired from the sensor device, and the first arithmetic device 200 may link the sensor device ID to the user ID.

[0056] Furthermore, the first arithmetic device 200 stores the first menstrual cycle. More specifically, the subject inputs the menstruation start date using the input unit 206 of the first arithmetic device 200. As described above, the menstrual cycle is the period from the first day of menstruation to the day before the start date of the next menstruation. The menstruation start date may be input using a software keyboard capable of inputting dates, or the system date may be automatically input during operation. Furthermore, the menstruation start date may be input by activating a calendar and selecting any date.

[0057] The control unit 204 accepts the input of the start of menstruation and sets a flag indicating whether or not the user is in the menstrual period (hereinafter referred to as the menstruation flag) to True. Next, the control unit 204 associates the menstruation start date with the menstruation flag True and stores it in the storage unit 203. The control unit 204 sets the menstruation flag to False after a certain period (for example, five days) has passed. In the above configuration, only the menstruation start date is input, and the day a certain period has passed since the menstruation start date is indicated as the menstruation end date. However, a configuration in which the menstruation end date is input may also be used. By inputting the menstruation end date, it is possible to accurately grasp the menstruation period.

[0058] The control unit 204 calculates the first menstrual cycle using the date of menstruation of the subject. The control unit 204 calculates the first average basal body temperature measured in the first menstrual cycle. As shown in FIG. 3(B), the control unit 204 associates a user ID that can identify the subject with the first menstrual cycle and the first average basal body temperature, and stores them in the storage unit 203. Similarly, the first arithmetic unit 200 associates the user ID, first menstrual cycle, first average basal body temperature, and menstruation flag, and transmits them to the second arithmetic unit 300. The second arithmetic unit 300 associates the user ID, first menstrual cycle, first average basal body temperature, and menstruation flag, and stores them in the storage unit 302.

[0059] It is preferable that personal information is deleted from the information stored in the storage unit 302. For example, as shown in Figures 3(A) and 3(B), the subject is represented by only the user ID.

[0060] [Processing Flow of the Calculation Device] As shown in FIG. 4, the control unit 204 performs calculations using the data shown in FIGS. 3A and 3B. The calculations described below are preferably performed after, for example, three or more first menstrual cycles have elapsed. If two or fewer first menstrual cycles have elapsed, various errors may prevent the intended results from being obtained. In this case, calculations may be performed by applying a predetermined weighting to the first basal body temperature and the first menstrual cycle. This weighting calculation may be performed using a value statistically obtained from the age of the subject, or by applying the average value of the first average basal body temperature, etc.

[0061] The first arithmetic device 200 acquires the first basal body temperature from the sensor device 100 (S11). The first arithmetic device 200 also acquires the menstruation start date input using the input unit 206.

[0062] Next, the control unit 204 calculates the deviation of the first menstrual cycle (S12). More specifically, the control unit 204 calculates the standard deviation of the first menstrual cycle. A specific example of the deviation is not limited to the standard deviation, and may be a variance. In the following, the deviation will be described as the standard deviation. The standard deviation of this first basal body temperature will be referred to as "x".

[0063] Next, the control unit 204 calculates the correlation coefficient between the first menstrual cycle and the first average basal body temperature (S13). More specifically, the correlation coefficient is calculated from the equation: correlation coefficient = (covariance between the first menstrual cycle and the first average basal body temperature) / ((standard deviation of the first menstrual cycle) x (standard deviation of the first average basal body temperature)). This correlation coefficient is designated as "y".

[0064] Here, we will explain the correlation coefficient. Generally, a menstrual cycle is divided into the number of days in the low temperature period when basal body temperature is low and the number of days in the high temperature period when basal body temperature is high. The number of days in the low temperature period fluctuates, but the number of days in the high temperature period is considered to be fixed. Therefore, the menstrual cycle fluctuates depending on the number of days in the low temperature period. In other words, the longer the number of days in the low temperature period, the longer the menstrual cycle, and therefore the lower the average basal body temperature in one cycle. On the other hand, the shorter the number of days in the low temperature period, the shorter the menstrual cycle, and therefore the higher the average basal body temperature in one cycle. In other words, the correlation coefficient y obtained from the menstrual cycle and the average basal body temperature in that cycle has a negative correlation.

[0065] On the other hand, from the early stages of menopause onwards, the number of days in the high temperature phase becomes shorter. Therefore, as the number of days in the high temperature phase becomes shorter, the number of days when basal body temperature is high also becomes shorter, and the average basal body temperature over one cycle becomes lower. In other words, the correlation coefficient y obtained from the menstrual cycle and the average basal body temperature over that cycle has a positive correlation.

