Information processing device, information processing method, and information processing program
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- UNI CHARM CORP
- Filing Date
- 2026-01-26
- Publication Date
- 2026-07-30
Smart Images
Figure JP2026002478_30072026_PF_FP_ABST
Abstract
Description
Information Processing Apparatus, Information Processing Method, and Information Processing Program
[0001] The present invention relates to an information processing apparatus, an information processing method, and an information processing program.
[0002] Conventionally, a technique has been proposed in which hormones in urine are detected, the amount of hormones is recorded in a recording means having a calendar function, and ovulation days and the presence or absence of pregnancy are determined from changes in the amount of hormones.
[0003] Japanese Patent Application Laid-Open No. 09-075352
[0004] However, the above-described conventional technology cannot always support users so that the success rate of pregnancy is increased.
[0005] For example, by grasping the menstrual cycle and estimating the ovulation day by the Ogino method, it is possible to determine a period during which pregnancy is likely (a period during which the success rate of pregnancy is increased). However, the ovulation day estimated by the Ogino method may deviate from the actually obtained ovulation day. Therefore, the period during which pregnancy is likely based on the ovulation day estimated by the Ogino method may not always be highly reliable.
[0006] By the way, in the above-described conventional technology, by detecting hormones in urine, the ovulation day and the presence or absence of pregnancy are determined from changes in the amount of hormones. Thus, in the above-described conventional technology, although the ovulation day is obtained from changes in the amount of hormones, the user himself / herself has to judge the period during which pregnancy is likely based on this ovulation day.
[0007] Also, generally, it is said that the period 1 to 2 days before the ovulation day is the period during which the success rate of pregnancy is the highest, but there are also users who do not know such a fact, and there is a need to teach a more reliable period during which pregnancy is likely so that they can approach sexual intercourse with confidence.
[0008] The present application has been made in view of the above, and an object thereof is to support a user so that the success rate of pregnancy is increased.
[0009] To solve the above problems, an information processing device according to the present invention comprises: an acquisition unit that acquires first event information, which is the result of predicting a first event based on user input information, and second event information, which is the result of predicting the timing of occurrence of a second event based on the first event information; a prediction unit that predicts the timing of occurrence of a second event using a predetermined calculation logic different from the prediction of the second event information, using detection result information obtained when a substance related to the second event is detected by a detection means provided on a nonwoven fabric product worn by the user; a generation unit that generates schedule information in which the timing of occurrence indicated by the prediction result information is displayed, based on prediction result information, which is the result of predicting the timing of occurrence of the second event using the predetermined calculation logic, the first event information, and the second event information.
[0010] According to one embodiment of the system, it is possible to support users in increasing their chances of successful pregnancy.
[0011] Figure 1 is a diagram showing an example of information processing related to the prerequisite technology. Figure 2 is a diagram showing an example of information processing related to the proposed technology. Figure 3 is a diagram illustrating the response of the detection means. Figure 4 is a diagram showing an example of screen transition (1). Figure 5 is a diagram showing an example of screen transition (2). Figure 6 is a diagram showing an example of the configuration of a server device according to the embodiment. Figure 7 is a flowchart (1) showing the operation procedure based on normality determination. Figure 8 is a flowchart (2) showing the operation procedure based on normality determination. Figure 9 is a diagram showing only the menstrual cycle portion of Figure 3. Figure 10 is a flowchart (1) showing the operation procedure based on input qualification. Figure 11 is a flowchart (2) showing the operation procedure based on input qualification. Figure 12 is a diagram showing an example of hardware configuration.
[0012] The following matters become clear from this specification and the accompanying drawings:
[0013] Embodiment 1 includes: an acquisition unit that acquires first event information, which is the result of predicting a first event based on user input information, and second event information, which is the result of predicting the timing of the occurrence of a second event based on the first event information; a prediction unit that predicts the timing of the occurrence of a second event using a predetermined calculation logic different from the prediction of the second event information, using detection result information obtained when a substance related to the second event is detected by a detection means provided on a nonwoven fabric product worn by the user; a generation unit that generates schedule information in which the timing of the occurrence of the second event indicated by the prediction result information is displayed, based on the prediction result information, the first event information and the second event information.
[0014] Embodiment 2 is an embodiment in which, in embodiment 1, the acquisition unit acquires first event information indicating information about the menstrual cycle predicted based on the menstrual start date input by the user, and acquires second event information indicating the timing of pregnancy in the menstrual cycle in which the possibility of pregnancy is higher, based on the expected ovulation date calculated by applying the menstrual cycle information to the Ogino calculation logic, and the prediction unit predicts the timing of pregnancy in the menstrual cycle in which the possibility of pregnancy is higher by applying the detection result information to a calculation logic different from the Ogino calculation logic as a predetermined calculation logic, and the generation unit generates a menstrual cycle calendar in which the timing of pregnancy is displayed based on the prediction result information indicating the timing of pregnancy predicted by the predetermined calculation logic, the first event information, and the second event information.
[0015] According to embodiments 1 and 2, it is possible to support users in order to increase the success rate of pregnancy. According to embodiments 1 and 2, it is possible to appropriately support fertility activities (an abbreviation for "pregnancy activities," which are preparatory activities undertaken by men and women who wish to become pregnant). Furthermore, according to embodiments 1 and 2, the proposed technology of the present application can be extended not only to predicting the timing of pregnancy, but also to determining menopause and predicting menstrual cycles.
[0016] Embodiments of the present invention will be described in detail below with reference to the attached drawings. In this specification and the drawings, components having substantially the same functional configuration are denoted by the same reference numerals, and redundant descriptions will be omitted.
[0017] The one or more embodiments (including examples, modifications, and applications) described below can each be implemented independently. On the other hand, at least some of the embodiments described below may be implemented in appropriate combination with at least some of the other embodiments. These embodiments may contain novel features that differ from each other. Therefore, these embodiments may contribute to solving different objectives or problems and may produce different effects.
[0018] Furthermore, the following describes an embodiment that focuses on the second aspect described above (i.e., prediction of the timing of pregnancy). Also, in the following, "period" may be expressed as "menstruation." For example, "menstrual cycle" may be expressed as "menstrual cycle."
[0019] (Implementation) [1. Introduction] The Ogino method is a technique that predicts the ovulation date based on the premise that the period from ovulation day to the start of the next menstruation day is constant (14 days). In addition, it is generally said that the period 1 to 2 days before ovulation day has the highest chance of success in conception, so users who are trying to conceive may, for example, try to have sexual intercourse 1 to 2 days before the ovulation date predicted by the Ogino method.
