JP2022072768A - Device, method, and program for processing information - Google Patents

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

The present invention relates to an information processing apparatus, an information processing method and an information processing program.

In recent years, due to improvements in communication technology and sensing technology, attempts have been made to electrically detect urine and the like even in absorbent articles such as disposable diapers, urine pads, and sanitary products (for example, Patent Document 1-6). reference). It has also been proposed to use a computer for long-term care in a long-term care facility or the like (see, for example, Patent Documents 7-9).

Japanese Unexamined Patent Publication No. 2019-130243 Japanese Unexamined Patent Publication No. 2019-130244 Japanese Unexamined Patent Publication No. 2019-141278 Japanese Unexamined Patent Publication No. 2019-146721 Japanese Unexamined Patent Publication No. 2019-141279 Japanese Unexamined Patent Publication No. 2019-141280 Japanese Unexamined Patent Publication No. 2007-25737 Japanese Unexamined Patent Publication No. 2008-20976 Japanese Unexamined Patent Publication No. 2019-139693

The wearer's excretion of absorbent articles may vary depending on the environment in which the wearer is present. Therefore, for example, the wearer's excretion cannot be accurately predicted only by the information on the past urination amount and the urination time.

Therefore, an object of the present invention is to provide a technique capable of improving the prediction accuracy of excretion of a wearer wearing an absorbent article.

In order to solve the above problems, the present invention predicts the excretion of the wearer of the absorbent article from the environmental information including at least one of the temperature and humidity of the room of the wearer of the absorbent article and the excretion information. I decided to do it.

Specifically, the present invention is an information processing apparatus, in which a storage unit for storing excretion information which is information about excretion excreted in the absorbent article, a temperature of a room of a wearer of the absorbent article, and the like. It is provided with an arithmetic processing unit that predicts the excretion of a wearer wearing an absorbent article from environmental information including at least one of humidity and excretion information, and an output processing unit that outputs the prediction result.

The arithmetic processing unit may predict the excretion of the wearer wearing the absorbent article by using a machine-learned prediction model using the excretion information and the environment information as teacher data.

In addition, the arithmetic processing unit uses the prediction model machine-learned using the past information and excretion information of the environment stored in the storage unit as teacher data, and the information of the current environment transmitted from the sensor installed in the living room. May be used to predict the excretion of the wearer wearing the absorbent article.

The excretion information stored in the storage unit is at least one of the information transmitted from the excretion sensor provided in the absorbent article and the information input to the terminal by the caregiver who exchanges the absorbent article. May include.

In addition, the arithmetic processing unit predicts that when the temperature of the room of the wearer of the absorbent article rises, the amount of urination of the wearer decreases, and when the temperature of the room of the wearer of the absorbent article falls, the urination of the wearer You may predict that the amount will increase.

The present invention can also be grasped from the aspect of the method. For example, the present invention refers to a storage unit which is an information processing method and stores excretion information which is information about excretion excreted in the absorbent article, and refers to the temperature of the room of the wearer of the absorbent article and the temperature of the room of the wearer of the absorbent article. The excretion of the wearer wearing the absorbent article may be predicted from the environmental information including at least one of the humidity and the excretion information, and the result of the prediction may be output.

The present invention can also be grasped from the aspect of the program. For example, the present invention is an information processing program, in which an information processing apparatus is made to refer to a storage unit in which excretion information, which is information about excretion excreted in an absorbent article, is stored, and a wearer of the absorbent article. The excretion of the wearer wearing the absorbent article may be predicted from the environmental information including at least one of the temperature and humidity of the living room and the excretion information, and the result of the prediction may be output.

According to the present invention, it is possible to improve the accuracy of predicting excretion of a wearer wearing an absorbent article.

FIG. 1 is an overall configuration diagram of an information processing system according to an embodiment. FIG. 2 is a functional block diagram of each device. FIG. 3 is a diagram showing an example of a processing flow when performing long-term care using an information processing system. FIG. 4 is a diagram showing an example of data referred to by the excretion prediction function. FIG. 5 is a diagram showing an example of a screen displayed on a field terminal. FIG. 6 is a diagram showing an example of a screen for correcting urine volume data. FIG. 7 is a diagram showing an example of a screen for inputting a stool volume and a stool property. FIG. 8 is a diagram illustrating the relationship between the correction of the urination volume and the change in the regression coefficient. FIG. 9 is a diagram showing an example of a processing flow related to the planning function. FIG. 10 is an example of a screen in which exchange schedule plans are comparatively displayed.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. The configurations of the following embodiments are examples, and the present invention is not limited to the configurations of these embodiments.

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, a field terminal 5, a management terminal 6, an excretion sensor 8, and an air conditioning sensor 9 capable of bidirectional communication via a network N and a wireless antenna 4. The information processing system 1 is a system suitable for facilities used by humans and animals in need of human help, and can be applied to, for example, nursing care facilities, wards, breeding facilities, and various other facilities.

In this embodiment, the information processing system 1 is applied to a long-term care facility used by a user 7 such as an elderly person who needs the help of a staff member 3, and mainly the work of exchanging absorbent articles (diapers and pads) is mainly performed. An example is given when it is applied to long-term care. However, the information processing system 1 is not limited to the application to such a nursing care facility or the exchange work of absorbent articles. Further, the information processing system 1 is not limited to a form in which long-term care is performed in the building of the long-term care facility, and can be applied to, for example, a home-visit type long-term care facility that visits the home of the user 7.

The network N is a communication line connecting information devices, and is constructed by using, for example, a LAN (Local Area Network) cable or hub installed in a nursing facility, a wireless LAN, or a public communication line such as the Internet. To.

The server 2 is a CPU (Central Processing Unit) or RAM (Random Access Memory).
, An information processing device including an input / output interface, SSD (Solid State Drive), and the like. The server 2 can be accessed from the field terminal 5 and the management terminal 6, and performs various request processing and various other arithmetic processing. The server 2 may be a cloud formed on the Internet.

