Systems, devices, and methods for health monitoring and user identification

Abstract

Disclosed herein are systems, devices, and methods for measuring sensor data of a user seated on a toilet and using statistical models and / or machine learning to detect / identify the user based on the measured sensor data. In some embodiments, the systems described herein can include multiple sensors, including force sensors, ECG sensors, PPG sensors, and other sensors, located within and / or integrated into the toilet. The sensors can measure and / or record sensor data, including load and force, BCG data, ECG data, PPG data, bioimpedance, etc., and can determine one or more physiological parameters and / or characteristics about the user based on the sensor data. The system can further be configured to associate the measured sensor data and biological conditions and / or characteristics with a user identifier, such that the user can be identified by comparing the user identifier with sensor data measured while the subject (e.g., an unknown subject) is seated on the toilet.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to and the benefit of U.S. Provisional Patent Application No. 63 / 443,903, entitled "Systems and Methods for Health Monitoring and Identification of Users," filed February 7, 2023, the disclosure of which is incorporated herein by reference in its entirety.

[0002] Technical Field FIELD OF THE INVENTION

[0002] Embodiments described herein relate generally to health monitoring systems, and more particularly to systems and methods for monitoring user characteristics or traits and performing user identification. [Background technology]

[0003] background

[0003] Patient health monitoring is an important tool for tracking a patient's physiological status and providing early warning or guidance to individuals and healthcare providers in the event of a patient's health deterioration. Patient monitoring is often intrusive, requiring individuals to actively wear specific devices or modify their lifestyle habits so that certain vital signs or characteristics of the patient can be measured. Non-intrusive systems and / or devices for monitoring individuals are limited. Furthermore, in several instances, these systems and / or devices are used and / or shared among multiple subjects, individuals, and / or users, for example, within a group and / or household. As a result, each subject, individual, and / or user included in a group and / or household may be required to routinely identify themselves before their vital signs and / or characteristics can be monitored and / or measured. Therefore, a need exists for developing more accurate techniques for identifying and subsequently monitoring multiple subjects, individuals, and / or users using non-intrusive systems. Summary of the Invention [Means for solving the problem]

[0004] overview

[0004] Described herein are systems, devices, and methods for identifying a user using measured physiological data, including measurements of a user near or seated on a toilet or other toilet device, obtained using a non-intrusive mechanism. [Brief explanation of the drawings]

[0005] BRIEF DESCRIPTION OF THE DRAWINGS [Figure 1]

[0005] FIG. 1 shows a schematic diagram of a sensing system for identifying a user based on one or more physical and / or physiological characteristics measured from the user, according to one embodiment. [Figure 2A]

[0006] 1 illustrates a schematic diagram of a network of devices for identifying a user based on one or more physical and / or physiological characteristics measured from the user, according to one embodiment. [Figure 2B]

[0007] 1 illustrates a schematic diagram of a network of devices for identifying multiple users based on physical and / or physiological characteristics measured from each user, according to one embodiment. [Figure 3A]

[0008] FIG. 1 is a top view of a toilet seat including a series of sensors for monitoring signals associated with one or more physical and / or physiological characteristics of a user (e.g., photoplethysmogram (PPG) signals, electrocardiogram (ECG) signals, load or force, etc.), according to one embodiment. [Figure 3B]

[0008] A side view of a toilet seat including a series of sensors for monitoring signals associated with one or more physical and / or physiological characteristics of a user (e.g., a photoplethysmogram (PPG) signal, an electrocardiogram (ECG) signal, load or force, etc.) in accordance with one embodiment. [Figure 3C]

[0008] A bottom view of a toilet seat according to one embodiment, including a series of sensors for monitoring signals associated with one or more physical and / or physiological characteristics of a user (e.g., photoplethysmogram (PPG) signals, electrocardiogram (ECG) signals, load or force, etc.). [Figure 4A]

[0009] 1 illustrates a flowchart of an exemplary method for onboarding a new user of a sensing system, according to one embodiment. [Figure 4B] 1 illustrates a flowchart of an exemplary method for onboarding a new user of a sensing system, according to one embodiment. [Figure 5]

[0010] 1 is a flowchart of an exemplary method of using a sensing system to measure one or more physical and / or physiological characteristics of a user seated on a toilet and to identify the seated user based on the measured characteristics, according to one embodiment. [Figure 6]

[0011] 1 is a flowchart of an exemplary method for calibrating or adapting a sensing system based on measurements of one or more physical and / or physiological characteristics of a user, according to one embodiment. [Figure 7]

[0012] 1 is a chart illustrating data points for one or more users, according to an embodiment. [Figure 8]

[0013] 1 is a chart illustrating changes in a user's data points over time and outlining the adaptability of a sensing system to such changes, according to an embodiment. [Figure 9A]