[0020] However, just as there are individual differences in menstrual cycles, there are also individual differences in the period from ovulation to the start of the next menstruation, making it difficult to reliably predict ovulation using the Ogino method. In other words, there is often a discrepancy between the ovulation date estimated by the Ogino method and the actual ovulation date, and the ovulation date predicted by the Ogino method is not necessarily reliable. Therefore, even if sexual intercourse occurs one or two days before the ovulation date predicted by the Ogino method, it does not guarantee successful conception. Thus, there is a need to know a more reliable period for conception so that people can approach sexual intercourse with confidence.
[0021] The Ogino formula has a problem in that it lacks reliability because it is a simple calculation logic that assumes the period from ovulation to the start of the next menstruation is constant. Therefore, the proposed technology of this application was conceived from the idea that if a calculation logic using actual biological information based on secretions related to pregnancy (e.g., female hormones) is used instead of the Ogino formula, the period of fertility can be determined with greater accuracy. In the proposed technology, for example, the timing of pregnancy derived from the Ogino formula is overwritten on the user's menstrual cycle calendar with the timing of pregnancy determined by the proposed method. As a result, the user can properly understand the period of fertility and approach sexual intercourse with confidence. In other words, the proposed technology can support fertility efforts.
[0022] [2. Prerequisite Technology] The proposed technology of this application is based on the Ogino method for predicting ovulation. Therefore, we will first explain the information processing related to the prerequisite technology. Figure 1 is a diagram showing an example of information processing related to the prerequisite technology. Figure 1 shows the information processing system 1. The information processing related to the prerequisite technology is implemented in the information processing system 1. As will be described later, the information processing related to the proposed technology is also implemented in the information processing system 1.
[0023] As shown in Figure 1, the information processing system 1 includes a user device 10 and a server device 100. The information processing system 1 may also include multiple user devices 10 and multiple server devices 100.
[0024] User device 10 is an example of an information processing terminal used by user U (a woman undergoing fertility treatment). User device 10 may be a smartphone, a wearable device, a tablet device, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), etc. For example, user device 10 may be equipped with an application AP (app AP) to enable the sending and receiving of information with server device 100. The application AP may be a general-purpose application such as a web browser, or it may be a dedicated application newly implemented to suit the proposed technology.
[0025] The server device 100 is a central device for processing information related to the prerequisite technology and the proposed technology, and may be implemented as a cloud server device. The server device 100 and the user device 10 are connected via a network N (not shown) via wired or wireless communication. The server device 100 can also be an application server that controls application APs, and manages information recorded via application APs.
[0026] From here, we will explain the information processing flow related to the prerequisite technology. In the prerequisite technology, when user U recognizes that menstruation has started, it records the menstrual start date MDA on the application AP. Then, user device 10 transmits menstrual information MT (an example of user input information), including the menstrual start date MDA, to server device 100 (step S11).
[0027] The server device 100 predicts the menstrual cycle Cy (an example of a first event) based on the menstrual start date MDA (step S12). For example, since user U records the current menstrual start date MDA each time she recognizes that menstruation has begun, the server device 100 may predict the menstrual cycle Cy from statistics of multiple cycles, with the number of days from one menstrual start date MDA to the next menstrual start date MDA being considered as one cycle. The information indicating the menstrual cycle Cy (an example of first event information) may include the number of cycle days and the actual date on the calendar corresponding to the number of cycle days.
[0028] Next, the server device 100 predicts the expected ovulation date ODA according to the menstrual cycle Cy using the Ogino calculation logic LG1 (step S13). For example, in step S12, the server device 100 may predict multiple consecutive menstrual cycles Cy (for example, a year's worth of menstrual cycles Cy) and predict the expected ovulation date ODA for each menstrual cycle Cy.
[0029] Then, the server device 100 predicts the pregnancy timing TA1 (an example of the timing of the second event), which is the most likely time for pregnancy (an example of the second event), based on the expected ovulation date (ODA) (step S14). For example, the server device 100 may define two days before the expected ovulation date (ODA) as a "particularly fertile day," and then predict the pregnancy timing TA1, which is composed of pregnancy levels, such as defining the day before and the day after the "particularly fertile day" as "more fertile days," and the day two days before and the day after the "particularly fertile day" as "fertile days." For example, the server device 100 may predict the pregnancy timing TA1 for each expected ovulation date (ODA).
[0030] The server device 100 then generates a menstrual cycle calendar CL that displays the menstrual cycle Cy, the expected ovulation date ODA, and the timing of conception TA1, and controls the display so that the generated menstrual cycle calendar CL is displayed on the user device 10 (step S15). Note that the display control of information on the user device 10 is equivalent to providing information to user U.
[0031] Up to this point, the information processing related to the prerequisite technology has been explained using Figure 1. As a result of the information processing related to the prerequisite technology, the server device 100 obtains information indicating the menstrual cycle Cy (an example of first event information) and information on the timing of pregnancy TA1 (an example of second event information).
[0032] [3. Proposed Technology] Next, the information processing related to the proposed technology will be explained. Figure 2 is a diagram showing an example of the information processing related to the proposed technology. As shown in Figure 2, the information processing related to the proposed technology may also be implemented in the information processing system 1. In the information processing related to the proposed technology, a predetermined calculation logic different from the Ogino calculation logic LG1 (hereinafter referred to as "proposed logic LG2") is used.
[0033] In the proposed logic LG2, it is necessary to detect substances related to pregnancy (for example, substances related to the second event) from the user U's body (specifically, secretions secreted from the user U's body). Substances related to pregnancy may be, for example, hormones secreted from the pituitary gland or hormones secreted from the ovaries, and these female hormones are contained in vaginal discharge such as menstrual blood. Therefore, a sanitary product PD may be used to detect these substances. A sanitary product PD may be an absorbent article (a nonwoven fabric product such as a panty liner) attached to underwear, etc., and has a detection means DC for detecting female hormones contained in vaginal discharge.
[0034] Figure 2 shows an example where user U is wearing the detection device DC. The detection device DC may be, for example, a biomarker. User U then checks the reaction results daily to see whether the biomarker has reacted to a specific female hormone.
[0035] Here, the reaction of the detection means DC will be explained using Figure 3. Figure 3 is a diagram illustrating the reaction of the detection means DC. Figure 3 shows one menstrual cycle. As shown in Figure 3, the menstrual cycle is divided into four phases: menstruation, follicular phase, ovulation, and luteal phase, and the period of about three days before and after ovulation is said to be the most fertile period.