[0066] Next, the control unit 204 performs clustering using the standard deviation x, the correlation coefficient y, and the grouping information stored in the storage unit 203 (S14). This grouping information is information for grouping (classifying) the degree of menopausal progression, as described above. The control unit 204 performs clustering using the thresholds shown in FIG. 5. As a result, as shown in FIG. 6, the states indicating menopause are classified into four groups based on this. In the scatter diagram (plot diagram) of FIG. 6, the x-axis represents the standard deviation of the menstrual cycle (cycle standard deviation), and the y-axis represents the correlation coefficient between the menstrual cycle and the first basal body temperature during that cycle. The threshold for the standard deviation x when clustering the menopausal stages is set as a first threshold, and the threshold for the correlation coefficient y is set as a second threshold.

[0067] The control unit 204 classifies the results into the first group and other groups shown in Fig. 5. The first group is a state in which menopause has not yet begun (first region in Fig. 6). Next, the control unit 204 classifies the group in which menopause has begun (menopause determination region) excluding the first group into a second group (second region in Fig. 6), a third group (third region in Fig. 6), and a fourth group (fourth region in Fig. 6).

[0068] Here, the center of gravity of each group region in FIG. 6 is defined. This center of gravity is the central point of each group region. The center of gravity of each group is determined as follows. For example, in the second region in FIG. 6, the point at which the sum of the distances from the multiple values ​​(standard deviation x, correlation coefficient y) determined to belong to the second group is the center of gravity.

[0069] For example, the center of gravity of three coordinates in the second group can be calculated as follows. Given coordinates a (xa, ya), coordinate b (xb, yb), and coordinate c (xc, yc), the center of gravity (xg, yg) is the point where the sum of the distance from the center of gravity to coordinate a, the distance from the center of gravity to coordinate b, and the distance from the center of gravity to coordinate c is smallest. This center of gravity is calculated for each group. In this case, the standard deviation x of the first center of gravity of the first group and the standard deviation x of the second center of gravity of the second group are smaller than the standard deviation x of the third center of gravity of the third group. Furthermore, the standard deviation x of the third center of gravity of the third group is smaller than the standard deviation x of the fourth center of gravity of the fourth group. This is thought to be due to the increasing variation in menstrual cycles as menopause progresses, and was set based on this.

[0070] Next, the control unit 204 displays the degree of menopause progression determined in step S14 on the display unit 202 as shown in Fig. 7 (S15). A specific example of displaying the degree of menopause progression will be described below.

[0071] First Group: The standard deviation x is less than the first threshold value "10" and the correlation coefficient y is less than the second threshold value "-0.6". In this case, the menstrual cycle state corresponds to a normal menstrual cycle. Menopause is classified as not having started.

[0072] Second group: The standard deviation x is less than the first threshold value "10" and the correlation coefficient y is equal to or greater than the second threshold value "-0.6." In this case, the menstrual cycle state corresponds to a state in which the menstrual cycle is shortening. The menopause is classified as an early stage.

[0073] - Third group: The standard deviation x is equal to or greater than the first threshold "10" and less than the third threshold "15." In this case, the state of the menstrual cycle corresponds to a state in which some menstruation is anovulatory menstruation. Menopause is classified as ranging from the early stage to the middle stage. This anovulatory menstruation corresponds to a case in which the first basal body temperature described above is not divided into two phases, a low temperature phase and a high temperature phase. More specifically, anovulatory menstruation refers to a case in which ovulation does not occur and menstrual-like bleeding occurs. In this case, the first basal body temperature indicates a low temperature phase state until bleeding occurs.

[0074] Fourth Group: The standard deviation x is equal to or greater than the third threshold value of 15. In this case, the menstrual cycle state corresponds to oligomenorrhea. The menopause is classified as being in the mid- or later stage.

[0075] That is, the menopausal stage progresses in stages from Group 1 to Group 4. More specific numerical values ​​will be used for the explanation.

[0076] (Pattern 1) The standard deviation x of the first menstrual cycle up to the nth cycle (n is 3 or more) is 3. The correlation coefficient y determined by the first menstrual cycle and the first average basal body temperature in the nth cycle is −0.625.

[0077] The results obtained based on this standard deviation x and correlation coefficient y fall into the first group (first region) shown in Figures 6 and 7. Therefore, the menstrual cycle is considered to be normal, and pattern 1 indicates a state in which menopause has not yet begun.

[0078] (Pattern 2) The standard deviation x of the first menstrual cycle up to the nth cycle (n is 3 or more) is 5. The correlation coefficient y calculated between the first menstrual cycle and the first average basal body temperature in the nth cycle is −0.5.

[0079] The results obtained based on this standard deviation x and correlation coefficient y fall into the second group (second region) shown in Figures 5 and 6. Therefore, it is considered that the menstrual cycle is shortening, and pattern 2 indicates the early stage of menopause.

[0080] (Pattern 3) The standard deviation x of the first menstrual cycle up to the nth cycle (n is 3 or more) is 12. The correlation coefficient y calculated using the first menstrual cycle in the nth cycle and the average first cycle body temperature is -0.5.