[0014] 1A-1C are top views of a toilet seat including a series of sensors for monitoring signals associated with one or more physical and / or physiological characteristics of a user (e.g., photoplethysmogram (PPG) signals, bioimpedance electrode signals, and / or electrocardiogram signals), according to different embodiments. [Figure 9B]

[0014] A top view of a toilet seat including a series of sensors for monitoring signals associated with one or more physical and / or physiological characteristics of a user (e.g., photoplethysmogram (PPG) signals, bioimpedance electrode signals, and / or electrocardiogram signals) according to different embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0006] Detailed Description

[0015]

[0001] Embodiments described herein relate generally to health monitoring systems and devices, and more particularly to systems, devices, and methods for measuring sensor data (e.g., electrical signals such as voltage and / or current, optical signals, and / or forces and loads) while a user is using a toilet, urinal, or other toilet device. Such systems, devices, and methods can provide accurate measurements of sensor data including, for example, weight, ballistocardiogram (BCG), electrocardiogram (ECG), photoplethysmogram (PPG), body temperature, and / or a user's bioimpedance, which can be used to monitor certain physiological data or conditions of the user and to alert the user and / or a healthcare provider to changes in such data or conditions that may require specific therapy, treatment, lifestyle changes, etc.

[0007]

[0016] Most individuals routinely use toilets, urinals, or other defecation or urination devices. Therefore, health monitoring that can be performed while an individual defecates and / or urinates into such devices can provide an unobtrusive way to regularly monitor information about the individual. Measurements such as an individual's seated weight, BCG, ECG, PPG, body temperature, and / or bioimpedance can be useful for monitoring information about the individual. For example, such measurements can be useful for monitoring specific conditions of an individual, such as, for example, an individual's cardiac or vascular heath, fever, menstrual health, circadian rhythm, insomnia and sleep disorders, and / or overall health and well-being.

[0008]

[0017] Various sensing or monitoring systems may be used to measure one or more physical and / or physiological characteristics of a user. For example, a scale may be used to measure a subject's weight or body mass index (BMI). Wearable devices may be used to measure a subject's heart rate, oxygen levels, movement, and / or other data. However, such devices may be intrusive, for example, requiring the user to incorporate their use into their daily life. However, many sensing or monitoring devices are limited to measuring one or a few different physical and / or physiological characteristics of a user and therefore lack comprehensive data capture to effectively or accurately identify different users. In private and public settings, multiple users may use or interact with the same sensing device. Therefore, it may be desirable to have systems and devices that can not only measure a user's physical and / or physiological characteristics but also identify and adapt to different users.

[0009]

[0018] In some embodiments, the systems, devices, and methods described herein may be implemented using a toilet. The toilet may include, for example, one or more sensors configured to measure physical and / or physiological characteristics of a user using or interacting with the toilet. In some embodiments, the systems, devices, and methods described herein may be implemented using a toilet and / or one or more other sensing devices, such as a scale device or a temperature measuring device. The combination of a user's physical and / or physiological characteristics that may be measured by such systems and devices may provide a more comprehensive assessment of an individual's health. For example, such physical and / or physiological characteristics may be used to monitor and assess conditions including, for example, an individual's respiration, weight, temperature, BCG, pulse wave velocity (PWV), stroke volume, cardiac output, urination or bowel movements or weight, and / or weight changes associated therewith.Examples of sensing devices are disclosed in U.S. Patent No. 10,292,658 (the '658 patent), entitled "Apparatus, System, and Method for Mechanical Analysis of Seated Individual," published on May 21, 2019; U.S. Patent Application Publication No. 2022 / 0378373 (the '373 application), entitled "Systems, Devices, and Methods for Monitoring Loads and Forces on a Seat," published on December 1, 2022; U.S. Patent No. 11,650,094 (the '094 patent), entitled "Systems, Devices, and Methods for Measuring Loads and Forces of a Seated Subject Using Scale Devices," published on May 16, 2023; and U.S. Patent No. 11,650,094 (the '094 patent), entitled "Systems, Devices, and Methods for Measuring Body Temperature of a Subject Using Characterization of Faces and / or Joints," published on November 17, 2022. No. 2022 / 0361754 (the '754 application), entitled "Photoplethysmography Sensing Module, Systems and Devices Thereof," filed September 29, 2023 (the '553 application), and International Application No. PCT / US2023 / 075553 (the '553 application), entitled "Photoplethysmography Sensing Module, Systems and Devices Thereof." The disclosures of each of the foregoing are incorporated herein by reference in their entirety.

[0010]

[0019] 1 shows a schematic diagram of a sensing system 100 according to an embodiment. In some embodiments, the sensing system 100 may be implemented as and / or coupled to a toilet, such as a toilet seat or ring. The sensing system 100 may be configured to measure one or more physical and / or physiological characteristics of a user seated on the toilet seat. In some embodiments, the sensing system 100 may identify which of a plurality of different users is seated on the toilet seat based on the user's measured physical and / or physiological characteristics. The sensing system 100 includes one or more sensors 110, a processor 120, a memory 122, and a communication interface 126.