[0036] The period from the end of menstruation to ovulation corresponds to the follicular phase. During the follicular phase, the blood concentrations of follicle-stimulating hormone and luteinizing hormone, which are secreted from the pituitary gland, increase. Therefore, the detection means DC may have the function of detecting two types of female hormones, follicle-stimulating hormone and luteinizing hormone. For example, the detection means DC may consist of a biomarker that changes color in response to follicle-stimulating hormone, or a biomarker that changes color in response to luteinizing hormone. In such an example, if user U is in the follicular phase and the concentration of follicle-stimulating hormone or luteinizing hormone in menstrual blood is elevated, two lines will appear on the sanitary product PD.
[0037] Furthermore, the period from the end of ovulation until the start of the next menstruation corresponds to the luteal phase. During the luteal phase, the blood concentrations of progesterone and estrogen secreted from the ovaries increase. For this reason, the detection means DC may have the function of detecting two types of female hormones, progesterone and estrogen. For example, the detection means DC may consist of a biomarker that changes color in response to progesterone, or a biomarker that changes color in response to estrogen. In such an example, if user U is in the luteal phase and the concentration of progesterone or estrogen in the menstrual blood is elevated, two lines will appear on the sanitary product PD.
[0038] The substance to which the detection means DC reacts is not limited to the above examples, and may also be estrogen, progesterone, short-chain fatty acids, etc.
[0039] Returning to the explanation of Figure 2, an example is shown where the detection means DC reacts to vaginal discharge (specifically, each of the two types of female hormones), resulting in the appearance of the judgment sign SK (two lines), which indicates that user U is in a period when she is fertile (for example, the follicular phase or the luteal phase).
[0040] In this manner, when the appearance of the judgment sign SK is confirmed, the user U records the appearance of the judgment sign SK on the application AP. The user device 10 then inputs detection result information RE, including the appearance date RDA of the judgment sign SK, to the server device 100 (step S21). The appearance date RDA includes the concepts of the date on which the user confirmed the appearance of the judgment sign SK and the date on which the user U recorded the appearance of the judgment sign SK. Furthermore, if the detection means DC is equipped with a sensor that has a communication function, the appearance date RDA may further include the concept of the date on which the sensor detected the appearance of the judgment sign SK and transmitted it to the server device 100.
[0041] The server device 100 predicts a pregnancy timing TA2 (an example of the occurrence timing of the second event) according to the appearance date RDA by means of the proposal logic LG2 (step S22). The proposal logic LG2 calculates, starting from the appearance part RDA (the first day), the subsequent three days as "days when pregnancy is likely to occur specified from the components of the body".
[0042] Therefore, the server device 100 uses the proposal logic LG2 to define the period from the date indicated by the appearance date RDA to three days later as "days when pregnancy is particularly likely to occur". Further, the server device 100 may predict the period constituted by combining the pregnancy levels determined in the information processing related to the prior art as the pregnancy timing TA2. For example, the server device 100 may predict the pregnancy timing TA2 for the menstrual cycle Cy including the appearance date RDA among a plurality of consecutive menstrual cycles Cy (for example, the menstrual cycles Cy for one year).
[0043] In such a state, the server device 100 overwrites and displays the pregnancy timing TA2 with respect to the pregnancy timing TA1 currently displayed in the menstrual cycle calendar CL (step S23). Specifically, the server device 100 generates a menstrual cycle calendar CL (an example of schedule information) in which the pregnancy timing TA2 is displayed based on the information indicating the menstrual cycle Cy (an example of the first event information), the information of the pregnancy timing TA1 (an example of the second event information), and the information of the pregnancy timing TA2 (an example of the prediction result information).
[0044] Here, the screen transition in the menstrual cycle calendar CL will be described with reference to FIGS. 4 and 5. FIG. 4 is a diagram showing an example (1) of the screen transition. FIG. 4(a) shows an example of the screen G11 displayed on the user device 10 by the display control in step S15 of FIG. 1.
[0045] Therefore, the menstrual cycle calendar CL included in the screen G11 is one of the menstrual cycles Cy predicted based on the menstrual start date MDA (for example, the most recent menstrual cycle Cy), and according to the Ogino method, the predicted ovulation date ODA "January 18th" is obtained. According to such an example, as shown in FIG. 4(a), the server device 100 determines "January 16th", which is two days before the predicted ovulation date ODA "January 18th", as a "particularly fertile day". Further, the server device 100 determines "January 15th" and "January 17th", which are the first day before and after starting from "January 16th", as "more fertile days". Further, the server device 100 determines "January 14th" and "January 18th", which are the second day before and after starting from "January 16th", as "fertile days". Thus, the server device 100 may predict the pregnancy level composed of a "particularly fertile day", a "more fertile day", and a "fertile day" as the pregnancy timing TA1. As shown in FIG. 4(a), the information on the pregnancy timing TA1 is displayed on the menstrual cycle calendar CL.
[0046] In addition, the menstrual cycle calendar CL may also show the predicted menstruation date, the menstruation date (menstruation start date), the follicular phase, the luteal phase, etc.
[0047] In such a state, when the user U confirms the appearance of the determination sign SK, the user U can record the detection result information RE in the app AP after designating the appearance date RDA. For example, if the appearance date RDA is "January 14th", the user U may, as shown in FIG. 4(a), designate the part of "January 14th" among the dates of the menstrual cycle calendar CL. Thus, when the appearance date RDA is designated via the menstrual cycle calendar CL, the screen transitions to the screen G12 for recording the detection result information RE.
[0048] FIG. 4(b) shows an example of the screen G12 displayed on the user device 10. The display content on the screen G12 is not limited to the example of FIG. 4(b), but at least includes an area for recording the appearance of the determination sign SK (double line). And a scene where the user U selects the area is shown.
[0049] Furthermore, suppose that user U presses the save button BT in this state. In this case, detection result information RE, which includes the appearance date RDA of the judgment sign SK (two lines) being "January 14th", is recorded in the application AP. That is, detection result information RE is input to the server device 100.
[0050] Next, Figure 5 will be explained. Figure 5 is a diagram showing an example of screen transition (2). When the save button BT is pressed, the server device 100 transitions from screen G12 to screen G2. Figure 5 shows an example of screen G2 displayed on the user device 10 after the save button BT is pressed.