[0081] The results obtained based on this standard deviation x and correlation coefficient y fall into the third group (third region) shown in Figures 5 and 6. Therefore, since some menstruation in multiple menstrual cycles is considered to be anovulatory menstruation, Pattern 3 indicates a state from early to mid-menopause.

[0082] (Pattern 4) The standard deviation x of the first menstrual cycle up to the nth cycle (n is 3 or more) is 28. The correlation coefficient y calculated using the first menstrual cycle in the nth cycle and the average first cycle body temperature is -0.5.

[0083] The results obtained based on this standard deviation x and correlation coefficient y correspond to the fourth group (fourth region) shown in Figures 5 and 6. Therefore, it is considered to be oligomenorrhea, and pattern 4 indicates a state from mid-menopause onwards.

[0084] In this way, the menopausal progression estimation system 10 can classify (estimate) the stage of menopause.

[0085] A more specific example of the display in the state of Pattern 2 will be described with reference to Fig. 7. Fig. 7 shows the display unit 202 of the first arithmetic device 200. The display unit 202 displays that the woman is in the early stage of menopause (early menopause). Note that this state of menopause may also be displayed using a numerical value.

[0086] In this way, the person taking the measure can visually recognize the progression of menopause. Furthermore, the person taking the measure can recognize the progression of menopause based on objectively determined values, rather than on subjective judgment. Therefore, the menopausal progression estimation system 10 can easily determine the progression of menopause through the simple operation of the person taking the measure, such as measuring basal body temperature and recording the date of the start of menstruation.

[0087] Menopause generally progresses in stages. That is, by having the person measuring the first basal body temperature continuously and recording the date of menstruation, the menopausal progression estimation system 10 can easily determine the progression of menopause. For example, if a woman transitions from a state where menopause has not yet begun to a state where menopause is in the mid-period, it is likely that menstrual irregularities are not due to menopause. Using these results, the person measuring the measurement can detect the possibility of other diseases, such as uterine cancer, cervical cancer, or uterine fibroids, at an early stage.

[0088] Also, as shown in FIG. 2 , a configuration in which calculations are performed in the control unit 204 of the first arithmetic device 200 is shown. However, both the first arithmetic device 200 and the second arithmetic device 300 may be user devices, or both may be cloud-based. In this case, the first arithmetic device 200 and the second arithmetic device 300 may share a common power supply unit and control unit. By storing user data in the cloud, data from multiple people can be processed together, as described below, thereby improving estimation accuracy. Furthermore, a configuration in which calculations are performed in the sensor device 100 or the second arithmetic device 300 may be used. When the sensor device 100 performs calculations, the sensor device 100 corresponds to the "menopausal progression assessment device" of the present invention. Furthermore, calculations of the menopausal progression level may be performed in a distributed manner among the sensor device 100, the first arithmetic device 200, and the second arithmetic device 300. Furthermore, calculations of the menopausal progression level may be performed in a distributed manner among the first arithmetic device 200 and the second arithmetic device 300.

[0089] Furthermore, the transmission and reception of the first basal body temperature and the measurement date between the sensor device 100 and the first computing device 200 may be configured such that the sensor device 100 transmits the temperature immediately after measurement, or may transmit the first basal body temperature and the measurement date manually, for example, by pressing a command button. Alternatively, the first computing device 200 may access the first basal body temperature and the measurement date stored in the storage unit 103 of the sensor device 100 (automatic reading of the first basal body temperature and the measurement date). Furthermore, if the network IF 101 of the sensor device 100 can be connected to the second computing device 300, the sensor device 100 may transmit the first basal body temperature and the measurement date to the second computing device 300. Furthermore, if the sensor device 100 does not have a network IF 101, the sensor device value may be manually input into the input unit of the first computing device 200, or the temperature value of the sensor device may be photographed with a camera (not shown) of the first computing device 200, the temperature information may be read by image analysis, and the temperature information may be recorded in the storage unit 203 of the first computing device 200.

[0090] Furthermore, the above configuration is described assuming that the first basal body temperature is measured by a healthy subject. However, if the subject has a cold or other illness, the first basal body temperature may be higher than normal. In this case, it is preferable to be able to input the subject's physical condition using the input unit 206. If there is a day on which the subject's physical condition is input, the first calculation device 200 may exclude this value from the calculation. Alternatively, the first calculation device 200 may use the average value of the first basal body temperature. Similarly, the same processing may be performed if the subject forgets to measure the first basal body temperature.

[0091] Furthermore, menopause can affect the amount of menstrual flow. The input unit 206 may have a function for accepting input of the amount of menstrual flow. For example, the input unit 206 may accept input such as "light," "medium," or "heavy." By taking into account the influence of the amount of menstrual flow, it becomes possible to more accurately determine the progression of menopause.