[0011]

[0020] Sensor 110 may be configured to measure data indicative of one or more physical and / or physiological characteristics of a user. In some embodiments, sensor 110 may be coupled to or incorporated into a toilet seat and / or positioned near a toilet and configured to measure data about a user while the user is seated on the toilet seat. Alternatively or additionally, sensor 110 may be coupled to, incorporated into, or positioned near other toilet devices and configured to measure data about a user while the user is using and / or in the vicinity of such devices. Sensor 110 may include one or more force sensors 130, electrocardiogram (ECG) sensors 140, and / or photoplethysmogram (PPG) sensors 150. Optionally, in some embodiments, sensor 110 may also include other types of sensors 160, as further described herein.

[0012]

[0021] The force sensor 130 of the sensing system 100 may be any suitable sensing device capable of measuring, recording, and / or collecting, for example, forces or loads present on the toilet seat when a user is seated on the toilet seat. The measured forces may be used to determine one or more physical or physiological characteristics of the user. The force sensor 130 may be located on, integrated into, and / or coupled to the ring (toilet seat and / or other waste receptacle) of the toilet. For example, in some embodiments, the ring may include or be coupled to one or more supports (e.g., bumpers) configured to house the force sensor 130 and support the ring at the top of the toilet bowl. Alternatively or additionally, the force sensor 130 may be located within or adjacent to a hinge or joint between the ring and the base of the toilet. The force sensor 130 may include a load cell (e.g., a pneumatic load cell, a hydraulic load cell, a piezoelectric crystal load cell, an inductive load cell, a capacitive load cell, a magnetostrictive load cell, a strain gauge load cell), a strain gauge, a force sensing resistor (FSR), or a printed or flexible force sensor, an optical force sensor, etc.

[0013]

[0022] The force sensor 130 may be configured to measure force data that provides information about the weight or BCG of a seated user and / or subject, for example, by accounting for static and / or dynamic loads or forces present on the toilet ring due to the weight of the subject seated on the ring. The force sensor 130 may be configured to measure changes in load and / or force, which may be used to calculate weight changes due to, for example, defecation or urination. In some embodiments, information collected by the force sensor 130 may be used to determine forces generated by the cardiac cycle of a seated user and / or subject. In particular, as the heart forcefully pumps fluid into the user's aorta, the user's body experiences downward and upward forces in a repetitive pattern, which may cause changes in the force and / or load the user exerts on the toilet ring. The force sensor 130 may be configured to measure these changes and provide BCG data for the user over time. In some embodiments, the force sensor 130 may be an independent sensor configured to measure changes in force and load, respectively, exerted by a user seated on the toilet ring and generate independent force data. Using an independent signal can improve signal quality, allowing for more accurate and repeatable measurements.

[0014]

[0023] In some embodiments, signals from multiple force sensors 130 can be used to determine a user's seated posture. For example, in some embodiments, a toilet seat may include a first number of force sensors 130 (e.g., forward force sensors) located on a forward portion of the toilet ring and a second number of force sensors 130 (e.g., rearward force sensors) located on a rearward portion of the toilet seat. A higher relative signal from the front force sensors may indicate a user leaning forward, and the ratio of the front and rear force sensors indicates a posture angle. In some examples, the user's weight, age, gender, and / or dimensional measurements related to the user, such as the user's height, foot-to-waist length, or seat-to-suprasternal notch distance, can be used in conjunction with the static signals described above for a more accurate determination of posture.

[0015]

[0024] In some embodiments, the force sensors 130 described herein may be similar to the force sensors described in US Patent Application Publication No. 2022 / 0378373, incorporated by reference above.

[0016]

[0025] The ECG sensor 140 of the sensing system 100 may be configured to measure the ECG of a subject, such as a user, seated on a toilet. In particular, the ECG sensor 140 may be configured to measure signals representative of the electrical activity of the user's and / or subject's heart, which occurs due to depolarization of conductive pathways in the heart and myocardial tissue during each cardiac cycle. In some embodiments, the ECG sensor 140 may include one or more electrodes or conductive elements disposed on, incorporated into, and / or coupled to the surface of the seat of a toilet (or other waste receptacle). In some embodiments, the ECG sensor 140 may include two or more electrodes or conductive elements to measure the user's ECG. Electrodes may be disposed on or incorporated into the toilet seat, for example, as shown in FIG. 3A , so that the electrodes can be in direct contact with the user's skin or tissue while the user is seated on the toilet. In some embodiments, a processor (e.g., processor 120) operably coupled to ECG sensor 140 may be configured to extract one or more features or characteristics from the ECG data, including, for example, heart rate, R-peak amplitude, PR interval, QRS duration, QT interval, etc.

