User detection and identification in a bathroom environment

Abstract

A system and method are provided for detecting or identifying the user of a bathroom device. [Solution] The system comprises at least one sensor coupled to a bathroom usage analysis device, the sensor generating data that can be used to detect and / or identify a user. A method for detecting a bathroom user is also provided. The method includes the step of detecting and / or identifying a user by analyzing the data generated by the sensor in the system described above.

Description

Technical Field

[0001] Broadly speaking, the present application relates to a method for detecting and identifying an individual. More specifically, a method and system for detecting and identifying a user of a bathroom are provided.

Background Art

[0002] WO 2018 / 187790 discloses a biological measurement monitoring device, method and system related to biological monitoring in a bathroom environment. As disclosed herein, it is beneficial or essential to detect or identify a user when the device and system are used.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] This specification provides a system and method for detecting or identifying a user of a bathroom device.

Means for Solving the Problems

[0005] A system for detecting a user of a bathroom is provided. The system includes at least one sensor coupled to a bathroom usage analysis device, and the sensor generates data that can be used to detect and / or identify a user.

[0006] Also provided is a method for detecting a user of a bathroom. The method includes analyzing data generated by a sensor in the above system to detect and / or identify a user.

Brief Description of the Drawings

[0007] [Figure 1] This is a perspective view of a toilet equipped with a waste analysis device having a user detection component. [Figure 2] This is an exploded view of the user detection component. [Figure 3] This is a perspective view of a waste analysis device having a user detection component. [Figure 4] This is a perspective view of a toilet with the seat raised and the seat lowered, equipped with a waste analysis device that includes a user detection component. [Figure 5] This is a flowchart of a user identification system integrated with a waste analysis device. [Figure 6] This is a perspective view of a toilet connected to various components that are part of a user identification system. [Figure 7] This is a flowchart of the steps used by a user identification system to identify a user. [Figure 8A] This is a diagram of a toilet seat showing the sensor configuration. [Figure 8B] This is a diagram of a toilet seat showing the sensor configuration. [Figure 8C] This is a diagram of a toilet seat showing the sensor configuration. [Figure 8D] This is a diagram of a toilet seat showing the sensor configuration. [Figure 8E] This is a diagram of a toilet seat showing the sensor configuration. [Figure 8F] This is a diagram of a toilet seat showing the sensor configuration. [Figure 9A] This is an exploded view of the user detection components inside the toilet seat lid. [Figure 9B] A perspective view of a toilet seat lid equipped with a two-component user detection system. [Figure 9C] This is a cross-sectional view of a lid made of two parts, each with a user detection component on the inside. [Figure 9D] This is a perspective view of the user-detectable component of the single component of the top cover. [Figure 10A]This is a perspective view of an upward-facing user detection component that enables movement with two degrees of freedom. [Figure 10B] A perspective view of a single, fixed, upward-facing user detection component. [Figure 11] Three perspective views of the location for the fingerprint reader or other sensor / user input. [Modes for carrying out the invention]

[0008] International Publication No. 2018 / 187790 provides devices, methods, and systems for analyzing the excrement of a bathroom user and for performing other tasks in the bathroom, such as weighing a user, administering medication to a user, and measuring a user's body temperature. The detection and / or identification of a user by these devices requires associating the user with information taken about the user for purposes such as drug suitability, drug dosage / prescription, compliance (e.g., drug testing by court order), billing, and obtaining baselines and abnormal results for that user. The present invention addresses such needs.

[0009] Provided herein is a system for detecting users in a bathroom. The system comprises at least one sensor coupled to a bathroom usage analysis device. In these embodiments, the sensor generates data that can be used to detect and / or identify users.

[0010] As used herein, a bathroom usage analysis device (hereinafter referred to as "BUAD") is a device that measures parameters of the use of bathroom fixtures such as sinks, mirrors, tubs, bidets, showers, medicine cabinets, or toilets. For example, BUAD can capture an image of a face from a mirror (see, e.g., Page 10, Figures 9A - 9D of WO 2018 / 187790), track the progress of a medicine cabinet, and / or dispense medicine from a medicine cabinet (see, e.g., Page 10, Figures 9A - 9D of WO 2018 / 187790), or measure and analyze the characteristics of excrement in a toilet (a "fecal analysis device") as in a plurality of embodiments described in, e.g., WO 2018 / 187790.

[0011] In some embodiments, the system detects the presence of a user but does not identify the user. Such embodiments can be used when the measurements made by the BUAD at that time are not compared to measurements from other times.

[0012] In other embodiments, the system can detect and identify users, distinguish between users, and create a user profile for each user. Such a system enables the evaluation of the usage of BUAD by users over time and provides diagnostic information when the BUAD obtains abnormal readings.

[0013] The sensors in such a system can be any currently known or later developed sensors that determine the presence of a user or measure characteristics that vary among individuals. Non - limiting examples include explicit identifiers, image sensors, time - of - flight cameras, load cells, capacitive sensors, microphones, image sensors, ultrasonic sensors, passive infrared sensors, thermopiles, temperature sensors, motion sensors, photoelectric sensors, structured light systems, fingerprint scanners, retinal scanners, iris analyzers, smartphones, wearable identifiers, scales integrated into bathroom mats, height sensors, skin color sensors, bioelectrical impedance circuits, electrocardiograms, or thermometers.

[0014] The system may include multiple sensors, or any combination of sensors housed together or separately connected to the system.

[0015] In various embodiments, the system may store a set of identifiers associated with a user. Non-restrictive examples of identifiers that can be used to identify a user include explicit identifiers, voice identifiers, image identifiers, structured light 3D scan identifiers (e.g., measurement of the three-dimensional shape of a face using a projection light pattern and camera system), fingerprint identifiers, retinal identifiers, and smartphone / wearable identifiers, which are further described below.

[0016] explicit identifier In some embodiments, the system can store a set of explicit identifiers associated with a user profile. These explicit identifiers are identification inputs received directly by the BUAD or through a pre-installed application running on the user device. For example, the system can assign a specific button or touchscreen input on the BUAD to a specific user and store this assignment in association with the user profile corresponding to that user. In one implementation example, the BUAD can display input areas via a touchscreen corresponding to each user profile associated with the bathroom usage analysis device. Alternatively, the BUAD could include a set of physical buttons, each of which could be assigned to a user profile. Thus, before using any fixtures in the bathroom, the user can verify their identity to the BUAD by interacting with the BUAD or a pre-installed application running on their user device.

[0017] Voice identifier In other embodiments, the system may store a set of voice identifiers associated with a user profile. These voice identifiers are audio clips of the user's voice speaking a specific word or phrase. In some such embodiments, during the onboarding process, the system may prompt the user to pronounce their name or another identifying phrase and record multiple audio clips of the user pronouncing their name. If the system then detects the presence of an unknown user, it may prompt the user to clearly state their name. The system can then record the response to the voice identification prompt and compare this response to a set of voice identifiers stored in association with the user profile. The system can then use the voice identifiers and / or authentication techniques to match the response against the set of voice identifiers associated with the user profile.

[0018] In various embodiments, the system may prompt the user to repeat an identification phrase to increase the likelihood of confidently identifying the user by increasing the number of voice identifiers associated with the user profile.

[0019] Image identifier In an additional embodiment, the system may store a set of image identifiers associated with a user profile. The image identifiers are photographs of the user that the system can use for recognition purposes.

[0020] When used herein, systems that utilize image identifiers, for example, systems that use a camera to identify a user, are not strictly limited to face detection but include any type of image that can be used to identify a person or distinguish a known user from a guest, such as an image of the body relative to the length of the shoulders / neck, i.e., an image of the back of the user's head.