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 can be carried by the staff 3 and whose screen can be easily checked, but there are various types such as smartphones, smart watches, wearable terminals, and computers mounted on mobile carts used by the staff 3. Information processing device can be applied. The on-site terminal 5 displays information necessary for the staff 3 to care for the user 7 and accepts various inputs.

The management terminal 6 is an information processing device installed in a station or the like of a staff member 3. The management terminal 6 can be applied to a desktop computer, a tablet computer, and various other information processing devices. The management terminal 6 is used when the staff 3 confirms the schedule and performs various setting operations.

The excretion sensor 8 is a sensor built in an absorbent article such as a water absorption pad or a diaper worn by the user 7. For example, in the case of an adult disposable diaper, the user 7 wears a tape type or a pants type and puts a urine pad inside the diaper, so that the urine pad is mainly responsible for absorption. And if the urine pad becomes dirty, replace it. Tape-type or pants-type diapers are usually changed once every 1-2 days. Depending on the replacement schedule, the urine pad may not be used together. When changing such disposable diapers, the diaper may be washed at the same time. When cleaning the pubic area, treat with the disposable diaper underneath, and absorb the cleaning solution into the disposable diaper and dispose of it. Therefore, it is a urine pad, tape type or pants type disposable diaper equipped with the sensor. On the other hand, in the case of children's disposable diapers, only one tape type or pants type is used, and in rare cases, a urine pad may be used together with a washable diaper cover. Therefore, in the case of children's disposable diapers, tape-type and pants-type disposable diapers and urine pads are the targets to which the excretion sensor 8 is attached. The position of the excretion sensor 8 provided on the disposable diaper is a position corresponding to the inseam of the disposable diaper, preferably the lower side of the absorber, but may be the upper side of the absorber. This depends on the morphology of the excretion sensor 8.

The excretion sensor 8 is provided with a communication circuit for sending the information obtained by the sensor to the server 2 in addition to the sensor for detecting the urine excreted from the user 7. The excretion sensor 8 is preferably one that sends the information obtained by the sensor to the server 2 by wireless communication, but may be one that sends the information obtained by the sensor to the server 2 by wire communication. Further, the excretion sensor 8 preferably uses a device (for example, a biofuel cell or an aluminum ion battery) that generates electricity when it comes into contact with urine, and the power of the communication circuit is also supplied from the device. It may use the next battery. When using a power source such as a secondary battery, as a sensor for detecting urine, for example, an element that energizes when urine comes into contact or an element that does not energize when urine comes into contact is used, and the amount of urine depends on the number of energized elements. Can be detected.

Further, when the excretion sensor 8 uses a device that generates electricity when it comes into contact with urine, the excretion sensor 8 may detect the amount of urine according to the magnitude of the generated power of the device.

For example, when the device increases or decreases the electric power according to the amount of the part where the urine contacts the element, the server 2 transmits the information on the urine volume by sending the information on the magnitude of the electric power to the server 2. It can be obtained. When the device is such that the generated power increases as the area of the electrode in contact with urine increases, the magnitude of the power can be used as information on the amount of urine.

Further, for example, when the type of the frequency of the radio wave transmitted by the device increases or decreases depending on the amount of the portion where the urine contacts the element and the magnitude of the electric power, the urine is based on the type of the transmitted radio wave. The quantity can be obtained. Assuming that three frequencies with different frequencies are frequencies A, B, and C, the device emits a radio wave of frequency A when it comes into contact with urine, and emits a radio wave of frequency B when it comes into contact with urine. If it has three elements, an element and an element that emits radio waves of frequency C when urine comes into contact, for example, depending on the number of frequencies of radio waves received by the radio antenna 4, the field terminal 5, or the like, for example. If only one of the radio waves of frequencies A, B, and C is received, the urine volume is "low", if two radio waves are received, the urine volume is "medium", and if all three radio waves are received, the urine volume is urine. It is possible to judge the amount as "many". In this case, the amount of urination may be predicted according to the elapsed time from receiving the radio wave of a specific frequency to receiving the radio wave of another specific frequency. For example, if the elapsed time from receiving a radio wave of a specific frequency to receiving a radio wave of another specific frequency is relatively short, the amount of urination is large, and if it is relatively long, the amount of urination is small. It is possible. When making such a prediction, the prediction accuracy is improved by using machine learning.

In addition, when the device increases or decreases the generated power according to the contact state of urine, the change in electrical behavior due to repeated urination is reflected in the estimation of the amount of urination based on the magnitude of the generated power. You may let me. For example, after the first urination, the urine in the absorber is absorbed by the polymer absorbent and the amount of urine that wets the electrodes decreases, so the voltage output by the device gradually decreases immediately after contact with the urine. Can be. Therefore, if the amount of urine at the time of urination is small, the element of the device cannot be continuously wet, and the output voltage of the device drops rapidly. On the other hand, if the amount of urine during urination is large, the element of the device can be continuously wet, so that it takes a long time for the output voltage of the device to decrease. Since the amount of water that can be absorbed by the absorber decreases due to the first urination, the water absorption capacity at the time of the second urination is lower than that of the first urination. Therefore, in the second urination detected by the device, the decrease in the output voltage is slower than in the first urination. Therefore, for example, if the number of urination is included in the input data of machine learning, it is possible to estimate the urination amount in consideration of the change in the correlation between the urination amount and the voltage decrease due to the repeated urination. In this way, if the amount of urination is estimated using not only the generated power but also the number of times of urination, the amount of urination can be estimated with high accuracy.

Further, the excretion sensor 8 is not limited to a form in which excretion information such as urine excreted from the user 7 is transmitted to the server 2 in real time via the wireless antenna 4. For example, when the excretion sensor 8 wirelessly detects that the patrol staff 3 holding the site terminal 5 has approached the excretion sensor 8, the excretion information stored in the memory of the excretion sensor 8 is stored in the site terminal 5. It may be transmitted to the server 2 from the field terminal 5 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 excretion sensor 8 with a clock and provide the information of the time when the excretion is detected to the server 2, but information processing is performed. The system 1 is not limited to such a form. For example, in a care facility where the staff 3 patrols every hour, if the error of the excretion time allowed in the excretion prediction described later is allowed for about 1 to 2 hours, the excretion without a clock is allowed. Even if the sensor 8 transmits excretion information to the server 2 via the on-site terminal 5 and the wireless antenna 4 at the timing when the patrol staff 3 approaches, the excretion information necessary for excretion prediction is provided to the server 2. can do.

