Information processing device, information processing method, and information processing program

Abstract

To provide a technique which allows for improving prediction accuracy of excretion by a wearer of an absorbent item.SOLUTION: An information processing device is provided, comprising a storage unit configured to store excretion information regarding excrement excreted on an absorbent item, an arithmetic processing unit configured to make predictions on excretion by a wearer of the absorbent item from the excretion information and environment information including at least either of temperature and humidity of a room of the wearer of the absorbent item, and an output processing unit for outputting a prediction result.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] In recent years, with the advancement of communication and sensing technologies, attempts have been made to electrically detect urine and the like in absorbent articles such as disposable diapers, urine pads, and sanitary products (see, for example, Patent Documents 1-6). Also, in nursing care facilities, the use of computers for nursing care has been proposed (see, for example, Patent Documents 7-9). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2019-130243 A [Patent Document 2] JP 2019-130244 A [Patent Document 3] JP 2019-141278 A [Patent Document 4] JP 2019-146721 A [Patent Document 5] JP 2019-141279 A [Patent Document 6] JP 2019-141280 A [Patent Document 7] JP 2007-25737 A [Patent Document 8] JP 2008-20976 A [Patent Document 9] JP 2019-139693 A Summary of the Invention [Problem to be solved by the invention]

[0004] The excretion of a wearer of an absorbent article may change depending on the environment the wearer is in. Therefore, for example, the excretion of the wearer cannot be accurately predicted only based on information regarding the past urination volume and urination time.

[0005] Therefore, an object of the present invention is to provide a technique capable of improving the accuracy of predicting excretion of a wearer wearing an absorbent article. [Means for solving the problem]

[0006] In order to solve the above problems, the present invention provides a method for predicting excretion by a wearer of an absorbent article based on environmental information, including at least one of the temperature and humidity of the room in which the wearer of the absorbent article lives, and excretion information.

[0007] In detail, the present invention is an information processing device comprising: a memory unit for storing excretion information, which is information relating to excrement excreted within an absorbent article; a calculation processing unit for making predictions regarding excretion by a wearer wearing the absorbent article based on environmental information including at least one of the temperature and humidity of the room in which the wearer of the absorbent article lives and the excretion information; and an output processing unit for outputting the results of the predictions.

[0008] The calculation processing unit may make predictions regarding excretion of a wearer who wears the absorbent article, using a prediction model that has been machine-learned using excretion information and environmental information as training data.

[0009] In addition, the calculation processing unit may use a prediction model trained by machine learning using past environmental information and excretion information stored in the memory unit as training data to make predictions regarding excretion by a wearer of the absorbent article based on information about the current environment transmitted from a sensor installed in the room.

[0010] In addition, the excretion information stored in the memory unit may include at least one of information transmitted from an excretion sensor provided in the absorbent article and information input into the terminal by the caregiver performing the work of replacing the absorbent article.

[0011] The calculation processing unit may also predict that the amount of urine excreted by the wearer of the absorbent article will decrease when the temperature of the room in which the wearer of the absorbent article lives increases, and that the amount of urine excreted by the wearer of the absorbent article will increase when the temperature of the room in which the wearer of the absorbent article lives decreases.

[0012] The present invention can also be understood from the aspect of a method. For example, the present invention may be an information processing method that refers to a storage unit that stores excretion information, which is information related to excreta excreted in an absorbent article, predicts excretion of a wearer who wears the absorbent article based on environmental information including at least one of the temperature and humidity of a room in which the wearer of the absorbent article lives, and the excretion information, and outputs the prediction result.

[0013] The present invention can also be understood from the aspect of a program. For example, the present invention may be an information processing program that causes an information processing device to refer to a storage unit that stores excretion information, which is information related to excreta excreted in an absorbent article, to predict excretion by a wearer of the absorbent article from environmental information including at least one of the temperature and humidity of a room in which the wearer of the absorbent article lives, and the excretion information, and to output the prediction result. Effect of the Invention

[0014] According to the present invention, it is possible to improve the accuracy of predicting excretion of a wearer wearing an absorbent article. [Brief description of the drawings]

[0015] [Figure 1] FIG. 1 is a diagram showing the overall configuration of an information processing system according to an embodiment. [Diagram 2] FIG. 2 is a functional block diagram of each device. [Diagram 3] FIG. 3 is a diagram showing an example of a processing flow when providing care using the information processing system. [Figure 4] FIG. 4 is a diagram showing an example of data referred to by the excretion prediction function. [Diagram 5] FIG. 5 is a diagram showing an example of a screen displayed on the field terminal. [Figure 6] FIG. 6 is a diagram showing an example of a screen for correcting data on urine volume. [Figure 7] FIG. 7 shows an example of a screen for inputting stool volume and stool properties. [Figure 8] FIG. 8 is a diagram illustrating the relationship between the correction of urination volume and the change in regression coefficient. [Figure 9] FIG. 9 is a diagram showing an example of a process flow related to the planning function. [Figure 10] FIG. 10 is an example of a screen displaying a comparison of exchange schedule plans. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] Hereinafter, embodiments of the present invention will be described with reference to the drawings. Note that the configurations of the following embodiments are merely examples, and the present invention is not limited to the configurations of these embodiments.

[0017] Fig. 1 is an overall configuration diagram of an information processing system according to an embodiment. As shown in Fig. 1, the information processing system 1 includes a server 2 capable of two-way communication via a network N and a wireless antenna 4, an on-site terminal 5, a management terminal 6, an excretion sensor 8, and an air conditioning sensor 9. The information processing system 1 is a system suitable for facilities used by people and animals who need help from others, and can be applied to, for example, nursing homes, hospital wards, animal care facilities, and various other facilities.

[0018] In this embodiment, the information processing system 1 is applied to a care facility used by users 7 such as elderly people who need the help of staff 3, and the information processing system 1 is applied to care mainly for changing absorbent articles (diapers and pads). The application of the information processing system 1 is not limited to a nursing home or to changing absorbent articles. The information processing system 1 is also not limited to a nursing home where care is provided within a nursing home building, and can be applied to, for example, a visiting nursing home where care is provided at the home of the user 7.

[0019] The network N is a communication line that connects information devices together, and is constructed using, for example, a LAN (Local Area Network) cable and hub installed in the care facility, a wireless LAN, or a public communication line such as the Internet.

[0020] Server 2 is a central processing unit (CPU) and random access memory (RAM). An information processing device equipped with an input / output interface, an SSD (Solid State Drive), etc. The server 2 can be accessed from the field terminal 5 and the management terminal 6, and processes various requests and performs various other arithmetic operations. The server 2 may be a cloud formed on the Internet.