[0021] In certain embodiments of such systems, the sensor comprises an image sensor, a time-of-flight camera, a load cell, a temperature sensor, or any combination thereof. In some of these embodiments, the sensor is an image sensor, such as a time-of-flight camera.

[0022] As an example, the system performs the following tasks during the onboarding process, namely The system may prompt the user to look at the camera integrated into the BUAD (or the camera on the user's smartphone), record multiple images of the user's face, record an image of each user before using the BUAD, and perform facial recognition technology to identify the current user of the BUAD by comparing the current user's image with a visual identifier stored in association with the user profile, or all of the above. In a specific embodiment, the system may also import pre-existing images or a set of images from a user device, such as the user's smartphone.

[0023] The image sensors in these embodiments can be installed in any location where they can sense the user's desired image. Non-limiting examples include wall-mounted mirrors, portable mirrors, toilet paper rolls, sinks, mats in front of the toilet or sink, mounted on or integrated with the toilet seat or seat cover, or integrated into or mounted on the seat cover, in which case the image sensor can only image the user when the seat cover is lifted. See also Figures 1, 3 and 4, and various embodiments in International Publication No. 2018 / 187790.

[0024] In one implementation example, the system could prompt the user to change the angle of their face relative to the camera to record various facial images, increasing the likelihood of user identification before using BUAD.

[0025] In another implementation example, the system could prompt the user to approach the camera in a way that changes its angle and position relative to it, or to position their body, in order to record images of various faces, in order to increase the likelihood of identifying the user before using BUAD. In this implementation example, the system performs gate or pose analysis before using BUAD.

[0026] In another implementation example, the system could prompt the user to wash their hands in a sink to record images of various hands, increasing the likelihood of identifying the user before using BUAD.

[0027] In another implementation example, the system could include a set of lighting fixtures that the system can activate in response to detecting the presence of the current user of the excrement analysis device. At this time, thanks to stable lighting conditions, the system can record an image of the current user with a high probability of user identification.

[0028] Therefore, the system can perform any or all of the following: record a first image of the first user in association with the first user's user profile; then, while using BUAD, record a second image of the current user; and compare the second image with the first image to identify the current user as the first user.

[0029] Structured Light / 3D Scan Identifier In another embodiment, the system may store a set of structured light / 3D scan identifiers associated with a user profile. These structured light / 3D scan identifiers are 3D representations of the user's face or body shape suitable for identification purposes. For example, during the onboarding process, the system may prompt the user to look at a camera, structured light system, or 3D scanner and record a 3D scan of the user's face. The system can then perform a 3D dimensional scan of each user's face before the urination event and, to identify the current user of BUAD, perform facial recognition technology to compare the current user's 3D scan with the 3D scans stored in association with the user profile.

[0030] In another implementation example, the structured light / 3D scan identifier is a 3D representation of the user's ears and the back of their head, suitable for identification purposes.

[0031] Fingerprint identifier In some embodiments, the system can store a fingerprint identifier associated with a user profile. The fingerprint identifier is a representation of the unique, identifiable features (i.e., details) of the user's fingerprint. In such embodiments, an example of the onboarding process is to prompt the user to scan their fingerprint (in multiple different orientations) at a fingerprint scanner located on the BUAD (e.g., a toilet flush handle or button), recording the user's fingerprint each time the user changes the position of their fingers. The system can then, upon detecting the presence of the current user, prompt the current user to scan their fingers at the BUAD to identify the user. Alternatively, in an implementation of the BUAD that includes a fingerprint scanner on the toilet flush handle or button, the system can record defecation events and, by scanning the user's fingerprint when the user flushes the toilet, identify the user involved in the defecation event.

[0032] Iris / retinal identifier In additional embodiments, the system may store an iris or retinal identifier associated with a user profile. The iris or retinal identifier is an image or other representation of the user's retina or iris. One example of an onboarding process relating to such embodiments is prompting the user to position their eyes in a predetermined position for a retinal scan placed in a retinal scanner adjacent to the BUAD, and recording an infrared image of the user's retina. Additionally, or alternatively, the system may prompt the user to look at a camera integrated into the BUAD, recording a high-resolution visible-light image of the user's face and retrieving an image of the user's iris. The system may then, upon detecting the presence of the user, prompt the current user to scan their retina with the retinal scanner or to look at a camera integrated into the BUAD in order to record an image of the user's iris.

[0033] Smartphone / Wearable Identifier In some embodiments, the system can store a smartphone / wearable identifier in association with a user profile. The smartphone / wearable identifier is a universally unique identifier (hereinafter "UUID") relating to the wireless communication protocol ID associated with a device owned by the user. For example, during the onboarding process, the system prompts the user to synchronize their device with the excrement analysis device and record the device's ID for the wireless protocol. The user's UUID may be added to the system remotely as part of a group of users. The system can then detect the device's proximity to the excrement analysis device and, therefore, associate the recorded excrement events with a specific user based on the smartphone / wearable identifier. More specifically, the system can transmit a wireless beacon signal, and upon receiving the beacon, the user can respond with their UUID. The system can then identify the current user by matching the received UUID with an existing smartphone / wearable identifier stored in association with the user profile.

[0034] In various embodiments, for example, in the implementation of a system for use in care facilities (such as hospitals or long-term care facilities), the system may include a wearable device. In this case, the system can store a wearable identifier associated with a user profile for each patient, and when proximity of the wearable device is detected, the use of BUAD can be associated with the patient associated with the wearable device.

[0035] The sensors described above enable the system to record user characteristics measured by specific sensors used, which are further described below.

[0036] Total weight In some embodiments, the system can measure and record the user's total weight and store the user's total weight in association with a user profile. In one implementation example, the system includes a weighing scale integrated with a bathroom mat, as shown in Figure 7 on page 9 of International Publication No. 2018 / 187790, which may include a set of load cells capable of measuring the user's total weight. Thus, when the current user is preparing to use BUAD, the system can measure the user's weight when the user steps onto the bathroom mat. The system can then compare the current user's weight to a set of weights stored in association with a user profile to increase the likelihood of identifying the user. Thus, the system can record a first weight in association with the first user's user profile, and then, during or before using BUAD, record a second weight of the current user, and compare the second weight with the first weight to identify the current user as the first user.

[0037] Load cell distribution of toilet seat In various embodiments, the system can measure and record the load distribution of a user on a toilet seat in a bathroom and store the load cell distribution in association with a user profile. In one implementation example, the excrement analysis device includes a set of load cells integrated inside the toilet seat, as shown, for example, on page 4, Figure 2D of International Publication No. 2018 / 187790. In such embodiments, when a user sits on the excrement analysis device during an excretion event, the system can measure the force distribution across the entire range of this set of load cells. A particular user may apply a similar load distribution each time they sit on or stand up from the excrement analysis device, even when their overall weight changes. The load cell signals may be used to identify individuals by finding unique patterns based on changes between specific events resulting from the use of toilet paper. Therefore, the example system can perform any or all of the following: record a first load cell distribution in association with the user profile of a first user; record a second load cell distribution of the current user during subsequent BUAD use; and identify the current user of BUAD as the first user by comparing the second load cell distribution with the first load cell distribution.

[0038] height In additional embodiments, the system may measure and record the user's height and store the user's height in association with a user profile. In one implementation example, the system includes a height sensor (e.g., a visible light camera or an infrared camera) configured to detect the user's height when the user sits or stands close to the BUAD. Thus, the exemplary system may perform any or all of the following: record the user's first height in association with the first user's user profile; record the current user's second height during or before subsequent use of the BUAD; and compare the second height with the first height to identify the current user as the first user.