When the excretion sensor 8 transmits the information obtained by the sensor to the server 2, the excretion sensor 8 adds the identification information for identifying the user 7 to the sensor information. This identification information is unique information individually assigned to each excretion sensor 8 if the excretion sensor 8 is a disposable sensor that is discarded together with the used absorbent article. Further, if the excretion sensor 8 is of a type in which a medium in which information unique to each user 7 is recorded is inserted into a slot, this identification information is unique information individually assigned to each user 7. Is. In the latter case, by managing the unique information assigned to each user 7 in the database 24 or the like of the server 2, the server 2 has the information sent from the excretion sensor 8 of any user 7. It is possible to identify whether it is a thing. On the other hand, in the former case, it is necessary for the server 2 side to grasp the correspondence relationship between the unique information individually assigned to each excretion sensor 8 and each user 7. Therefore, in the former case, when the staff 3 attaches the absorbent article to the user 7, the identification information of the excretion sensor 8 built in the attached absorbent article and the correspondence relationship with the user 7 are recorded. It is necessary to carry out the tying work. In such a linking operation, for example, when the staff 3 attaches the absorbent article to the user 7, the wireless communication unit 53 of the on-site terminal 5 reads the identification information of the excretion sensor 8, or the excretion sensor 8 is used. The displayed identification information can be manually input by the staff 3 to the on-site terminal 5, or can be realized by various other methods.

Further, the excretion sensor 8 may be capable of acquiring not only urination but also data related to defecation such as defecation time and defecation amount. Generally, from the time of excretion to the end of excretion, the humidity and temperature inside the absorbent article tend to rise sharply and then gradually decrease. In addition, in the case of fluid excrement (fluid excrement) such as urinary stool, menstrual blood and watery stool, and solid excrement (solid excrement) such as feces and cage, the humidity and temperature after excretion is completed. The degree of decrease, that is, the amount of decrease in humidity and temperature per unit time tends to be different. For example, fluid excrement has a smaller heat capacity than solid excrement. In addition, fluid excrement is easy to diffuse. Therefore, the humidity and temperature of the fluid excrement are more likely to be lower than those of the solid excrement. Therefore, for example, it is possible to discriminate between liquid excrement and solid excrement by measuring the humidity and temperature inside the absorbent article and the rate of change thereof.

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 includes not only a sensor that measures environmental information including at least one of temperature and humidity, but also a communication circuit for sending the information obtained by the sensor to the server 2. The air conditioning sensor 9 is preferably one that sends the information obtained by the sensor to the server 2 by wireless communication, but may be one that sends the information obtained by the sensor to the server 2 by wired communication. The air conditioning sensor 9 may be substituted with one that outputs temperature and humidity data from the control circuit of the air conditioning equipment. Further, the data provided from the air conditioning sensor 9 to the server 2 may include temperature and humidity control target values set in the control circuit of the air conditioning equipment, or may include a perimeter zone near the window side of the facility. The amount of solar radiation may be included.

The wireless antenna 4 is an antenna for wirelessly communicating with the on-site terminal 5, the excretion sensor 8, and the air conditioning sensor 9 described above, and is installed in various places in the building of the nursing facility where the information processing system 1 is used. The wireless antenna 4 may be, for example, an antenna compliant with the standard of wireless equipment for LAN such as Wi-Fi (registered trademark), or if the network N is a public communication line, the 4G provided by the mobile communication operator. It may be a base station antenna for a mobile communication operator such as 5G or 5G.

FIG. 2 is a functional block diagram of each device. Hereinafter, the functions realized in each device will be described.

When the CPU executes the computer program loaded in the RAM, the server 2 realizes the input processing unit 21, the arithmetic processing unit 22, and the output processing unit 23. Further, the server 2 has a database 24 in which various information is stored in the storage. The input processing unit 21 receives information received from the field terminal 5, the management terminal 6, the excretion sensor 8, and the air conditioning sensor 9 via the network N. The arithmetic processing unit 22 performs various arithmetic processings 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 information to the field terminal 5 and the management terminal 6 via the network N.

The contents to be calculated by the calculation processing unit 22 include, for example, planning of a replacement schedule for absorbent articles worn by the user 7, prediction of the urination time of the user 7, and the like. Since the content of the arithmetic processing by the arithmetic processing unit 22 is diverse, the details of the processing content will be described later.

When the CPU executes a computer program loaded in the RAM, the field 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 the touch panel and operation switches provided on the field terminal 5. The output processing unit 52 outputs various information to the touch panel or the like when the information received by the input processing unit 51 or the user operation is triggered. 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 field terminal 5 or connects with the wireless antenna 4. It converts the wireless signal exchanged with the on-site terminal 5.

When the CPU executes the computer program loaded in the RAM, the management terminal 6 realizes the input processing unit 61 and the 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 information to the liquid crystal monitor or the like when the information received by the input processing unit 61 or the user operation is triggered.