[0021] The on-site terminal 5 is an information processing device used by the staff 3 when caring for the user 7. The on-site terminal 5 is preferably a tablet computer that the staff 3 can carry with them and whose screen is easy to check, but various information processing devices such as a smartphone, a smart watch, a wearable terminal, or a computer mounted on a mobile cart used by the staff 3 can be used. The on-site terminal 5 displays information and accepts various inputs required when the staff 3 cares for the user 7.

[0022] The management terminal 6 is an information processing device installed in the office of the staff 3. The management terminal 6 may be a desktop computer, a tablet computer, or any other type of information processing device. The management terminal 6 is used by the staff 3 to check the schedule and perform various setting operations.

[0023] The excretion sensor 8 is a sensor built into an absorbent article such as an absorbent pad or diaper worn by the user 7. For example, in the case of adult paper diapers, the user 7 wears a tape type or pants type diaper and places a urine pad inside the diaper, so that the urine pad mainly absorbs the urine. Then, when the urine pad becomes dirty, it is changed. Tape type or pants type diapers are usually changed once every one to two days. Depending on the changing schedule, a urine pad may not be used in combination. When changing such paper diapers, genital washing may be performed at the same time. When washing the genitals, the paper diaper is placed on the floor and the cleaning liquid is absorbed into the paper diaper and discarded. Therefore, it is the urine pad, tape type or pants type paper diaper that is equipped with a sensor. On the other hand, in the case of children's paper diapers, most people use only one tape type or pants type, and in rare cases, a urine pad is used in combination with a washable diaper cover. Therefore, in the case of baby diapers, tape-type and pants-type diapers and urine pads are targets for attaching the excretion sensor 8. The position of the excretion sensor 8 to be provided on the disposable diaper is a position corresponding to the crotch part of the disposable diaper, preferably below the absorbent body, but may be above the absorbent body. This depends on the form of the excretion sensor 8.

[0024] The excretion sensor 8 is provided with a sensor for detecting urine excreted by the user 7, as well as a communication circuit for transmitting information obtained by the sensor to the server 2. The excretion sensor 8 is preferably one that transmits information obtained by the sensor to the server 2 via wireless communication, but may be one that transmits information to the server 2 via wired communication. The excretion sensor 8 is preferably one that uses a device that generates electricity when it comes into contact with urine (e.g., a biofuel cell or an aluminum ion battery), and the power for the communication circuit is also preferably supplied from the device, but may be one that uses a secondary battery such as a rechargeable battery. When a power source such as a secondary battery is used, for example, an element that conducts electricity when it comes into contact with urine, or an element that does not conduct electricity when it comes into contact with urine, is used as the urine detection sensor, and the amount of urine can be detected depending on the number of elements that conduct electricity.

[0025] Furthermore, when a device that generates electricity upon contact with urine is used as the excretion sensor 8, the amount of urine may be detected according to the amount of electricity generated by the device.

[0026] For example, if the device increases or decreases the power depending on the area where urine comes into contact with the element, information on the magnitude of the power can be sent to the server 2, allowing the server 2 to acquire information on the amount of urine. If the device generates more power the larger the area of ​​the electrode in contact with urine, the magnitude of the power can be used as information on the amount of urine.

[0027] Also, for example, if the device increases or decreases the type of frequency of the radio waves emitted depending on the number of parts where urine comes into contact with the element or the power level, the urine volume can be obtained based on the type of the emitted radio waves. Assuming that the three frequencies are frequencies A, B, and C, and the device has three elements, an element that emits radio waves of frequency A when urine comes into contact with the element, an element that emits radio waves of frequency B when urine comes into contact with the element, and an element that emits radio waves of frequency C when urine comes into contact with the element, then, depending on the number of frequencies of radio waves received by the wireless antenna 4, the on-site terminal 5, etc., it is possible to determine, for example, that the urine volume is "small" when only one of the frequencies A, B, and C is received, that the urine volume is "medium" when two radio waves are received, and that the urine volume is "large" when all three radio waves are received. In this case, the urination volume may be predicted depending on the elapsed time from receiving a radio wave of a specific frequency to receiving a radio wave of another specific frequency. For example, if the time that elapses between receiving radio waves of a specific frequency and receiving radio waves of another specific frequency is relatively short, it is possible to predict that the amount of urination will be large, and if it is relatively long, it is possible to predict that the amount of urination will be small. When making such predictions, the accuracy of the predictions can be improved by using machine learning.

[0028] In addition, if the device increases or decreases the power generation according to the contact state of urine, the change in electrical behavior due to repeated urination may be reflected in the estimation of the amount of urination based on the magnitude of the power generation. For example, after the first urination, the urine in the absorbent is absorbed by the polymer absorbent, and the amount of urine that wets the electrodes decreases, so the voltage output by the device may gradually decrease immediately after the urine comes into contact with the electrodes. Therefore, if the amount of urine during urination is small, the device elements cannot be kept wet, so the output voltage of the device decreases quickly. On the other hand, if the amount of urine during urination is large, the device elements can be kept wet, so it takes a long time for the output voltage of the device to decrease. The absorbent body has a lower water absorption capacity during the second urination than the first urination, because the amount of water that can be absorbed decreases due to the first urination. Therefore, the output voltage decreases more slowly during the second urination detected by the device than during the first urination. For this reason, for example, if the number of urinations is included in the input data for machine learning, it is possible to estimate the amount of urination taking into account the change in the correlation between the amount of urination and the voltage decrease due to repeated urination. In this way, if the amount of urination is estimated using not only the generated power but also the number of urinations, it becomes possible to estimate the amount of urination with high accuracy.

[0029] In addition, the excretion sensor 8 is not limited to a form that transmits excretion information such as urine excreted from the user 7 to the server 2 via the wireless antenna 4 in real time. For example, the excretion sensor 8 may transmit the excretion information stored in the memory of the excretion sensor 8 to the on-site terminal 5 when it detects by wireless that the staff member 3 on patrol with the on-site terminal 5 approaches the excretion sensor 8, and then transmit the excretion information from the on-site terminal 5 to the server 2 via the wireless antenna 4. In this case, in order to provide the excretion information to the server 2 as time-series data, it is preferable to provide the server 2 with information such as the time when the excretion was detected together with the excretion information, but the information processing system 1 is not limited to such a form. For example, in a care facility where the staff member 3 makes rounds every hour, if the error in the excretion time allowed in the excretion prediction described later is allowed to be about 1 to 2 hours, the excretion information required for excretion prediction can be provided to the server 2 even if the excretion sensor 8 does not have a clock and transmits the excretion information to the server 2 via the on-site terminal 5 and the wireless antenna 4 when the staff member 3 on patrol approaches.