[0039] skin color In certain embodiments, the system may record the user's skin color in association with a user profile. In one implementation example, the system may include a skin color sensor (e.g., a low-resolution visible light camera and LEDs) configured to detect the user's skin color when it detects the user's skin in contact with the surface of the BUAD (e.g., the surface of the toilet seat of the excrement analysis device). Thus, in this example, the system may perform any or all of the following: record a first skin color in association with a user profile; record a second skin color of the current user of the BUAD during use; and identify the current user as the first user by comparing the first skin color with the second skin color.

[0040] Bioelectrical impedance In other embodiments, the system can record the user's bioelectrical impedance in association with a user profile. Electrodes for bioelectrical impedance can be arranged in any beneficial pattern on the toilet seat or lid. Figures 8A, 8B, 8C, 8D, 8E, and 8F show example patterns. The patterns shown therein may be on either the top or bottom of the toilet seat.

[0041] In one implementation example, the system may include a bioelectrical impedance circuit (e.g., integrated with the toilet seat of the excrement analysis device) configured to measure the user's bioelectrical impedance while the user is using the BUAD. The bioelectrical impedance electrodes may consist of various patterns, and multiple electrodes may be used to improve the measurement. Furthermore, repeated measurements may be performed over the use of the system to distinguish users. Thus, the system may perform one or all of the following: record a first bioelectrical impedance in association with the user profile of a first user, record a second bioelectrical impedance of the current user during subsequent use of the BUAD, and identify the current user as the first user by comparing the second bioelectrical impedance with the first bioelectrical impedance.

[0042] Heart rate / ECG In additional embodiments, the system may record heart rate, heart rate variability, or any other detectable features of the user's heartbeat via an electrocardiogram (using electrodes installed in the BUAD, such as on the toilet seat of a waste analysis device). The heart rate / ECG electrodes may be configured in various patterns, and multiple electrodes may be used to improve the measurement. Repeated measurements may also be performed over the use of the system to further distinguish users. Thus, the system may perform any or all of the following: record a first heart rate in association with the user profile of a first user, record a second heart rate of the current user during subsequent use of the BUAD, and identify the current user as the first user by comparing the second heart rate with the first heart rate. In one implementation example, the system can record a first electrocardiogram pattern associated with a first user (e.g., including the average duration of the user's P wave, PR segment, QRS complex, ST segment, T wave, and U wave, or the average allocation from the PR interval to the QT interval), record a second electrocardiogram pattern during subsequent use of BUAD, and compare the second electrocardiogram pattern with the first electrocardiogram pattern.

[0043] Pulse oximetry In additional embodiments, the system can record heart rate, heart rate variability, or any other detectable features of the user's heartbeat via a pulse oximeter. Several different optical techniques can be used, for example, by stimulating the skin with two or more wavelengths of light and analyzing the received signal using a detector. Similarly, it is possible to create a pulse oximetry system within the system by using a broadband light source and selective filters on the detector. By using a combination of optical and acoustic methods known as photoacoustic or acousto-optical imaging techniques, costs, power, and / or processing requirements can be reduced. Different users of the system can be identified by employing repeated measurements and / or by using multiple measurements during a particular event. The system may consist of one or more sensor configurations as shown in Figures 8A, 8B, 8C, 8D, 8E, and 8F. Therefore, the system can perform any or all of the following: record the first blood oxygen of the first user in association with the first user's user profile; record the second blood oxygen of the current user during subsequent BUAD use; and identify the current user as the first user by comparing the second blood oxygen with the first blood oxygen.

[0044] Acoustic sensor In additional embodiments, the system may include acoustic, sound wave, or ultrasonic sensors that can be used to identify a person. In one embodiment, the system may include a 1, 1.5, or 2-dimensional ultrasound imaging system to image the user's thigh and generate a 2 or 3-dimensional image / volume for identification. The user's ultrasound image can be uniquely identified using a variety of methods, but not limited to, tissue composition analysis (fat, muscle, and bone), Doppler or flow-based analysis, machine learning, or neural networks. Thus, the system may perform any or all of the following: record a first ultrasound image / volume of a first user in association with a user profile of a first user; record a second ultrasound image / volume of the current user during subsequent BUAD use; and identify the current user as the first user by comparing the second ultrasound image / volume with the first ultrasound image / volume.

[0045] In additional embodiments, the system may include a single ultrasonic transducer that can be used for activation or identification. In one implementation, the system may include a single ultrasonic sensor configured to measure the profile and / or thickness of a user's leg when it detects contact between the user's skin and the surface of the BUAD (e.g., the surface of the toilet seat of the excrement analysis device). The profile can be compared to a stored user for identification. The unit may be activated by using the change in the electrical response of the ultrasonic transducer upon contact with the human body. In another implementation, a skin profile may be recorded instead of the entire leg by using a higher frequency ultrasonic transducer. In yet another embodiment, the system may record the sound of the user's breathing by including an acoustic sensor within the audible frequency range. From this recording, several indirect identifying pieces of information can be recorded, such as respiratory rate, intensity / volume, and / or sound quality.

[0046] temperature In various embodiments, the system can record the user's body temperature via a temperature sensor in the BUAD (e.g., the toilet seat of the excrement analysis device) or via an infrared temperature sensor. Thus, the system can perform any or all of the following: record a first body temperature of a first user in association with the first user's user profile; record a second body temperature of the current user during subsequent use of the BUAD; and identify the current user as the first user by comparing the second body temperature with the first body temperature.

[0047] Capacity sensor In various embodiments, the system can measure changes in a capacitive sensor as a method of activity and / or identification. In one implementation using a capacitive sensor covering the entire toilet seat, the change in the electrical signal from the capacitor is proportional to the area of ​​the body in contact with the toilet seat. Thus, the sensor can be used to distinguish between users with different contact areas on the toilet seat, for example, children and adults. In another implementation, the capacitive sensor may be designed to sense changes in body composition and / or weight. Thus, the system can perform one or all of the following: record a first capacitance change in association with the user profile of a first user, record a second capacitance change of the current user during subsequent BUAD use, and identify the current user as the first user by comparing the second capacitance change with the first capacitance change. In yet another implementation, the capacitive sensor can register a user at a specific threshold of presence and activate BUAD.

[0048] body composition In various embodiments, the system can estimate the user's body composition via a body composition sensor in the BUAD (e.g., the toilet seat of the excrement analysis device), or via a scale or connected floor sensor. Thus, the system can perform any or all of the following: record a first body composition estimate in association with the user profile of a first user, record a second body composition estimate of the current user during subsequent use of the BUAD, and identify the current user as the first user by comparing the second body composition estimate with the first body composition estimate.

[0049] Examples of user detection and / or identification systems associated with excrement analysis devices are provided in Figures 1 to 4.

[0050] Figure 1 shows one embodiment of a waste analysis device 10, which includes an example of a user detection component 100 installed on an exemplary toilet 20.

[0051] Details of the illustrated user detection components are shown in Figure 2. The housing 102 houses the lens cover 104, which may have a coating that hardens the material and provides anti-reflective properties that allow infrared light to pass through, and is hydrophilic, hydrophobic, and / or fouling resistant. An indirect time-of-flight camera module 108 with a sensing element 106a is shown, but any of the other sensors described above may be used. In this embodiment, the housing 102 is held together by screws 110.