[0051] Screen G2 displays a menstrual cycle calendar CL similar to that of screen G1. The menstrual cycle calendar CL shows that the expected ovulation date (ODA) is "January 18th," as well as the pregnancy timing TA1, which is composed of pregnancy levels, the expected date of menstruation, the actual date of menstruation, the follicular phase, the luteal phase, etc. However, as shown in Figure 5, the information for pregnancy timing TA1 is overwritten by the information for pregnancy timing TA2.
[0052] Following the example in Figure 4(a), if the appearance date RDA is "January 14th", the server device 100 uses the proposed logic LG2 to define the period from the appearance date RDA "January 14th" to three days later, i.e., the period from "January 14th to January 16th", as "particularly fertile days". The server device 100 may then generate a menstrual cycle calendar CL by overwriting the pregnancy timing TA1, which is composed of pregnancy levels, with the pregnancy timing TA2, which defines the period from "January 14th to January 16th" as "particularly fertile days". As a result, as shown in Figure 5, the information of the pregnancy timing TA2, which is composed of pregnancy levels, can be displayed on the menstrual cycle calendar CL.
[0053] Furthermore, through this screen transition, user U can learn that the most reliable period for conception is "January 14th to January 16th," and that having sexual intercourse during this period increases the chances of successful conception.
[0054] Furthermore, user U can learn about periods that overlap with the results of the Ogino method, as well as periods that differ from the results of the Ogino method, which allows for a wider range of choices regarding when to have sexual intercourse. For example, if the proposed logic LG2 suggests that intercourse should be performed between January 14th and January 16th, but the user is not feeling well, they can consider shifting it to January 17th, calculated based on the proposed logic LG1, as part of their fertility plan.
[0055] [4. Server Device Configuration] The server device 100 according to the embodiment will be described using Figure 6. Figure 6 is a diagram showing an example of the configuration of the server device 100 according to the embodiment. As shown in Figure 6, the server device 100 has a communication unit 110, a storage unit 120, and a control unit 130.
[0056] (Communication Unit 110) The communication unit 110 is implemented by, for example, a NIC (Network Interface Card). For example, the communication unit 110 transmits and receives information with the user device 10.
[0057] (Storage Unit 120) The storage unit 120 is implemented by, for example, a semiconductor memory element such as RAM (Random Access Memory) or flash memory, or a storage device such as a hard disk or optical disc. The storage unit 120 may store, for example, data and programs related to the information processing according to the embodiment. Also, as shown in Figure 6, the storage unit 120 may consist of a menstruation-related information storage unit 121, a detection result-related information storage unit 122, and condition information 123.
[0058] The menstrual cycle-related information storage unit 121 may store the menstrual cycle-related information, including the menstrual cycle start date (MDA), menstrual cycle (Cy), expected ovulation date (ODA), and pregnancy timing (TA1). For example, the menstrual cycle-related information storage unit 121 may store menstrual cycle-related information for each user U.
[0059] The detection result-related information storage unit 122 may store detection result information RE and pregnancy timing TA2 as detection result-related information. For example, the detection result-related information storage unit 122 may store detection result-related information for each user U.
[0060] Condition information 123 may store condition information used in the condition determination described later.
[0061] (Control Unit 130) The control unit 130 is implemented by a CPU (Central Processing Unit) or MPU (Micro Processing Unit), etc., which executes various programs (for example, information processing programs according to the embodiment) stored in the storage device inside the server device 100 using RAM as the working area. The control unit 130 is also implemented by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array).
[0062] As shown in Figure 6, the control unit 130 includes a reception unit 131, a first prediction unit 132, a second prediction unit 133, an acquisition unit 134, a generation unit 135, a display control unit 136, and a determination unit 137, and realizes or executes the information processing functions and operations described below. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in Figure 6, and other configurations are also possible as long as they perform the information processing described later. Also, the connection relationships of the various processing units in the control unit 130 are not limited to the connection relationships shown in Figure 6, and other connection relationships are also possible.
[0063] (Reception Unit 131) The reception unit 131 receives various types of information related to requests, inputs, inquiries, etc. For example, the reception unit 131 receives menstrual information MT. The reception unit 131 also receives detection result information RE.
[0064] (First prediction unit 132) The first prediction unit 132 performs predictions in information processing related to the prerequisite technology. For example, the first prediction unit 132 may predict the menstrual cycle Cy based on the menstrual start date MDA. The first prediction unit 132 may also predict the expected ovulation date ODA according to the menstrual cycle Cy using the Ogino calculation logic LG1. The first prediction unit 132 may also predict the timing of conception TA1 based on the expected ovulation date ODA.
[0065] (Second prediction unit 133) The second prediction unit 133 performs predictions in the information processing related to the proposed technology. That is, the second prediction unit 133 predicts the pregnancy timing TA2 according to the appearance date RDA by applying the detection result information RE to the proposed logic LG2. The detection result information RE may be information indicating the timing at which a predetermined reaction result (e.g., the appearance of two lines) is obtained by a detection means DC provided in the sanitary product PD worn by user U reacts to the user U's secretions (e.g., female hormones).
[0066] (Acquisition Unit 134) The acquisition unit 134 acquires information necessary for information processing related to the proposed technology. For example, the acquisition unit 134 may acquire information indicating the menstrual cycle Cy (an example of first event information) and information indicating the timing of pregnancy TA1 (an example of second event information). The acquisition unit 134 may also acquire information indicating the timing of pregnancy TA2 (an example of prediction result information).
[0067] (Generation Unit 135) Based on information indicating the menstrual cycle Cy (an example of first event information), information indicating the pregnancy timing TA1 (an example of second event information), and information indicating the pregnancy timing TA2 (an example of prediction result information), the generation unit 135 generates a menstrual cycle calendar CL (an example of schedule information) in which the pregnancy timing TA2 is displayed. For example, the generation unit 135 may generate a menstrual cycle calendar CL in which the pregnancy timing TA1 is overwritten by the pregnancy timing TA2.
[0068] (Display control unit 136) The display control unit 136 controls the display so that the menstrual cycle calendar CL is displayed on the user device 10.
[0069] (Determination Unit 137) The determination unit 137 performs a process to determine whether or not to execute a prediction process to predict the timing of pregnancy TA2. For example, if the determination unit 137 can determine that user U's menstrual cycle Cy is normal based on whether or not there is a change in the menstrual cycle Cy, the relationship between a predetermined period T2 starting from the expected ovulation date ODA and the appearance date RDA, and the number of days in the menstrual cycle Cy, it may execute a prediction process to predict the timing of pregnancy TA2. On the other hand, if the determination unit 137 can determine that user U's menstrual cycle Cy is not normal, it does not need to execute a prediction process to predict the timing of pregnancy TA2.