The excretion sensor 8 includes a measuring unit 81 composed of a sensor for detecting urine excreted in an absorbent article, and a transmitting unit 82 that wirelessly transmits information about the measured value of the measuring unit 81. Both the measuring unit 81 and the transmitting unit 82 are built in the absorbent article worn by the user 7. The excretion sensor 8 is built in, 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. Absorbable articles are usually in the gaps between short fibers of cellulose-based fibers such as pulp fibers, rayon fibers, or cotton fibers, or synthetic fibers such as polyethylene, polypropylene, or polyethylene terephthalate that have been hydrophilized. , It is provided with an absorber that retains a granular absorbent resin such as SAP (Super Absorbent Polymer), which is a hydrophilic polymer having a crosslinked structure capable of absorbing and retaining water. Then, a water-permeable top sheet or the like is arranged on the skin surface side of the absorber. Therefore, the measuring unit 81 is arranged at a position where urine excreted from the wearer's anus or the like can easily come into contact with the measuring unit 81. Positions where urine excreted from the wearer's anus or the like is likely to come into contact include, for example, between the top sheet and the absorber, the skin side of the top sheet, and various other parts adjacent to the top sheet. .. The area occupied by the measuring unit 81 on the top sheet depends on the type of detection element used in the measuring unit 81, the detection performance required of the measuring unit 81, and various other conditions. For example, if the measuring unit 81 aims to detect the amount of urine with an accuracy of about three stages of high, medium, and low, the measuring unit 81 is a portion of the front body corresponding to the wearer's abdomen. Therefore, it is preferable that it is provided in a wide area extending from the inseam of the wearer to the back body portion corresponding to the back of the wearer. Further, for example, if the measurement unit 81 aims to detect only the presence or absence of urine, the measurement unit 81 may be provided only on the portion corresponding to the inseam of the wearer. On the other hand, since the transmission unit 82 is intended to wirelessly transmit information regarding the measured value of the measurement unit 81, it is preferable that the transmission unit 82 is provided at a portion where the radio wave transmitted from the transmission unit 82 to the radio antenna 4 is not blocked. .. Therefore, although it depends on the transmission output of the transmitting unit 82, the shape of the antenna, etc., for example, the exterior portion of the absorbent article is formed as a portion where the radio wave of the transmitting unit 82 is not blocked by the urine absorbed by the absorbent article. A portion adjacent to the cover sheet or the like is preferable.

The air conditioning sensor 9 is a measuring unit 91 composed of various elements such as a thermistor whose resistance value changes according to a temperature change and a resistance changing type sensor whose electric resistance changes depending on the water absorption rate of the wet and dry material, and the measuring unit 91. A transmission unit 92 for wirelessly transmitting information regarding measured values is provided. The information of the air conditioning sensor 9 is used for the purpose of correcting various predicted values related to excretion such as the urination time and the amount of urination of the user 7 by using the information such as the temperature in the room where the user 7 is located. Therefore, the air conditioning sensor 9 is mainly installed in a room or a hall where the user 7 stays in the building of the nursing facility where the information processing system 1 is used.

Next, the flow of processing when performing long-term care using the information processing system 1 will be described. FIG. 3 is a diagram showing an example of a processing flow when performing long-term care using the information processing system 1. When the staff 3 starts the nursing care work in the nursing care facility using the information processing system 1, first, the schedule of the work on the day is confirmed. When the staff 3 wants to confirm the work schedule of the day, for example, he / she operates the management terminal 6 at the station and performs a request operation of the schedule (R101). In the management terminal 6, when the input processing unit 61 receives the schedule request operation, the output processing unit 62 requests the server 2 for information data regarding the schedule (R102). In the server 2, when the input processing unit 21 receives a request for information data regarding the schedule from the management terminal 6, the arithmetic processing unit 22 inquires about the data stored in the database 24 (R103). Then, in the server 2, the output processing unit 23 provides the management terminal 6 with the data of the information regarding the schedule acquired by the arithmetic processing unit 22 inquiring to the database 24 (R104). In the management terminal 6, when the input processing unit 61 receives the data of the information about the schedule provided from the server 2, the output processing unit 62 displays the information of the data on the liquid crystal monitor (R105). The staff 3 confirms the schedule displayed on the management terminal 6 (R106).

The staff member 3 who confirmed the schedule displayed on the management terminal 6 prepares to move to the user's room in order to care for the user 7 (R107). As the preparatory work, for example, a new absorbent article newly attached to the user 7, a waste bag for disposing of the used absorbent article, and an article for work to be performed at the time of replacement work of the absorbent article. Kind of preparation etc. can be mentioned.

The staff member 3 who is ready to move moves to the user 7 together with the prepared articles and the on-site terminal 5 (R108). Then, when the staff 3 arrives at the user 7, the staff 3 operates the on-site terminal 5 and calls up the information necessary for the care of the user 7. In the on-site terminal 5, when the input processing unit 51 receives the operation of the staff 3, the output processing unit 52 displays the information necessary for the care of the staff 3 on the touch panel (R109). The information displayed on the touch panel by the output processing unit 52 may be information stored in advance in the storage of the on-site terminal 5, or the output processing unit 52 each time the input processing unit 51 accepts the operation of the staff 3. May be information that is inquired to the server 2 and provided from the server 2 to the field terminal 5.

In addition, the on-site terminal 5 detects the approach to the user 7 by reading the signal of the wireless identification device such as RFID worn by the user 7, and it is necessary to replace the absorbent article or change the position. Information for nursing care related to user 7 such as no or not is automatically displayed, or information is displayed when the user 7 performs a reading operation to read the barcode or QR code (registered trademark) of the identification display worn by the user 7. Alternatively, the user 7 may be identified by biometric authentication (face, fingerprint, iris, vein, ear shape, body odor, etc.) and information may be displayed. In this case, the wireless communication unit 53 of the field terminal 5 functions as a detection unit for detecting the radio wave of the RFID. Then, the field terminal 5 inquires the server 2 about the information of the user 7 specified by the identification information included in the RFID radio wave, and the information is sent from the server 2 to the field terminal 5 and displayed. The RFID may be a band-shaped one worn on the wrist, ankle, or the like of the user 7, but is realized as a function attached to the excretion sensor 8 provided in the absorbent article worn by the user 7, for example. Alternatively, it may be embedded in an absorbent article together with the excretion sensor 8. RFID can be read using various short-range wireless communication techniques. Examples of the wireless communication standard for reading RFID include various standards such as Bluetooth (registered trademark), ZigBee (registered trademark), and UWB (Ultra Wide Band).

The staff 3 confirms the information displayed on the on-site terminal 5 and confirms the identity (R110). Identity verification is an important procedure for preventing the user 7 from being mistaken, and is a confirmation performed for the purpose of preventing erroneous care for the user 7.

