JP2007068839A - Electronic thermometer for women, and method and program for electronic thermometer for women - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an electronic thermometer for women with which precise prediction is performed in a short-time for measuring. <P>SOLUTION: The electronic thermometer for women has: an input means for inputting menstruation item data; a predicted value derivation means for deriving a plurality of predicted values of equilibrium temperature according to a plurality of prediction formulas from a measured value; a selection means for selecting a single prediction formula from the plurality of prediction formulas based on the respective change with time of the plurality of predicted values; a storage means for storing the predicted values and the menstruation item data; and a prediction means for predicting the next menstruation date based on the predicted values and the menstruation item data. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an easy-to-use electronic thermometer for women, and more particularly to an electronic thermometer for women having a body temperature prediction function at high speed.

A woman's basal body temperature periodically has two phases, a high temperature phase and a low temperature phase, and a female thermometer is used to measure the basal body temperature. By recording a basal body temperature daily with a female thermometer and creating a trend graph, the measurer can know the cycle of the high temperature phase and the low temperature phase. Further, there has been disclosed an electronic thermometer that has a function of not only measuring body temperature but also recording the measured body temperature and creating a trend graph itself, and an estimation function for estimating from a record of body temperature obtained by measuring the next physiological date, etc. (Patent Document 1). Moreover, if the prediction day corresponds to a high-temperature phase, a technique for further improving the prediction accuracy of the next menstrual day by making a prediction based on the last ovulation day is disclosed (Patent Document 2).
JP 61-159934 A JP 2000-88661 A

  However, the high temperature phase and the low temperature phase are actually only a minute temperature difference, and it is necessary to measure the basal body temperature with high accuracy (for example, 1/100 degree) in order to correctly determine the two phases. For this reason, an actually measured thermometer is usually used to measure the basal body temperature. However, in order to accurately measure the body temperature with an actually measured thermometer, it is necessary to spend a sufficient time (for example, 10 minutes) until the equilibrium temperature is reached. Therefore, a long time is required until the measurement of the basal body temperature is completed, and the burden on the measurer is large.

  The present invention has been made in view of the above problems, and an object of the present invention is to realize a female electronic thermometer capable of highly accurate prediction in a shorter measurement time and to reduce the burden on the measurer.

  In an electronic thermometer for women, input means for inputting physiological data, predicted value deriving means for deriving a plurality of predicted values of equilibrium temperature from a measured value of the temperature detected by the temperature sensing element according to a plurality of prediction formulas, and a plurality of predictions A selection means for selecting a single prediction formula from a plurality of prediction formulas based on each time-dependent change of the value, a prediction value derived based on the selected prediction formula, and the input physiological matter data together with the date And storing means for storing each time, and predicting means for predicting the next menstruation date based on the stored predicted value and physiological data.

  In an electronic thermometer for women, input means for inputting physiological data, predicted value deriving means for deriving a plurality of predicted values of equilibrium temperature from a measured value of the temperature detected by the temperature sensing element according to a plurality of prediction formulas, and a plurality of predictions A selection means for selecting a single prediction formula from a plurality of prediction formulas based on each time-dependent change of the value, a prediction value derived based on the selected prediction formula, and the input physiological matter data together with the date And storing means for storing each of them, and predicting means for predicting the next ovulation day based on the stored predicted value and physiological data.

  In an electronic thermometer for women, input means for inputting physiological data, predicted value deriving means for deriving a plurality of predicted values of equilibrium temperature from a measured value of the temperature detected by the temperature sensing element according to a plurality of prediction formulas, and a plurality of predictions A selection means for selecting a single prediction formula from a plurality of prediction formulas based on each time-dependent change of the value, a prediction value derived based on the selected prediction formula, and the input physiological matter data together with the date Storage means for storing each of them, and prediction means for predicting the expected date of delivery based on the stored predicted values and physiological data.

  In an electronic thermometer for women, input means for inputting physiological data, predicted value deriving means for deriving a plurality of predicted values of equilibrium temperature from a measured value of the temperature detected by the temperature sensing element according to a plurality of prediction formulas, and a plurality of predictions A selection means for selecting a single prediction formula from a plurality of prediction formulas based on each time-dependent change of the value, a prediction value derived based on the selected prediction formula, and the input physiological matter data together with the date Storage means for storing each of the data, and estimation means for estimating the first day of the menstrual day based on the stored predicted value and physiological data.

  In an electronic thermometer for women, input means for inputting physiological data, predicted value deriving means for deriving a plurality of predicted values of equilibrium temperature from a measured value of the temperature detected by the temperature sensing element according to a plurality of prediction formulas, and a plurality of predictions A selection means for selecting a single prediction formula from a plurality of prediction formulas based on each time-dependent change of the value, a prediction value derived based on the selected prediction formula, and the input physiological matter data together with the date Storage means for storing each of the data, and estimation means for estimating the date of ovulation based on the stored predicted value and physiological data.

  Further, the selection means selects a prediction formula with the smallest change in predicted value over time.

  In an electronic thermometer for women, input means for inputting physiological data, predicted value deriving means for deriving a plurality of predicted values of the equilibrium temperature from a measured value of the temperature detected by the temperature sensing element according to a plurality of prediction formulas, A selection unit that selects a single prediction formula from a plurality of prediction formulas based on changes over time, a prediction value derived based on the selected prediction formula, and input physiological data are stored for each date. It has a memory | storage means and the prediction means which estimates the next menstruation date based on the memorize | stored predicted value and physiological matter data, It is characterized by the above-mentioned.

  Here, the plurality of prediction formulas are set to correspond to a plurality of groups divided into groups according to the characteristics of actual measurement values with time.

  Further, the temperature measuring element and its peripheral part have a small heat capacity.

  In the control method of the female thermometer for women, an input step for inputting physiological data, a predicted value derivation step for deriving a plurality of predicted values of the equilibrium temperature from a measured value of the temperature detected by the temperature sensing element according to a plurality of prediction formulas, A selection step of selecting a single prediction formula from a plurality of prediction formulas based on changes over time of each of the plurality of prediction values, a prediction value derived based on the selected prediction formula, and input physiological data In addition, the method includes a storing step of storing for each date, and a predicting step of predicting the next menstrual date based on the stored predicted value and physiological data.

  In the control program for women's electronic thermometers, the program code for executing the input process to input physiological data and the predicted values of the equilibrium temperature are derived from the measured values of the temperature detected by the temperature sensor according to the multiple prediction formulas. Program code for executing a predicted value derivation step, and program code for executing a selection step of selecting a single prediction formula from a plurality of prediction formulas based on respective temporal changes of the plurality of prediction values, A program code for executing a storage step of storing the predicted value derived based on the selected prediction formula and the input physiological data together for each date, and the stored predicted value and physiological data And a program code for executing a prediction process for predicting the next menstrual date.