[0070] Furthermore, the determination unit 137 may determine whether or not to execute a prediction process to predict the timing of pregnancy TA2 based on the input status of the detection result information RE by the user U. For example, the determination unit 137 may determine whether or not to execute a prediction process to predict the timing of pregnancy TA2 based on the suitability of the input based on the input status of the detection result information RE by the user U.
[0071] As described above, according to the example, the server device 100 performs a prediction process to predict the timing of pregnancy TA2 according to the normality of the menstrual cycle Cy. The server device 100 also performs a prediction process to predict the timing of pregnancy TA2 according to the input qualifications of the detection result information RE.
[0072] [5. Examples of Server Device Operation] From here, we will explain examples of the operation of the server device 100. Specifically, we will explain examples of operation based on the normality determination of the menstrual cycle Cy and examples of operation based on the input qualification of the detection result information RE. Note that the following examples of operation are for one user U, but similar information processing may be performed for each different user U.
[0073] (Operation Example 1) An example of operation based on normality determination will be explained using Figure 7. Figure 7 is a flowchart (1) showing the operation procedure based on normality determination. Figure 7 shows a scene in which normality determination is made based on whether or not there is a change in the menstrual cycle Cy. In the example of Figure 7, it is assumed that the server device 100 has already predicted the menstrual cycle Cy by information processing related to the prerequisite technology and is waiting for the input of detection result information RE.
[0074] The determination unit 137 determines whether or not a new menstrual start date (MDA) has been entered (step S701). The second prediction unit 133 adopts the current menstrual cycle Cy as the target of operation as long as no new menstrual start date (MDA) has been entered (step S701; No) (step S702). Adopting as the target of operation means controlling the information processing related to the proposed technology so that the current menstrual cycle Cy is used. The current menstrual cycle Cy is the latest predicted menstrual cycle Cy.
[0075] On the other hand, if a new Menstrual Start Date (MDA) is entered (step S701; Yes), the determination unit 137 determines whether or not a change has occurred in the current menstrual cycle (Cy) based on the newly entered Menstrual Start Date (MDA) (step S703).
[0076] Returning to Figure 7, if no change has occurred in the current menstrual cycle Cy (step S703; No), the determination unit 137 may select the current menstrual cycle Cy as the target for operation (step S702). No change in the current menstrual cycle Cy may indicate, for example, that the menstrual cycle Cy is normal.
[0077] On the other hand, if a change occurs in the current menstrual cycle Cy (step S703; Yes), the first prediction unit 132 re-predicts the menstrual cycle Cy based on the newly entered menstrual start date MDA (step S704). A change in the current menstrual cycle Cy may indicate, for example, that the menstrual cycle Cy is not normal.
[0078] Then, the generation unit 135 regenerates the menstrual cycle calendar CL in which the re-predicted menstrual cycle Cy is displayed (step S705).
[0079] In step S704, the first prediction unit 132 may re-predict the expected ovulation date ODA according to the re-predicted menstrual cycle Cy using the Ogino calculation logic LG1, and re-predict the pregnancy timing TA1 based on the re-predicted expected ovulation date ODA. Therefore, the generation unit 135 may regenerate a menstrual cycle calendar CL that displays the menstrual cycle Cy, the expected ovulation date ODA, and the pregnancy timing TA1.
[0080] The display control unit 136 controls the display so that the regenerated menstrual cycle calendar CL is displayed on the user device 10 (step S706).
[0081] Once the menstrual cycle Cy is updated in this way, the process from step S701 may be repeated for the updated menstrual cycle Cy.
[0082] (Operation Example 2) An example of operation based on normality determination will be explained using Figure 8. Figure 8 is a flowchart (2) showing the operation procedure based on normality determination. Figure 8 shows a scenario in which normality determination is made based on the relationship between a predetermined period T2 starting from the expected ovulation day ODA and the appearance day RDA. Furthermore, the operation procedure shown in Figure 9 may be executed when the current menstrual cycle Cy is selected as the target of the operation according to the operation procedure explained in Figure 7.
[0083] The reception unit 131 determines whether or not it has received the detection result information RE (step S801). If the reception unit 131 has not received the detection result information RE (step S801; No), it waits until it receives the detection result information RE.
[0084] On the other hand, if the acquisition unit 134 receives the detection result information RE (step S801; Yes), it acquires information on one menstrual cycle Cy (hereinafter referred to as "the target menstrual cycle Cy") that includes the appearance date RDA from among the current menstrual cycle Cy (for example, multiple consecutive menstrual cycles Cy) (step S802).
[0085] The determination unit 137 determines whether the number of days in the target menstrual cycle Cy is greater than a predetermined number of days (step S803). Generally, a menstrual cycle of 25 to 38 days is considered to be within the normal range, but depending on age, the menstrual cycle may be shorter, around 20 days. Therefore, the determination unit 137 may determine whether the number of days in the target menstrual cycle Cy is 20 days or more.
[0086] The second prediction unit 133 does not need to perform the prediction process to predict the timing of pregnancy TA2 if the number of days in the target menstrual cycle Cy is less than a predetermined number of days (less than 20 days) (step S803; No) (step S804). A number of days in the menstrual cycle Cy being less than a predetermined number of days may indicate, for example, that the menstrual cycle Cy is not normal.
[0087] Furthermore, the display control unit 136 may notify the user U that the prediction process will not be executed (step S805).
[0088] On the other hand, if the number of days in the target menstrual cycle Cy is greater than a predetermined number of days (20 days or more) (step S803; Yes), the determination unit 137 determines whether the detection result information RE was entered during a predetermined period T2 starting from the expected ovulation date ODA (step S806). The predetermined period T2 may be a statistically determined period. For example, if it is statistically known that 80% or more of different users U have entered the detection result information RE during the period from "5 days before" the expected ovulation date ODA to "3 days after" the expected ovulation date ODA, then that period may be set as the predetermined period T2.
[0089] If the detection result information RE is input outside the predetermined period T2 (step S806; No), the second prediction unit 133 does not need to perform the prediction process to predict the pregnancy timing TA2 (step S804). This allows the server device 100 to determine, for example, inputs that are too far removed from the expected ovulation date ODA as invalid inputs and control the system so that prediction processing based on invalid inputs is not performed.
[0090] If detection result information RE is input during a predetermined period T2 (step S806; Yes), the determination unit 137 determines, based on the target menstrual cycle Cy, whether the appearance date RDA is included in a phase other than the menstrual phase, such as the menstrual phase, follicular phase, ovulation phase, or luteal phase (step S807). Specifically, the determination unit 137 may determine whether the appearance date RDA is included in any of the follicular phase, ovulation phase, or luteal phase among the classification periods indicated by the target menstrual cycle Cy.