After completing the identity verification, the staff 3 operates the on-site terminal 5 to call up necessary information, and confirms various instructions such as precautions and procedures for providing long-term care to the user 7 (R111). Then, the staff 3 exchanges the used absorbent article worn by the user 7 and takes various other measures related to long-term care (R112). The on-site terminal 5 may analyze the voice of the staff 3 using the voice recognition technique and display the information requested by the staff 3.

When the staff 3 performs a procedure related to long-term care, the staff 3 inputs the recorded items to the on-site terminal 5 (R113). The record items to be input to the on-site terminal 5 include, for example, the amount of urine absorbed in the used absorbent article, the position of the user 7, information on the work performed at the time of exchanging the absorbent article, and the like. be. The information regarding the recorded items input by the staff 3 is received by the input processing unit 51 of the on-site terminal 5 (R114). Then, in the field 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. The server 2 receives the information received from the field terminal 5 by the input processing unit 21 (R115). Then, in the server 2, the arithmetic processing unit 22 accesses the database 24, and based on the information received by the input processing unit 21, a process of updating the data stored in the database 24 is performed (R116). Information on ancillary work such as postural change is used to determine the content of the next ancillary work.

It should be noted that the above series of processes is not performed for each user 7. That is, when the staff 3 departs from the station, he / she will return to the station again after providing nursing care to a plurality of users 7. Therefore, in the above series of processes, for example, after the processes from R101 to R107 are performed, the processes from R108 to R114 are repeated a plurality of times, and then the processes after R115 may be performed. Alternatively, for example, after the processes from R101 to R107 are performed, the processes from R108 to R116 may be repeated a plurality of times.

The staff 3 of the nursing facility using the information processing system 1 of the present embodiment can confirm various information related to nursing care by using the on-site terminal 5 and the management terminal 6 described above. Therefore, for example, compared to the case where the work is performed while confirming the communication items and precautions attached to the sleeper used by the user 7 and the fixtures in the vicinity thereof, the work is performed while confirming more information easily. be able to.

Hereinafter, the details of some functions of the information processing system 1 will be described individually.

<Excretion prediction function>
The information processing system 1 of the above embodiment is provided with an excretion prediction function of the user 7. The excretion prediction function is a function for predicting the urination time, the amount of urination, the defecation time, and the like. The excretion prediction function is mainly controlled by the arithmetic processing unit 22 of the server 2. The urination time, urination volume, and defecation time can be predicted based on the past urination time, eating and drinking, medicines taken, temperature and humidity of the living room, air conditioning setting of the living room, and various other information.

The excretion prediction is periodically executed by the arithmetic processing unit 22 of the server 2, and the prediction result is stored in the database 24. Therefore, the staff 3 can confirm the predicted time and the amount of urination that the user 7 will urinate next even if the on-site terminal 5 is operated at an arbitrary timing. Therefore, the staff 3 can perform a preliminary preparatory action based on the excretion prediction.

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 the present embodiment is based on data such as the amount of excretion automatically acquired by the excretion sensor 8, data on excretion manually input by the staff 3, air conditioning sensor 9, and the like. Machine learning is used to analyze the acquired data such as the environment of the living room, the type and amount of food and drink, and the data of the medicines ingested, and the excretion pattern of the user 7 is learned to create a prediction model for each user 7. Then, the urination time, urine volume, etc. of the user 7 are predicted from the model. Since some medicines have a diuretic effect or an antidiuretic effect, their administration times and doses affect the prediction of the excretion pattern of the user 7. In addition, since the administration time and dose of the laxative are directly related to excretion, they affect the prediction of the excretion pattern of the user 7. Therefore, although the data referred to by the excretion prediction function includes information on such drugs, it is possible to omit the information on drugs.

Machine learning means a process for generating a model that outputs a predicted value for input data. In machine learning, learning processes that update the parameters that define the model are executed multiple times using the training data. In this embodiment, various data related to the care of the user 7 such as the amount of urination and the time of urination are used for machine learning as learning data, and predicted values related to the work schedule of the staff 3 such as the amount of urination and the time of urination in the future are output. The model parameters for this are updated.

This function basically analyzes from a plurality of data within a predetermined time immediately before the time when excretion occurs. For example, in the case of predicting the urination time, the urination time is extracted from the data recorded in the database 24. Then, by analyzing the extracted urination time data by machine learning and calculating the feature amount of the urination time, the urination pattern of the user 7 can be learned and the future urination time can be predicted. .. As the machine learning algorithm, a random forest, a support vector machine (SVM), a linear discriminant analysis, a k-nearest neighbor method, a naive Bayes classification method, a decision tree, a neural network, a bagging method, a boosting method, or the like can be used.

Then, as described above, this function improves the prediction accuracy of excretion prediction from the data of the current environment, etc. by considering the data of the past environment, etc. of the living room acquired by the air conditioning sensor 9 or the like. .. Specifically, in the above machine learning, for example, not only the data of the feature amount of the urination itself such as the urination time and the urine amount, but also the feature amount indirectly related to the urination such as the past temperature and humidity of the user 7's room. By including this data in the training data, it is possible to make predictions that take into account the current temperature and humidity of the living room. The environmental information such as temperature and humidity may be individual data for each user 7, or may be average data for the entire long-term care facility. For example, when the temperature rises due to a seasonal change from winter to summer, the amount of water discharged as sweat from a place other than the bladder increases, so that the amount of urination tends to decrease. In addition, when the humidity rises due to the change of season from the dry season to the rainy season, the amount of water evaporated from the skin surface decreases, so that the amount of urination tends to increase. Therefore, in the above machine learning, by including the data of the feature amount indirectly related to urination such as the temperature and humidity of the user 7's room in the learning data, the prediction accuracy of the excretion prediction can be further improved.