  According to the present invention, it is possible to realize an electronic thermometer for women that is easy to use and capable of predicting with high accuracy in a shorter measurement time, and the burden on the measurer can be reduced.

  Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the drawings. However, the constituent elements described in this embodiment are merely examples, and are not intended to limit the scope of the present invention only to them.

(First embodiment)
<Overview>
In this embodiment, in the electronic thermometer for women, the thermal response is improved by further reducing the heat capacity of the temperature sensor portion by predicting the equilibrium temperature based on the actual measurement value, and obtaining the actual measurement value used for the prediction. The measurement time is shortened. At that time, the selection based on the calculation results using a plurality of prediction formulas suppresses a decrease in accuracy due to fluttering of the actual measurement value accompanying an improvement in the thermal response.

<Prerequisite technology>
Electronic thermometers include prediction-type electronic thermometers in addition to actual measurements. This is when the actual measurement value is equal to or greater than the predetermined value and the temperature rise rate is equal to or greater than the predetermined value, and the prediction calculation start point is when the fluctuation of the predicted value is within the predetermined value. The prediction formula is generally given by Y = T + U, where Y is the predicted value, T is the actually measured value, and U is the amount of increase.

Various calculation methods are known as the upper amount U in this case. For example, if t is the elapsed time from the prediction start point, U = a ₁ × dT / dt + b ₁ or U = (a ₂ × t + b ₂ ) × dT + (c ₂ × t + d ₂ ).

Here, the parameters a ₁ , b ₁ , a ₂ , b ₂ , c ₂ , and d ₂ are constants selected to keep the accuracy of the added amount U constant regardless of the subject or the temperature measuring element. It is.

<Configuration of electronic thermometer for women>
FIG. 1 is a view showing an appearance of a female thermometer according to the first embodiment, and (a) is a front view (b) is a side view. FIG. 2 is an internal block diagram of the female thermometer for women according to the first embodiment.

  In FIG. 1, reference numeral 30 denotes a display unit which can display numbers, letters and figures (characters, icons, etc.). For example, it is composed of a dot matrix liquid crystal and measures date, measured body temperature, body temperature trend, etc. Information related to values and information related to device control such as battery exhaustion are displayed. Reference numeral 2 denotes a main body case formed of a synthetic resin having impact resistance and chemical resistance, in which an electronic circuit such as an arithmetic control unit 20 described later, a buzzer 31, a battery (power supply unit) 40, and the like are accommodated. Reference numeral 3 denotes a stainless steel metal cap, which is housed by fixing a temperature measuring unit for measuring body temperature by inserting it into the mouth including the thermistor 13 (see FIG. 2) and the like with an adhesive. The main body case 2 and the metal cap 3 are joined and fixed in a liquid-tight manner to an extending portion 2b extending from the main body case 2 via an adhesive. Thus, the metal cap 3 causes the thermistor 13 to transfer the body temperature (temperature) and protect the thermistor 13 from external impacts and the like. The base of the extended portion 2b is provided with a plurality of minute protrusions 2a with rounded tips, and has a non-slip prevention function. Further, the extending portion 2b has a length of about 60 mm and is bent from the main body case 2 by about 15 degrees. Because of these structures, it is stable and easy to get in the mouth.

  On the main body case 2, a function button 4 for selecting / determining various function modes to be described later, a completion button 5 for completing various settings and returning to the initial screen, and a backlight for turning on / off the backlight A button 6, a left movement button 7 and a right movement button 8 used for menu selection, graph movement, and the like, and a power button 9 for power ON / OFF are provided.

  Further, although not shown, an external communication unit (including a connector) for connecting a personal computer (PC) or the like as a host is also provided. In addition, this electronic thermometer for women has a wake-up function for prompting a regular measurement, and sounds a wake-up sound at a separately set time to prompt the user to measure the body temperature.

  The display unit 30 will be described in more detail. The display unit 30 displays the date, the measured body temperature, or the trend graph of the measured body temperature, as well as the basics such as the next ovulation date, the next menstruation date, and the expected delivery date. The date estimated based on the measurement result of body temperature is displayed. In addition, each memo item such as a physiological memorandum and a fever memo, which is input along with the measurement of the basal body temperature, is also displayed using the display unit 30. Note that FIG. 1 shows an example of display, and various screens are displayed in accordance with display and input of corresponding items.

  In FIG. 2, the electronic thermometer for ladies includes a temperature measuring unit 10 that measures temperature and outputs it as a digital value, an arithmetic control unit 20 that calculates a predicted temperature from the measured temperature and controls the electronic thermometer. The display unit 30 includes a backlight LED 30c for displaying the measurement result, and the input unit 32 receives an operation from the user.

  The temperature measurement unit 10 includes a thermistor 13 and a capacitor 14 installed in a temperature sensing unit connected in parallel, and a temperature measurement CR oscillation circuit 11, and a change in the count amount of the counter 16 corresponding to the temperature of the thermistor 13. And output the temperature as a digital quantity. In addition, the structure of this temperature measurement part 10 is an example, Comprising: It does not limit to this.

  The arithmetic control unit 20 stores the measured temperature once a day as a measured value and various set values input by the input unit 32 for a predetermined number of days (for example, 240 days), and the menstrual cycle (from the first menstruation day to the next menstruation day) RAM 23 for temporarily storing intermediate data for every day), ROM 22 for storing programs such as parameters and prediction formulas necessary for body temperature measurement, display control unit 30d for controlling display unit 30, CR oscillation for temperature measurement A counter 16 that counts oscillation signals of the circuit 11, an arithmetic processing unit 21 that performs various calculations including prediction according to a program in the ROM 22, a timer 24 that manages time, a counter 16, an arithmetic processing unit 21, and a display control unit 30d And a control circuit 50 for controlling. If a non-volatile rewritable memory is used as a temporary storage area for measurement data or the like, there is no need for battery backup.

  The input unit 32 includes the function button 4, the completion button 5, the backlight button 6, the left movement button 7, the right movement button 8, the power button 9, and the like, and receives various operations from the user.

  Furthermore, as a characteristic part of this embodiment, the heat capacity of the thermistor 13 and its peripheral part is much smaller than that of a conventional predictive electronic thermometer, and the thermal response characteristic is improved. Can be mentioned. Here, the heat capacity of the peripheral part includes the heat capacity of the metal cap 3 that covers the thermistor 13 and is in contact with the measurement site of the body, and the adhesive between the metal cap 3 and the thermistor 13, and is about 0.1 J / ° C. .

<Operational mode of electronic thermometer for women>
Fig.3 (a) is a figure which shows the transition of the operation mode of the female thermometer for women which concerns on 1st Embodiment. Each operation mode is realized by the arithmetic processing unit 21 executing a program stored in the ROM 22. FIG. 3B shows a menu selection screen.