[0092] Furthermore, after the onset of menopause, the device may have a function to record subjective symptoms of menopause such as "hot flush," "easily sweating," "irritability," "headache," "dizziness," etc. By reflecting the effects of these menopausal symptoms, it becomes possible to more accurately determine the progression of menopause.

[0093] The control unit 104 of the sensor device 100, the control unit 204 of the first arithmetic unit 200, and the control unit 303 of the second arithmetic unit 300 are configured by an arithmetic processing device such as a computer device. The storage unit 203 of the first arithmetic unit 200 or the storage unit 302 of the second arithmetic unit 300 stores a menopausal progression estimation program. The program may also be stored in both. The arithmetic processing device executes the menopausal progression estimation program to realize the functions of the above-mentioned functional units.

[0094] [Modification of First Embodiment] A menopausal progression estimation system, a menopausal progression estimation device, a menopausal progression estimation method, and a menopausal progression estimation program according to a modification of the first embodiment of the present invention will be described.

[0095] The menopausal progression estimation system, menopausal progression estimation device, menopausal progression estimation method, and menopausal progression estimation program according to the modified example of the first embodiment differ from the first embodiment in that communication is performed between the sensor device 100 and the second calculation device 300. Other configurations of the menopausal progression estimation system, menopausal progression estimation device, menopausal progression estimation method, and menopausal progression estimation program according to the modified example of the first embodiment are the same as those according to the first embodiment, and descriptions of similar parts will be omitted.

[0096] The sensor device 100 communicates with the second arithmetic unit 300. More specifically, the person taking the measurement measures their first basal body temperature using the sensor device 100. The control unit 104 acquires the person's first basal body temperature measured by the sensing unit 102. The control unit 104 associates the first basal body temperature with the measurement date and stores it in the storage unit 103. The control unit 104 transmits the first basal body temperature, the measurement date, and an ID (e.g., a user ID) that can identify the person taking the measurement to the second arithmetic unit 300 via the network IF 101.

[0097] That is, the sensor device 100 and the second arithmetic device 300 communicate with each other without going through the first arithmetic device 200. This configuration can reduce memory consumption in the first arithmetic device 200. Furthermore, compared to the first embodiment, communication with the first arithmetic device 200 can be omitted, so the number of communications can be reduced. This reduces the probability that the second arithmetic device 300 will not be able to acquire the data measured by the sensor device 100 due to a communication error.

[0098] [Second Embodiment] A menopausal progression estimation system, a menopausal progression estimation device, a menopausal progression estimation method, and a menopausal progression estimation program according to a second embodiment of the present invention will be described with reference to the drawings. The menopausal progression estimation system, the menopausal progression estimation device, the menopausal progression estimation method, and the menopausal progression estimation program according to the second embodiment differ from the first embodiment in that the methods for setting the first and second thresholds are different. Other configurations of the menopausal progression estimation system, the menopausal progression estimation device, the menopausal progression estimation method, and the menopausal progression estimation program according to the second embodiment are the same as those according to the first embodiment, and descriptions of similar parts will be omitted.

[0099] Fig. 8(A) is a table showing the relationship between menstruation and basal body temperature according to a second embodiment of the present invention, and Fig. 8(B) is a table showing the relationship between menstrual cycle and average body temperature according to a second embodiment of the present invention. Fig. 9 is a flowchart showing an example of determining the stage of menopause according to the second embodiment of the present invention. Fig. 10 is a table showing thresholds for grouping the stage of menopause according to the second embodiment of the present invention. Fig. 11 is a scatter diagram (plot diagram) for grouping the stage of menopause according to the second embodiment of the present invention.

[0100] In the second embodiment, a second basal body temperature, a second average basal body temperature, a second menstrual cycle, and a second average menstrual cycle are used for explanation. That is, the second embodiment uses data obtainable from multiple subjects, rather than only data obtainable from one subject.

[0101] For example, a user ID is assigned to each of n users. The second basal body temperature is calculated from the basal body temperatures of each of the n users (users). The second average basal body temperature is the average of the second basal body temperatures. The second menstrual cycle is determined from the second menstrual cycles of multiple users (users). The second average menstrual cycle is the average of the second menstrual cycles.

[0102] As shown in FIG. 9, the control unit 204 performs calculation processing using the data shown in FIGS. 8(A) and 8(B).

[0103] The first arithmetic device 200 acquires the second basal body temperature from the sensor device 100 (S21). The first arithmetic device 200 also acquires the menstruation start date input using the input unit 206.

[0104] Next, the control unit 204 calculates the standard deviation of the second menstrual cycle for each of the multiple user IDs (S22). More specifically, the control unit 204 calculates the standard deviation of the second menstrual cycle for each of the multiple user IDs. The standard deviation of the second basal body temperature calculated for each of the multiple user IDs is designated as "x1."