[0091] Figure 9 shows an excerpt from Figure 3, specifically the menstrual cycle portion. As explained in Figure 3, blood levels of certain female hormones increase from the follicular phase to the ovulation phase. Blood levels of certain female hormones also increase during the luteal phase. In other words, the appearance of the detection sign SK is usually confirmed during this period. Therefore, it is generally considered that the detection result information RE is entered between the follicular phase and the luteal phase.
[0092] Based on this approach, if the second prediction unit 133 determines that the onset date RDA is included in the menstrual period (step S807; No), it does not need to perform the prediction process to predict the pregnancy timing TA2, in accordance with its judgment that an abnormality is occurring in which the blood concentration of a specific female hormone increases during the menstrual period (step S804). In addition to this judgment, the second prediction unit 133 may also, for example, not perform the prediction process if it determines that the detection result information RE received this time is an invalid input.
[0093] On the other hand, if the second prediction unit 133 determines that the RDA for the onset date is outside of the menstrual period (step S807; Yes), it predicts the pregnancy timing TA2 according to the RDA for the onset date using the proposed logic LG2 (step S808).
[0094] Furthermore, the acquisition unit 134 acquires information on the menstrual cycle (Cy), expected ovulation date (ODA), and pregnancy timing (TA1) as a result of the information processing related to the prerequisite technology (step S809).
[0095] The generation unit 135 generates a menstrual cycle calendar CL based on the information obtained in step S809 and the information indicating the pregnancy timing TA2 (step S810). For example, the generation unit 135 generates a menstrual cycle calendar CL in which pregnancy timing TA2 is overwritten with pregnancy timing TA2 based on the information indicating the menstrual cycle Cy, the information indicating pregnancy timing TA1, and the information indicating pregnancy timing TA2.
[0096] Then, the display control unit 136 controls the display so that the menstrual cycle calendar CL is displayed on the user device 10 (step S811).
[0097] From here, we will explain examples of operations based on the input qualifications of the detection result information RE. Note that the following examples of operations can be considered operating procedures based on the judgment conditions on the edge side (user U side).
[0098] (Operation Example 3) An example of operation based on input qualification will be explained using Figure 10. Figure 10 is a flowchart (1) showing the operation procedure based on input qualification.
[0099] For example, the judgment sign SK may continue to appear over multiple dates. For instance, if user U confirms that the judgment sign SK first appeared on January 14th, they will record detection result information RE including the appearance date RDA "January 14th".
[0100] However, the judgment sign SK may continue to appear even after January 14th, so for example, user U may record detection result information RE on the following day, January 15th. In this way, if detection result information RE is entered consecutively, a new pregnancy timing TA2 will be predicted each time it is entered, resulting in a situation where the pregnancy timing TA2 shifts. To avoid this situation, regardless of whether detection result information RE is entered consecutively or not, performing prediction processing using only the first input detection result information RE (detection result information RE that includes the appearance date RDA "January 14th") will allow for a more reliable prediction of pregnancy timing TA2. Therefore, the server device 100 may operate according to the procedure shown in Figure 11.
[0101] For example, the display control unit 136 determines whether or not the menstrual cycle calendar CL generated based on the initial input detection result information RE has already been presented to the user U (step S1001). If the display control unit 136 has not yet presented the menstrual cycle calendar CL generated based on the initial input detection result information RE to the user U (step S1001; No), it waits until it presents the menstrual cycle calendar CL generated based on the initial input detection result information RE to the user U.
[0102] If the reception unit 131 has already presented the user U with the menstrual cycle calendar CL generated based on the detection result information RE entered initially (step S1001; Yes), it determines whether the detection result information RE has been re-entered (step S1002). If the detection result information RE has not been re-entered (step S1002; No), the reception unit 131 waits until the detection result information RE is re-entered.
[0103] Here, the determination unit 137 determines that if the detection result information RE is re-entered (step S1002; Yes), the detection result information RE has been entered consecutively (step S1003). Consecutive input of detection result information RE includes not only the re-entry of detection result information RE on a day after the initial input date of detection result information RE (an example of the first input date), but also the input of detection result information RE multiple times on the initial input date.
[0104] Furthermore, if the second prediction unit 133 determines that detection result information RE has been input consecutively, it does not need to perform prediction processing using the re-inputted detection result information RE (step S1004).
[0105] The determination unit 137 may also determine whether the detection result information RE from the initial input has been deleted and then re-input. For example, the determination unit 137 may determine whether the detection result information RE from the initial input has been deleted and then re-input on a date after the initial input date.
[0106] The second prediction unit 133 may perform a re-prediction using the detection result information RE re-entered on a later date after the initial input date has been deleted. The generation unit 135 may also generate a menstrual cycle calendar CL that displays the re-predicted pregnancy timing TA2.
[0107] (Operation Example 4) An example of operation based on input qualification will be explained using Figure 11. Figure 11 is a flowchart (2) showing the operation procedure based on input qualification.
[0108] For example, suppose user U recorded detection result information RE including the appearance date RDA "January 14th" after the appearance of judgment sign SK, and then remembered that although judgment sign SK had also appeared on the previous day, January 13th, user U had not recorded detection result information RE including the appearance date RDA "January 13th". In such a case, user U may re-record detection result information RE, for example, specifying "January 13th" as the appearance date RDA. In this example, the pregnancy timing TA2 predicted based on detection result information RE including the appearance date RDA "January 13th" is more reliable than the pregnancy timing TA2 predicted based on detection result information RE including the appearance date RDA "January 14th". Therefore, the server device 100 may operate according to the procedure shown in Figure 11.
[0109] For example, the display control unit 136 determines whether or not the menstrual cycle calendar CL generated based on the initial input detection result information RE has already been presented to the user (step S1101). If the display control unit 136 has not yet presented the menstrual cycle calendar CL generated based on the initial input detection result information RE to the user U (step S1101; No), it waits until it presents the menstrual cycle calendar CL generated based on the initial input detection result information RE to the user U.
[0110] If the reception unit 131 has already presented the user U with the menstrual cycle calendar CL generated based on the detection result information RE entered initially (step S1101; Yes), it determines whether the detection result information RE has been re-entered (step S1102). If the detection result information RE has not been re-entered (step S1102; No), the reception unit 131 waits until the detection result information RE is re-entered.