  The pictograph (icon) 30b displayed at the bottom of the display unit 30 corresponds to various setting items of menstrual day, menstrual pain, sexual intercourse, drug intake, fever, and cage in order from the left. It is selected by operating the left movement button 7 and the right movement button 8. Note that the currently selected pictograph is displayed surrounded by a fence. FIG. 3B shows a state in which a pictograph corresponding to “memo” is selected by the function button 4.

  The pictograms (icons) 30a displayed on the upper part of the display unit 30 are various selection items in order from the left: memo, next menstruation date, next ovulation date, wake-up time setting, buzzer volume setting, and time setting. After the function button 4 is pressed, the item selected by the left movement button 7 and the right movement button 8 blinks. When confirming, the function button 4 is pushed again. Hereinafter, each operation mode of the female thermometer will be described.

(I) Measurement mode:
When the power button 9 is pressed or the alarm set time arrives, the female thermometer is turned on and the measurement mode is entered. In the measurement mode, the current date and latest measurement values are displayed in the initial state. In addition, by operating the left movement button 7 and the right movement button 8, a memo item corresponding to the designated day is displayed together with the measured value of the designated day. In this measurement mode, the measurement value by the temperature measurement unit 10 is monitored, and body temperature measurement is started when the measurement start condition is met. Details of the operation of body temperature measurement in the measurement mode will be described later. When the function button 4 is pressed in the measurement mode, the menu selection screen described above is displayed.

(Ii) Memo mode:
When the body temperature measurement is completed in a state where the electronic thermometer for women is turned on, and the body temperature is displayed on the display unit 30, when the function button 4 is pressed, it is displayed on the upper portion of the display unit 30. The pictograph (icon) 30a blinks “memo” among various selection items. When the function button 4 is pressed again, the mode transits to the memo mode, and “menstruation day” of the pictographs (icons) 30b is surrounded by a heel and displayed. The item to be entered for memo is selected by the left move button 7 and the right move button 8. The selected item is displayed surrounded by ∩. Next, the memo input is completed by pressing the completion button 5 for a predetermined second. The input memo item is stored in the RAM 23 in association with the date, and then transitions to the measurement mode.

(Iii) Predicted date display mode:
When the function button 4 is pressed in a state where the “predicted date display” pictograph is selected on the menu selection screen, the mode is shifted to the predicted date display mode. In the prediction date display mode, prediction data derived in the data processing mode described later and stored in the RAM 23 is displayed. Predicted data includes, for example, the next menstruation date, the next ovulation date, the expected date of birth, and the like. When the completion button 5 is pressed during display in the predicted date display mode, the mode changes to the measurement mode.

(Iv) Data processing mode:
The data processing mode is a mode for executing data processing on time series data of body temperature measured in the measurement mode. This is a mode that transitions when the power is turned off by the power button 9 or when a predetermined time (for example, 5 hours) elapses from the alarm setting time. Note that the data processing is performed only once a day. When the data processing mode is shifted to the data processing mode more than once a day, the actual data processing is not performed after the second time and the processing is immediately terminated. To the stop mode described later. Details of data processing in the data processing mode will be described later.

(V) Stop mode:
After completion of data processing in the data processing mode or when the button non-input state continues for a predetermined time in the measurement mode, the mode is changed to the stop mode. In the electronic thermometer for women, the power supply of the entire circuit is not cut off even in the stop mode, but the timer 24, the arithmetic processing unit 21 and the like are used to perform functions in the alarm and data processing mode. The power is supplied to the part of, although it is weak.

  The operation mode of the electronic thermometer for women of this embodiment has the above five modes. In each of the modes (ii) and (iii), when the completion button 5 is pressed, the measurement mode is restored. Further, in each of the modes (ii) and (iii), when a predetermined time elapses without input of various buttons, the mode returns to the measurement mode as in the case where the completion button 5 is pressed. Further, in the measurement mode, when a predetermined time elapses without inputting various buttons, the mode is changed to the stop mode. It should be noted that when a button is input to make a transition from the measurement mode to each mode, it is preferable that the input is performed by pressing the button for a long time in order to prevent erroneous input.

<Method for measuring body temperature: grouping and prediction formula>
FIG. 4 is a diagram exemplarily showing changes in actual measurement values by the temperature measurement unit.

  As shown in the figure, the actual measurement value approaches the equilibrium temperature with time, but the rate of change differs depending on the measurement condition such as the constitution of the person to be measured and the contact state between the temperature measurement and the body surface. Therefore, case classification (grouping) is performed according to the time-varying characteristics of the measured values.

  Below, grouping is demonstrated from the characteristic of the measured value detected by the thermistor 13. FIG. However, in the present embodiment, as described above, the thermal response characteristics of the temperature sensing element are good, and variations in the time-varying characteristics of measured values are likely to occur. Therefore, an example will be shown in which more grouping (here, 13 groups) is performed as compared with the conventional grouping (for example, 7 groups) to cope with the improved thermal response characteristics.

  FIG. 5 is a diagram showing an example of grouping according to the temporal change characteristic of the actual measurement value.

  FIG. 5 shows an example in which the whole is divided into 13 groups using the temperature rise value for 15 to 20 seconds (vertical axis in FIG. 5) and the temperature for 20 seconds (horizontal axis in FIG. 5). Each point shows the distribution in the measurement sample. The first group is the group with the fastest thermal response, and is the part where the initial temperature is high but the rise is quickly stopped. Conversely, the eighth group is the group with the slowest thermal response, and is the portion where the initial temperature is low but the temperature rise continues until late. Here, since the ninth group and the tenth group greatly deviate from the normal change in the actual measurement value, for example, the prediction may be impossible and the error may be terminated, or the actual measurement value may be displayed without performing the prediction. It may be configured to do. In addition, the eleventh group and the twelfth group are groups whose body temperature is 36.5 degrees or more at 20 seconds.

  When the grouping as described above is performed, for example, the predicted value is the time when the actual measurement value is 30 ° C. or more and the temperature increase rate is 0.03 ° C./0.5 seconds or more as the starting point (t = 0). Y can be approximated by the following equation using the measured value T and the elapsed time t.

U = (a * t + b) * dT + (c * t + d)
Y = T + U where a to d: constant, dT: temperature rise in the past 5 seconds.

  After 20 seconds, as described in the grouping, prediction calculation is performed using the coefficients a to d corresponding to each group. As an example, an example of the values of the coefficients a to d in each group during 20 to 25 seconds is shown below. These coefficients a to d are obtained from a large number of measurement samples, and are a part of the parameters 22b stored in the ROM 22 in advance.