[0105] Next, the control unit 204 calculates the correlation coefficient between the second menstrual cycle and the second average basal body temperature for each of the multiple user IDs (S23). More specifically, the correlation coefficient is calculated from the equation: correlation coefficient = (covariance of the second menstrual cycle and the second average basal body temperature) / ((standard deviation of the second menstrual cycle) x (standard deviation of the second average basal body temperature)). The correlation coefficient calculated for each of the multiple user IDs is designated as "y1".

[0106] 10 and 11, a first threshold value and a second threshold value are used to classify the stage of menopause. Based on expert knowledge, the threshold value for the standard deviation x1 when clustering the stages of menopause is set as the first threshold value α, and the threshold value for the correlation coefficient y1 is set as the second threshold value β (S24).

[0107] The first threshold value α and the second threshold value β are set by a medical professional, such as a doctor or nurse. The medical professional may set the first threshold value α and the second threshold value β based on the subject's age, medical history, lifestyle habits such as smoking and drinking, etc. Furthermore, the medical professional may set the first threshold value α and the second threshold value β using second average basal body temperature and second average menstrual cycles obtained from multiple subjects who are close in age to the subject. The control unit 204 updates the grouping information stored in the storage unit 203. Furthermore, the control unit 303 updates the grouping information stored in the storage unit 302 upon receiving this grouping information from the first calculation device 200. The grouping information is obtained from the subject's age, medical history, lifestyle habits such as smoking and drinking, and multiple subjects. The first average basal body temperature, first average menstrual cycle, second average basal body temperature, and second average menstrual cycle correspond to "statistical values" in the present invention. These statistical values ​​are updated using values ​​calculated from numerical properties, regularity, or irregularity.

[0108] It is preferable that the first threshold value α and the second threshold value β are set and stored by the subject to be classified this time before the subject performs the classification.

[0109] Next, the control unit 204 performs clustering using the first threshold value α, the second threshold value β, the standard deviation x1, and the correlation coefficient y1 (S25). More specifically, as shown in Figures 10 and 11, the conditions indicative of menopause are classified into four groups.

[0110] Next, the control unit 204 displays the stage of menopause classified (estimated) in step S25 on the display unit 202 (S26). A specific example of displaying the stage of menopause is shown below.

[0111] First group (first region in FIG. 11): The standard deviation x1 is less than the first threshold value α, and the correlation coefficient y1 is less than the second threshold value β. In this case, the menstrual cycle is normal. Menopause is classified as not having started.

[0112] Second group (second region in FIG. 11): The standard deviation x1 is less than the first threshold α, and the correlation coefficient y1 is equal to or greater than the second threshold β. In this case, the menstrual cycle state corresponds to a state in which the menstrual cycle is shortening. The menopause is classified as an early stage.

[0113] Third group (third region in FIG. 11): The standard deviation x1 is equal to or greater than the first threshold value α and is less than the third threshold value 15. In this case, the state of the menstrual cycle corresponds to a state in which some menstruation is anovulatory menstruation.

[0114] Fourth group (fourth region in FIG. 11): The standard deviation x1 is equal to or greater than the third threshold value of 15. In this case, the menstrual cycle state corresponds to oligomenorrhea. The menopause is classified as a mid- or later stage.

[0115] Even with this structure, the person being measured can visually recognize the progression of menopause. Furthermore, the person being measured can recognize the progression of menopause based on objectively determined values, rather than subjective judgment. Therefore, the person being measured can easily determine the progression of menopause through simple operations such as measuring basal body temperature and recording the start date of menstruation. Furthermore, in the second embodiment, the number of people being measured can be increased compared to the first embodiment, and the second average basal body temperature and second average menstrual cycle can be determined. Furthermore, in the second embodiment, a threshold value for grouping (classification) can be set. In other words, the progression of menopause can be more accurately determined based on classification parameters obtained from multiple people.

[0116] In the above configuration, an example is shown in which the third threshold value is a fixed value of 15. However, the third threshold value 15 does not have to be a fixed value and may be set according to the situation of the user.

[0117] [Third Embodiment] A menopausal progression estimation system, menopausal progression estimation device, menopausal progression estimation method, and menopausal progression estimation program according to a third embodiment of the present invention will be described with reference to the drawings. The menopausal progression estimation system, menopausal progression estimation device, menopausal progression estimation method, and menopausal progression estimation program according to the third embodiment differ from the first embodiment in that they include an AI calculation unit and use this AI calculation unit to determine the progression of menopause. Other configurations of the menopausal progression estimation system, menopausal progression estimation device, menopausal progression estimation method, and menopausal progression estimation program according to the third embodiment are the same as those of the first embodiment, and descriptions of similar parts will be omitted.

