Excretion management system

Abstract

To provide an excretion management system capable of appropriately making a notification when it is time for a user to excrete.SOLUTION: An excretion management system 10 is provided, comprising a history information acquisition unit (acquisition device 100) for acquiring excretion history information including at least excretion timing of a user, an excretion timing estimation unit (control unit 270) for estimating the future excretion timing of the user on the basis of the excretion history information, and a notification unit (touch panel 210) for making a notification of the future excretion timing.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to an excretion management system.

Background Art

[0002] For example, Patent Document 1 discloses a toilet device that determines the progress state of a user's excretion behavior based on the excretion state in the user's excretion behavior and communicates the determination result to the outside from a communication means.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, from the viewpoint of reducing the burden on caregivers, it has been required to appropriately notify caregivers of the excretion timing of users.

[0005] An object of the present disclosure is to provide an excretion management system capable of appropriately notifying the excretion timing of a user.

Means for Solving the Problems

[0006] An excretion management system according to an aspect of the present disclosure includes a history information acquisition unit that acquires excretion history information including at least the excretion timing of a user, an excretion timing estimation unit that estimates the future excretion timing of the user based on the excretion history information, and a notification unit that notifies the future excretion timing.

Effects of the Invention

[0007] According to the present disclosure, it is possible to provide an excretion management system capable of appropriately notifying the excretion timing of a user.

Brief Description of the Drawings

[0008]

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Embodiments for Carrying Out the Invention

[0009] Hereinafter, embodiments of the excretion management system according to the present disclosure will be described in detail with reference to the drawings. Note that each of the embodiments described below shows a preferred specific example of the present disclosure. Therefore, numerical values, shapes, materials, components, arrangements and connection forms of the components shown in the following embodiments are merely examples and are not intended to limit the present disclosure. In addition, among the components in the following embodiments, components not described in the independent claims are described as optional components.

[0010] Note that the accompanying drawings and the following description are provided for those skilled in the art to fully understand the present disclosure, and are not intended to limit the subject matter described in the claims.

[0011] Also, each figure is a schematic diagram and is not necessarily drawn precisely. In each figure, substantially the same configuration is denoted by the same reference numeral, and redundant descriptions may be omitted or simplified.

[0012] [Embodiment] (Excretion Management System) The excretion management system according to the embodiment is for managing information related to the excretion of a user. Excretion includes defecation and urination, and in this excretion management system, information on at least one of defecation and urination is managed.

[0013] FIG. 1 is a block diagram showing the configuration of an excretion management system 10 according to the embodiment. As shown in FIG. 1, the excretion management system 10 includes an acquisition device 100, an information notification device 200, and a server device 300.

[0014] The acquisition device 100 is an example of a history information acquisition unit that acquires excretion history information related to the excretion of a user. Here, the excretion history information includes the excretion timing of the user, the excretion amount per excretion, the time required per excretion, the properties of the excrement, and the like.

[0015] FIG. 2 is an explanatory diagram showing a schematic configuration of the acquisition device 100 according to the embodiment. As shown in FIG. 2, the acquisition device 100 is built into the toilet seat 2 of the toilet 1. The acquisition device 100 includes a use detection unit 110, an excretion detection unit 120, and a control unit 130.

[0016] The use detection unit 110 is a sensor that detects the use of the toilet by the user. For example, it is a seating sensor that detects that the user has sat on the toilet seat 2 and outputs the detection signal to the control unit 130. Other use detection units 110 include, for example, a human presence sensor that detects that the user has entered the toilet compartment of the toilet 1. Furthermore, it is also possible to adopt a local cleaning device as another use detection unit 110. In this case, the use of the toilet by the user can be detected based on the presence or absence of an operation signal for the local cleaning device.

[0017] The excretion detection unit 120 is a sensor that detects the excretion of the user performed in the toilet 1. For example, the excretion detection unit 120 includes an illumination unit 121 that illuminates the inside of the toilet bowl of the toilet 1 and a camera 122 that images the excrement in the toilet bowl illuminated by the illumination unit 121. The camera 122 outputs the captured image to the control unit 130. Examples of the camera 122 include a visible light camera, an infrared camera, etc.

[0018] As shown in FIG. 1, the control unit 130 includes a communication unit 131, a storage unit 132, and a control unit 133. The communication unit 131 is a communication module that performs wired and / or wireless communication. The control unit 133 includes a CPU, a ROM, and a RAM, and the CPU expands and executes a program in the ROM in the RAM to control each part of the toilet 1 and the acquisition device 100. The control unit 133 recognizes that the toilet 1 has been used based on the detection signal from the usage detection unit 110. The control unit 133 performs known image analysis processing on the image from the camera 122 to detect the user's excretion. Thereby, the control unit 133 acquires the user's excretion history information and stores it in the storage unit 132. Further, the control unit 133 reads the excretion history information from the storage unit 132, controls the communication unit 131, and outputs it to the server device 300. Furthermore, the control unit 133 outputs the detection signal detected by the usage detection unit 110 to the server device 300 by controlling the communication unit 131.

[0019] In the detection of the user's excretion, as excretion history information, the excretion amount per excretion (weight or volume of excrement), the time required per excretion, and the properties of the excrement (color, hardness, etc.) are detected.