Group 1 a = 0.554: b = −6.5185: c = −0.1545: d = 2.8915
Group 2 a = 1.1098: b = -15.446: c = -0.244: d = 4.5294
Group 3 a = 0.7187: b = −6.9987: c = −0.0571: d = 1.0682
4 groups a = 0.8092: b = −7.8356: c = −0.0448: d = 0.8609
Group 5 a = 0.8555: b = −9.2469: c = −0.0697: d = 1.5205
6 groups a = 0.4548: b = −2.1512: c = 0.0083: d = 0.2872
7 groups a = 0.378: b = -1.3724: c = 0.527: d = 0.912
<Operation flow in measurement mode>
FIG. 6 is an operation flowchart of a measurement mode in the electronic thermometer for women of the first embodiment. The following operation is triggered by a change in temperature obtained by the arithmetic control unit 20 from the temperature measurement unit 10 when the user inserts the peripheral part of the metal cap 3 into the mouth when the electronic thermometer for women is in the measurement mode. Be started. The following steps are realized by the arithmetic processing unit 21 executing a program stored in the ROM 22.

  In step S601, the electronic thermometer is initialized, and detection of the temperature value by the thermistor 13 is started. For example, the temperature value is detected using a sensor every 0.5 seconds.

  In step S602, for example, the time point at which the temperature value at which the rise from the previous actual measurement value (that is, the actual measurement value 0.5 seconds before) becomes a predetermined value (for example, 1 degree) or more is measured. = 0), and storage in the RAM 23 as specific timing and measured value data (time-series data) is started. In other words, by detecting a rapid temperature rise, it is considered that the measurement person wears a predetermined measurement site.

  In step S603, it is determined whether or not a decrease in measured temperature is observed during measurement. When the predetermined decrease is observed, the process proceeds to step S611, and when the predetermined temperature decrease is not observed, the process proceeds to step S604.

  In step S604, sequential prediction values are derived (for example, every 0.5 seconds) using the above-described prediction formula using the data stored in step S602. However, unlike the prior art, prediction calculations are performed in parallel based on prediction formulas corresponding to each of the plurality of groups shown in FIG. Note that computation may be performed in parallel for all the groups (here, 10 types of 1 to 8, 11 and 12), or an approximate group is set based on some actually measured values, and some of the surrounding groups are set. The calculation may be performed only for.

  In step S605, after a lapse of a predetermined time (for example, 25 seconds) from the reference point (t = 0), grouping determination is performed based on the change in each predicted value corresponding to the plurality of groups derived in step S604. Details of this group determination operation will be described later.

  In step S606, the calculation other than the group determined in step S605 is stopped, and the prediction calculation in the determined group is continuously derived for a predetermined time.

  In step S607, when a predetermined time (for example, 30 seconds) has elapsed from the reference point (t = 0), a predicted value in a predetermined section (for example, t = 25 to 30 seconds) derived as a result of step S606 is set in advance. Check whether the predicted establishment condition is satisfied. For example, it is a check as to whether or not it falls within a predetermined range (for example, 0.1 degree). If the prediction establishment condition is satisfied, the process proceeds to step S608. If the prediction establishment condition is not satisfied, the process proceeds to step S613.

  In step S608, the buzzer 31 that announces the prediction is sounded, and the process proceeds to step S609.

  In step S609, the derived predicted value is displayed on the display unit 30.

  In step S610, the temperature measurement result is stored in the RAM together with the time acquired from the timer.

  In step S611, the measured data is corrected. If the correction process has been performed normally, the process returns to step S602. On the other hand, if the correction process does not end normally, the process proceeds to step S612.

  In step S612, the buzzer 31 reporting an error is sounded and the temperature measurement is terminated. At this time, the buzzer sound is desirably different from that in step S608.

  In step S613, for example, when a predetermined time (for example, 45 seconds) has elapsed from the start of measurement using a timer or the like, prediction is forcibly established, and the process proceeds to step S607. That is, the prediction value derived at that time is regarded as the final prediction value as it is.

  Through the above steps, the temperature measurement operation in the measurement mode is terminated, the measured body temperature value is displayed on the display unit 30 together with the measurement time, and the body temperature value is stored in the RAM 23.

<Determination of groups based on predicted values>
Hereinafter, processing (corresponding to step S605) when determining a group corresponding to the prediction formula used for the final prediction value from the plurality of prediction values derived based on the plurality of prediction formulas will be described.

  FIG. 7 is a diagram exemplarily showing the temporal change of the predicted value based on the actual measurement value and a plurality of prediction formulas. In this figure, along with the actual measurement values detected by the thermistor 13, changes in predicted values corresponding to the five groups of the first group to the fifth group derived in step S604 are shown. In the following, the group is determined based on the temporal change of these predicted values. That is, it is determined whether the most accurate predicted value is obtained when the prediction formula corresponding to which group is used.

  Here, as an example, a group in which both of the following two points are established is selected.

  -Change in 10-second regression is less than a predetermined value (for example, 0.1 degree).

  -The above condition corresponding to the predicted value derived every 0.5 seconds is continuously evaluated five times.

  That is, as a result, it is considered that the group corresponding to the time series in which the fluctuation of the predicted value is small selects the optimum group in the main measurement. In this way, a prediction calculation is performed for a plurality of groups, and a group is determined by comparing changes of respective predicted values over time, thereby enabling more accurate prediction.

  In the above, in order to improve the accuracy of prediction, the predicted value is continuously derived for a predetermined time after the group is determined (steps S606 to S607), and the final predicted value is determined. However, if the change is sufficiently small (for example, less than 0.05 degrees) at the time of group determination, the predicted value corresponding to the determined group can be regarded as sufficiently accurate, so it is immediately determined as the final predicted value. May be.

  On the other hand, the group may be determined based on the change over time of the actually measured values. That is, the time series data of the actual measurement values may be associated with the grouping table shown in FIG. 5, and the group with the most corresponding points may be selected and determined.

<Contents of data processing>
FIG. 8 is a diagram showing the relationship between the menstrual cycle and body temperature. Symbols D1 to D8 each represent the first menstrual period in the menstrual cycle, and symbols a to e represent the menstrual cycle starting from each menstrual first day. Each menstrual cycle includes a high-temperature phase period A to G that starts from the date of ovulation and a low-temperature phase period H to N that starts from the first day of menstruation. In FIG. 8, the date of ovulation is indicated by symbol ◎. Using these relationships, the electronic thermometer for women predicts the next menstrual day and the next ovulation date with high accuracy from the time series data of the body temperature stored in the RAM by the measurement mode in the data processing mode. In addition, if the measurer is determined to be pregnant from the measurement result, the expected delivery date is also predicted.

  That is, first, the first day of menstruation is determined from time series data of body temperature. Next, the latest menstrual cycle is determined from the number of days from the first menstrual day before the update to the previous day of the first menstrual cycle, triggered by the fact that the first menstrual day has been updated, that is, it has been determined that one or more menstrual cycles have been measured. Ask. Then, using the past menstrual cycle data, the menstrual cycle average days, the high temperature phase period average days, the low temperature phase period average days, and a reference body temperature to be described later are derived. Furthermore, it is determined whether the day of measurement was the high temperature phase or the low temperature phase, and the ovulation date and the average body temperature are derived. Finally, these data are used to predict the next menstrual date, the next ovulation date, and the expected date of delivery.