[0118] Fig. 12 is a configuration diagram of a menopausal progression estimation system according to a third embodiment of the present invention. Fig. 13 is a flowchart showing an example of determining the menopausal progression according to the third embodiment of the present invention. Fig. 14 is a tree diagram for determining the menopausal progression according to the third embodiment of the present invention.

[0119] As shown in Fig. 12, the first calculation device 200B includes an AI calculation unit 207. The AI ​​calculation unit 207 generates criteria for determining the degree of progression of the subject's menopause. A more specific processing flow will be described below. The AI ​​calculation unit 207 uses, for example, a decision tree as a machine learning algorithm.

[0120] The control unit 204 performs calculation processing using the data shown in FIGS. 3A and 3B (see the flowchart in FIG. 13).

[0121] The first arithmetic device 200 acquires the first basal body temperature from the sensor device 100 (S31). The first arithmetic device 200 also acquires the menstruation start date input using the input unit 206.

[0122] Next, the control unit 204 calculates the standard deviation x of the first basal body temperature (S32).

[0123] Next, the control unit 204 determines the correlation coefficient between the first menstrual cycle and the first average basal body temperature (S33).

[0124] Next, the AI ​​calculation unit 207 sets the multiple groups to be classified as objective variables. The AI ​​calculation unit 207 also sets the standard deviation x and the correlation coefficient y as explanatory variables.

[0125] The AI ​​calculation unit 207 generates a prediction model that classifies into four groups based on the standard deviation x and the correlation coefficient y using a decision tree (decision tree learning) in machine learning, as shown in FIG. 14, for example. A more specific structure will be explained using the second group (the second group in FIG. 5) as an example. First, the objective variable is set to be the second group (early menopause). Next, a threshold value for the standard deviation x is calculated as an explanatory variable. Furthermore, a threshold value for the correlation coefficient y is calculated as an explanatory variable.

[0126] Through this control, the threshold value of the standard deviation x and the threshold value of the correlation coefficient y are estimated and set by AI (S34).

[0127] It is preferable that the threshold value of the standard deviation x and the threshold value of the correlation coefficient y by AI be set and stored before the subject who will be performing the classification this time performs the classification.

[0128] Next, the control unit 204 performs clustering using the threshold value of the standard deviation x and the threshold value of the correlation coefficient y learned by the AI, and the standard deviation x and the correlation coefficient y (S35). The control unit 204 performs clustering using the threshold values ​​shown in Fig. 5, for example. As a result, the control unit 204 can classify the conditions indicating menopause into four groups (see Fig. 6).

[0129] Next, the control unit 204 displays the stage of menopause classified (estimated) in step S35 on the display unit 202 (S36).

[0130] Even with this structure, the person being measured can visually recognize the progression of menopause. Furthermore, the person being measured can recognize the progression of menopause based on objectively determined values, rather than subjective judgments. Therefore, the person being measured can easily determine the progression of menopause through simple operations such as measuring basal body temperature and recording the start date of menstruation. In the third embodiment, compared to the first embodiment, it is possible to set a threshold value for classification using the path from the root objective variable to the endpoint as a predicted value. Furthermore, in the third embodiment, it is possible to determine the final progression of menopause and predict the progression of menopause.

[0131] In the above configuration, an example has been described in which a decision tree is used as the algorithm used by the AI ​​calculation unit 207. However, the algorithm is not limited to a decision tree, and an SVM (support vector machine), a random forest, or the like may also be used.

[0132] [Modification] A menopausal progression estimation system, menopausal progression estimation device, menopausal progression estimation method, and menopausal progression estimation program according to a modification of the present invention will be described with reference to the drawings. The menopausal progression estimation system, menopausal progression estimation device, menopausal progression estimation method, and menopausal progression estimation program according to the modification differ from those of the first embodiment in the area of ​​the groups used during clustering. Other configurations of the menopausal progression estimation system, menopausal progression estimation device, menopausal progression estimation method, and menopausal progression estimation program according to the modification are the same as those of the first embodiment, and descriptions of similar parts will be omitted.

[0133] FIG. 15 is a scatter diagram (plot diagram) for grouping the degree of menopausal progression according to a modified example of the present invention. In FIG. 6 of the first embodiment, the regions into which the first, second, third, and fourth groups are classified are divided by regions perpendicular to the x-axis and y-axis. However, in the scatter diagram (plot diagram) of the modified example, the regions into which the first, second, third, and fourth groups are classified are divided by regions that are not perpendicular to the x-axis and y-axis. More specifically, the regions in each group may be circular, polygonal, or the like, from the center of gravity. Furthermore, the regions in each group may have shapes that partially overlap.