[0030] When transmitting information obtained by the sensor to the server 2, the excretion sensor 8 adds identification information for identifying the user 7 to the sensor information. If the excretion sensor 8 is a disposable sensor that is disposed of together with the used absorbent article, this identification information is unique information individually assigned to each excretion sensor 8. If the excretion sensor 8 is a type that is used by inserting a medium on which information unique to each user 7 is recorded into a slot, this identification information is unique information individually assigned to each user 7. In the latter case, the server 2 can identify which user 7 the information sent from the excretion sensor 8 belongs to by managing the unique information assigned to each user 7 in the database 24 of the server 2 or the like. On the other hand, in the former case, the server 2 needs to know the correspondence between the unique information individually assigned to each excretion sensor 8 and each user 7. Therefore, in the former case, when the staff member 3 puts on the absorbent article on the user 7, a linking operation is required to record the correspondence between the identification information of the excretion sensor 8 built into the put-on absorbent article and the user 7. This type of linking work can be achieved, for example, by having staff 3 read the identification information of the excretion sensor 8 using the wireless communication unit 53 of the on-site terminal 5 when putting on the absorbent article on the user 7, or by staff 3 manually inputting the identification information displayed on the excretion sensor 8 into the on-site terminal 5, or by various other methods.

[0031] Furthermore, the excretion sensor 8 may be capable of acquiring not only urination but also data related to defecation, such as the time of defecation and the amount of defecation. In general, the humidity and temperature inside the absorbent article tend to rise sharply from the time of excretion until the end of excretion, and then gradually decrease. In addition, the degree of decrease in humidity and temperature after the end of excretion, that is, the amount of decrease in humidity and temperature per unit time, tends to differ between fluid excretion (fluid excretion) such as urine, menstrual blood, and watery stool, and solid excretion (solid excretion) such as feces and vaginal discharge. For example, fluid excretion has a smaller heat capacity than solid excretion. In addition, fluid excretion is easily diffused. Therefore, the humidity and temperature of fluid excretion are more likely to decrease than solid excretion. Therefore, for example, by measuring the humidity and temperature inside the absorbent article and the rate of change thereof, it is possible to distinguish between fluid excretion and solid excretion.

[0032] The air conditioning sensor 9 is a sensor that is installed in various places in the building of the nursing facility where the information processing system 1 is used, and measures environmental information such as temperature and humidity. The air conditioning sensor 9 is equipped with a communication circuit for sending information obtained by the sensor to the server 2 in addition to a sensor that measures environmental information including at least one of temperature and humidity. The air conditioning sensor 9 is preferably one that sends information obtained by the sensor to the server 2 by wireless communication, but may also be one that sends information to the server 2 by wired communication. The air conditioning sensor 9 may be substituted by one that outputs temperature and humidity data from a control circuit of an air conditioning device. In addition, the data provided from the air conditioning sensor 9 to the server 2 may include control target values ​​for temperature and humidity set in the control circuit of the air conditioning device, and may also include the amount of solar radiation in the perimeter zone near the windows of the facility.

[0033] The wireless antenna 4 is an antenna for wireless communication with the above-mentioned on-site terminal 5, excretion sensor 8, and air conditioning sensor 9, and is installed in various locations within the building of the nursing facility in which the information processing system 1 is used. The wireless antenna 4 may be, for example, an antenna that complies with standards for LAN wireless equipment such as Wi-Fi (registered trademark), or may be a base station antenna for a mobile communications carrier such as 4G or 5G provided by the mobile communications carrier if the network N is a public communication line.

[0034] 2 is a functional block diagram of each device. The functions realized by each device will be described below.

[0035] Server 2 receives the input when the CPU executes the computer program loaded in the RAM. The server 2 implements an input processing unit 21, a calculation processing unit 22, and an output processing unit 23. The server 2 also has a database 24 storing various types of information in its storage. The input processing unit 21 receives information arriving via the network N from the on-site terminal 5, the management terminal 6, the excretion sensor 8, and the air conditioning sensor 9. The calculation processing unit 22 performs various types of calculation processing based on the information received by the input processing unit 21 and the information in the database 24. The output processing unit 23 sends various types of information to the on-site terminal 5 and the management terminal 6 via the network N.

[0036] Examples of the contents of the calculation processing unit 22 that are calculated and processed include planning a replacement schedule for absorbent articles worn by the user 7 and predicting the urination time of the user 7. Since the contents of the calculation processing unit 22 that are calculated and processed are wide-ranging, the details of the processing contents will be described later.

[0037] When the CPU executes the computer program loaded in the RAM, the on-site terminal 5 realizes an input processing unit 51, an output processing unit 52, and a wireless communication unit 53. The input processing unit 51 receives information received from the server 2 via the network N and user operations input through a touch panel or operation switches provided on the on-site terminal 5. The output processing unit 52 outputs various information to the touch panel or the like in response to the information received by the input processing unit 51 or a user operation. The wireless communication unit 53 is a functional unit for performing wireless communication with the wireless antenna 4 and various other electronic devices, and establishes a wireless connection between the wireless antenna 4 and the on-site terminal 5 and converts wireless signals exchanged between the wireless antenna 4 and the on-site terminal 5.

[0038] When the CPU executes the computer program loaded in the RAM, the management terminal 6 realizes an input processing unit 61 and an output processing unit 62. The input processing unit 61 receives information received from the server 2 via the network N and user operations input through input means such as a keyboard and a mouse provided in the management terminal 6. The output processing unit 62 outputs various types of information to a liquid crystal monitor or the like in response to the information received by the input processing unit 61 or user operations.