[0052] Figure 3 shows the arrangement of an exemplary embodiment of a user detection component 100 on an exemplary biomonitoring device 10 shown in Figure 2 of International Publication No. 2018 / 187790. Depending on the position of the user detection component 100 in the illustrated embodiment, together with the support arm, it is possible to detect the presence of a user while a separate toilet seat, often known as a commode chair, is in use, which may be height-adjustable.

[0053] Figure 4 shows an alternative positioning of the sensor 106b of a user detection component that, when used in conjunction with a raised toilet seat 32 and / or support arm, can assist the user in sitting down and standing up from the toilet. In the device disclosed in Figure 2 of International Publication No. 2018 / 187790, the toilet seat 34 can be used when a commode chair or other device to assist the user in sitting down and standing up from the toilet is not required. When the user is standing to urinate, the toilet seat cover 32 is in the up position, and the position of the distance-determining sensor 106 is positioned directly above the toilet seat level so that the range of the sensor is not affected by the toilet cover when the toilet seat is in the up position. The distance-determining sensor can detect when the toilet cover 30 is in the down position.

[0054] Sensor position The sensors in the systems described herein can be positioned anywhere in the bathroom, for example, near the BUAD. Examples of sensor positions, as shown in Figure 6, include on the wall-mounted mirror 106d, on the toilet paper roll 106e, on the sink 106f, on the mat 106g in front of the toilet, on 106h which is separately mounted on the wall, and on or integrated with the toilet seat or seat cover on the toilet 460 (see also Figure 10).

[0055] When housed in a toilet seat or lid (cover), the sensor can adopt a variety of electrode configurations for capacitive, bioelectrical impedance, and / or electrocardiogram measurements, as shown in Figure 8. Figure 8A shows a single sensor located on the top of the toilet seat, represented by a rectangle. Figure 8B shows four sensors located on the top of the toilet seat. Figures 8C, 8D, 8E, and 8F show various configurations of multiple sensors located on the top of the toilet seat. The electrodes can be incorporated into the toilet seat or lid by any means, including, for example, chemical vapor deposition, sputtering, vapor deposition, inkjet printing, immersion coating, screen printing, ultrasonic welding, or laser welding of the module to the plastic, thus allowing the electrical connections to be securely wired to the control and sensing electronics. The electrodes can be guaranteed good signal quality by including a specific biocompatible coating, without any adverse effect on the user's response.

[0056] Figures 9A, 9B, 9C, and 9D show embodiments in which a sensor array 460 or sensor 460b is mounted on or within the lid / cover 430 so that bathroom parameters (e.g., visual images if at least one of the sensors is a camera) are measured when the lid is lifted to prepare the toilet and the excrement analysis device 410 mounted therein. In Figure 9A, the sensor array 460 is located on the edge 432 of the lid 430. In these embodiments, the sensor array consists of a recess 461, a time-of-flight camera module 462, a mounting base 463, a lens cover 464 and a rubber cover 465 on which a coating may be present, which hardens the material, provides anti-reflective properties that allow infrared light to pass through, is hydrophilic, hydrophobic, and / or has anti-fouling properties. At the hinge 440 of the lid, a hinge cap 442 and a cable 444 are present to allow secure wiring of electrical connections to control and sensing electronics. An alternative embodiment is shown in Figure 9B, in which two sensors 460b having either the same or different functionality are located near the top of the lid 430b. Figures 9C and 9D show an embodiment in which an internal cavity 470 of the lid 430c houses electronic equipment 480 and connects the sensors to an excrement analysis device 410 or a computing device.

[0057] In another implementation example, the system may include an upward-oriented optical or thermal imaging sensor to image the anal and genital areas, thereby capturing images that can be used to uniquely identify the user. Figures 10A and 10B illustrate an example of such a system, which has a sensor array on top of the lid, as in Figure 9A. In Figure 10A, the upward-facing system includes an image sensor 510, a rotating mirror 512, and a focusing lens 514, the sensor within which can be rotated to face upward when used. In an alternative embodiment shown in Figure 10B, the sensor 500 is stationary. In some embodiments, a series of mirrors and lenses are used to image upward from below the toilet seat.

[0058] In another embodiment, the sensor may be located on the BUAD. As one example, Figure 11 shows a toilet equipped with a waste analysis device 410, where a sensor, such as a fingerprint reader, is shown at three different positions 610a, 610b, and 610c on the waste analysis device 410a. Such a system may also include additional sensors, such as the sensor array 460 further described above and shown in Figure 10A.

[0059] User profile initialization In various embodiments, the system is configured for situations where the user is standing, sitting, or using a device that facilitates the use of an appliance associated with the BUAD, such as a toilet seat lifter or support arm.

[0060] In the embodiment of the system shown in Figure 5, the system can generate user profiles representing users of the system.210 More specifically, the system can generate user profiles that include the user's personal information in order to associate identifiers, characteristics, excretory events, and diagnostic information with a particular user. The system can generate user profiles via a built-in application running on a smartphone or another computing device of the user. Alternatively, the system can include a touchscreen or other input / output device to allow the user to input personal information to include in the user profile. The system can provide a secure application programming interface (API) to add user profiles. The system can generate user profiles that include name, age, gender, medical history, address (for example, for billing purposes), or any other information relating to the analysis of the user's BUAD (in this example, excretory analysis device) use. To collect personal information from the user, the system can prompt the user to input any of the personal information listed above in the BUAD or via a built-in application and store the personal information in association with a UUID in a database located in the BUAD, on a server, or on another computing device connected to the BUAD.

[0061] In some embodiments, the system may associate user profiles with specific BUADs in order to instruct each particular BUAD to identify the users of that particular BUAD.

[0062] Get the user identifier In the embodiment shown in Figure 5, the system can prompt a new and / or first user to specify a first set of user identifiers,220 and associate the new and / or first user identifiers with the user's new and / or first user profile.222 More specifically, the system can prompt a new and / or first user to provide identifiers that the system can use to identify the new and / or first user with high credibility. In one implementation example, the system can display a prompt to select from a predefined list of identifier options, such as through an interface on the BUAD or through a built-in application running on the user's mobile device. Upon receiving a user selection corresponding to a particular identifier option, the system can record the identifier by providing an interface or by performing a series of steps.

[0063] User characteristic detection As shown in Figure 5, the system can measure a first set of user characteristics of a new and / or first user,230 and associate the first set of user characteristics with the new and / or first user profile.232 More specifically, the system can measure a set of user characteristics via BUAD and / or other integrated sensors to characterize users independently of identifiers associated with them (e.g., via sensor fusion), thereby improving the system's ability to identify users. Thus, if the system cannot identify a user based on a set of identifiers associated with a user profile, the system can measure the characteristics of the current user and match the current set of user characteristics with a set of characteristics associated with the user profile in order to identify the user.

[0064] In one implementation example, during the onboarding process, the system can prompt the user to use the nearest restroom while recording a set of user characteristics corresponding to the user as they use the nearest restroom. Additionally, or alternatively, the system can instruct the user to locate themselves as if they were using the restroom in order to record a set of user characteristics of the user.

[0065] In one implementation example, the system can store one set of user characteristics for each use of BUAD and / or other integrated sensors. Across repeated measurements, the system can distinguish users from each other based on patterns or similarities in the recorded user characteristics.