[0020] For example, the control unit 133 can obtain the area of the brown region in the image by known image analysis processing and detect the presence and amount of feces based on the area. The control unit 133 can obtain the area of the yellow region in the image by known image analysis processing and detect the presence and amount of urine based on the area. The control unit 133 can also determine whether it is bloody stool from the presence or absence of the red region in the image by known image analysis processing. The color of the excrement may be indicated by a binary classification of whether it contains red or not. Also, the color of the excrement may be indicated by the main color of the excrement (for example, black, green, gray, dark yellow, light yellow, etc.). If the color of the excrement can be detected in detail, the symptoms of the disease can be grasped and used for diagnosis and the like.

[0021] Furthermore, the control unit 133 can recognize the hardness of the feces from the boundary shape (the contour shape of the feces) between the toilet bowl and the feces in the image of the feces at the bottom of the toilet bowl. For example, when the contour shape is a lumpy shape similar to clearly defined rabbit feces characteristic of constipation, the control unit 133 estimates hard feces. On the other hand, when the contour shape is blurred or not clear, the control unit 133 estimates soft feces.

[0022] Moreover, even if it is not an image of the excrement that has fallen to the bottom of the toilet bowl, it may be estimated based on an image of the excrement during falling. For example, when the excrement is falling while scattering in the air or has a narrow width, the control unit 133 estimates it as soft feces containing a large amount of moisture. On the other hand, in the case of excrement with a wide width and a relatively short length, the control unit 133 estimates hard feces. When estimating, instead of the entire image, using a cut-out image that cuts out the range through which the falling excrement passes in a horizontally long shape can suppress false detection due to the reflection of the excrement after falling. The hardness of the feces may be indicated by a two-category classification of hard or soft, or may be classified in more detail, for example, by determining using the Bristol scale 7-category classification.

[0023] Regarding the excretion amount of urine (urination volume), it may also be estimated based on an image of the urine during falling. The control unit 133 detects the width of the urine during falling and the number of them in the cut-out image from color information and contour information, and estimates the urine flow rate at the moment when the image is taken. The urine flow rate may be estimated in two steps of high or low, or may be a more multi-step estimation. Furthermore, it may be estimated with a quantitative value (ml / sec). In this case, the excretion amount per excretion may be estimated by integrating the quantitative value with respect to the time from the start to the end of urination. Alternatively, the image may be taken at a relatively high frequency (interval of about 10 msec to 5 msec), and the excretion amount per excretion may be estimated from the cumulative sum of the estimated flow rate of each image × the imaging interval.

[0024] Furthermore, it is also possible to use machine learning for these estimations. In this case, a large number of images including the presence or absence of excretion, the amount of excretion per excretion, and the properties of the excreted matter are input into the machine learning in advance to create a pre-trained model. The control unit 133 obtains the estimation result by inputting the image captured by the camera 122 into the pre-trained model. The learning model may be created for each estimation item, or one learning model may be created by grouping a plurality of items together.

[0025] Furthermore, when the control unit 133 estimates the presence or absence and properties of the excreted matter, not only the image obtained by the camera 122 but also the detection result of the usage detection unit 110 may be used. For example, the local cleaning water discharged from the nozzle (not shown) of the local cleaning device is likely to be misdetected because its appearance is similar to urine. Therefore, while the local cleaning device is in use, false detection can be prevented by not determining the presence or absence of urine. In addition, some cleaning tools such as a mop used for toilet cleaning are likely to be misdetected because their color and the like are similar to feces. However, by using the detection result of the seating sensor, it is possible to determine that the image taken in the non-seated state is not feces, thereby preventing false detection. Furthermore, even feces such as watery diarrhea feces are similar to dark-colored urine, making it easy to misjudge between urine and feces. If the diarrhea feces contain solids or floating substances, it can be determined as feces from the image. However, since there are rare cases where there are no solids, if it is possible to determine solid-free diarrhea feces as feces, urine is also likely to be determined as feces. Therefore, by using the detection result of the seating sensor, it can be determined as urine in the non-seated state, suppressing the false detection of urine as feces. Thereby, the estimation accuracy can be improved.

[0026] Also, even without directly detecting the excreted matter, for example, sensors may be provided for the "large" and "small" of the flushing operation unit of the toilet 1. For example, based on the detection signal when large flushing is performed, the excretion timing of feces can be detected, and based on the detection signal when small flushing is performed, the excretion timing of urine can be detected.

[0027] In addition, in this embodiment, the case where the acquisition device 100 is built into the toilet seat 2 of the toilet 1 is illustrated. However, at least a part of the acquisition device 100 may be detachable from the toilet seat 2.

[0028] FIG. 3 is a perspective view showing a modified example of the acquisition device according to the embodiment. FIG. 4 is an exploded perspective view showing a modified example of the acquisition device according to the embodiment. As shown in FIGS. 3 and 4, in the acquisition device 100A according to the modified example, the usage detection unit 110a and the excretion detection unit 120a are integrated and detachable from the toilet seat 2. The control unit 130a is built into a control panel 140a having functions such as an operation unit and a display unit. The control unit 130a is connected to the usage detection unit 110a and the excretion detection unit 120a so as to be communicable by wire or wirelessly.

[0029] Further, the acquisition device 100 may have a personal authentication unit for identifying the user. For example, the acquisition device 100 may include a camera for photographing the user, and may identify the user by performing face authentication using the camera. The camera may be provided integrally with the acquisition device 100, or may be connected so as to be communicable. The camera may be arranged inside the toilet cubicle or outside the cubicle. The image taken for authentication may be deleted without being saved after authentication. The image taken by this camera for personal authentication may be used for other purposes. For example, it is possible to estimate the presence or absence of the accompaniment of a care staff included in the image. Further, based on the face of the user included in the image, it is possible to estimate age, gender, stress level, urgency of excretion, etc. Based on the state of the user included in the image, it is possible to estimate walking posture, walking speed, degree of independence, height, weight, etc. By notifying these estimated information to the care staff, the care staff can utilize it for care judgment for the user. Further, the care staff can also estimate the health state of the user or use it as a basis for making an improvement proposal judgment by comparing and analyzing the estimated information and the excretion history information.