[0039] The excretion sensor 8 comprises a measuring unit 81, which is composed of a sensor that detects urine excreted in the absorbent article, and a transmitting unit 82 that wirelessly transmits information regarding the measurement value of the measuring unit 81. Both the measuring unit 81 and the transmitting unit 82 are built into the absorbent article worn by the user 7. The excretion sensor 8 is built into, for example, a pad-type absorbent article that can be attached to a diaper, a pants-type or tape-type diaper that can be used alone, and various other absorbent articles. Absorbent articles are generally made of short fibers of cellulosic fibers such as pulp fibers, rayon fibers, or cotton fibers, or short fibers made of synthetic fibers such as polyethylene, polypropylene, or polyethylene terephthalate that have been subjected to a hydrophilic treatment, and granular materials such as SAP (Super Absorbent Polymer), which is a hydrophilic polymer with a cross-linked structure that can absorb and retain water, are placed between the gaps of the short fibers. The measuring unit 81 is provided with an absorbent body that holds the absorbent resin. A water-permeable top sheet or the like is disposed on the skin-facing side of the absorbent body. Thus, the measuring unit 81 is disposed at a position where urine excreted from the wearer's anus or the like is likely to come into contact with the measuring unit 81. Examples of positions where urine excreted from the wearer's anus or the like is likely to come into contact with the measuring unit 81 include between the top sheet and the absorbent body, the skin-facing side of the top sheet, and various other parts adjacent to the top sheet. The area that the measuring unit 81 occupies on the top sheet depends on the type of detection element used in the measuring unit 81, the detection performance required for the measuring unit 81, and various other conditions. For example, if the measuring unit 81 is intended to detect the amount of urine with an accuracy of about three levels, high, medium, and low, the measuring unit 81 is preferably provided in a wide area from the front body part corresponding to the wearer's abdomen, through the wearer's crotch, to the back body part corresponding to the wearer's back. Also, for example, if the measuring unit 81 is intended to detect only the presence or absence of urine, the measuring unit 81 may be provided only in the part corresponding to the wearer's crotch. On the other hand, since the purpose of the transmitting unit 82 is to wirelessly transmit information related to the measurement value of the measuring unit 81, it is preferable that the transmitting unit 82 is provided in a location where the radio waves transmitted from the transmitting unit 82 to the wireless antenna 4 are not blocked. Therefore, although it depends on the transmission output of the transmitting unit 82 and the shape of the antenna, the transmission output of the transmitting unit 82 may be affected by urine absorbed in the absorbent article. As a portion where the radio waves of 82 are not blocked, for example, a portion adjacent to a cover sheet forming the exterior part of the absorbent article is preferable.

[0040] The air conditioning sensor 9 includes a measurement unit 91 that is composed of various elements such as a thermistor whose resistance value changes according to a change in temperature and a resistance change type sensor whose electrical resistance changes according to the water absorption rate of a wet or dry material, and a transmission unit 92 that wirelessly transmits information about the measurement value of the measurement unit 91. Information from the air conditioning sensor 9 is used for the purpose of correcting various predicted values ​​related to excretion such as the urination time and urination volume of the user 7 using information such as the temperature in the room where the user 7 is present. Therefore, the air conditioning sensor 9 is installed in rooms and halls where the user 7 mainly stays, within the building of the care facility where the information processing system 1 is used.

[0041] Next, a process flow when nursing care is provided using the information processing system 1 will be described. FIG. 3 is a diagram showing an example of a process flow when nursing care is provided using the information processing system 1. When the staff member 3 starts nursing care work in a nursing facility using the information processing system 1, the staff member 3 first checks the schedule of work for that day. When the staff member 3 wants to check the schedule of work for that day, for example, he / she operates the management terminal 6 at the guardhouse and performs a schedule request operation (R101). When the input processing unit 61 of the management terminal 6 accepts the schedule request operation, the output processing unit 62 requests the server 2 for data on information related to the schedule (R102). When the input processing unit 21 of the server 2 accepts a request for data on information related to the schedule from the management terminal 6, the calculation processing unit 22 queries the data stored in the database 24 (R103). Then, in the server 2, the output processing unit 23 provides the schedule information data acquired by the calculation processing unit 22 querying the database 24 to the management terminal 6 (R104). In the management terminal 6, when the input processing unit 61 receives the schedule-related information data provided by the server 2, the output processing unit 62 displays the data information on the liquid crystal monitor (R105). The staff member 3 checks the schedule displayed on the management terminal 6 (R106).

[0042] The staff member 3, having checked the schedule displayed on the management terminal 6, prepares to move to the room of the user 7 to care for the user 7 (R107). Examples of preparation work include preparing new absorbent articles to be fitted to the user 7, waste bags for disposing of used absorbent articles, and items to be used when replacing absorbent articles.

[0043] The staff member 3, who has completed preparations for the move, moves to the location of the user 7 together with the prepared items and the on-site terminal 5 (R108). Then, when the staff member 3 arrives at the location of the user 7, he operates the on-site terminal 5 to call up information necessary for nursing care of the user 7. When the input processing unit 51 of the on-site terminal 5 accepts the operation of the staff member 3, the output processing unit 52 displays the information necessary for nursing care of the staff member 3 on the touch panel (R109). The information displayed on the touch panel by the output processing unit 52 may be information previously stored in the storage of the on-site terminal 5, or may be information that the output processing unit 52 queries the server 2 and that is provided to the on-site terminal 5 from the server 2 every time the input processing unit 51 accepts the operation of the staff member 3.

[0044] The on-site terminal 5 may detect the approach of the user 7 by reading a signal from a wireless identification device such as an RFID worn by the user 7, and automatically display nursing care information related to the user 7, such as whether the absorbent article needs to be changed or whether the user needs to change his / her position. Alternatively, the on-site terminal 5 may display information when a barcode or QR code (registered trademark) of an identification mark worn by the user 7 is read, or the user 7 may be identified by biometric authentication (face, fingerprint, iris, vein, ear shape, body odor, etc.) and information displayed. In this case, the wireless communication unit 53 of the on-site terminal 5 functions as a detection unit that detects radio waves of the RFID. The on-site terminal 5 then queries the server 2 for information on the user 7 identified by the identification information contained in the radio waves of the RFID, and the information is sent from the server 2 to the on-site terminal 5 and displayed. The RFID may be a band-shaped device worn on the wrist, an ankle, etc. of the user 7, or may be a device attached to an absorbent article worn by the user 7, for example. The RFID tag may be realized as an accessory function of the excretion sensor 8, or may be embedded in the absorbent article together with the excretion sensor 8. The RFID tag can be read using various short-range wireless communication technologies. Examples of wireless communication standards for reading RFID tags include Bluetooth (registered trademark), ZigBee (registered trademark), and UWB (Ultra Wide Band). Examples of such standards include:

[0045] The staff member 3 checks the information displayed on the on-site terminal 5 and performs identity verification (R110). Identity verification is an important procedure for preventing the mistake of identifying the user 7, and is performed for the purpose of preventing the wrong care from being provided to the user 7.