[0066] Detection of existence As shown in Figure 5, after completing a new user profile for a new user during the first period, the system detects the presence of the current user of the system during the subsequent (second) period.240 In specific embodiments, the system includes any or all of the following sensors: a time-of-flight camera, a passive infrared sensor (hereinafter "PIR sensor"), a visible light camera, a capacitive sensor, a door switch, or any other sensor capable of detecting the presence of the current user. In response to the detection of the presence of the current user, the system may prompt the user to provide an identifier from their user profile via an indicator light, a touchscreen display, or an audible message. In one implementation example, the system activates a visual indicator that the presence of a user has been detected, indicating that the system is ready to record the use of the BUAD. In some embodiments, the system may detect the presence of a user standing in front of the excrement analysis device while preparing to urinate or a user sitting on the toilet seat of the excrement analysis device.

[0067] User identifier As shown in Figure 5, the system may perform any or all of the following in response to the detection of the presence of a current user: attempt to detect a first user identifier 250; measure a set of characteristics of the current user 260 in response to the failure to detect the first user identifier; and match the set of characteristics of the current user with the characteristics of the first set of users 270. More specifically, the system may implement identification logic to reliably identify the current user of BUAD, or to identify the current user as a guest user of BUAD.

[0068] In response to the detection of a user's presence, in some embodiments, the system may activate a camera (infrared or visual light) to record an image of the detected user's face or body, activate a digital microphone to record the detected user's voice, and / or activate a BLUETOOTH® or WIFI chip to detect the proximity of a known user device to the excrement analysis device. The system may also await explicit identifier input from the user via a button or touchscreen on the excrement analysis device. In one implementation example, the system continues to detect the identifier throughout the entire period in which the current user is detected in proximity to the BUAD.

[0069] In some embodiments, if the system detects an identifier such as a facial image, body image, voice recording, direct input, fingerprint, and / or wireless ID of a user device, the system can match the detected identifier with a set of identifiers associated with the user profile to identify the current user. Additionally, when a user begins using BUAD, the system can simultaneously begin measuring a set of current features of the user to identify the user if no identifier is detected, and add this to a set of data about the current user when the current user is identified. Furthermore, the system can record defecation events when the current user uses the nearby toilet in the form of images of the toilet contents, while the system continues to collect a set of features of the current user and attempt to detect the current user's identifier.

[0070] method As shown in Figure 5, the method 200 for associating the use of BUAD with a user includes any or all of the following steps: during a first period, a step 210 to generate a new and / or first user profile representing a new and / or first user; a step 220 to prompt the new and / or first user to specify a first set of user identifiers; a step 222 to associate the new and / or first identifiers with the new and / or first user profile; a step 230 to measure a first set of user characteristics of the new and / or first user; and a step 232 to associate the first set of user characteristics with the first user profile. During a second period following the first period, in response to the detection of the presence of a current user, 240 an attempt is made to detect a first user identifier, 250 and 260 one set of characteristics of the current user is measured. Method 200 further includes, during a second period and in response to matching one set of current user characteristics with the first set of user characteristics 270, the steps of recording the use of the BUAD, for example, a toilet defecation event in the vicinity of the excrement analysis device, in the BUAD, in BUAD 280, and associating the use of the BUAD with the user profile 290.

[0071] As noted above, in some embodiments, the bathroom use analysis device is a stool analysis device that analyzes excrement while a user is using the toilet. Any stool analysis devices that are not known or will be discovered later can be incorporated into the systems provided herein. See also the examples of various stool analysis devices (referred to there as biomonitoring devices) in International Publication No. 2018 / 187790. In various embodiments, the stool analysis device analyzes urine, feces, intestinal gases, or gases released from feces or urine. In additional embodiments, the stool analysis device comprises a stool analysis sensor that detects electromagnetic radiation or sample chemicals in the toilet bowl.

[0072] In some of these embodiments, the excrement analysis device comprises a urine container, for example, as described in U.S. Provisional Patent Application No. 62 / 959139 ("US62 / 959139"). As illustrated therein, the urine container may be disposable or reusable. In some embodiments, the excrement analysis device further comprises a replaceable visual urine analyzer, such as a dipstick, as described in U.S.62 / 959139.

[0073] In additional embodiments, the excrement analysis device comprises a washable fecal collector, as illustrated, for example, on page 9, Figures 6A-6C of International Publication No. 2018 / 187790.

[0074] In embodiments for identifying specific users, the system utilizes a computing device capable of analyzing data to determine user characteristics detected by sensors. Various computer systems and data transfer formats are discussed in International Publication No. 2018 / 187790.

[0075] In some embodiments, the computing device is dedicated solely to user detection and identification and is coupled to the sensor within the housing. In other embodiments, the computing device is not dedicated solely to user detection and identification and is not housed together with the sensor.

[0076] In additional embodiments, data from the sensor is transferred to a computing device via a wired or wireless communication protocol.

[0077] In various embodiments, the computing device can also analyze data from bathroom usage analysis devices, such as excrement analysis devices.

[0078] According to various variations of the system described above, the computing device is equipped with software that can detect and identify a first user using data from sensors, and similarly detect and identify different users. By repeating the protocol described above in a loop, any number of users can be identified as users of BUAD.

[0079] In one alternative implementation example, the system may include a waste analysis device, along with toilet hardware such as the toilet bowl, tank, and other plumbing hardware.

[0080] In another implementation example shown in Figure 9A, the system includes a group of sensors mounted on top of the toilet lid and electrically coupled to the excrement analysis device, so that the sensors can capture images of the user of the excrement analysis device.

[0081] In one implementation example, the system may also include a user interface mounted on a support rail adjacent to the excrement analysis device, a nearby toilet, a toilet paper holder, a towel rack, and / or the excrement analysis device, such as a touchscreen display, microphone, speaker, indicator light, and a set of buttons, to communicate with the user and receive input from the user.

[0082] In one implementation example, a connected toilet paper holder is used to house user activity and identification sensors. The toilet paper holder can be configured to house several sensors, including, but not limited to, image sensors (visible and / or infrared), time-of-flight cameras, LEDs or other light sources, fingerprint readers, LCD touchscreens, and / or temperature sensors. In one implementation example, an inertial measuring unit (IMU) is enclosed inside the arm that holds the roll to measure the rotation and use of the toilet paper. Records of toilet paper use can be used for automatic toilet paper reordering or to distinguish users based on toilet paper consumption.

[0083] A method for detecting a bathroom user is also provided here. The method includes the step of detecting and / or identifying a user by analyzing data generated by sensors in one of the systems described above.

[0084] In some embodiments of these methods, data from the sensor is transferred to a computing device that analyzes the data to detect and identify the user, as described above. In some of these implementation examples, the computing device identifies the user by comparing the data from the sensor with data in a stored user profile, in which case (a) if the data from the sensor matches the user profile, the user is identified as the user in the user profile, or (b) if the data from the sensor does not match the user profile or any other stored user profile, the user is identified as a guest or a new user, in which case the data from the sensor is used to create a user profile for the new user.

[0085] In some of these methods, BUAD is a stool analysis device.

[0086] In other embodiments of these methods, the system generates user profiles that identify individual users, detects the presence of the current user, matches the current user to the user profile, records bathroom usage events, and associates bathroom usage events with the matched user profile. In another embodiment, a computing device or a second computing device analyzes data from a waste analysis device and associates the data from the waste analysis device with the user's user profile.

[0087] When BUAD is an excrement analysis device, the present invention is not limited to detecting any specific parameter or the user's physical condition. In various embodiments, data from the excrement analysis device can be used to determine whether the user has symptoms that can be discerned from a clinical urine or stool test, such as diarrhea, constipation, changes in the frequency of urination, changes in urine volume, changes in the frequency of defecation, changes in stool volume, changes in stool consistency, changes in urine color, changes in urine clarity, changes in stool color, changes in the physical properties of stool or urine, or any combination thereof. See, for example, International Publication No. 2018 / 187790.