[0030] The personal authentication unit may be a biometric authentication device that performs fingerprint, palmprint, or iris authentication. In this case, the biometric authentication device may be installed in the operation unit of Toilet 1, inside or outside the individual toilet compartment. Furthermore, an RFID tag may be provided on an item (such as a card, nameplate, wristband, etc.) carried by the user, and a reading device for reading the RFID tag may be used as the personal authentication unit. An authentication device that performs authentication by communicating with a terminal (such as a mobile phone, wearable terminal, etc.) owned by the user may also be used as the personal authentication unit. An input device for inputting a password assigned to the individual user may also be used as the personal authentication unit.

[0031] The information notification device 200 shown in FIG. 1 is a terminal device that is communicably connected to the acquisition device 100 and the server device 300. The information notification device 200 includes a touch panel unit 210, a sound output unit 220, a sound input unit 230, a storage unit 240, an imaging unit 250, a communication unit 260, and a control unit 270. The touch panel unit 210 is a touch panel having a liquid crystal or organic EL panel. The sound output unit 220 is a speaker. The sound input unit 230 is a microphone. The storage unit 240 is a storage device such as a hard disk drive or SSD (Solid State Drive). The imaging unit 250 is a camera. The communication unit 260 is a wired and / or wireless communication module. The control unit 270 includes a CPU, a ROM, and a RAM, and the CPU expands and executes the program in the ROM to control each part of the information notification device 200.

[0032] Examples of the information notification device 200 include smartphones, tablet terminals, wearable terminals (such as smartwatches, smart glasses, etc.), notebook PCs, portable game machines, and the like. The information notification device 200 may be a terminal owned by the user himself / herself, or a terminal owned by a caregiver who takes care of the user.

[0033] Other information other than the user's excretion history information may be input to the information notification device 200. The other information is output to the server device 300 via the communication unit 260.

[0034] Other information includes, for example, user attribute information, vital information, lifestyle information, other excretion information, medication information, and care information. Attribute information is information indicating the attributes of the user and includes age, gender, degree of care need, dementia symptoms, past medical history, and the like. Vital information is information indicating the vital signs of the user and includes height, weight, body temperature, blood pressure, pulse, heart rate, SpO2 (arterial oxygen saturation), and the like. Lifestyle information is information related to the user's life activities and includes sleep (time, depth, body movement), diet (content, amount), exercise (content, activity level), and the like.

[0035] Other excretion information is information related to the user's excretion that could not be detected by the acquisition device 100 and includes excretion timing, excretion amount per excretion, time required per excretion, properties of excrement, and the like. That is, other excretion information is information related to excretion not performed in the toilet 1 due to going out or the like. In order to detect the user's incontinence, an odor sensor or a conductivity sensor may be provided near the user's bed, and other excretion information caused by incontinence may be acquired based on the detection result.

[0036] Medication information is information about the medications the user is taking and includes the types of medications taken and the dosage. Care information is information related to the care of the user and includes care content (toilet guidance assistance, diaper change, abdominal rubbing, etc.). These pieces of information may be manually input into the information notification device 200 or may be detected by various sensors and transmitted to the information notification device 200. In any case, since the information notification device 200 acquires various information, it is an example of each acquisition unit (medication information acquisition unit, attribute information acquisition unit, lifestyle information acquisition unit) according to the present disclosure. Also, when the information notification device 200 is a wearable terminal device, it is also possible to detect at least one of the above-mentioned information by a sensor provided in the wearable terminal device. Note that other information may be input from an input device different from the information notification device 200. In any case, other information is associated with the user's ID in the server device and collectively managed together with the excretion history information.

[0037] In addition, in this embodiment, the case where the acquisition device 100 detects the excretion history information of the user is exemplified. However, the excretion history information of the user may be acquired by manually inputting it to the information notification device 200. Further, the information notification device 200 may acquire the information related to excretion in the care data by reading the care data from a recording device that records the care data of the user, and use it as the excretion history information. When the care data is described on paper, the information notification device 200 may photograph the care data and perform character recognition processing to acquire the information related to excretion and use it as the excretion history information. In this case, the information notification device 200 is an example of a history information acquisition unit.

[0038] Based on the excretion history information of the user acquired from the server device 300, the control unit 270 of the information notification device 200 estimates the future excretion timing of the user. That is, the control unit 270 is an excretion timing estimation unit. The future excretion timing is the timing when the user excretes in the future compared to the current time. Further, the control unit 270 controls at least one of the touch panel unit 210 and the sound output unit 220 to notify the future excretion timing. That is, the touch panel unit 210 and the sound output unit 220 are examples of notification units. The estimation of the future excretion timing and its notification will be described later.

[0039] The server device 300 is a server device that can communicate with the acquisition device 100 and the information notification device 200. For example, the server device 300 can communicate with the acquisition device 100 and the information notification device 200 via the Internet or a local area network. The server device 300 associates and stores the ID of each user, the excretion history information, and other information. When other excretion information is included in the other information, the server device 300 updates the excretion history information by arranging the other excretion information and the excretion history information acquired from the acquisition device 100 in chronological order and summarizing them. The server device 300 executes this update process for each user ID.