  Hereinafter, a method for predicting the next menstruation date, the next ovulation date and the expected date of birth, and a method for deriving data associated therewith will be described in detail. In the following, description will be given with reference to FIG. 8, but at this time, it is assumed that the measurement starts from the middle of the menstrual cycle “a”, and the sign D1 is the first physiological period first confirmed. These processes are executed in the data processing mode as described above. In other words, it is performed once a day when the power switch is turned off or when the alarm processing time is changed to the data processing mode after 5 hours. Note that the initial value of the wake-up time is set, for example, at 6:00 am, and the measurer measures the body temperature immediately after getting up.

(1) Menstruation first day When menstruation memo input continues for a predetermined number of days or more, for example, three days or more, the first day of menstrual memo input is determined to be the menstrual first day. If it is less than a predetermined number of days, for example, less than 3 days, the determination is canceled as a physiological mistake. If it is determined that the low temperature phase has been started from the change in body temperature because no physiological memo has been input, the start date of the low temperature phase is taken as the first day of menstruation. However, if the menstrual memo is input before the high temperature phase is started, the first day of menstrual period is corrected to the date when the menstrual memo is input.

(2) Average number of menstrual cycles The average number of menstrual cycles is obtained by averaging the predetermined number of menstrual cycles (for example, four times) excluding the longest cycle and the shortest cycle from the menstrual cycle for the most recent predetermined number of times (for example, six times). It is done. The average menstrual cycle for a predetermined number of times (here, four times) has at least a predetermined number of menstrual cycles (for example, three times), and the longest cycle and the shortest in the menstrual cycle used to derive the average number of menstrual cycles When the cycle satisfies the relationship of “longest cycle <shortest cycle × 2”, it is assumed that the derived menstrual cycle average number of days is valid. The effective menstrual cycle refers to a menstrual cycle that satisfies a predetermined range of days (for example, 21 days to 42 days).

When data for a predetermined number of times (for example, 6 times) has not been obtained since the start of measurement, if there is an effective menstrual cycle for a predetermined number of times (for example, 3 times) or more as a provisional treatment, the average is taken as the average number of days for menstrual cycle . For example, in the period e of FIG. 8, “average menstrual cycle = (b + c + d) / 3”. Here, b, c, and d are effective menstrual cycles. In the period g, the average of the effective menstrual cycles over a predetermined number of times (for example, three times) excluding the longest cycle is defined as the menstrual cycle average number of days.

  Therefore, effective menstrual cycle average days are not derived in the periods a, b, c, and d. In addition, when there is no effective menstrual cycle more than a predetermined number of times (for example, 3 times) in the recent predetermined number of times (for example, 6 times), or in the menstrual cycle used for deriving the average number of days of the menstrual cycle, Even if the period × 2 ″ is not satisfied, an effective menstrual cycle average number of days is not derived.

  The average number of menstrual cycle days is derived after the first menstrual day is confirmed, and is retained until the first menstrual day is confirmed. For example, in the period g of FIG. 8, the menstrual cycle average number of days is derived after the first menstrual day D6 is determined and held until the next first menstrual day D7 is confirmed.

(3) High-temperature phase average days The high-temperature phase average days averages the high-temperature phase days for a predetermined number of times (for example, 4 times) excluding the longest and shortest days from the high-temperature phase days for the most recent predetermined number of times (for example, 6 times). Obtained. It is assumed that the derived high-temperature phase average days are valid when there are effective high-temperature phase days more than predetermined times (for example, 3 times) out of the averaged predetermined times (here, 4 times). The effective high-temperature phase days means the high-temperature phase days that satisfy a predetermined range of days (for example, 12 days or more and 16 days or less).

  When data for a predetermined number of times (for example, 6 times) has not been obtained since the start of measurement, if there are effective high-temperature phase days for a predetermined number of times (for example, 3 times) as a provisional treatment, the average is regarded as the high-temperature phase average number of days. To do. For example, in the period e of FIG. 8, “high temperature phase average days = (A + B + C) / 3”. Here, A, B, and C are effective high-temperature phase days. In the period g, the average number of effective high-temperature phase days over a predetermined number of times (for example, three times) excluding the longest number of days is defined as the high-temperature phase average number of days.

  Therefore, the effective high-temperature phase average days are not derived in the periods a, b, c, and d. Also, the effective high-temperature phase average days are not derived even when the effective high-temperature phase days are not greater than or equal to the predetermined number of times (for example, 3 times) in the recent predetermined number of times (for example, 6 times).

  Note that the average number of high-temperature phase days is derived after the first day of menstruation is determined, and is retained until the next day of menstruation is confirmed. For example, in the period g of FIG. 8, the high-temperature phase average days are derived after the physiological first day D6 is determined and held until the next physiological first day D7 is determined.

(4) Low-temperature phase average days The low-temperature phase average days is the average of the low-temperature phase days for a predetermined number of times (for example, 4 times) excluding the longest and shortest days from the low-temperature phase days for the latest predetermined number of times (for example, 6 times). Obtained. It is assumed that the average number of days for the low-temperature phase to be derived is valid when there are effective low-temperature phase days for a predetermined number of times (for example, three times) out of the average number of low-temperature phases for a predetermined number of times (here, four times). In addition, the effective low-temperature phase days means the low-temperature phase days satisfying a predetermined range of days (for example, 5 days or more and 30 days or less).

  If data for a predetermined number of times (for example, 6 times) has not been obtained since the start of measurement, if there is an effective low-temperature phase number for a predetermined number of times (for example, 3 times) as a provisional treatment, the average is referred to as the low-temperature phase average number of days. To do. For example, in the period e of FIG. 8, “low temperature phase average days = (H + I + J) / 3”. Here, H, I, and J are effective low-temperature phase days. In the period g, the average of the effective low-temperature phase days over a predetermined number of times (for example, three times) excluding the longest number of days is defined as the low-temperature phase average days.

  Therefore, the effective low-temperature phase average days are not derived in the periods a, b, c, and d. Further, the effective low-temperature phase average days are not derived even when the effective low-temperature phase days are not more than the predetermined number of times (for example, 3 times) in the recent predetermined number of times (for example, 6 times).

  Note that the low-temperature phase average days are derived after the first menstrual day is determined, and are retained until the next first menstrual day is confirmed. For example, in the period g of FIG. 8, the low-temperature phase average days are derived after the physiological first day D6 is determined and held until the next physiological first day D7 is determined.

(5) Reference body temperature The reference body temperature is determined by using the high-temperature phase average body temperature and the low-temperature phase average body temperature in the menstrual cycle for a predetermined number of times in the past (for example, 3 times). High temperature phase average body temperature + predetermined number (for example, three times) of low temperature phase average body temperature) / 2 ". The derivation of the high temperature phase average body temperature and the low temperature phase average body temperature will be described later.