[0134] Even with this structure, the person being measured can visually recognize the progression of menopause. Furthermore, the person being measured can recognize the progression of menopause based on objectively determined values, rather than subjective judgments. Therefore, the person being measured can easily determine the progression of menopause through simple operations such as measuring basal body temperature and recording the start date of menstruation. Furthermore, since the ranges of each group can be defined more flexibly, the progression of menopause can be determined more accurately.

[0135] The configurations of the above-described embodiments can be combined as appropriate, and effects according to each combination can be achieved.

[0136] The correspondence between the configuration of this invention and the above-mentioned configuration is described below. [Note] <1> A menopausal progression estimation system comprising: a control unit; and a storage device, wherein the storage device stores a plurality of menstrual cycle periods of a subject and a plurality of basal body temperatures of the subject, and the control unit estimates the progression of menopause of the subject based on the plurality of menstrual cycle periods and the plurality of basal body temperatures.

[0137] <2> The menopausal progression estimation system described in <1>, wherein the control unit calculates a correlation coefficient between each menstrual cycle period of the plurality of menstrual cycles and the average values ​​of the plurality of basal body temperatures in the one cycle, and estimates the menopausal progression of the subject based on the correlation coefficient.

[0138] <3> The menopausal progression estimation system according to <2>, wherein the control unit calculates deviations in the plurality of menstrual cycles, and estimates the degree of menopausal progression of the subject based on the deviations.

[0139] <4> The menopausal progression estimation system according to <3>, wherein the deviation is a standard deviation.

[0140] <5> The menopausal progression estimation system described in <3> or <4>, wherein the storage device sets a region indicated by the correlation coefficient as the y-axis and the deviation as the x-axis, and includes a first region for determining that the menopause has not started and a menopause determination region, and stores grouping information having a plurality of groups in which points indicated by the correlation coefficient and the deviation are classified into the first region or the menopause determination region.

[0141] <6> The menopausal progression estimation system according to <5>, wherein the control unit estimates that the subject is in the menopausal stage if the point in the grouping information is within the menopausal stage determination region.

[0142] <7> The menopausal progression estimation system described in <6>, wherein the menopausal assessment area has a second area, a third area, and a fourth area, the value of the center of gravity of the second area on the x-axis is smaller than the value of the center of gravity of the third area on the x-axis, and the value of the center of gravity of the third area on the x-axis is smaller than the value of the center of gravity of the fourth area on the x-axis, and the control unit estimates that the person's menopause is progressing in the order of the second area, the third area, and the fourth area.

[0143] <8> The menopausal progression estimation system described in <7>, wherein the correlation coefficient of the first region is less than a first threshold and the deviation of the first region is less than a second threshold; the correlation coefficient of the second region is equal to or greater than the first threshold and the deviation of the second region is less than the second threshold; the deviation of the third region is equal to or greater than the second threshold and less than a third threshold; and the deviation of the fourth region is equal to or greater than the third threshold.

[0144] <9> The menopausal progression estimation system described in <5>, wherein the control unit updates the grouping information using the subjective symptoms of the person being measured or the diagnosis results of a doctor, and statistical values ​​of the person's menstrual cycle and basal body temperature.

[0145] <10> The menopausal progression estimation system described in <5>, wherein the control unit updates the grouping information using subjective symptoms of a person other than the person measuring, or a doctor's diagnosis, and statistical values ​​of the menstrual cycle and basal body temperature of a person other than the person measuring.

[0146] <11> The menopausal progression estimation system according to any one of <1> to <10>, further comprising a display unit that displays the degree of menopausal progression of the person being measured, wherein the control unit causes the display unit to display the degree of progression.

[0147] <12> The menopausal progression estimation system according to any one of <1> to <11>, further comprising a sensor device that continuously measures a plurality of body temperatures of the subject.

[0148] <13> A menopausal progression estimation device comprising: a control unit; a storage device; and a display unit, wherein the storage device stores a plurality of menstrual cycles of the subject and a plurality of basal body temperatures of the subject, and the control unit estimates the menopausal progression of the subject based on the plurality of menstrual cycles and the plurality of basal body temperatures, and displays the menopausal progression on the display unit.

[0149] <14> A method for estimating menopausal progression, comprising: a step of storing a plurality of menstrual cycles of a person and a plurality of basal body temperatures of the person; and a step of estimating the menopausal progression of the person based on the plurality of menstrual cycles and the plurality of basal body temperatures.

[0150] <15> A menopausal progression estimation program that causes a computer to execute the steps of: storing a plurality of menstrual cycles of a person and a plurality of basal body temperatures of the person; and estimating the menopausal progression of the person based on the plurality of menstrual cycles and the plurality of basal body temperatures.

[0151] <16> A menopausal progression estimation program that causes a first computer to execute the steps of: storing a plurality of menstrual cycles of a person being measured and a plurality of basal body temperatures of the person being measured; transmitting the plurality of menstrual cycles and the plurality of basal body temperatures to a second computer; and receiving the menopausal progression of the person being measured estimated by the second computer based on the plurality of menstrual cycles and the plurality of basal body temperatures.