[0046] After completing the identity verification, the staff member 3 operates the on-site terminal 5 to call up the necessary information and confirm various instructions such as precautions and procedures for providing care to the user 7 (R111). The staff member 3 then replaces the used absorbent articles worn by the user 7 and performs various other care-related procedures (R112). The on-site terminal 5 may analyze the voice of the staff member 3 using voice recognition technology and display the information requested by the staff member 3.

[0047] When the staff member 3 performs a care-related procedure, the staff member 3 inputs the record items into the on-site terminal 5 (R113). The record items to be input into the on-site terminal 5 include, for example, the amount of urine absorbed in the used absorbent article, the body position of the user 7, and information on the work performed at the time of replacing the absorbent article. The information on the record items input by the staff member 3 is received by the input processing unit 51 of the on-site terminal 5 (R114). Then, in the on-site terminal 5, the output processing unit 52 transmits the information received by the input processing unit 51 to the server 2 using the wireless communication unit 53. In the server 2, the input processing unit 21 receives the information received from the on-site terminal 5 (R115). Then, in the server 2, the calculation processing unit 22 accesses the database 24, and a process of updating the data stored in the database 24 is performed based on the information received by the input processing unit 21 (R116). Information on the incidental work such as changing the body position is used to determine the content of the next incidental work.

[0048] It should be noted that the above series of processes is not performed for each user 7. That is, when the staff member 3 leaves the station, he or she will provide care to multiple users 7 and then return to the station. Therefore, in the above series of processes, for example, after the processes from R101 to R107 are performed, the processes from R108 to R114 may be repeated multiple times, and then the processes from R115 onwards may be performed. Or, for example, after the processes from R101 to R107 are performed, the processes from R108 to R116 may be repeated multiple times.

[0049] The staff 3 of the care facility using the information processing system 1 of this embodiment can check various information related to care by using the above-mentioned on-site terminal 5 and management terminal 6. Therefore, compared to the case where the staff 3 works while checking notices and cautions attached to the bed used by the user 7 or the fixtures nearby, the staff 3 can work while easily checking more information.

[0050] Hereinafter, the details of some of the functions of the information processing system 1 will be individually explained.

[0051] <Excretion prediction function> The information processing system 1 of the above embodiment has an excretion prediction function for the user 7. The excretion prediction function is a function for predicting the urination time, urination volume, defecation time, etc. The excretion prediction function is mainly managed by the calculation processing unit 22 of the server 2. The urination time, urination volume, and defecation time can be predicted based on past urination times, food and drink, ingested medicines, room temperature and humidity, room air conditioning settings, and various other information.

[0052] The excretion prediction is periodically performed by the calculation processing unit 22 of the server 2, and the prediction results are stored in the database 24. Therefore, the staff member 3 can check the predicted time of the user 7's next urination and the amount of urination by operating the on-site terminal 5 at any time. Therefore, the staff member 3 can take advance preparation action based on the excretion prediction.

[0053] FIG. 4 is a diagram showing an example of data referred to by the excretion prediction function. The excretion prediction function of the information processing system 1 according to this embodiment analyzes data such as the amount of urine automatically acquired by the excretion sensor 8, data on excretion manually input by the staff 3, data on the environment of the room acquired by the air conditioning sensor 9, data on the type and amount of food and drink, data on ingested medicines, etc., by machine learning, learns the excretion pattern of the user 7, creates a prediction model for each user 7, and predicts the urination time and amount of urine of the user 7 from the model. Since some medicines have a diuretic effect or an antidiuretic effect, the administration time and dosage of these drugs affect the prediction of the excretion pattern of the user 7. In addition, the administration time and dosage of laxatives are directly related to excretion, and therefore affect the prediction of the excretion pattern of the user 7. For this reason, the data referred to by the excretion prediction function includes information on such medicines, but the information on the medicines can be omitted.

[0054] Machine learning refers to a process for generating a model that outputs a predicted value for input data. In machine learning, a learning process for updating parameters that define a model is executed multiple times using learning data. In this embodiment, various data related to the care of the user 7, such as the amount of urine and the time of urination, are used as learning data in machine learning, and the parameters of the model for outputting predicted values ​​related to the work schedule of the staff member 3, such as the amount of urine and the time of urination in the future, are updated.

[0055] In this function, the time of excretion is basically used as a reference, and analysis is performed from a plurality of data within a predetermined time immediately prior to the time of excretion. For example, in the case of predicting the time of urination, the time of urination is extracted from the data recorded in the database 24. Then, the extracted data of the time of urination is analyzed by machine learning, and the feature amount of the time of urination is calculated, so that the urination pattern of the user 7 can be learned and the future time of urination can be predicted. As the algorithm for machine learning, random forest, support vector machine (SVM), linear discriminant analysis, k-nearest neighbor method, naive Bayes classification method, decision tree, neural network, bagging method, boosting method, etc. can be used.

[0056] As described above, this function improves the prediction accuracy of excretion prediction from data on the current environment by considering data on the past environment of the room acquired by the air conditioning sensor 9 and the like. Specifically, in the above machine learning, for example, by including not only data on the feature amount of urination itself, such as the urination time and urination amount, but also data on feature amounts indirectly related to urination, such as the past temperature and humidity of the user 7's room, in the learning data, prediction taking into account the current temperature and humidity of the room is possible. Environmental information such as temperature and humidity may be individual data for each user 7, or may be average data for the entire nursing facility. For example, when the temperature rises due to the change in season from winter to summer, the amount of moisture excreted as sweat from parts other than the bladder increases, so the amount of urination tends to decrease. In addition, when the humidity rises due to the change in season from the dry season to the rainy season, the amount of moisture transpire from the skin surface decreases, so the amount of urination tends to increase. Therefore, in the above machine learning, by including data on feature amounts indirectly related to urination, such as the temperature and humidity of the user 7's room, in the learning data, the prediction accuracy of excretion prediction can be further improved.

[0057] In addition, as described above, this function improves the accuracy of predicting the urination time by taking into account data on the type and amount of food and drink consumed by the user 7. Specifically, in the above machine learning, in addition to data on the features of urination itself, such as the urination time and urination volume, By including data on features indirectly related to urination, such as the type and amount of food and drink ingested by the user 7, in the learning data, predictions can be made that take into account the type and amount of food and drink. For example, if a person consumes a lot of soup, which is high in water content, the amount of water that enters the body increases, so the amount of urination tends to increase. Also, if the amount of drink consumed is reduced, the amount of water that enters the body decreases, so the amount of urination tends to decrease. Therefore, in the above machine learning, by including data on features indirectly related to urination, such as the type and amount of food and drink ingested by the user 7, in the learning data, the prediction accuracy of excretion prediction can be further improved.