[0111] If the detection result information RE is re-entered (step S1102; Yes), the determination unit 137 determines whether or not a date prior to the initial input date is specified as the occurrence date RDA in the re-entered detection result information RE (step S1103). In other words, the determination unit 137 determines whether or not the detection result information RE is re-entered with a date prior to the initial input date specified as the detection date (occurrence date of the determination sign SK).
[0112] If the second prediction unit 133 does not specify a date prior to the initial input date as the occurrence date RDA (step S1103; No), it does not need to perform prediction processing using the re-entered detection result information RE (step S1104).
[0113] On the other hand, if a date prior to the initial input date is specified as the occurrence date RDA (step S1103; Yes), the second prediction unit 133 may perform prediction processing using the re-input detection result information RE (step S1105).
[0114] Up to this point, we have shown examples of how the determination unit 137 determines whether or not to execute the prediction process from various perspectives. However, the determination unit 137 may also make the following determination regarding whether or not to execute the prediction process.
[0115] For example, if detection result information RE is input for several consecutive days (for example, three consecutive days), and then after a certain period of time, detection result information RE is input again for several consecutive days (for example, three consecutive days), the determination unit 137 may determine that it will not perform prediction processing using the detection result information RE after the period of time has elapsed.
[0116] [6. Other Embodiments] (Modification 1) The display control unit 136 may control the display so that predetermined information based on a trend calculated based on the appearance date RDA (an example of detection timing) included in each of the detection result information REs accumulated so far is displayed on the user device 10. For example, the display control unit 136 may determine a predetermined timing according to the trend calculated based on the appearance date RDA, and when the determined predetermined timing is reached, it may control the display so that predetermined information such as information indicating that the possibility of pregnancy is increasing, or information suggesting the use of sanitary products PD is displayed on the user device 10.
[0117] Let's look at a concrete example of this information processing. As explained above, when the second prediction unit 133 receives the detection result information RE, it predicts the pregnancy timing TA2 for the menstrual cycle Cy (the target menstrual cycle Cy) corresponding to the appearance date RDA included in the detection result information RE. On the other hand, for menstrual cycles Cy prior to the target menstrual cycle Cy (if the target menstrual cycle Cy is this month's menstrual cycle, then the earlier menstrual cycle Cy is the menstrual cycle from the following month onwards), the pregnancy timing TA1 based on the Ogino calculation logic LG1 is used and presented to the user U. The received detection result information RE is also sequentially stored in the server device 100.
[0118] Here, for example, the server device 100 can learn the trend of the appearance date RDA by inputting the detection result information RE into the AI model. As a result, for example, suppose the AI model learns and calculates a trend for one user U, such as "the judgment sign SK often appears three days before ovulation." In this case, the display control unit 136 may determine "a timing of three days or more before" (an example of a predetermined timing) based on the statistical timing of "three days before ovulation." Furthermore, if this timing actually occurs in the menstrual cycle Cy, the display control unit 136 may control the display so that notification information such as "Why not try using a panty liner soon?" or "Your fertile days may be approaching" is displayed on the user device 10. For example, the display control unit 136 may push the notification information or display it on the screen within the application AP.
[0119] The information processing described in Modification 1 personalizes the notification timing for each user U, enabling the promotion of the use of sanitary products PD and appropriate support for fertility treatment.
[0120] (Modification 2) Furthermore, as described above, the proposed technology of the present invention is applicable not only to cases such as predicting the timing of pregnancy TA2, but also to a variety of other cases. For example, the proposed technology can predict the timing of menopause from changes in the amount of secretions (e.g., female hormones) of user U (e.g., changes in the amount of female hormones over time) and overwrite the timing of menopause predicted by a predetermined conventional method. In addition, the proposed technology can predict the expected date of menstruation from changes in the amount of secretions (e.g., female hormones) of user U (e.g., changes in the amount of female hormones over time) and overwrite the expected date of menstruation predicted by a predetermined conventional method. Thus, the proposed technology can be particularly effectively used for predicting health conditions that may fluctuate under the influence of female hormones.
[0121] [7. Hardware Configuration] The server device 100 (an example of an information processing device) according to the above-described embodiment is realized by a computer 1000 having a configuration such as that shown in Figure 12. Figure 12 is a diagram showing an example of a hardware configuration. The computer 1000 is connected to an output device 1010 and an input device 1020, and an arithmetic unit 1030, a cache 1040, a memory 1050, an output interface 1060, an input interface 1070, and a network interface 1080 are connected by a bus 1090.
[0122] The arithmetic unit 1030 operates based on programs stored in the cache 1040 and memory 1050, as well as programs read from the input device 1020, and executes various processes. The cache 1040 is a cache that temporarily stores data used by the arithmetic unit 1030 for various calculations, such as RAM. The memory 1050 is a storage device in which data used by the arithmetic unit 1030 for various calculations and various databases are registered, and is implemented as ROM (Read Only Memory), HDD (Hard Disk Drive), flash memory, etc.
[0123] The output IF 1060 is an interface for transmitting information to be output to an output device 1010 that outputs various types of information, such as a monitor or printer. This interface may be implemented using connectors of standards such as USB (Universal Serial Bus), DVI (Digital Visual Interface), or HDMI (High Definition Multimedia Interface). On the other hand, the input IF 1070 is an interface for receiving information from various input devices 1020, such as a mouse, keyboard, and scanner. This interface may be implemented using USB, for example.
[0124] For example, the input device 1020 may be implemented by a device that reads information from an optical recording medium such as a CD (Compact Disc), DVD (Digital Versatile Disc), or PD (Phase Change Rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), tape media, magnetic recording media, or semiconductor memory. Alternatively, the input device 1020 may be implemented by an external storage medium such as a USB memory.
[0125] The network interface 1080 has the function of receiving data from other devices via the network N and sending it to the computing device 1030, and also transmitting data generated by the computing device 1030 to other devices via the network N.
[0126] Here, the arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output IF 1060 and the input IF 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or memory 1050 onto the cache 1040 and executes the loaded program. For example, if the computer 1000 functions as a server device 100, the arithmetic unit 1030 of the computer 1000 will realize the functions of the control unit 130 by executing the program loaded onto the cache 1040.
[0127] [8. Others] Furthermore, all or part of the processes described as being performed automatically in each of the above embodiments may be performed manually, or all or part of the processes described as being performed manually may be performed automatically by known methods. In addition, the processing procedures, specific names, and information including various data and parameters shown in the above documents and drawings may be changed at will unless otherwise specified. For example, the various information shown in each figure is not limited to the information shown.