[0040] (Estimation of Future Excretion Timing and Its Notification) Next, the estimation of future excretion timing and its notification will be described. In the present embodiment, the case where the estimation of future excretion timing and its notification are executed by the information notification device 200 will be exemplified. However, the estimation of future excretion timing may be executed by another device (for example, the server device 300), and the notification thereof may be executed by the information notification device 200.

[0041] FIG. 5 is a flowchart showing the flow of determination of future excretion timing and its notification according to the embodiment. Here, the future excretion timing may sometimes be referred to as the next excretion timing.

[0042] As shown in FIG. 5, in step S101, when the user ID is input to the touch panel unit 210, the control unit 270 of the information notification device 200 controls the communication unit 260 to acquire the excretion history information associated with the ID from the server device 300.

[0043] In step S102, the control unit 270 estimates the next excretion timing based on the user's excretion history information. Specifically, the control unit 270 obtains the average excretion interval of the past excretion time intervals (the difference between the nth excretion timing and the (n + 1)th excretion timing: hereinafter referred to as the excretion interval) based on the excretion history information. This average excretion interval is, for example, the average value per a predetermined period such as one month. The control unit 270 estimates the timing obtained by adding the average excretion interval to the most recent excretion timing at the current time as the next excretion timing. Thus, in the present embodiment, the control unit 270 estimates the next excretion timing based on the user's excretion history information. When the user's excretion history information is not sufficiently accumulated, the control unit 270 may estimate the excretion timing by adopting the average excretion interval of the same age group as the user.

[0044] In step S103, the control unit 270 controls the touch panel unit 210 and the sound output unit 220 to notify the next excretion timing. FIG. 6 shows an example of notification in the information notification device 200 held by a caregiver according to the embodiment. As shown in FIG. 6, on the touch panel unit 210, the current time and the next excretion timing of the user (Mr. A) are displayed side by side. Thereby, the caregiver can recognize the next excretion timing of the user and can prepare for the next excretion of the user.

[0045] (Effects, etc.) As described above, according to the present embodiment, since the next excretion timing of the user is notified, the caregiver can grasp the next excretion timing of the user. Thus, according to the present disclosure, an excretion management system 10 that can appropriately notify the next excretion timing of the user can be provided.

[0046] Since the acquisition device 100 that detects the excretion of the user and acquires the excretion timing of the excretion is used as the history information acquisition unit, it is possible to automatically acquire the excretion timing. Thereby, compared with the case of manual input, the labor of the user or the caregiver can be reduced.

[0047] [Modification Example] Hereinafter, each modification example of the above embodiment will be described. In the following description, the same parts as those in the above embodiment or other modification examples may be denoted by the same reference numerals and the description thereof may be omitted.

[0048] (Modification Example 1) In Modification Example 1, a case of estimating future excretion timing in consideration of the nighttime sleep time zone will be described. During sleep, a certain hormone that suppresses excretion is secreted. As a result, the excretion interval during sleep becomes longer, so it may be possible to estimate future excretion timing by distinguishing between when awake and when asleep. For example, by detecting the user's actions, position, etc. with a camera in the bedroom, when the user's body movement is below a certain level or the user's position is on the bed, it is possible to determine that the user is asleep. The control unit 270 acquires sleep information regarding the user's sleep based on the video from the camera. In this way, the control unit 270 is an example of a sleep information acquisition unit. The control unit 270 makes the above determination based on the sleep information. Then, based on this determination result, the control unit 270 classifies each excretion included in the excretion history information as either excretion during the sleep time zone or excretion during the waking time zone, and obtains the average excretion interval for the sleep time zone and the average excretion interval for the waking time zone. By adopting these two average excretion intervals at the time of estimation, it is possible to estimate the future excretion timing during the sleep time zone and the future excretion timing during the waking time zone.

[0049] In addition, if the user transitions from sleep to wakefulness or from wakefulness to sleep before the future excretion timing, the excretion timing may be corrected. For example, if the average excretion interval during the waking time zone is 3 hours and the average excretion interval during the sleep time zone is 6 hours, when transitioning, these average times (4.5 hours) may be adopted as the average excretion interval, or the average excretion interval may be corrected based on the ratio of the actual sleep time to the waking time.

[0050] Even without using a sleep detection sensor such as the above-described camera, it is also possible to simply calculate the average excretion interval by time zone. For example, it is also possible to classify each excretion included in the excretion history information with 6:00 to 22:00 as the waking time zone and 22:00 to 6:00 as the sleep time zone.

[0051] (Modification Example 2) In Modification 2, the control unit 270 obtains the excretion frequency for each of a plurality of time zones based on the excretion history information, and estimates the time zone in which the excretion frequency exceeds a predetermined value as the future excretion timing.

[0052] FIG. 7 is a graph showing the excretion frequency for each time zone of one day according to Modification 2. In FIG. 7, the excretion frequency per hour of one day is shown. Note that in FIG. 7, the graphing of the frequency after 12:00 is omitted. The time zone is not limited to one hour, and may be, for example, every 0.5 hours, every 2 hours, etc. In the case of the elderly, since the time during which excretion can be postponed after feeling the urge to urinate or defecate is about 30 minutes, it is preferable that the time zone be 30 minutes or less.

[0053] The control unit 270 obtains the excretion frequency for each time zone of one day based on the excretion history information for a predetermined period (for example, for one month, for one year, etc.). The control unit 270 estimates the time zone in which the excretion frequency exceeds a predetermined value as the future excretion timing.