Further, as described above, this function improves the accuracy of predicting the urination time by considering the data of the type and amount of food and drink ingested by the user 7. Specifically, in the above machine learning, not only the data of the feature amount of the urination itself such as the urination time and the urination amount, but also the feature amount indirectly related to the urination such as the type and amount of food and drink ingested by the user 7. By including the data in the learning data, it is possible to make predictions considering the type and amount of food and drink. For example, when a large amount of soup with a large amount of water is ingested, the amount of water entering the body increases, so that the amount of urination tends to increase. In addition, when the amount of drink to be drunk is reduced, the amount of water entering the body is reduced, so that the amount of urination tends to decrease. Therefore, in the above machine learning, the prediction accuracy of excretion prediction can be further improved by including the data of the feature amount indirectly related to urination such as the type and amount of food and drink ingested by the user 7 in the learning data. ..

As described above, in this excretion prediction function, in addition to the data on the environment and food and drink, the data on the ingested medicine, the data on the amount of exercise, and various other data are used as the data used for machine learning. It is possible to improve the prediction accuracy of excretion prediction as much as possible. Then, as the result of the excretion prediction, for example, the amount of urination after several hours, the time of urination, and the probability of occurrence of the amount of defecation can be obtained as a percentage. Therefore, for example, by displaying the time zone with the highest probability as the predicted urination time or displaying the percentage in a graph, the staff 3 can set the replacement time of the absorbent article worn by each user 7. It becomes possible to grasp.

Further, in this machine learning, in presenting the exchange timing of the absorbent article whose core data is the amount of urination, the data regarding the position 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 greatly depending on the body position at the time of excretion. For example, when the user 7 is lying on his back, the urine diffuses substantially evenly on both the left and right sides of the user 7 and is absorbed by the absorber. On the other hand, in the case where the user 7 is in a posture facing either left or right, the urine is diffused in a state of being biased toward the direction in which the user 7 is facing. There is a high possibility of leaking from the absorber. Therefore, in this machine learning, if the data regarding the position of the user 7 manually input by the staff 3 is included in the learning data, it is possible to present a more appropriate exchange timing in consideration of the diffusion distribution of the absorber depending on the position. In addition, it is possible to calculate the next position in consideration of the diffusion distribution.

In the explanation of this function, not only the data automatically acquired by using the sensor device such as the excretion sensor 8 but also the data manually input to the on-site terminal 5 by the staff 3 was explained. This function is not limited to such a form. This function may predict excretion using only the data automatically acquired by using a sensor device such as the excretion sensor 8, or only the data manually input to the on-site terminal 5 by the staff 3. May be used to predict excretion.

FIG. 5 is a diagram showing an example of a screen displayed on the field terminal 5. For example, the staff member 3 can display a screen as shown in FIG. 5 displayed on the on-site terminal 5 in the step of R109 described above, and can confirm the prediction result or the like obtained by the present excretion prediction function. On the screen shown in FIG. 5, information necessary for the staff 3 to perform work related to long-term care at the user 7 is displayed. As shown in FIG. 5, this information includes, for example, the name and number, gender, date of birth, and age of the user 7, and is used in the step of R110 described above. Since this screen contains information for identifying the user 7, it is convenient to display it as the top screen at the initial stage of starting the operation of the on-site terminal 5, but after performing one or more operations. It may be the screen to be displayed.

As shown in FIG. 5, on the screen displayed on the on-site terminal 5, in addition to information such as the name of the user 7, time-series information related to excretion of urine, feces, etc., body position, meal, and water intake It contains various information such as the condition of the patient, infusion, and the presence or absence of diarrhea (see the "excretion record" column in FIG. 5). It also includes information on incidental work such as the type of absorbent article to be worn on the user 7, the type of cleaning solution used for cleaning the pubic area, the method of pressure ulcer care, and the method of changing the position.

In the column of information regarding the excretion record, information from 8:00 am to 12:00 pm on the day is displayed. Therefore, when the screen of the on-site terminal 5 is opened during the daytime of the day, the information from 8:00 am to the present of the day is displayed as actual measurement data, and the information from the present to 12:00 pm is the data of the above-mentioned prediction result. Is displayed. Since the data related to excretion such as the amount of urine is transmitted from the excretion sensor 8 built in the absorbent article worn by the user 7 and recorded in the database 24, the urine volume is displayed in a bar graph in the range of 0 cc to 500 cc. It is displayed in chronological order. The accuracy of the urine volume displayed in the bar graph depends on the performance of the excretion sensor 8. For example, in the case where the measuring unit 81 is configured by using a plurality of elements that are energized when urine comes into contact, the element is used. Since the urine volume has a resolution corresponding to the number of urine, a stepwise bar graph will be drawn.

For incidental work, a work procedure manual that describes the details of the work procedure is prepared in advance at each nursing care facility. Therefore, the screen displayed on the on-site terminal 5 is also provided with a "procedure manual" button for displaying this work procedure manual. Therefore, the staff 3 can confirm the specific procedure of the incidental work by touching the "procedure manual" button of each incidental work. Therefore, even if a person who does not have sufficient experience is a staff member of a nursing care facility 3 due to various circumstances such as a decrease in the working population and a shortage of human resources in the nursing care industry in recent years, the user 7 should take appropriate measures. It is possible to do it.

Further, the screen displayed on the on-site terminal 5 includes information on the name of the user 7 and incidental work, as well as operation buttons for recording the results of the replacement work of the absorbent article (FIG. 5). See "Records after changing diapers" column). The excretion sensor 8 is built in the absorbent article worn by the user 7, and as described above, data on excretion such as the amount of urination is recorded in the database 24. Therefore, on the screen displayed on the on-site terminal 5, the latest urine volume transmitted from the excretion sensor 8 is displayed as a sensor value. However, when the staff 3 confirms the used absorbent article when exchanging the absorbent article of the user 7, the urine volume detected by the excretion sensor 8 may differ from the actual urine volume. Therefore, the screen displayed on the on-site terminal 5 is provided with a correction button or the like for correcting the urine volume data acquired by the excretion sensor 8 and stored in the database 24. In addition, buttons for inputting various recorded 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 are provided.