  For example, the reference body temperature on the first physiological day D4 is “reference body temperature = ((average body temperature in period A + average body temperature in period B + average body temperature in period C) / 3 + (average body temperature in period H + average body temperature in period I + period) J average body temperature) / 3) / 2 ". It should be noted that, on the first physiological day D2, “reference body temperature = (average body temperature in period A + average body temperature in period H) / 2” is derived. In addition, the reference body temperature in the periods a to b is given in advance as, for example, “reference body temperature = 36.5 ° C.”.

  The reference body temperature is derived after the first menstruation day is determined and is held until the next menstruation day is confirmed. For example, in the period g of FIG. 8, the reference body temperature is derived after the first menstrual day D6 is determined and held until the next first menstrual day D7 is confirmed.

(6) Phase determination Phase determination determines whether a body temperature is a high temperature phase or a low temperature phase. When “body temperature ≧ reference body temperature”, the high temperature phase is set, and when “body temperature <reference body temperature”, the low temperature phase is set.

  In addition, when the low temperature phase continues for a predetermined number of days (for example, 3 days), the low temperature phase start date is traced back for a predetermined number of days (for example, 2 days) from that day. Alternatively, when the first day of menstruation is confirmed, the first day of menstruation is set as the low temperature phase start date. Further, when the high temperature phase continues for a predetermined number of days (for example, 3 days), the high temperature phase start date is traced back for a predetermined number of days (for example, 2 days) from that day. However, when there is a fever memo input within a predetermined number of days (for example, 3 days), or when the body temperature is 37.5 ° C. or higher, the measurement result is excluded from the calculation.

  The phase determination is performed every predetermined number of days (for example, one day) after the low temperature phase is first determined, and is also determined for interpolation data described later.

(7) Ovulation date determination Since the ovulation date is the last day of the low temperature phase, it is derived by “ovulation date = high temperature phase start date−1”. The ovulation date is determined after the start date of the high temperature phase is updated.

(8) Average Body Temperature The high-temperature phase average body temperature is calculated based on the body temperature from a predetermined date (for example, 3 days) after the high-temperature phase start date to a predetermined date (for example, 3 days) before the low-temperature phase start date. Similarly, for the low-temperature phase average body temperature, the average body temperature is calculated from the body temperature after a predetermined date (for example, 3 days) from the low-temperature phase start date to a predetermined date (for example, 3 days) before the high-temperature phase start date.

  As for the average body temperature, the high-temperature phase average body temperature and the low-temperature phase average body temperature are derived after the first physiological first day is determined.

(9) Prediction of the next menstrual day The next menstrual date is derived as a predetermined period (for example, 3 to 7 days). For example, when the day on which the prediction process is being performed is a low-temperature phase, “next menstrual day = recent menstrual first day + menstrual cycle average days−1.5σ / 2−recent menstrual first day + menstrual cycle average days + 1.5σ / 2” ". Here, σ is a standard deviation when it is assumed that the distribution of the number of days in the menstrual cycle follows a normal distribution. The forecast results are rounded to the first decimal place. On the other hand, when the day on which the prediction process is performed is the high temperature phase, “next menstrual day = recent ovulation date + high temperature phase average days−1.5σ / 2−recent ovulation date + high temperature phase average days + 1.5σ / 2” ". Here, σ is a standard deviation when it is assumed that the distribution of the number of days in the high temperature phase follows a normal distribution. The forecast results are rounded to the first decimal place.

  When the period derived in this way is displayed, processing is performed as follows according to the condition of the day to be displayed. If the current day is not included in the period of the next menstrual day, the derived period is displayed as it is. On the other hand, if it is in the period of the next menstrual day from which the current day is derived and is before a predetermined number of days (for example, 3 days) before the last day of the period, the displayed period is derived from “the date of the current day to The last day of the period. That is, “from the current day to the latest first physiological period + the average number of menstrual cycles + 1.5σ / 2”, or “the current day to the latest day of ovulation + the average number of days in the high temperature phase + 1.5σ / 2”. Or, if the current period is within the period of the next period, and the period is after a predetermined number of days (for example, 3 days) after the last day of the period, the displayed period is Date + 3 ”.

  In addition, when the derived period is a predetermined number of days (for example, 8 days) or more, when the day is a high temperature phase and the number of days from the ovulation day is a predetermined number of days (for example, 17 days) or more, the menstrual cycle average days or the high temperature phase average days is In the case where it is not fixed, for example, since a highly accurate prediction cannot be made, for example, “--month--day to --- month--day” is displayed.

  The next menstrual day prediction process is performed after the first menstrual period of a predetermined time (for example, four times) is confirmed and the menstrual cycle average days and high temperature phase average days are derived. Therefore, the next menstrual date is not derived in the periods a to d in FIG.

(10) Prediction of next ovulation date The next ovulation date is derived as a predetermined period (for example, 3 to 7 days). For example, when the day on which the prediction process is being performed is the low temperature phase, “next ovulation day = recent physiological first day + low temperature phase average days−1.5σ / 2−recent physiological first day + low temperature phase average days + 1.5σ / 2” ". Here, σ is a standard deviation when it is assumed that the distribution of days in the low temperature phase follows a normal distribution. The forecast results are rounded to the first decimal place. On the other hand, when the day on which the prediction process is being performed is in the high temperature phase, “next ovulation date = recent ovulation date + menstrual cycle average days−1.5σ / 2−recent ovulation date + menstrual cycle average days + 1.5σ / 2” ". Here, σ is a standard deviation when it is assumed that the distribution of the number of days in the menstrual cycle follows a normal distribution. The forecast results are rounded to the first decimal place.

  When the period derived in this way is displayed, processing is performed as follows according to the condition of the day to be displayed. If the day is not included in the next ovulation date period derived, the derived period is displayed as it is. On the other hand, if the current day is in the period of the next ovulation date that has been derived and is before a predetermined number of days (for example, 3 days) before the last day of that period, the displayed period is derived from The last day of the period. That is, “the current day to the latest physiological first day + the average number of low-temperature phases + 1.5σ / 2”, or “the current day to the latest ovulation day + the average number of menstrual cycle + 1.5σ / 2”. Or, if the day is in the next ovulation date period from which the day was derived and if it is after a predetermined number of days (for example, 3 days) from the last day of the period, the displayed period will be “from the current day to the current day” Date + 3 ”.

  In addition, when the derived period is a predetermined number of days (for example, 8 days) or more, when the day is the high temperature phase and the number of days from the ovulation day is the predetermined number of days (for example, 17 days) or more, the menstrual cycle average days or the low temperature phase average days is In the case where it is not fixed, for example, since a highly accurate prediction cannot be made, for example, “--month--day to --- month--day” is displayed.