[0054] When the control unit 270 approaches the time zone in which the excretion frequency exceeds a predetermined value, it controls the touch panel unit 210 and the sound output unit 220 to notify the time zone estimated as the future excretion timing. FIG. 8 shows an example of notification on the information notification device 200 held by the caregiver according to Modification 2. As shown in FIG. 8, on the touch panel unit 210, the time zone in which person A is likely to excrete is included in the message and displayed. Thereby, the caregiver can recognize the time zone in which the user is likely to excrete, and can prepare for the user's next excretion. Note that the above-described graph may be displayed on the touch panel unit 210 to show the time zone with a high possibility of becoming the future excretion timing. Further, when the time zone in which the frequency is equal to or higher than the predetermined value approaches, notifications such as "The possibility of excretion is gradually increasing" and "There is a high possibility of excretion from 9:00 to 9:30" may be made, or the user may be able to check the estimation result (graph) when the user wants to see it without making a notification. At this time, a table showing the cumulative probability may be created in increments of a certain fraction (1 minute, 5 minutes), etc., and that may be notified.

[0055] Furthermore, the control unit 270 may estimate the excretion probability of the user at a predetermined time. In this case, the touch panel unit 210 notifies the excretion probability at the predetermined time. For example, based on the above table, the cumulative probability during the interval (difference) between the previous excretion time and the current time can be estimated and notified as the excretion probability at the current time. For example, when the interval between the previous excretion time and the current time is 5 minutes, if the excretion cumulative probability is 1% when the interval in the above table is from 0 minutes to 10 minutes, it is notified that "the current excretion possibility is 1%". As time passes, when the interval between the previous excretion time and the current time becomes 15 minutes, if the cumulative excretion probability is 5% when the interval in the above table is 11 minutes or more and less than 20 minutes, it is notified that "the current excretion possibility is 5%".

[0056] Here, the user may sometimes want to make a plan for the business in the near future. To cope with this, the control unit 270 may cause the touch panel unit 210 to notify the excretion probability at a future time such as 30 minutes after the current time. In that case, simply refer to the table based on the value obtained by adding 30 minutes to the interval between the previous excretion time and the current time, calculate the cumulative excretion probability, and notify that "the excretion probability after 30 minutes is 48%". Note that the user may be able to input the number of minutes indicating the possibility.

[0057] (Modification Example 3) In Modification Example 3, the control unit 270 estimates the excretion probability for each excretion interval of excretion based on the excretion history information and estimates the cumulative excretion probability, thereby estimating the excretion interval at which the cumulative excretion probability exceeds the threshold value as the future excretion timing.

[0058] FIG. 9 is a graph showing the excretion probability for each excretion interval according to Modification Example 3. In FIG. 9, the broken line indicates the excretion probability, and the solid line indicates the cumulative excretion probability. The control unit 270 obtains the excretion probability for each excretion interval and its cumulative excretion probability based on the excretion history information for a predetermined period (for example, for one month, for one year, etc.). Here, (excretion probability for excretion interval) = (excretion frequency for excretion interval) / (total excretion frequency for excretion interval).

[0059] The control unit 270 estimates the excretion interval at which the cumulative excretion probability exceeds the threshold as the future excretion timing. Specifically, the control unit 270 estimates the time point obtained by adding the excretion interval to the most recent past excretion timing as the future excretion timing.

[0060] When the future excretion timing approaches, the control unit 270 controls the touch panel unit 210 and the sound output unit 220 to notify the future excretion timing. At this time, the cumulative excretion probability may also be included in the notification. Note that the control unit 270 may use, as the future excretion timing, the excretion interval at which the cumulative excretion probability exceeds a second threshold larger than the threshold. In this case, a margin is created until the future excretion timing, so the caregiver can perform another task during that time.

[0061] (Modification Example 4) In Modification Example 4, the control unit 270 estimates the future excretion timing including the user's diet information. The user's diet information is information regarding food and drink (beverages and foodstuffs) acquired by the user. The diet information includes the time when the user ate or drank, the type of food and drink, the amount of water, the calorie amount, and the like. The diet information is input by the user or the caregiver operating the touch panel unit 210 of the information notification device 200. That is, the touch panel unit 210 is an example of a diet information acquisition unit that acquires the user's diet information.

[0062] The control unit 270 estimates the amount of water intake by the user based on the acquired food and drink information. For example, assume the user had a meal at 12:00 and drank water at 13:00. Generally, it is known that when awake, 1 ml of water is processed per kilogram of body weight per hour. For a 70 kg user, 70 ml of water can be processed per hour when awake (processing capacity). On the other hand, if the calorie content of the food is 750 kcal, at an average conversion value, the amount of water per kcal is 0.4 ml, so the amount of water is 750 × 0.4 = 300 ml. By dividing the obtained amount of water by the processing capacity, the processing time for processing the amount of water can be obtained (300 / 70 ≈ 4.3 hours). When 100 ml of water is drunk at 13:00, the processing time is 100 / 70 ≈ 1.4 hours. From these, the estimated urine volume that can be expected when awake can be estimated.

[0063] Note that urine production is suppressed during sleep. Therefore, a coefficient (for example, 0.5) is integrated with respect to the processing capacity per hour when awake. For example, when the control unit 270 detects the user's sleep based on the video from the camera in the bedroom, the processing capacity per hour during the sleep time zone is set to 35 ml (= 70 × 0.5), and the processing time is calculated.