[0088] In a specific embodiment, the method is performed by a waste analysis device integrated with or including a toilet, and by a set of servers (or other computing devices) connected to the waste analysis device, performing one or all of the following tasks: generating user profiles that identify individual users, detecting the presence of the current user in proximity to the waste analysis device, matching the system's current user with the user profile, recording excretion events, and associating excretion events with the matched user profile. Thus, the system can associate a series of excretion events with individual users over a period of time, even though multiple users urinate and / or defecate in the toilet into which the system is integrated over the same period. As a result, the system, and / or systems associated with access to a series of user-labeled excretion events, can statistically detect patterns in the user's excrement, including through machine learning, and thereby analyze the excretion events over time to improve the diagnosis of the user's medical condition or the identification of gastrointestinal changes.

[0089] One implementation of the system may use data from sensors used for identification, such as an electrocardiogram used to diagnose a user's atrial fibrillation, to assist in diagnosing a medical condition. Another implementation of system data from sensors used for identification may be used to assist in measuring changes in a user's gastrointestinal tract, such as changes in heart rate during defecation. Yet another implementation of system data from sensors used for identification may be used to assist in identifying a user with a fever. Yet another implementation of system data may be used to assist in monitoring a user for signs of infection or fever.

[0090] The system can implement various parts of the method, for example, locally on the BUAD, or remotely on a computing device operablely connected to the BUAD. By selectively implementing specific steps of the method, either locally or remotely, and by implementing encryption and other security mechanisms, the system can reduce the likelihood of a malicious third party linking potentially sensitive diagnostic information to a user's identity, while still allowing analysis of a set of BUAD usage associated with a particular user. Additionally, the system can interface with a user device via BLUETOOTH®, Wi-Fi, NFC, or any other wireless communication protocol while implementing parts of the method.

[0091] In various embodiments, the system can incorporate new users of BUAD by prompting the user to input identifying information such as the user's name, age, and gender in order to generate a user profile about the user. Additionally, some embodiments of the method can prompt the user to specify a first set of identifiers, such as explicit identifiers (e.g., button presses or touchscreen interactions in the excrement analysis device), voice identifiers (e.g., sample audio clips for user identification), image identifiers (a set of images of the user's face or body), structured optical 3D scan identifiers (e.g., measuring the three-dimensional shape of the face or body using a projection light pattern or camera system), fingerprint identifiers, retinal identifiers, and smartphone / wearable identifiers (e.g., the BLUETOOTH® ID of the user's smartphone / wearable device). Thus, the system can reliably identify a specific user of BUAD at the time of detection by detecting one identifier or combination of identifiers from a set of specified identifiers corresponding to a particular user.

[0092] During the onboarding process, or during subsequent use of BUAD that has been reliably identified as corresponding to an existing user profile, some embodiments of the Method may also measure and record a set of the user's physical characteristics so that the system can identify the user when none of the user-specified identifiers are present. As previously discussed, the Method can record physical characteristics such as the user's height, weight, weight distribution on the toilet proximal to the excrement analysis device, skin color, heart rate, electrocardiogram, body temperature, and bioelectrical impedance, and associate such characteristics with the user profile. These embodiments of the Method can therefore match the user's characteristics in the excrement analysis device with a set of characteristics associated with the user profile in order to identify the user, for example, if the user forgets their phone, or is unable to communicate due to cognitive decline (e.g., dementia), does not present their face to the camera of the excrement analysis device, or does not respond to voice prompts to identify their identity, thereby preventing direct identification of the user.

[0093] While the method attempts to identify the current user of the BUAD, some embodiments of the method can record the current user's excretion events with the BUAD and store any recorded optical data or other data representing the use of the BUAD. Once the current user is identified, the method can associate the use of the BUAD with a user profile corresponding to the current user's identity. However, in some implementations, the method can store the use of the BUAD in association with some measured characteristic of the user involved in the excretion event, without associating it with a user profile. Thus, by recording a threshold number of BUAD uses associated with a sufficiently similar set of characteristics (e.g., within a threshold similarity range), the method can create an unidentified user profile and prompt an anonymous user involved in the excretion event to input user information into the excretion analysis device.

[0094] The system and method are described below with reference to "First User". However, the system can also support additional users (second, third, etc.) by repeatedly performing parts of the method to support multiple simultaneous users of the excrement analysis device by generating multiple user profiles.

[0095] In response to the completion of BUAD use, or the system detecting that the current user is not near BUAD, the system may evaluate any detected identifiers and / or detected features according to the identification logic shown in Figure 7.

[0096] In the example implementation shown in Figure 7, the system first detects the presence of the current user 300. The system evaluates whether it has detected any identifier that matches a set of identifiers associated with the user profile of the first user 310, and determines whether an identifier has been detected 320. For example, if the system records an image of the current user's face, the system can then perform facial recognition techniques to match the current user's face with an image identifier stored in association with the user profile. In another example, if the system records an audio clip of the current user, the system can match the audio recording with a voice identifier stored in association with the user profile according to voice recognition techniques. In yet another example, if the system records direct interactions with buttons or touchscreens of the BUAD, the system can identify the corresponding user profile assigned to the button or touchscreen input. In yet another example, if the system records fingerprints with a fingerprint scanner on an excrement analysis device, the system can match the recorded fingerprints with a fingerprint identifier stored in association with the user profile.

[0097] As described above, if the system is unable to identify a user through an identifier,330 the system may match a set of stored features of the current user with a set of features stored in relation to a user profile.350 In one implementation example, the system may calculate a probability distribution based on the typical or observed variation of each feature of the first user, and then, by measuring the features of the current user, calculate the probability that the current user matches the first user based on the probability distribution. The system may repeat this process for each feature in the set of features to calculate the total probability of a match between the first user and the current user. In response to calculating a total probability of a match that exceeds a threshold probability, the system may identify the current user as the first user.

[0098] In this implementation example, the system can define probability distributions for specific users and / or specific individuals. For example, the system can define a narrow distribution for a user's height because height is not expected to vary beyond the range of measurement error, but a broader distribution for a user's weight because the expected variation in a user's weight is often about 1% of the user's average weight. In another example, the system can store a time series of each of a user's features and calculate a probability distribution based on the time series of each feature. For example, the system can calculate the standard deviation of a user's weight when measured over multiple defecation events by a stool analysis device and then calculate a probability distribution for the user's weight between subsequent defecation events. Additionally, the system can calculate a probability distribution weighted by the most recent of the previously measured features, for example, by calculating the weighted standard deviation or weighted mean of the previously measured features and then calculating the probability distribution for the features based on the weighted standard deviation or weighted mean. Furthermore, since the system can predict that fluctuations in user characteristics such as weight will increase over longer periods, it can expand the range of probability distributions for specific characteristics based on the amount of time elapsed since the most recent excretion event contributing to the user.

[0099] In another implementation example, the system can utilize a machine / deep learning model to identify users by classifying them from a set of known user profiles. For example, the system could run an artificial neural network to define two input vectors for the network: one relating to the user profile and the other relating to the features recorded about the current user. The system could then run the network to calculate a credit score for how well the current user's features match the user profile. In one implementation example, the system trains a machine / deep learning model based on previous instances of the system recording user features.

[0100] In additional embodiments, the system can match a current set of user features with a stored set of user features by performing any statistical or machine / deep learning classification algorithm.