  The prediction process for the next ovulation day is performed after the first menstrual period of a predetermined time (for example, 4 times) is determined and the average number of menstrual cycle days and the average number of low-temperature phases are derived. Therefore, the next ovulation date is not derived in the periods a to d in FIG.

(11) Prediction of expected birth date When the number of days from the last ovulation day exceeds a predetermined number of days (for example, 20 days) and the body temperature measured on the day is determined to be the high temperature phase, it is determined that the child is pregnant. . Then, the estimated date of birth is predicted using “scheduled date of birth = ovulation date + 265 days”. If the date of delivery is not derived, such as when it is not determined that the child is pregnant, “--month--day to --- month--day” is displayed.

(12) Interpolation of missing data Since basal body temperature should be measured every day as a general rule, in the explanation of each processing described above, it was assumed that daily measurement data existed without omission. If measurement data is missing due to forgetting to measure, etc., interpolation is performed using measurement data before and after the date of missing measurement data. However, the interpolated data is not displayed on the display unit in order to clearly indicate that the data was originally missing, for example, “--.-- ° C.”.

  For example, when the measured body temperature data is missing for m days, the body temperature the day before the start of the loss is a, the body temperature the day after the end of the loss is b, and “the body temperature of the start of the missing day n = a + n (ba) / (m + 1) ) "Is interpolated using linear approximation. Here, the measurement data missing continuous days m is allowed up to a predetermined number of days (for example, 8 days). If there is an omission that exceeds the predetermined number of days, it is impossible to predict with high accuracy. Further, only when the measurement data of the measured body temperature stored in the RAM is not less than a predetermined ratio (for example, 50% or more) of the number of days in the menstrual cycle, the data in the menstrual period is valid and less than the predetermined ratio (for example, 50 Less than%), the data in the menstrual cycle is invalidated.

<Operation flow in data processing mode>
FIG. 9 is an operation flowchart of a data processing mode of the electronic thermometer for women according to the first embodiment. The following steps are realized when the arithmetic processing unit 21 executes a program stored in the ROM 22 as described above. The processing procedure will be described below with reference to the flowchart. 10 to 13 show details of some steps in the flowchart of FIG. 9, so only a brief description will be given.

  In step S901, it is determined whether or not execution of the first data processing mode is performed today. If it is determined to execute the first data processing mode, the process proceeds to step S902. If it is the execution of the data processing mode for the second time or later today, it is determined that the data processing has already been performed once a day today, and the flow is terminated.

  In step S902, it is determined whether or not the measurement data stored in the RAM 23 is missing, and the missing date data is interpolated. That is, it is determined whether or not data continuously exists from the start date of measurement to today, and if there is a missing data, the data is interpolated. The interpolation processing is as described in “(12) Interpolation of missing data”.

  In step S903, the first day of menstruation is determined. The determination process is as described in “(1) First physiological period”, and the operation flow is shown in FIG. That is, when the menstrual memo is continuously input for a predetermined number of days (for example, three days) or more, the first menstrual day is updated with the date of the first three consecutive days (step S1003). Further, when the low temperature phase start date is updated in the phase determination described later, the physiological first day is updated with the low temperature phase start date (step S1008). Further, even when the menstrual memo is not continuous for a predetermined number of days (for example, three days) or more, if the menstrual memo is not in the high temperature phase, the menstrual first day is updated (step S1006). The first day of menstruation is updated with any of these three as a trigger.

  In step S904, it is determined whether or not this is the first data processing after the latest physiological first day is determined. If it is the first data processing, the process proceeds to step S905. If it is the second or subsequent data processing, the process proceeds to step S909.

  In step S905, it is determined whether or not the latest menstrual cycle data is valid. If it is valid, the process proceeds to step S906. If not valid, the process proceeds to step S909.

  In step S906, the menstrual cycle average number of days is derived. The derivation process is as described in “(2) Menstrual cycle average days”.

  In step S907, the high temperature phase average days and the low temperature phase average days are derived. The derivation process is as described in “(3) Average number of days of high temperature phase” and “(4) Average number of days of low temperature phase”.

  In step S908, a reference body temperature is derived. The derivation process is as described in “(5) Reference body temperature”.

  In step S909, phase determination and ovulation date determination are performed. The determination process is as described in “(6) Phase determination” and “(7) Ovulation day determination”. FIG. 11 shows an operation flow. That is, in principle, if the body temperature is low or high for a predetermined number of days (for example, 3 days), the first day is set as the start date of the low temperature phase or the high temperature phase, respectively (steps S1103 and S1106). However, even if the body temperature is not continuously low for a predetermined number of days (for example, 3 days), if the first day of menstruation is updated on that day, the updated first day of menstruation is set as the low temperature phase start date (steps S1108 and S1109). However, when the temperature exceeds a predetermined temperature or when a heat generation memo is input, the measurement value for that day is not adopted. Further, the day before the high temperature phase start date is set as the ovulation day in the menstrual cycle (step S1107).

In step S910, it is determined whether the low-temperature phase start date is updated and the physiological first day is not updated. In the case of YES, since it is necessary to update the first period of menstruation with the low temperature phase start date, the process returns to step S903.
If no, the process proceeds to step S911.

  In step S911, an average body temperature is derived. The derivation process is as described in “(8) Average body temperature”.

  In step S912, the next menstrual date is predicted. The prediction process is as described in “(9) Prediction of next period”, and the operation flow is shown in FIG. That is, if it is the current high temperature phase, the average number of high temperature phase days is added on the basis of the recent ovulation day, and the prediction is performed by taking into account the variation around that day (step S1205). In the case of the current low temperature phase, the menstrual cycle average number of days is added with reference to the first day of the latest menstrual period, and the prediction is performed by taking into account variations around that day (step S1203).

  In step S913, the next ovulation date is predicted. The prediction process is as described in “(10) Prediction of next ovulation date”, and the operation flow is shown in FIG. That is, if it is the current high temperature phase, the average number of menstrual cycles is added based on the most recent ovulation day, and the prediction is made by taking into account variations around that day (step S1214). In the case of the current low temperature phase, the average number of days of the low temperature phase is added based on the first day of the recent menstruation, and the prediction is performed by taking into account variations around that day (step S1216).

  In step S914, the expected delivery date is predicted. The prediction process is as described in “(11) Prediction of expected delivery date”, and FIG. 13 shows an operation flow. That is, when a predetermined number of days (for example, 20 days) have passed since the most recent ovulation day and in the high temperature phase, the 265th day from the most recent ovulation day is predicted as the expected delivery date (step S1303).

  In addition, step S906-S908 mentioned above is a process performed once by one menstrual cycle. On the other hand, steps S909 to S914 are executed every time data processing is executed.