[0064] Based on these, the control unit 270 estimates the change in urine volume, and estimates the time point when the urine volume is estimated to exceed the threshold as the next excretion timing. FIG. 10 is a graph showing the change in urine volume according to Modification 4. In FIG. 10, 90% of the user's past urine volume is set as the threshold. In FIG. 10, 11:00 is estimated and notified as the next excretion timing. By displaying the graph shown in FIG. 10 on the touch panel unit 210, the next excretion timing may be notified. Here, urine is exemplified, but the same applies to feces. The past urine volume and the threshold can be adjusted.

[0065] Furthermore, the type of food and drink may be reflected in the estimation of the next excretion timing. For example, coffee, tea, and alcohol have a diuretic effect, so excretion is promoted. In the case of food and drink with a diuretic effect, the next excretion timing may be estimated to be earlier.

[0066] In the case of food, in addition to inputting based on calories, the control unit 270 may convert it into calories based on the input content by inputting weight or a menu.

[0067] (Modification Example 5) In Modification Example 5, a processing example after notification of future excretion timing will be described. FIG. 11 is a flowchart showing the flow of processing according to Modification Example 5. As shown in FIG. 11, steps S101 to S103 are the same as those in the above-described embodiment.

[0068] In step S104, the control unit 270 determines whether or not the excretion detection unit 120 has detected the user's excretion near the excretion timing. The vicinity of the excretion timing is a period of several minutes to several tens of minutes before and after the excretion timing as a reference. If excretion is detected near the excretion timing, the control unit 270 proceeds to step S105, and if excretion is not detected near the excretion timing, the control unit 270 proceeds to step S106.

[0069] In step S105, the control unit 270 determines to maintain the same estimation method in the subsequent estimation of the excretion timing.

[0070] In step S106, the control unit 270 determines whether or not excretion has been detected earlier than near the excretion timing. If excretion has been detected earlier, the control unit 270 proceeds to step S107, and if excretion has been detected later than near the excretion timing, the control unit 270 proceeds to step S108.

[0071] In step S107, the control unit 270 determines to adopt a coefficient by which the estimation result becomes shorter than before.

[0072] In step S108, the control unit 270 determines to adopt a coefficient by which the estimation result becomes longer than before.

[0073] This makes it possible to perform an estimation suitable for the user's situation. In the case where excretion that cannot be detected by the excretion detection unit 120 (for example, incontinence, etc.) occurs, a caregiver may operate the information notification device 200 to input excretion history information regarding the excretion.

[0074] (Modification Example 6) In Modification Example 6, other estimation methods will be described regarding the estimation of future excretion timing.

[0075] For example, the control unit 270 of the information notification device 200 may estimate future excretion timing using a learning model obtained by machine learning with excretion history information. For example, using the past excretion timing of the user as the target variable and the excretion history information up to the previous excretion timing as the explanatory variable, a machine learning model is created using a method such as Partial Least Squares Regression (PLS). Or, if you want to predict, for example, "whether there is excretion within 30 minutes from now" or "whether there is excretion between 30 minutes and 60 minutes from now" instead of the excretion timing, use that as the target variable and the excretion history information up to now as the explanatory variable to create an opportunity learning model. Although the number of data is necessary, it is also possible to create a machine learning model using a plurality of variables that are difficult for humans, and in this case, the estimation accuracy will be higher. Clustering may be performed based on the data and states of multiple people, and a model for each cluster may be created individually.

[0076] The control unit 270 may estimate future excretion timing including the properties of the excrement. By creating a machine learning model including the properties of the excrement, it is possible to estimate future excretion timing considering the properties of the excrement.

[0077] The control unit 270 may estimate future excretion timing including the user's attribute information in addition to the excretion history information. By creating a machine learning model including the user's attribute information, it is possible to estimate future excretion timing considering the attribute information.

[0078] In addition to the excretion history information, the control unit 270 may estimate the future excretion timing including the medication information of the user. By creating a machine learning model including the medication information of the user, the future excretion timing considering the medication information can be estimated.

[0079] In addition to the excretion history information, the control unit 270 may estimate the future excretion timing including the lifestyle information of the user. By creating a machine learning model including the lifestyle information of the user, the future excretion timing considering the lifestyle information can be estimated.

[0080] Furthermore, the information notification device 200 may acquire the environmental information of the environment where the toilet 1 is installed. In this case, the information notification device 200 is an example of an environmental information acquisition unit. The environmental information includes temperature, humidity, atmospheric pressure, and the like. In addition to the excretion history information, the control unit 270 may estimate the future excretion timing including the environmental information. By creating a machine learning model including the environmental information, the future excretion timing considering the environmental information can be estimated.

[0081] The control unit 270 may estimate the current state of the user based on various information. For example, the control unit 270 estimates the posture, behavior, exercise intensity, and presence or absence of sleep of the user from the information acquired from the sensors of the wearable terminal device. In this way, the control unit 270 is an example of a state estimation unit. In addition to the excretion history information, the control unit 270 may also estimate the future excretion timing including the currently estimated state of the user. By creating a machine learning model including the current state of the user, the future excretion timing considering the current state of the user can be estimated.

[0082] These estimation methods can be used alone or in combination. In any case, it is possible to improve the accuracy of the estimation. Also, in this modified example, the estimation using a machine learning model is illustrated, but even without using machine learning, the future excretion timing may be estimated using each piece of information illustrated in this modified example. Further, after notifying the estimated excretion timing and the user has confirmed the notified content, if there is a change in the value used for estimating the excretion timing, it may be notified that there has been a change in the value used for the estimation. For example, after a caregiver has confirmed the excretion timing of all care recipients for a day on terminal A in the caregiver's room, if there has been a significant change in the drinking water or napping of a care recipient, resulting in a change in the estimated excretion timing, the caregiver's mobile terminal B may be separately notified of which care recipient has had what kind of change. By notifying only the changed content, it becomes easier for the caregiver to notice the change, and the trouble of re-checking all care recipients can be saved.