FIG. 6 is a diagram showing an example of a screen for correcting urine volume data. When the correction button for correcting the urine volume data is pressed, for example, a pop-up window for data correction as shown in FIG. 6 is displayed on the field terminal 5. The urine volume data can be modified by operating a button to add or subtract sensor values, as shown in FIG. When the "OK" button at the lower 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 corrected content of the urine volume is confirmed. In the case of a nursing facility that does not use an absorbent article having a built-in excretion sensor 8, the urine volume data detected by the excretion sensor 8 is not input, so that the urine volume is manually input by these operations. Then, the above-mentioned excretion prediction is also performed based on the information manually input by these operations.

FIG. 7 is a diagram showing an example of a screen for inputting a stool volume and a stool property. When it is desired to input data related to the volume of stool and the properties of stool, 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. Regarding the amount of stool, there are three types of touch parts that are based on the image of "small, medium, and large" with the number of round symbols representing the stool. You can enter the amount. As for the stool properties, seven types of buttons expressing the stool properties in words are prepared, so that the staff 3 can input the stool properties by touching any of the buttons. Various data such as the amount of stool and the properties of stool input to the on-site terminal 5 are sent to the server 2 via the network N and stored in the database 24. Then, it is used for predicting the above-mentioned urination time and the like.

When the urine volume data stored in the database 24 is modified, the coefficient (return coefficient) of the explanatory variable used in the machine learning of the excretion prediction function described above also changes. FIG. 8 is a diagram illustrating the relationship between the correction of the urination volume and the change in the regression coefficient. Although the flowchart is shown in FIG. 8, the regression coefficient is calculated by machine learning of the arithmetic processing unit 22. Therefore, the flowchart shown in FIG. 8 does not show the processing content executed by the arithmetic processing unit 22.

For example, it is assumed that the data of the amount of urine discharged from the user 7 is corrected and the amount of urine is increased from that before the correction (when YES in S101). When the amount of urination stored in the database 24 is increased by the modification, the regression coefficient in the machine learning performed before the modification is affected. That is, the correlation between the explanatory variable and the objective variable in machine learning that was executed before the modification changes depending on the modification of the micturition volume. Therefore, when machine learning is re-executed after the urine volume is corrected, the regression coefficient is also added (S102). Further, it is assumed that the amount of urination is smaller than that before the correction (when YES in S103). In this case, if machine learning is performed after the urine volume is corrected, the regression coefficient will also be subtracted. (S104).

When the urine volume data stored in the database 24 is corrected by the staff 3, the coefficients of the explanatory variables used in the machine learning of the excretion prediction function also change in this way. Such an effect on the excretion prediction function occurs not only in the correction of the urination volume but also in the correction of the stool volume, the stool properties, and other various items. And, such an influence on the excretion prediction function also affects, for example, the planning function of the exchange schedule of the absorbent article described later.

<Planning function>
Hereinafter, the function of planning the replacement schedule of absorbent articles will be described. 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 the present embodiment is executed at the start of work such as early morning of a nursing care facility, and is used when the staff 3 starts work. The planning function of the information processing system 1 according to the present embodiment is a process mainly executed by the arithmetic processing unit 22.

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 the data stored in the database 24, and includes the above-mentioned urine volume information and various other information.

Further, the arithmetic processing unit 22 refers to the shift (scheduled work) data of each employee 3 (S202). The shift data of each staff 3 is the data stored in the personnel management server used in the nursing facility or the data stored in the database 24, and the manager who manages each staff 3 and each of them. This is the data input by the staff 3 himself to the management terminal 6, the site terminal 5, or the like.

Further, the arithmetic processing unit 22 refers to the data related to the long-term care of each user 7 (S203). The data related to the care of the user 7 referred to by the arithmetic processing unit 22 is the data stored in the database 24, the type of the absorbent article worn by the user 7, and the measures necessary to be performed on the user 7. It includes various information such as the contents of (decubitus care, genital cleansing, necessity of repositioning, etc.), brand of absorbent article worn by user 7, and absorption capacity.

The arithmetic processing unit 22 creates a plan for the exchange schedule of the absorbent article based on the referenced data (S204). More specifically, the arithmetic processing unit 22 creates a plurality of plans in which high-priority items are staggered. As a plan created by the arithmetic processing unit 22, in this embodiment, "total number of exchanges priority" (hereinafter referred to as "plan 1"), "diaper cost priority" (hereinafter referred to as "plan 2"), and "excretion care charge" Four types of "minimum load priority per person" (hereinafter referred to as "plan 3") and "scheduled exchange priority" (hereinafter referred to as "plan 4") are exemplified. However, the information processing system 1 is not limited to the form of creating these four types of plans. The information processing system 1 may create various other plans.

Plan 1 is a plan in which the number of times of replacement work of absorbent articles performed by the staff 3 is minimized. Plan 1 is a plan suitable for, for example, when the number of staff 3 is relatively small. In this plan, for example, replacement with an absorbent article having a large amount of absorption is proposed by the arithmetic processing unit 22.

Plan 2 is the plan that minimizes the total cost of the absorbent goods to be replaced. Plan 2 is a suitable plan, for example, when the number of staff members 3 is relatively large and inexpensive absorbent articles having a small absorption capacity can be frequently replaced.

Plan 3 is a plan that minimizes the amount of work per employee 3. Plan 1 is the plan that minimizes the total number of exchanges for all staff 3, while Plan 3 is the plan that minimizes the work per staff 3, so for example, during a specific time during the day. However, when the shift is such that the number of staff 3 is small, the total replacement work in the relevant time zone is less than in other time zones. As a result, in a time zone in which a relatively large number of staff members 3 are present outside the time zone, the replacement work increases, so that the concentration of work on the specific staff member 3 is eased.

Plan 4 is a plan for allowing the exchange of absorbent articles to take place at a predetermined time. For example, it is a suitable plan when various schedules are prepared for the user 7 and the time zone in which the absorbent article can be exchanged is limited. In Plan 4, the type of absorbent article to be replaced and the timing of replacement are determined so that the absorbent article can be replaced at a predetermined time zone.