[0058] As described above, in the excretion prediction function, in addition to such data on the environment and food and drink, data on ingested medicines, data on the amount of exercise, and various other data are used as data for machine learning, making it possible to improve the prediction accuracy of excretion prediction as much as possible. The results of the excretion prediction can be obtained, for example, as a percentage of the probability of the amount of urine, urination time, and amount of stool several hours later. Therefore, for example, by displaying the time period with the highest probability as the predicted time of urination and displaying the percentage in a graph, the staff 3 can know when to change the absorbent articles worn by each user 7.

[0059] In addition, in this machine learning, when presenting the timing of changing the absorbent article with the urination volume as the core data, data on the posture of the user 7 manually input by the staff 3 may be included in the learning data. The absorption distribution of liquids such as urine in the absorbent article also changes significantly depending on the posture at the time of excretion. For example, when the user 7 is lying on his / her back, the urine is diffused almost evenly to both the left and right sides of the user 7 and absorbed into the absorbent body. On the other hand, when the user 7 is facing either left or right, the urine is diffused in a state biased toward the direction the user 7 is facing, and is more likely to leak from the absorbent body than when it is diffused to both the left and right sides. Therefore, in this machine learning, if data on the posture of the user 7 manually input by the staff 3 is included in the learning data, it becomes possible to present a more appropriate timing of changing the absorbent body taking into account the diffusion distribution of the absorbent body depending on the posture. It is also possible to calculate the next posture taking into account the diffusion distribution.

[0060] In the explanation of this function, predictions are explained using not only data automatically acquired using sensor devices such as the excretion sensor 8, but also data manually input by the staff member 3 to the on-site terminal 5, but this function is not limited to this form. For example, this function may predict excretion using only data automatically acquired using sensor devices such as the excretion sensor 8, or may predict excretion using only data manually input by the staff member 3 to the on-site terminal 5.

[0061] FIG. 5 is a diagram showing an example of a screen displayed on the on-site terminal 5. The staff member 3 can display, for example, a screen as shown in FIG. 5 displayed on the on-site terminal 5 in step R109 described above, and can check the prediction result obtained by the excretion prediction function. The screen shown in FIG. 5 displays information required when the staff member 3 performs nursing care work at the user 7's place. As shown in FIG. 5, this information includes, for example, the name, number, sex, date of birth, and age of the user 7, and is used in step R110 described above. Since this screen includes information for identifying the user 7, it is convenient to display this screen as a top screen at the beginning of the operation of the on-site terminal 5, but it may also be a screen displayed after one or more operations have been performed.

[0062] As shown in Fig. 5, the screen displayed on the on-site terminal 5 includes information such as the name of the user 7, as well as various information such as time series information related to excretion of urine, feces, etc., posture, diet, fluid intake status, IV drip, and the presence or absence of diarrhea (see the "Excretion record" column in Fig. 5). In addition, information related to incidental tasks such as the type of absorbent article to be worn by the user 7, the type of cleaning solution to be used for genital washing, methods of bedsore care, and methods of changing posture is included.

[0063] In the information column for the excretion record, information from 8:00 a.m. to midnight on the day is displayed. Therefore, when the screen of the on-site terminal 5 is opened during the day, information from 8:00 a.m. to the present on the day is displayed as actual measurement data, and for information from the present to midnight, the above-mentioned predicted result data is displayed. Data on excretion such as the amount of urine excreted is transmitted from the excretion sensor 8 built into the absorbent article worn by the user 7 and recorded in the database 24, so that the amount of urine is displayed in a chronological order in a bar graph in the range of 0cc to 500cc. The accuracy of the amount of urine displayed in the bar graph depends on the performance of the excretion sensor 8. For example, if the measurement unit 81 is configured using multiple elements that are energized when urine comes into contact with the sensor, the amount of urine will have a resolution corresponding to the number of elements, so that a bar graph with stages will be drawn.

[0064] For the ancillary tasks, a work procedure manual detailing the work procedure is prepared in advance for each care facility. Therefore, a "Procedure Manual" button for displaying this work procedure manual is also provided on the screen displayed on the on-site terminal 5. Therefore, the staff member 3 can check the specific procedure for each ancillary task by touching the "Procedure Manual" button for that task. Therefore, even if the staff member 3 at the care facility does not have sufficient experience due to various circumstances such as the recent decline in the working population and the labor shortage in the care industry, it is possible to provide appropriate treatment to the user 7.

[0065] The screen displayed on the on-site terminal 5 includes the name of the user 7, information on the associated work, and operation buttons for recording the results of the absorbent article replacement work (see the "After Diaper Change Record" column in FIG. 5). The absorbent article worn by the user 7 has a built-in excretion sensor 8, and as described above, data on excretion such as the amount of urine excreted is recorded in the database 24. Therefore, the screen displayed on the on-site terminal 5 displays the most recent amount of urine transmitted from the excretion sensor 8 as a sensor value. However, when the staff member 3 checks the used absorbent article when replacing the absorbent article of the user 7, there may be cases where the amount of urine detected by the excretion sensor 8 differs from the actual amount of urine. Therefore, the screen displayed on the on-site terminal 5 is provided with a correction button for correcting the data on the amount of urine acquired by the excretion sensor 8 and stored in the database 24. In addition, buttons are provided for inputting various record items such as the amount of stool, the properties of stool, and the amount of leakage that cannot be detected by the excretion sensor 8.

[0066] FIG. 6 is a diagram showing an example of a screen for correcting data on the amount of urine. When a correction button for correcting data on the amount of urine is pressed, a pop-up window for data correction, for example, as shown in FIG. 6, is displayed on the field terminal 5. Data on the amount of urine can be corrected by operating a button for adding or subtracting a sensor value, as shown in FIG. 6. When an "OK" button at the bottom left of the pop-up screen shown in FIG. 6 is pressed, the corrected value is sent to the database 24 of the server 2, and the correction of the amount of urine is confirmed. In the case of a care facility that does not use an absorbent article with a built-in excretion sensor 8, data on the amount of urine detected by the excretion sensor 8 is not input, so the amount of urine is manually input by these operations. The above-mentioned excretion prediction is also performed based on the information manually input by these operations.