[0152] 10...Menopausal progression estimation system 100...Sensor device 101, 201, 301...Network IF 102...Sensing unit 103...Storage unit 104...Control unit 105...Power supply unit 200, 200B...First calculation unit 202...Display unit 203...Storage unit 204...Control unit 205...Power supply unit 206...Input unit 207...AI calculation unit 300...Second calculation unit 302...Storage unit 303...Control unit 304...Power supply unit

Claims

1. A menopausal progression estimation system comprising: a control unit; and a memory device, wherein the memory device stores a plurality of menstrual cycles of a person and a plurality of basal body temperatures of the person, and the control unit estimates the progression of menopause of the person based on the plurality of menstrual cycles and the plurality of basal body temperatures.

2. The menopausal progression estimation system of claim 1, wherein the control unit calculates a correlation coefficient between a menstrual cycle in one of the plurality of menstrual cycles and an average value of the plurality of basal body temperatures in the one cycle, and estimates the menopausal progression of the subject based on the correlation coefficients.

3. The menopausal progression estimation system according to claim 2, wherein the control unit calculates deviations in the multiple menstrual cycles and estimates the menopausal progression of the subject based on the deviations.

4. The menopausal progression estimation system according to claim 3, wherein the deviation is a standard deviation.

5. The menopausal progression estimation system of claim 3 or claim 4, wherein the storage device sets a region indicated with the correlation coefficient on the y-axis and the deviation on the x-axis, and includes a first region in which it is determined that menopause has not begun and a menopause determination region, and stores grouping information having a plurality of groups in which points indicated by the correlation coefficient and the deviation are classified into the first region or the menopause determination region.

6. The menopausal progression estimation system of claim 5, wherein the control unit estimates that the subject is progressing through menopause if the point in the grouping information is within the menopausal determination region.

7. The menopause progression estimation system of claim 6, wherein the menopause determination area has a second area, a third area, and a fourth area, the value of the center of gravity of the second area on the x-axis is smaller than the value of the center of gravity of the third area on the x-axis, and the value of the center of gravity of the third area on the x-axis is smaller than the value of the center of gravity of the fourth area on the x-axis, and the control unit estimates that the person's menopause is progressing in the order of the second area, the third area, and the fourth area.

8. The menopausal progression estimation system of claim 7, wherein the correlation coefficient of the first region is less than a first threshold and the deviation of the first region is less than a second threshold, the correlation coefficient of the second region is equal to or greater than the first threshold and the deviation of the second region is less than the second threshold, the deviation of the third region is equal to or greater than the second threshold and less than a third threshold, and the deviation of the fourth region is equal to or greater than the third threshold.

9. The menopausal progression estimation system of claim 5, wherein the control unit updates the grouping information using the subjective symptoms of the person taking the measurement or the diagnosis by a doctor and statistical values ​​of the person's menstrual cycle and basal body temperature.

10. The menopausal progression estimation system of claim 5, wherein the control unit updates the grouping information using subjective symptoms of a person other than the person measuring, or a doctor's diagnosis, and statistical values ​​of the menstrual cycle and basal body temperature of a person other than the person measuring.

11. A menopausal progression estimation system as described in any one of claims 1 to 10, further comprising a display unit that displays the degree of menopausal progression of the person being measured, wherein the control unit causes the display unit to display the degree of progression.

12. A menopausal progression estimation system as described in any one of claims 1 to 11, comprising a sensor device that continuously measures a plurality of body temperatures of the subject.

13. A menopausal progression estimation device comprising a control unit, a storage device, and a display unit, wherein the storage device stores a plurality of menstrual cycles of the person being measured and a plurality of basal body temperatures of the person being measured, and the control unit estimates the degree of menopausal progression of the person being measured based on the plurality of menstrual cycles and the plurality of basal body temperatures, and displays the degree of menopausal progression on the display unit.

14. A method for estimating menopausal progression, comprising the steps of: storing a plurality of menstrual cycles of a person and a plurality of basal body temperatures of the person; and estimating the menopausal progression of the person based on the plurality of menstrual cycles and the plurality of basal body temperatures.

15. A menopausal progression estimation program that causes a computer to execute the steps of: storing a plurality of menstrual cycles of a person and a plurality of basal body temperatures of the person; and estimating the menopausal progression of the person based on the plurality of menstrual cycles and the plurality of basal body temperatures.

16. A menopausal progression estimation program that causes a first computer to execute the steps of: storing a plurality of menstrual cycles of a person and a plurality of basal body temperatures of the person; transmitting the plurality of menstrual cycles and the plurality of basal body temperatures to a second computer; and receiving the menopausal progression of the person estimated by the second computer based on the plurality of menstrual cycles and the plurality of basal body temperatures.

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