[0101] As shown in Figure 7, if the system fails to match the current user's identifier with an identifier associated with the user profile 330, and fails to match a set of characteristics of the current user with a set of characteristics associated with the user profile 340, the system classifies the user as a guest user and stores the excretion event data associated with the guest user 340.

[0102] excrement analysis As shown in Figure 5, some embodiments of the system can record defecation events in a toilet near the excrement analysis device,280 and associate the defecation events with a first user profile,290. More specifically, in various embodiments, the system can acquire images and spectral data collected via selective laser and / or LED excitation of the user's excrement. In another embodiment, the system can label images and other data recorded in the excrement analysis device based on the presence of face, urine, and toilet paper. Once the user involved in the defecation event is identified, the system can store the relevant images and data of the defecation event in association with the user profile. The system can then analyze such data across multiple defecation events to improve the user's health / health status or to diagnose the user's gastrointestinal symptoms via image analysis, machine learning, and other statistical tools.

[0103] Therefore, in one implementation example, the system can store excretory events that are not identified in a corresponding set of user characteristics, generate a guest user profile based on a set of user characteristics, and associate the unidentified excretory events with the guest user profile. Thus, the system can identify new users of the excretory analysis device and track excretory events before or without explicitly enrolling the user. Therefore, when an anonymous user is profiled by the system, the system has already recorded the user's excretory event data and characteristics and can immediately provide the new user with any diagnostic results or insights.

[0104] Additionally, the system can attempt to match subsequent unidentified users with guest profiles generated so far. If the system calculates a high probability match between the measured features of an unidentified user and a set of features associated with the guest user profile, the system can store the excretion events corresponding to the unidentified user along with the guest user profile.

[0105] In one implementation example, the system can prompt the guest user to create a user profile in response to recording a threshold number of defecation events associated with the guest user profile (when it detects the presence of the guest user before, during, and / or immediately after a defecation event). In response to the guest user's response to this prompt (either through the interface of the defecation analysis device or through input in the pre-installed application), the system can initiate the onboarding process described above.

[0106] In another implementation example, the system may, in response to failing to identify the current user, prompt a known user of the excrement analysis device to prove whether the user was involved in the recent excretion event (e.g., via a pre-installed application on the user's personal device). For example, if the system cannot identify the current user during an excretion event, the system may send a notification to the user's smartphone requesting the user to prove whether they actually used the nearest toilet. In response to receiving input from a user claiming to have used the nearest toilet, the system may associate the excretion event with a known user. In response to receiving input from a user denying to have used the nearest toilet, the system may generate a guest user profile for a set of features of the current user corresponding to the excretion event.

[0107] In yet another implementation example, the system can discard excretion event data when it does not identify the current user, in order to mitigate privacy concerns.

[0108] Privacy mechanism Because the system handles potentially embarrassing private information, some embodiments of the system can implement privacy mechanisms to obscure diagnostic information, identifying information, and information related to the use of BUAD (such as raw images of excrement and the timing of the user's defecation). Therefore, the system can implement specific parts of the method locally at BUAD or remotely, for example, on a server connected to BUAD, to reduce the possibility of sensitive data being intercepted during transport or when it is in a distributed location such as BUAD. In addition, some embodiments of the system can schedule and / or transfer data between the excrement analysis device and a set of servers in the system, obscuring the timing of specific defecation events and the relevant identities of users involved in specific defecation events by transferring identification information and diagnostic information separately. Furthermore, various embodiments of the system can encrypt all transmissions between the excrement analysis device and the system's remote servers.

[0109] In one implementation example, the system performs an analysis of BUAD usage on the BUAD and sends the resulting diagnostic information to a remote server. The system may then also send identifiers and user characteristics recorded in association with the diagnostic information. The remote server can then identify the user associated with the diagnostic information. Thus, in such an embodiment, the system does not transmit images of the excrement, thereby preventing interception of these images by malicious actors. Alternatively, the system may prioritize the security of the diagnostic information and prevent the transfer of diagnostic information between the excrement analysis device and a set of remote servers by performing the diagnostic analysis of the excrement images on the remote server.

[0110] In another implementation example, the system batches identification information (identifiers and user characteristics) and images of excrement and / or diagnostic information, and transfers this information to a remote server for further analysis on a predetermined schedule. Additionally, or alternatively, the system may transfer identification information separately from diagnostic information and / or images of excrement to prevent malicious actors from associating the diagnostic information and / or images of excrement with the user's identity. For example, the system may transfer data between an excrement analysis device and a set of remote servers at two different times: the first time to transfer identification information about a specific excretion event, and the second time to transfer diagnostic information and / or images of excrement. The system can then associate these essentially differently transferred data at the remote servers according to identification labels unrelated to the user profile.

[0111] The systems and methods described herein can be at least partially embodied and / or implemented as machines configured to house computer-readable media for storing computer-readable instructions. Instructions can be executed by computer-executable components integrated with applications, applets, hosts, servers, networks, websites, communication services, communication interfaces, hardware / firmware / software elements of user computers or mobile devices, wristbands, smartphones, or any preferred combination thereof. Other systems and methods of the embodiments can also be at least partially embodied and / or implemented as machines configured to house computer-readable media for storing computer-readable instructions. Instructions can be executed by computer-executable components integrated with computer-executable components integrated with the types of devices and networks described above. The computer-readable media can be any suitable computer-readable media such as RAM, ROM, flash memory, EEPROM, optical devices (CD or DVD), hard drives, floppy drives, or any preferred device. The computer-executable component may be a processor, but any preferred dedicated hardware device can also execute the instructions (as an alternative or in addition).

[0112] References International Publication No. 2018 / 187790 U.S. Provisional Patent Application No. 62 / 809522 U.S. Provisional Patent Application No. 62 / 900309 U.S. Provisional Patent Application No. 62 / 959139

[0113] In view of the above, it will be clear that some of the objectives of the present invention are achieved and other advantages are obtained.

[0114] Since various modifications can be made to the above methods and configurations without departing from the scope of the present invention, all matters included in the above description and shown in the accompanying drawings are intended to be interpreted as illustrative rather than limiting.

[0115] All references cited in this specification, including, but not limited to, patent publications and non-patent literature, are incorporated herein by reference. The references discussed herein are intended merely to summarize the claims made by the authors, and no reference is assumed to constitute prior art. The applicant reserves the right to object to the accuracy and appropriateness of the cited references.

[0116] When used herein in specific embodiments, the terms “approximately” or “approximately” when followed by a numerical value refer to a range of plus or minus 10%. Where a range of values ​​is provided, unless the context explicitly indicates otherwise, it is understood that values ​​falling between each of the upper and lower limits of that range, up to one-tenth of the lower limit, and any other specified or intermediate values ​​within that range are included in the scope of this disclosure. The upper and lower limits of these smaller ranges, which may independently be included in smaller ranges, are also included in this disclosure and are constrained by any explicitly excluded limits within the specified range. Where a specified range includes one or both of the limits, any range excluding one or both of such included limits is also included in this disclosure.

[0117] As used herein in the specification and examples, the indefinite articles “a” and “an” should be understood to mean “at least one” unless the opposite is explicitly indicated.

[0118] When used herein and in the examples, the phrase “and / or” should be understood to mean “either or both” of the elements thus combined, i.e., elements that exist conjunct in some cases and disjunct in others. Multiple elements mentioned with “and / or” should be interpreted in the same manner, i.e., “one or more” of the elements thus combined. Other elements may exist at will, whether in relation to or not to the elements specifically identified by the “and / or” clause. Thus, as a non-restrictive example, when used in conjunction with an open expression such as “equipped with,” in one example, it may refer to A only (including elements other than B at will), in another example to B only (including elements other than A at will), and in yet another example to refer to both A and B (including other elements at will).