[0083] (Modified Example 7) In Modified Example 7, the case where the excretion timings of multiple users are notified by one information notification device 200 will be described. FIG. 12 is a display example on the touch panel unit 210 according to Modified Example 7. As shown in FIG. 12, on the touch panel unit 210, the next excretion timings of multiple users (Mr. A, Mr. B, Mr. C) are displayed in a list. Specifically, the next excretion timing of Mr. A is 12:00, the next excretion timing of Mr. B is 6:00, and the next excretion timing of Mr. C is 11:00. The time zone until the excretion timing is displayed in a gradually darkening gradation. The length of the gradation part is set according to the characteristics of that user. For example, for a person who can endure the urge to urinate / defecate, the gradation part is set long, and for a person who has difficulty enduring the urge to urinate / defecate, the gradation part is set short. Near the name of each user, the ratio of the excretion timing to the current time is displayed. Thereby, the current degree of endurance of each user can be grasped.

[0084] Since the excretion timings of multiple users are displayed in a list, the caregiver can grasp the excretion timings of multiple users collectively and schedule their own work during time periods considering each excretion timing.

[0085] FIG. 13 is a display example on the touch panel unit 210 according to Modification 7. In FIG. 13, the caregiver's schedule is registered. While checking the pre-determined tasks (exercise assistance, meal assistance, clothing change), the caregiver registers excretion assistance (indicated by a dashed line in the figure) in the schedule for a time period that does not overlap with these and is close to the excretion timing. The time period for excretion assistance can be adjusted according to the situation of the user or the caregiver. If there is no time period available for registering excretion assistance due to other schedules, a support notification to other caregivers may be sent to the information notification device 200 of the other caregivers. The information notification device 200 of the caregiver may give a notification indicating that it is the start time before the time period of each task. The information notification device 200 of the caregiver may give a notification indicating that no excretion was detected during the time period of excretion assistance. Check boxes for completion of each task may be displayed on the touch panel unit 210.

[0086] (Modification 8) In Modification 8, the case where multiple users are clustered will be described. It is also possible to register in the database by associating the excretion history information of multiple users with physical information (height, weight, age, gender), lifestyle information, and dietary information. The excretion history information, physical information, lifestyle information, and dietary information are used to group multiple users using a well-known clustering method such as the k-means method. As a result, when estimating the future excretion timing, it is also possible to estimate using the basic model of the group to which the user belongs. The basic model may be the average pattern of multiple users included in the group or other common patterns. In this case, even for a user with few logs, the next excretion timing can be accurately estimated.

[0087] Furthermore, a transition model between each group may be created, and the user's time pattern may be estimated based on the transition model. FIG. 14 is an image diagram of the estimation using the transition model according to Modification 8. First, clustering is performed based on the excretion history information, physical information, life information, and diet information of a plurality of other users. Thereby, a model for each pattern of the excretion history information is created. From the transition data of the model, a transition model M21 is created. In the transition model M21, the probability of transitioning from pattern A to pattern B is 70%, and the probability of transitioning to other patterns is 30%.

[0088] Next, based on the excretion history information, physical information, life information, and diet information of the user, the group to which the user belongs is selected, and the transition model M21 is applied. As described above, in the transition model M21, since the probability of transitioning from pattern A to pattern B is high, when the user is in pattern A, it is estimated that the user will transition to pattern B.

[0089] [Others] Although the embodiments have been described above, the present disclosure is not limited to the above embodiments. In addition, forms obtained by applying various modifications that those skilled in the art can conceive to each embodiment, or forms realized by arbitrarily combining the components and functions in each embodiment without departing from the gist of the present disclosure are also included in the present disclosure.

[0090] [Appendix] Through the description of the above embodiments and the like, the following technologies are disclosed.

[0091] (Technology 1) A history information acquisition unit that acquires excretion history information including at least the excretion timing of the user, An excretion timing estimation unit that estimates the future excretion timing of the user based on the excretion history information, And a notification unit that notifies the future excretion timing. An excretion management system.

[0092] (Technology 2) The excretion timing estimation unit obtains the excretion frequency for each of a plurality of time zones based on the excretion history information, and estimates the time zone in which the excretion frequency exceeds a predetermined value as the future excretion timing. The excretion management system according to Technique 1.

[0093] (Technique 3) The notification unit notifies the time zone estimated as the future excretion timing. The excretion management system according to Technique 2.

[0094] (Technique 4) The excretion timing estimation unit estimates the excretion probability for each excretion interval based on the excretion history information, and estimates the cumulative excretion probability, and estimates the excretion interval at which the cumulative excretion probability exceeds a threshold value as the future excretion timing. The excretion management system according to Technique 1.

[0095] (Technique 5) The notification unit notifies the cumulative excretion probability for each excretion interval. The excretion management system according to Technique 4.

[0096] (Technique 6) The excretion timing estimation unit estimates the excretion probability of the user at a predetermined time point. The notification unit notifies the excretion probability of the user at the predetermined time point. The excretion management system according to any one of Techniques 1 to 5.

[0097] (Technique 7) The excretion timing estimation unit performs estimation using a learning model obtained by machine learning using the excretion history information. The excretion management system according to Technique 1.