[0067] FIG. 7 is a diagram showing an example of a screen for inputting stool volume and stool properties. When data on stool volume and stool properties is to be input, by pressing the corresponding button, for example, a pop-up window for input as shown in FIG. 7 is displayed on the site terminal 5. For stool volume, three types of touch parts are provided, which represent "little, medium, and lots" by the number of circles representing stool, so the staff member 3 can input the stool volume by touching any of the parts. For stool properties, seven types of buttons are provided, which express the stool properties in words, so the staff member 3 can input the stool properties by touching any of the buttons. The various data such as stool volume and stool properties inputted to the site terminal 5 are sent to the server 2 via the network N and stored in the database 24. Then, the above-mentioned prediction of urination time, etc. are inputted. It is used for measurement.

[0068] When the data on the amount of urine stored in the database 24 is corrected, the coefficients (regression coefficients) of the explanatory variables used in the machine learning of the excretion prediction function described above also change. FIG. 8 is a diagram explaining the relationship between the correction of the amount of urine and the change in the regression coefficients. Although FIG. 8 shows a flowchart, the regression coefficients are calculated by the machine learning of the arithmetic processing unit 22. Therefore, the flowchart shown in FIG. 8 does not show the processing contents executed by the arithmetic processing unit 22.

[0069] For example, assume that the data on the amount of urine excreted from the user 7 is corrected and the amount of urine excreted has increased compared to before the correction (YES in S101). If the amount of urine excreted stored in the database 24 increases due to the correction, the regression coefficient in the machine learning executed before the correction is affected by this. In other words, the correlation between the explanatory variable and the objective variable in the machine learning executed before the correction changes due to the correction of the amount of urine excreted. For this reason, when machine learning is executed again after the correction of the amount of urine excreted, the regression coefficient is also increased (S102). Also assume that the amount of urine excreted has decreased compared to before the correction (YES in S103). In this case, when machine learning is executed after the correction of the amount of urine excreted, the regression coefficient is also decreased (S104).

[0070] When the data on the amount of urine stored in the database 24 is corrected by the staff member 3, the coefficients of the explanatory variables used in the machine learning of the excretion prediction function also change in this way. Such an impact on the excretion prediction function occurs not only in the correction of the amount of urine, but also in the correction of the amount of stool, the properties of stool, and various other items. Such an impact on the excretion prediction function also has an impact on, for example, the function of planning the replacement schedule for absorbent articles, which will be described later.

[0071] <Planning function> The planning function of the absorbent article replacement schedule will be described below. Fig. 9 is a diagram showing an example of a processing flow related to the planning function. The planning function of the information processing system 1 according to this embodiment is executed, for example, at the start of work in the early morning of the nursing care facility, and is used when the staff 3 starts their shift. The planning function of the information processing system 1 according to this embodiment is a process executed mainly by the calculation processing unit 22.

[0072] The arithmetic processing unit 22 refers to the data of the user 7 (S201). The data of the user 7 referred to by the arithmetic processing unit 22 is data stored in the database 24, and includes the above-mentioned information on the amount of urine and various other information.

[0073] The calculation processing unit 22 also refers to the shift (work schedule) data of each staff member 3 (S202). The shift data of each staff member 3 is data stored in a personnel management server used in the nursing facility, or data stored in the database 24, and is data input to the management terminal 6, the on-site terminal 5, etc. by the manager managing each staff member 3 or each staff member 3 himself / herself.

[0074] Furthermore, the calculation processing unit 22 refers to data related to care for each user 7 (S203). The data related to care for the user 7 referred to by the calculation processing unit 22 is data stored in the database 24, and includes various information such as the type of absorbent article worn by the user 7, the details of treatment that needs to be performed on the user 7 (bedsore care, genital washing, the need for position change, etc.), and the brand and absorption capacity of the absorbent article worn by the user 7.

[0075] The calculation processing unit 22 creates a plan for the replacement schedule of absorbent articles based on the above-mentioned referenced data (S204). More specifically, the calculation processing unit 22 creates a plurality of plans in which items with higher priorities are staggered. Four types of plans are exemplified: "total number of changes given a priority" (hereinafter referred to as "Plan 1"), "disposable diaper cost given a priority" (hereinafter referred to as "Plan 2"), "minimum load given to each excretion caregiver given a priority" (hereinafter referred to as "Plan 3"), and "regular change given a priority" (hereinafter referred to as "Plan 4"). However, the information processing system 1 is not limited to creating these four types of plans. The information processing system 1 may create various other plans.

[0076] Plan 1 is a plan that minimizes the number of times that the staff 3 must replace absorbent articles. Plan 1 is a plan that is suitable, for example, when the number of staff 3 is relatively small. In this plan, for example, the calculation processing unit 22 suggests replacing absorbent articles with ones that have a high absorption capacity.

[0077] Plan 2 is a plan that minimizes the total cost of replacing absorbent articles. Plan 2 is a suitable plan for cases where, for example, there is a relatively large number of staff 3 and inexpensive absorbent articles with low absorption capacity can be frequently replaced.

[0078] Plan 3 is a plan that minimizes the workload per staff member 3. While Plan 1 is a plan that minimizes the total number of replacements for all staff members 3, Plan 3 is a plan that minimizes the workload per staff member 3, so for example, in a shift where there are fewer staff members 3 during a specific time period during the day, the total replacement work during that time period will be less than other time periods. As a result, more replacement work will be done during times other than that time period when there are relatively more staff members 3, and the concentration of work on specific staff members 3 will be alleviated.

[0079] Plan 4 is a plan for changing absorbent articles at a specified time. For example, this plan is suitable for a case where the user 7 has various plans and the time period during which the absorbent articles can be changed is limited. In plan 4, the type of absorbent article to be changed and the timing of change are determined so that the change of the absorbent articles is performed during a predetermined time period.

[0080] The calculation processing unit 22 searches for an absorbent article replacement schedule, the type of absorbent article to be worn, and the like, for example, using the Dijkstra algorithm. When using the Dijkstra algorithm, for example, the work time required for replacement and incidental work, the cost of the absorbent article, the time required for moving within the facility, the predicted amount of urination and urination time, and the like are set as weights for a number of nodes between the start node and the end node, and a route with the smallest weight is searched for. When searching for a plurality of plans such as the above-mentioned plans 1 to 4, a coefficient is added so that the weight corresponding to each plan is prioritized in the search, and a route search is performed. This completes the calculation of replacement schedules corresponding to the various plans 1 to 4. It goes without saying that in any plan, a plan is created for a time period during which the staff member 3 can replace the absorbent article. For example, in any of the above plans, a time period during which the staff member 3 cannot work, such as late night hours when there are almost no staff members 3 or break times, is excluded from the candidate time periods for replacement work.