[0128] Furthermore, the components of each illustrated device are functionally conceptual and do not necessarily need to be physically configured as shown. In other words, the specific forms of distribution and integration of each device are not limited to those shown, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads and usage conditions.
[0129] Furthermore, the above embodiments can be combined as appropriate, provided that the processing content is not contradictory.
[0130] Although some embodiments of the present invention have been described in detail above with reference to the drawings, these are illustrative examples, and the present invention can be implemented in various other forms with modifications and improvements based on the knowledge of those skilled in the art, including the embodiments described in the section on the present invention.
[0131] 1 Information Processing System 10 User Device 100 Server Device 110 Communication Unit 120 Storage Unit 130 Control Unit 131 Reception Unit 132 First Prediction Unit 133 Second Prediction Unit 134 Acquisition Unit 135 Generation Unit 136 Display Control Unit 137 Judgment Unit
Claims
1. An information processing device comprising: an acquisition unit that acquires first event information, which is the result of predicting a first event based on user input information, and second event information, which is the result of predicting the timing of the occurrence of a second event based on the first event information; a prediction unit that predicts the timing of the occurrence of a second event using a predetermined calculation logic different from the prediction of the second event information, using detection result information obtained when a substance related to the second event is detected by a detection means provided on a nonwoven fabric product worn by the user; and a generation unit that generates schedule information in which the timing of the occurrence indicated by the prediction result information is displayed, based on prediction result information, which is the result of predicting the timing of the occurrence of the second event using the predetermined calculation logic, the first event information, and the second event information.
2. The information processing apparatus according to claim 1, wherein the acquisition unit acquires first event information indicating a predicted menstrual cycle based on the menstrual start date input by the user, acquires second event information indicating a pregnancy timing within the menstrual cycle in which the possibility of pregnancy is higher, based on the expected ovulation date calculated by applying the menstrual cycle to the Ogino calculation logic, the prediction unit predicts a pregnancy timing within the menstrual cycle in which the possibility of pregnancy is higher by applying the detection result information to a calculation logic different from the Ogino calculation logic as a predetermined calculation logic, and the generation unit generates a menstrual cycle calendar in which the pregnancy timing is displayed based on the prediction result information indicating the pregnancy timing predicted by the predetermined calculation logic, the first event information, and the second event information.
3. The information processing apparatus according to claim 2, wherein the prediction unit predicts one pregnancy timing consisting of a level of likelihood of conception for each menstrual cycle, using the detection result information input during the period of the menstrual cycle, and the generation unit executes a process to overwrite the pregnancy timing indicated by the second event information in the menstrual cycle calendar with the pregnancy timing predicted by the predetermined calculation logic.
4. The information processing apparatus according to claim 2, wherein the detection result information is information indicating the timing at which a predetermined reaction result was obtained when the detection means provided in the sanitary product worn by the user reacted to the user's secretions, and the information indicating the timing is input by the user.
5. The information processing apparatus according to claim 2, further comprising a determination unit that determines whether or not to execute a prediction process to predict the timing of pregnancy based on whether or not a first condition regarding input timing indicated by the detection result information is met, wherein the prediction unit predicts the timing of pregnancy if it is determined that the first condition is met.
6. The determination unit determines whether or not to execute a prediction process for predicting the timing of pregnancy based on whether or not at least one of the first condition relating to the input timing or the second condition relating to the menstrual cycle is met, and the prediction unit predicts the timing of pregnancy if it is determined that the first condition or the second condition is met, the information processing apparatus according to claim 5.
7. The information processing apparatus according to claim 6, wherein the first condition is a period starting from the expected ovulation date and is based on a period determined from the statistics of input timing indicated by the detection result information, and the second condition is a condition based on the number of days in the menstrual cycle.
8. The information processing apparatus according to claim 2, wherein the prediction unit predicts the timing of pregnancy using the detection result information on the first input day among the input days on which the detection result information is input during the period included in the menstrual cycle, and the generation unit generates the menstrual cycle calendar on which the timing of pregnancy is displayed during the menstrual cycle including the first input day.
9. The information processing apparatus according to claim 8, wherein if the detection result information is re-input on a day later than the initial input date, the prediction unit does not perform a prediction using the re-input detection result information.
10. The information processing apparatus according to claim 8, wherein, while the menstrual cycle calendar generated based on the detection result information on the initial input date is being presented to the user, the prediction unit performs a re-prediction using the detection result information re-entered on a later date, and the generation unit generates the menstrual cycle calendar displaying the re-predicted timing of pregnancy.
11. The information processing apparatus according to claim 8, wherein the prediction unit, when the detection result information is re-input with a date earlier than the initial input date specified as the detection date, performs a re-prediction using the re-inputted detection result information.
12. The information processing apparatus according to claim 2, further comprising an output control unit that controls the output of predetermined information to each user, which is a trend for each user calculated based on the detection result information accumulated for each user, and which corresponds to the trend of detection timing indicated by the detection result information.
13. The information processing apparatus according to claim 12, wherein the output control unit determines a predetermined timing corresponding to the user based on the trend, and controls the output of the predetermined information to the user when the predetermined timing is reached, and the predetermined information includes at least one of the following: information indicating that the possibility of pregnancy is high, or information suggesting the use of the nonwoven fabric product.
14. An information processing method executed by an information processing device, comprising: an acquisition step of acquiring first event information, which is the result of predicting a first event based on user input information, and second event information, which is the result of predicting the timing of occurrence of a second event based on the first event information; a prediction step of predicting the timing of occurrence of a second event using a predetermined calculation logic different from the prediction of the second event information, using detection result information of a substance related to the second event detected by a detection means provided on a nonwoven fabric product worn by the user; and a generation step of generating schedule information in which the timing of occurrence indicated by the prediction result information is displayed, based on prediction result information, which is the result of predicting the timing of occurrence of the second event using the predetermined calculation logic, the first event information, and the second event information.
15. An information processing program that causes a computer to execute the following steps: an acquisition step for acquiring first event information, which is the result of predicting a first event based on user input information, and second event information, which is the result of predicting the timing of the occurrence of a second event based on the first event information; a prediction step for predicting the timing of the occurrence of a second event using a predetermined calculation logic different from the prediction of the second event information, using detection result information obtained when a substance related to the second event is detected by a detection means provided on a nonwoven fabric product worn by the user; and a generation step for generating schedule information in which the timing of the occurrence indicated by the prediction result information is displayed, based on prediction result information, which is the result of predicting the timing of the occurrence of the second event using the predetermined calculation logic, the first event information, and the second event information.