[0098] (Technique 8) The excretion history information includes the properties of the user's excrement. The excretion management system according to any one of Techniques 1 to 7.

[0099] (Technology 9) It includes a diet information acquisition unit that acquires the diet information of the user, The excretion timing estimation unit estimates the future excretion timing, including the diet information. The excretion management system according to any one of Technologies 1 to 8.

[0100] (Technology 10) It includes a sleep information acquisition unit that acquires the sleep information of the user, The excretion timing estimation unit estimates the future excretion timing, including the sleep information. The excretion management system according to any one of Technologies 1 to 9.

[0101] (Technology 11) It includes a medication information acquisition unit that acquires the medication information of the user, The excretion timing estimation unit estimates the future excretion timing, including the medication information. The excretion management system according to any one of Technologies 1 to 10.

[0102] (Technology 12) It includes an environmental information acquisition unit that acquires the environmental information of the environment where the toilet is installed, The excretion timing estimation unit estimates the future excretion timing, including the environmental information. The excretion management system according to any one of Technologies 1 to 11.

[0103] (Technology 13) It includes an attribute information acquisition unit that acquires the attribute information of the user, The excretion timing estimation unit estimates the future excretion timing, including the attribute information. The excretion management system according to any one of Technologies 1 to 12.

[0104] (Technology 14) It includes a life information acquisition unit that acquires the life information related to the life behavior of the user, The excretion timing estimation unit estimates the future excretion timing, including the living information. The excretion management system according to any one of Technologies 1 to 13.

[0105] (Technology 15) It includes a state estimation unit that estimates the current state of the user. The excretion timing estimation unit estimates the future excretion timing, including the current state of the user. The excretion management system according to any one of Technologies 1 to 14.

[0106] (Technology 16) The history information acquisition unit detects the excretion of the user and acquires the excretion timing of the excretion. The excretion management system according to any one of Technologies 1 to 15.

Industrial Applicability

[0107] The present disclosure is applicable to an excretion management system that can manage the excretion information of a user.

Explanation of Signs

[0108] 1 Toilet 2 Toilet seat 10 Excretion management system 100, 100A Acquisition device 110, 110a Usage detection unit 120, 120a Excretion detection unit 121 Lighting unit 122 Camera 130, 130a Control unit 131 Communication unit 132 Storage unit 133 Control unit 140a Control panel 200 Information notification device 210 Touch panel unit 220 Sound output unit 230 Sound input unit 240 Storage unit 250 Imaging unit 260 Communication Unit 270 Control Unit 300 Server Device

Claims

1. A history information acquisition unit that acquires excretion history information including at least the excretion timing of the user; An excretion timing estimation unit that estimates the future excretion timing of the user based on the excretion history information; An excretion management system comprising a notification unit that notifies the future excretion timing.

2. The excretion timing estimation unit obtains the excretion frequency for each of a plurality of time zones based on the excretion history information, and estimates the time zone in which the excretion frequency exceeds a predetermined value as the future excretion timing. The excretion management system according to Claim 1.

3. The notification unit notifies the time zone estimated as the future excretion timing. The excretion management system according to Claim 2.

4. The excretion timing estimation unit estimates the excretion probability for each excretion interval based on the excretion history information, and estimates the cumulative excretion probability. Then, the excretion interval at which the cumulative excretion probability exceeds a threshold value is estimated as the future excretion timing. The excretion management system according to Claim 1.

5. The notification unit notifies the cumulative excretion probability for each excretion interval. The excretion management system according to Claim 4.

6. The excretion timing estimation unit estimates the excretion probability of the user at a predetermined time point. The notification unit notifies the excretion probability of the user at the predetermined time point. The excretion management system according to Claim 1.

7. The excretion timing estimation unit performs estimation using a learning model obtained by machine learning using the excretion history information. The excretion management system according to Claim 1.

8. The excretion history information includes the properties of the user's excrement. The excretion management system according to any one of Claims 1 to 7.

9. Comprising a diet information acquisition unit that acquires the diet information of the user; The excretion timing estimation unit estimates the future excretion timing including the diet information. The excretion management system according to any one of Claims 1 to 7.

10. Comprising a sleep information acquisition unit that acquires the sleep information of the user; The excretion timing estimation unit estimates the future excretion timing including the sleep information. The excretion management system according to any one of Claims 1 to 7.

11. Comprising a medication information acquisition unit that acquires the medication information of the user; The excretion timing estimation unit estimates the future excretion timing including the medication information. The excretion management system according to any one of Claims 1 to 7.

12. ​ It includes an environmental information acquisition unit that acquires environmental information of the environment where the toilet is installed. The excretion timing estimation unit estimates the future excretion timing including the environmental information. The excretion management system according to any one of claims 1 to 7.

13. It includes an attribute information acquisition unit that acquires the attribute information of the user. The excretion timing estimation unit estimates the future excretion timing including the attribute information. The excretion management system according to any one of claims 1 to 7.

14. It includes a living information acquisition unit that acquires living information related to the user's daily activities. The excretion timing estimation unit estimates the future excretion timing including the living information. The excretion management system according to any one of claims 1 to 7.

15. It includes a state estimation unit that estimates the current state of the user. The excretion timing estimation unit estimates the future excretion timing including the current state of the user. The excretion management system according to any one of claims 1 to 7.

16. The history information acquisition unit detects the user's excretion and acquires the excretion timing of the excretion. The excretion management system according to any one of claims 1 to 7.

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