[0081] When the calculation processing unit 22 completes the creation of the plan, it causes each plan to be displayed comparatively on the screen of the on-site terminal 5 or the management terminal 6 (S205). FIG. 10 is an example of a screen displaying plans of exchange schedules comparatively. When the calculation processing unit 22 completes the creation of the plan, the on-site terminal 5 or the management terminal 6 is in a state in which the plan created by the calculation processing unit 22 can be displayed on the screen. Therefore, the staff 3 can compare and consider various plans created by the calculation processing unit 22 by operating the on-site terminal 5 or the management terminal 6. In addition, when the staff 3 selects one of the plans (S206), the calculation processing unit 22 causes the details of the selected plan to be displayed on the terminal operated by the staff 3 (S207). This allows the staff 3 to check the detailed display of the selected plan.

[0082] By using such a planning function, in a care facility using the information processing system 1, various tasks such as planning the visiting routes for the users 7 and the schedules for each staff member 3, and deciding on the placement of the staff members 3 can be easily performed. Therefore, in a care facility using the information processing system 1, even with a limited number of staff members 3, it becomes possible to provide appropriate care to the users 7.

[0083] In actual nursing care sites, since there are few caregivers, it is not realistic to change disposable diapers every time a user defecates. Therefore, even if the user's defecation time can be predicted, the reality is that the disposable diaper cannot be changed at the predicted time. In this regard, with the present planning function, planning is performed using not only data on the predicted amount of urination and urination time, but also various data such as the shifts of the staff 3, so that it is possible to propose and select the time to change absorbent articles according to the shifts and allocation situation of the staff 3 on a day. In addition, by using the present planning function, it is possible to calculate the required number of staff 3 by time period, etc., based on the timing of changing absorbent articles, etc., so that the information processing system 1 can also be used to consider the attendance schedule of the staff 3.

[0084] Furthermore, with the information processing system 1 of this embodiment, it is possible to browse and record procedures for not only excretion care such as changing absorbent articles, but also for incidental tasks such as skin care that are performed at the same time, and to refer to and input the procedures together with excretion care information. Therefore, with the information processing system 1 of this embodiment, it is possible to perform various tasks related to the care of the user 7 in an extremely rational manner.

[0085] <Computer-readable recording medium> A program for causing a computer or other machine or device (hereinafter, computer, etc.) to realize any of the above functions can be recorded on a computer-readable recording medium. The computer, etc. can then read and execute the program from the recording medium to provide the function. Here, a computer-readable recording medium refers to a storage medium that can store information such as data and programs through electrical, magnetic, optical, mechanical, or chemical action and can be read by a computer, etc. Examples of such storage media include optical disks, SSDs, HDDs, non-volatile memories, etc. [Explanation of symbols]

[0086] N·Network 1. Information Processing System 2. Server 3. Staff 4. Radio antenna 5. Field terminal 6. Management terminal 7...User 8. Excretion sensor 9. Air conditioning sensor 21 Input processing section 22. Processing unit 23 Output Processing Section 24·Database 51 Input processing unit 52 Output processing section 53 Wireless Communication Section 61 Input processing unit 62 Output processing section 81...Measuring section 82 Transmitter 91...Measuring section 92 Transmitter

Claims

1. a storage unit for storing excretion information, which is information relating to excreta excreted in the absorbent article; a calculation processing unit that predicts excretion of a wearer of the absorbent article based on environmental information including at least one of a temperature and humidity of a room in which the wearer of the absorbent article lives and the excretion information, stores the prediction in the storage unit, and creates a schedule for a caregiver based on the information stored in the storage unit; an output processing unit that outputs a result of the prediction and a schedule of the caregiver; the calculation processing unit creates at least four or more types of schedules for the caregiver, with alternating priorities for four items, namely, the total number of times the absorbent article is replaced, the cost of the absorbent article, the amount of work per caregiver, and the regular replacement of the absorbent article; Information processing device.

2. The calculation processing unit predicts excretion of a wearer who wears the absorbent article by using a prediction model that has been machine-learned using the excretion information and the environmental information as training data. The information processing device according to claim 1 .

3. the calculation processing unit uses a prediction model that has been machine-learned using the past information about the environment and the excretion information stored in the storage unit as training data to make a prediction regarding excretion of a wearer who wears the absorbent article, based on information about a current environment transmitted from a sensor installed in the room.

3. The information processing device according to claim 1 or 2.

4. The excretion information stored in the memory unit includes at least one of information transmitted from an excretion sensor provided in the absorbent article and information input to a terminal by a caregiver who replaces the absorbent article. The information processing device according to claim 1 .

5. the calculation processing unit predicts that the amount of urine excreted by the wearer of the absorbent article will decrease when the temperature of the room in which the wearer of the absorbent article lives increases, and predicts that the amount of urine excreted by the wearer of the absorbent article will increase when the temperature of the room in which the wearer of the absorbent article lives decreases. The information processing device according to claim 1 .

6. An information processing device comprising: Refer to a storage unit in which excretion information, which is information related to excreta excreted in the absorbent article, is stored; making a prediction regarding excretion of a wearer who wears the absorbent article based on environmental information including at least one of temperature and humidity of a room in which the wearer of the absorbent article lives and the excretion information; The prediction is stored in the storage unit; creating at least four or more types of schedules for caregivers based on the information stored in the storage unit, with alternating priorities for four items, namely, the total number of times the absorbent article is replaced, the cost of the absorbent article, the amount of work per caregiver, and the regular replacement of the absorbent article; outputting the results of the prediction and the schedule of the caregiver; Information processing methods.

7. In the information processing device, Refer to a memory unit in which excretion information, which is information regarding excreta excreted in the absorbent article, is stored; making a prediction regarding excretion of a wearer who wears the absorbent article based on environmental information including at least one of temperature and humidity of a room in which the wearer of the absorbent article lives and the excretion information; The prediction is stored in the storage unit; creating at least four or more types of schedules for caregivers based on the information stored in the storage unit, in which the priorities of four items, namely, the total number of times the absorbent article is replaced, the cost of the absorbent article, the amount of work per caregiver, and the regular replacement of the absorbent article, are staggered; outputting the results of the prediction and the schedule of the caregiver; Information processing program.

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