The arithmetic processing unit 22 uses, for example, the Dijkstra method to search for an exchange schedule for absorbent articles, the type of absorbent articles to be attached, and the like. When using the Dijkstra method, for example, for a large number of nodes between the start node and the end node, the work time required for replacement and ancillary, the cost of absorbent goods, the time required to move within the facility, and the above-mentioned prediction. Set the urination volume, urination time, etc. as weights, and search for the route with the least weight. 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 the route search is executed. This completes the calculation of the exchange schedule corresponding to the various plans of Plans 1 to 4. Needless to say, regardless of the plan, a plan for a time zone in which the staff 3 can exchange the absorbent articles is created. For example, a time zone in which the staff member 3 cannot work, such as a midnight time zone in which the staff member 3 is scarcely present or a break time zone of the staff member 3, is excluded from the time zones of candidates for replacement work in any of the above plans.

When the creation of the plan is completed, the arithmetic processing unit 22 causes each plan to be compared and displayed on the screen of the field terminal 5 or the management terminal 6 (S205). FIG. 10 is an example of a screen in which exchange schedule plans are comparatively displayed. When the arithmetic processing unit 22 completes the creation of the plan, the plan created by the arithmetic processing unit 22 can be displayed on the screen on the field terminal 5 or the management terminal 6. Therefore, the staff 3 can compare and examine various plans created by the arithmetic processing unit 22 by operating the on-site terminal 5 or the management terminal 6. Further, when the staff 3 selects any plan (S206), the arithmetic processing unit 22 causes the details of the selected plan to be displayed on the terminal operated by the staff 3 (S207). As a result, the staff 3 can confirm the detailed display of the selected plan.

By using such a planning function, in a nursing care facility using the information processing system 1, various tasks such as formulating a patrol route for user 7, a schedule for each staff member 3, and deciding the placement of staff member 3 become easy. .. Therefore, in a long-term care facility that uses the information processing system 1, even a limited number of staff members 3 can provide appropriate long-term care to the user 7.

In the actual nursing care site, it is not realistic to change the disposable diapers every time excretion because the number of people in charge of nursing care is small. Therefore, even if the excretion time of the user is predictable, the reality is that the disposable diaper cannot be replaced at the predicted time. In this regard, with this planning function, not only the data of the predicted urination volume and urination time but also various data such as the shift of the staff 3 are used for planning, so that the staff 3 of the day can make a plan. It is possible to propose and select the replacement time of absorbent goods according to the shift and placement situation. In addition, by using this planning function, it is possible to determine the required number of staff 3 by time zone, etc. from the replacement timing of absorbent goods, etc., so the information processing system 1 can be used for the work schedule of staff 3. It can also be used for examination.

Further, in the case of the information processing system 1 of the present embodiment, not only the excretion care such as the exchange of absorbent articles but also the incidental work such as the skin care to be performed at the same time, the procedure browsing and the record are referred to together with the excretion care information. , Can be entered. Therefore, with the information processing system 1 of the present embodiment, it is possible to perform various operations related to the care of the user 7 extremely rationally.

<Computer readable recording medium>
A program that realizes any of the above functions in a computer or other machine or device (hereinafter referred to as a computer or the like) can be recorded on a recording medium that can be read by a computer or the like. Then, by having a computer or the like read and execute the program of this recording medium, the function can be provided. Here, a recording medium that can be read by a computer or the like is a storage medium that can store information such as data and programs by electrical, magnetic, optical, mechanical, or chemical action and can be read from a computer or the like. To say. Examples of such a storage medium include an optical disk, SSD, HDD, non-volatile memory and the like.

N ・ ・ Network 1 ・ ・ Information processing system 2 ・ ・ Server 3 ・ ・ Staff 4 ・ ・ Wireless antenna 5 ・ ・ Site terminal 6 ・ ・ Management terminal 7 ・ ・ User 8 ・ ・ Excretion sensor 9 ・ ・ Air conditioning sensor 21 ... Input processing unit 22 ... Arithmetic processing unit 23 ... Output processing unit 24 ... Database 51 ... Input processing unit 52 ... Output processing unit 53 ... Wireless communication unit 61 ... Input processing unit 62 ... Output Processing unit 81 ... Measuring unit 82 ... Transmitting unit 91 ... Measuring unit 92 ... Transmitting unit

Claims (7)

A storage unit that stores excretion information, which is information about excrement excreted in the absorbent article,
An arithmetic processing unit that predicts the excretion of the wearer wearing the absorbent article from the environmental information including at least one of the temperature and humidity of the wearer of the absorbent article and the excretion information.
An output processing unit that outputs the result of the prediction is provided.
Information processing equipment. The arithmetic processing unit predicts the excretion of a wearer wearing the absorbent article by using a prediction model machine-learned using the excretion information and the environment information as teacher data.
The information processing apparatus according to claim 1. The arithmetic processing unit uses a prediction model machine-learned using the past information of the environment and the excretion information stored in the storage unit as teacher data, and is currently transmitted from a sensor installed in the living room. Predict the excretion of the wearer wearing the absorbent article based on environmental information.
The information processing apparatus according to claim 1 or 2. The excretion information stored in the storage unit is not a small amount of the information transmitted from the excretion sensor provided in the absorbent article and the information input to the terminal by the caregiver who exchanges the absorbent article. Including either,
The information processing apparatus according to any one of claims 1 to 3. The arithmetic processing unit predicts that when the temperature of the room of the wearer of the absorbent article rises, the amount of urination of the wearer decreases, and when the temperature of the room of the wearer of the absorbent article decreases, the wearer Predict that a person's urination volume will increase,
The information processing apparatus according to any one of claims 1 to 4. Refer to the storage unit that stores excretion information, which is information about excrement excreted in the absorbent article.
From the environmental information including at least one of the temperature and humidity of the wearer of the absorbent article and the excretion information, the excretion of the wearer wearing the absorbent article is predicted.
Output the result of the prediction,
Information processing method. For information processing equipment
Refer to the storage unit where excretion information, which is information about excrement excreted in the absorbent article, is stored.
From the environmental information including at least one of the temperature and humidity of the wearer of the absorbent article and the excretion information, the wearer who wears the absorbent article is made to predict the excretion.
Output the result of the prediction,
Information processing program.

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