  The measured body temperature and the data derived as described above are all stored in the RAM 23 and stored for a predetermined period (for example, 240 days). That is, for example, if it is a value derived for each menstrual cycle such as menstrual cycle, high temperature phase days, low temperature phase days, average body temperature, about 6 to 10 cycles are stored. For this reason, sufficient data can be preserve | saved also in order to derive | lead out the data obtained based on the data in many past menstrual cycles, such as a high temperature phase average days and a low temperature phase average days.

  As described above, the feminine electronic thermometer of the present embodiment makes it possible to acquire a highly accurate body temperature in a short measurement time. As a result, a feminine electronic thermometer capable of accurately predicting the next menstrual date or the like can be realized. Moreover, since the time for measuring body temperature each time can be greatly shortened, the burden on the measurer can be reduced.

(Other embodiments)
Note that the present invention can also be achieved by supplying a program for realizing the functions of the above-described embodiments directly or remotely to a device, and reading and executing the supplied program code. Accordingly, the program code itself installed in the computer in order to realize the functional processing of the present invention by the computer is also included in the technical scope of the present invention.

It is a figure which shows the external appearance of the female thermometer for women which concerns on 1st Embodiment. It is an internal block diagram of the electronic thermometer for women concerning a 1st embodiment. It is a state transition diagram which shows the transition of the function mode for performing the various functions by a calculation control part. It is the figure which showed the actual value change by the temperature measurement part exemplarily. It is the figure which showed the example of the grouping according to the time-dependent change characteristic of measured value. It is a body temperature measurement flowchart which concerns on the electronic thermometer for women of 1st Embodiment. It is the figure which showed illustratively the time-dependent change of the predicted value based on a measured value and a some prediction formula. It is a figure which shows the relationship between a menstrual cycle and body temperature. It is a whole operation | movement flowchart of the electronic thermometer for women which concerns on 1st Embodiment. It is an operation | movement flowchart of menstruation first day determination. It is an operation | movement flowchart of a phase determination and ovulation day determination. It is an operation | movement flowchart of the next menstrual day and the next ovulation day prediction. It is an operation | movement flowchart of a scheduled delivery date.

Claims (11)

An input means for inputting physiological data;
Predicted value deriving means for deriving a plurality of predicted values of the equilibrium temperature from a measured value of the temperature detected by the temperature measuring element according to a plurality of prediction formulas;
Selection means for selecting a single prediction formula from the plurality of prediction formulas based on changes over time of each of the plurality of prediction values;
Storage means for storing the predicted value derived based on the selected prediction formula and the inputted physiological data together for each date;
A predicting means for predicting the next menstrual date based on the stored predicted value and the physiological data;
An electronic thermometer for women characterized by comprising: An input means for inputting physiological data;
Predicted value deriving means for deriving a plurality of predicted values of the equilibrium temperature from a measured value of the temperature detected by the temperature measuring element according to a plurality of prediction formulas;
Selection means for selecting a single prediction formula from the plurality of prediction formulas based on changes over time of each of the plurality of prediction values;
Storage means for storing the predicted value derived based on the selected prediction formula and the inputted physiological data together for each date;
Predicting means for predicting the next ovulation day based on the stored predicted value and the physiological data;
An electronic thermometer for women characterized by comprising: An input means for inputting physiological data;
Predicted value deriving means for deriving a plurality of predicted values of the equilibrium temperature from a measured value of the temperature detected by the temperature measuring element according to a plurality of prediction formulas;
Selection means for selecting a single prediction formula from the plurality of prediction formulas based on changes over time of each of the plurality of prediction values;
Storage means for storing the predicted value derived based on the selected prediction formula and the inputted physiological data together for each date;
A predicting means for predicting the expected date of delivery based on the stored predicted value and the physiological data;
An electronic thermometer for women characterized by comprising: An input means for inputting physiological data;
Predicted value deriving means for deriving a plurality of predicted values of the equilibrium temperature from a measured value of the temperature detected by the temperature measuring element according to a plurality of prediction formulas;
Selection means for selecting a single prediction formula from the plurality of prediction formulas based on changes over time of each of the plurality of prediction values;
Storage means for storing the predicted value derived based on the selected prediction formula and the inputted physiological data together for each date;
Estimating means for estimating a first day of a physiological date based on the stored predicted value and the physiological data,
An electronic thermometer for women characterized by comprising: An input means for inputting physiological data;
Predicted value deriving means for deriving a plurality of predicted values of the equilibrium temperature from a measured value of the temperature detected by the temperature measuring element according to a plurality of prediction formulas;
Selection means for selecting a single prediction formula from the plurality of prediction formulas based on changes over time of each of the plurality of prediction values;
Storage means for storing the predicted value derived based on the selected prediction formula and the inputted physiological data together for each date;
Estimating means for estimating the date of ovulation based on the stored predicted value and the physiological matter data;
An electronic thermometer for women characterized by comprising:   The electronic thermometer for women according to any one of claims 1 to 5, wherein the selection means selects a prediction formula having the smallest change in predicted value over time. An input means for inputting physiological data;
Predicted value deriving means for deriving a plurality of predicted values of the equilibrium temperature from a measured value of the temperature detected by the temperature measuring element according to a plurality of prediction formulas;
Selection means for selecting a single prediction formula from the plurality of prediction formulas based on a change with time of the actual measurement value;
Storage means for storing the predicted value derived based on the selected prediction formula and the inputted physiological data together for each date;
A predicting means for predicting the next menstrual date based on the stored predicted value and the physiological data;
An electronic thermometer for women characterized by comprising:   The female prediction system according to any one of claims 1 to 7, wherein the plurality of prediction formulas are set corresponding to a plurality of groups divided into groups according to characteristics of changes in measured values over time. Electronic thermometer.   The female thermometer according to any one of claims 1 to 8, wherein the thermometer and its peripheral part have a small heat capacity. An input process for inputting physiological data;
A predicted value derivation step for deriving a plurality of predicted values of the equilibrium temperature from a measured value of the temperature detected by the temperature measuring element according to a plurality of prediction formulas;
A selection step of selecting a single prediction formula from the plurality of prediction formulas based on changes over time of each of the plurality of prediction values;
A storage step of storing the predicted value derived based on the selected prediction formula and the inputted physiological data together for each date;
A predicting step of predicting a next menstruation date based on the stored predicted value and the physiological data;
A method for controlling an electronic thermometer for women, comprising: A control program for an electronic thermometer for women,
Program code for executing an input process for inputting physiological data;
A program code for executing a predicted value deriving step of deriving a plurality of predicted values of the equilibrium temperature from a measured value of the temperature detected by the temperature measuring element according to a plurality of prediction formulas;
Program code for executing a selection step of selecting a single prediction formula from the plurality of prediction formulas based on changes over time of the plurality of prediction values,
A program code for executing a storage step of storing the predicted value derived based on the selected prediction formula and the inputted physiological data together for each date;
A program code for executing a prediction step of predicting a next menstruation date based on the stored predicted value and the physiological data;
A control program comprising:

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