[0119] As used herein and in the examples, “or” should be understood to have the same meaning as “and / or” as defined above. For example, when distinguishing items in a list, “or” or “and / or” should be interpreted as inclusive, that is, including at least one of the number of elements or the list, but also including two or more, and optionally including items that are not in the additional list. Terms that clearly indicate the opposite, such as “one of” or “exactly one of” or, as used in the examples, “consist of,” refer to including exactly one element of the number of elements or the list. In general, as used herein, the term “or” should be interpreted exclusively as indicating an exclusive choice (i.e., “one or the other, but not both”) when preceded by terms of exclusivity such as “either,” “one of,” “only one of,” or “exactly one of.” “Consists of” should, as used in the examples, have its customary meaning as it is used in the field of patent law.

[0120] When used herein and in the examples, the phrase “at least one” referring to a list of one or more elements should be understood to mean at least one element selected from any one or more elements in the list of elements, but not necessarily including at least one of each and all elements specifically enumerated in the list of elements, nor excluding any combination of elements in the list of elements. This definition also acknowledges that, whether related to such specifically identified elements or not, there may be other elements in the list of terms to which the phrase “at least one” refers, that are of optional nature. Therefore, as an unrestrictive example, “at least one of A and B” (or similarly, “at least one of A or B” or similarly, “at least one of A and / or B”) may, in one implementation example, refer to at least one that optionally includes two or more elements, i.e., A in the absence of B (and optionally including elements other than B); in another embodiment, refer to at least one that optionally includes two or more elements, i.e., B in the absence of A (and optionally including elements other than A); and in yet another embodiment, refer to at least one that optionally includes two or more elements, i.e., A, and at least one that optionally includes two or more elements, i.e., B (and optionally including other elements).

Claims

1. A system for detecting a bathroom user, comprising at least one sensor coupled to a bathroom usage analysis device, wherein the sensor is configured to generate data that can be used to detect and / or identify the user.

2. The system according to claim 1, wherein the sensors include an explicit identifier, an image sensor, a time-of-flight camera, a load cell, a capacitive sensor, a microphone, an acoustic sensor, a sound wave sensor, an ultrasonic sensor, a passive infrared sensor, a thermopile, a temperature sensor, a motion sensor, an ambient light sensor, a photoelectric sensor, a structured light system, a fingerprint scanner, a retinal scanner, an iris analyzer, a smartphone, a wearable identifier, a weighing scale integrated into a bathroom mat, a height sensor, a skin color sensor, a bioelectric impedance circuit, an electrocardiogram, a pulse oximeter, a thermometer, or any combination thereof.

3. The system according to claim 1, comprising two or more sensors that generate data that can be used to detect and / or identify the user.

4. The bathroom usage analysis device analyzes behavior in the mirror, sink, tub, shower, medicine cabinet, toilet, bidet, or any combination thereof, according to claim 1.

5. The system according to claim 1, wherein the bathroom usage analysis device is a waste analysis device that analyzes waste while the user is using the toilet.

6. The excrement analysis device analyzes urine, feces, intestinal gas, or gases released from feces or urine, according to claim 5.

7. The excrement analysis device is the system according to claim 5, which analyzes urine.

8. The excrement analysis device is a system according to claim 5, which analyzes feces.

9. The excrement analysis device analyzes urine and feces, according to the system of claim 5.

10. The system according to claim 5, wherein the excrement analysis device comprises an excrement analysis sensor that detects electromagnetic radiation or sample chemical substances in the toilet bowl.

11. The excrement analysis device comprises a urine container, according to claim 5.

12. The system according to claim 11, wherein the urine container is disposable.

13. The system according to claim 11, wherein the urine container is reusable.

14. The excrement analysis device further comprises a replaceable visual urine analyzer, according to claim 11.

15. The system according to claim 14, wherein the replaceable visual urine analyzer comprises a dipstick.

16. The excrement analysis device comprises a washable fecal collector, according to claim 5.

17. The system according to claim 1, wherein the sensor comprises an image sensor, a time-of-flight camera, a load cell, a temperature sensor, an ultrasonic sensor, a capacitive sensor, or any combination thereof.

18. The system according to claim 5, wherein the sensor is an image sensor.

19. The system according to claim 18, wherein the image sensor is a time-of-flight camera.

20. The system according to claim 18, wherein the image sensor is installed on the toilet seat or toilet seat cover of the toilet.

21. The system according to claim 18, wherein the image sensor is installed on or integrated into the toilet seat or toilet seat cover of the toilet.

22. The system according to claim 21, wherein the image sensor is integrated into or mounted on the toilet seat cover of the toilet, and the image sensor is capable of capturing an image of the user only when the toilet seat cover is lifted.

23. The system according to claim 21, wherein the image sensor is integrated between the toilet seat cover and the toilet seat, or installed such that the image sensor can capture an image of the user only when the toilet seat cover is lifted.

24. The system according to claim 5, wherein the sensor is two or more load cells integrated into the foot at the bottom of the toilet seat on the toilet, and the load cells measure the weight distribution of the user on the toilet.

25. The system according to claim 1, wherein data from the sensor is transferred to a computing device, and the computing device can analyze the data to determine the user's characteristics detected by the sensor.

26. The system according to claim 25, wherein the computing device is dedicated to user detection and identification and is coupled to the sensor within a housing.

27. The system according to claim 25, wherein the computing device is not dedicated to user detection and identification and is not housed together with the sensor.

28. The system according to claim 27, wherein data from the sensor is transferred to the computing device by a wired or wireless communication protocol.

29. The system according to claim 27, wherein the computing device is also capable of analyzing data from the bathroom usage analysis device.

30. The system according to claim 29, wherein the bathroom usage analysis device is an excrement analysis device.

31. The system according to claim 25, wherein the computing device is capable of detecting and identifying a first user using data from the sensor, and similarly is capable of detecting and identifying one or more additional different users.

32. The system according to claim 31, wherein the software can generate a first user profile for the first user and generate a second user profile for the second user.

33. A method for detecting a bathroom user, comprising the step of detecting and / or identifying the user by analyzing data generated by a sensor in a system according to any one of claims 1 to 32.

34. The method according to claim 33, wherein data from the sensor is transferred to a computing device that analyzes the data to detect and / or identify the user.

35. The method according to claim 34, wherein the computing device identifies the user by comparing the data from the sensor with data in a stored user profile, (a) if the data from the sensor matches the user profile, the user is identified as a user in the user profile, or (b) if the data from the sensor does not match the user profile or any other stored user profile, the user is identified as a guest or a new user, and a user profile for the new user is created using the data from the sensor.

36. The method according to claim 34, wherein the bathroom usage analysis device is an excrement analysis device.

37. The method according to claim 34, wherein the system generates a user profile that identifies individual users, detects the presence of a current user, matches the current user with a user profile, records bathroom usage events, and associates the bathroom usage events with the matched user profile.

38. The method according to claim 37, wherein the bathroom usage analysis device is an excrement analysis device.

39. The method according to claim 38, wherein the computing device or the second computing device analyzes data from the excrement analysis device and associates the data from the excrement analysis device with the user's user profile.

40. The method according to claim 39, wherein the data from the excrement analysis device is used to determine whether the user has symptoms that can be determined from a clinical urine or stool examination, diarrhea, constipation, changes in the frequency of urination, changes in urine volume, changes in urine color, changes in the frequency of defecation, changes in stool volume, changes in stool consistency, changes in stool color, or any combination thereof.

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