[0017]

[0026] The PPG sensor 150 of the sensing system 100 may be any suitable sensing device that can be configured to measure the PPG of a subject, such as a user seated on a toilet. The PPG sensor 150 may include an electromagnetic radiation source (e.g., a light source) configured to generate and direct an electromagnetic radiation signal (e.g., an optical signal) toward an area and / or tissue of the user, and the PPG sensor 150 may include an electromagnetic radiation sensor, such as a photodetector, photodiode, photoresistor, photovoltaic cell, etc., that can measure light reflected by, scattered by, and / or transmitted through an area of ​​the user's skin or tissue. The amount of light absorbed, reflected, scattered, and / or transmitted by an area of ​​tissue can be correlated with volumetric blood flow fluctuations in the user. In some embodiments, the electromagnetic radiation source may include a light-emitting diode (LED), a xenon energy discharge lamp (XED), a fluorescent light source and / or lamp, a mercury light source, an incandescent light source, a laser diode, etc. In some embodiments, the electromagnetic radiation source of the PPG sensor 150 may be configured to generate electromagnetic radiation having one or more predetermined characteristics, such as a predetermined frequency or range thereof. For example, the electromagnetic radiation source of PPG sensor 150 can be configured to generate visible light, infrared (IR) light, ultraviolet (UV) light, etc. In some embodiments, PPG sensor 150 can include multiple electromagnetic radiation sources capable of generating light with different characteristics. In some embodiments, the light source of PPG sensor 150 can be coupled to one or more filters and / or lenses designed to modify and manipulate the electromagnetic radiation (e.g., light) generated by the light source, and can be positioned on, incorporated into, and / or coupled to the seat of a toilet (or other waste receptacle). PPG sensor 150 can be positioned on, incorporated into, and / or coupled to the seat of a toilet (or other waste receptacle). In some embodiments, PPG sensor 150 can be positioned on or incorporated into a toilet seat such that PPG sensor 150 can emit and capture reflected light or other electromagnetic radiation from a user when the user is seated on the toilet seat.

[0018]

[0027] In some embodiments, the PPG sensor 150 described herein may be similar to the PPG sensor described in International Application No. PCT / US2023 / 075553, which was incorporated by reference above.

[0019]

[0028] In some embodiments, sensing system 100 may include one or more other types of sensors, such as sensor 160. Sensor 160 may be configured to measure one or more properties or characteristics of a user, a toilet or other urinal device to which sensor 160 is coupled, and / or the environment in the vicinity of the user or toilet. In some embodiments, the measurement data may be used to determine or assess one or more physical or physiological parameters and / or characteristics of the user.

[0020]

[0029] For example, in some embodiments, the sensor 160 of the sensing system 100 may include a temperature sensor. The temperature sensor may be incorporated into and / or coupled to a toilet and configured to measure, record, and / or collect the temperature of the urine stream or feces excreted by a user. In some embodiments, the temperature sensor may be coupled to a toilet seat. Its housing may be small enough so that the temperature sensor can fit within the toilet bowl (or other waste collection device) without interfering with a user and / or individual's use of the toilet (or other waste collection device). The temperature sensor may be stationary or movable, e.g., linearly and / or rotatably about an axis, to straddle an opening in the toilet bowl (or other waste collection device) through which urine and / or feces may be collected. Thus, the temperature sensor may be used to capture the temperature of urine and / or feces regardless of the exact location where such urine and / or feces are received in the toilet bowl (or other waste collection device). In one embodiment, the temperature sensor may include one or more heat flux sensors integrated into the toilet seat to measure core body temperature. The heat flux sensor includes an insulating material disposed on the top surface of the toilet seat such that a first side and / or surface of the insulating material is in direct contact with a portion of the user's skin (e.g., skin surface) when the user is seated on the toilet. The insulating material may be covered on a second side and / or surface by an electric heater that may be controlled and / or used to eliminate heat flow through the insulating material until the temperature of the heater and the skin surface are equal (e.g., a zero heat flux condition). In a zero heat flux condition, an isothermal tunnel is created between the skin surface and subcutaneous tissue located a short distance below the skin surface, which approximates the temperature of the user's skin (e.g., skin temperature). Additionally or alternatively, in some embodiments, the insulating material may be coupled to a temperature sensor configured to measure and / or sense the temperature of a first side and / or surface of the insulating material, thereby facilitating measurement of heat flux (e.g., by measuring the temperature of the first side and / or surface of the insulating material and the temperature of the heater) and the user's skin temperature (e.g., in zero heat conditions).In some embodiments, the sensor 160 of the system 100 may include one or more temperature and heat flux sensors integrated into the toilet seat and operatively coupled to the processor 120 and / or a processor of a user device or a third-party device such as those described with reference to FIGS. 2A and 2B. The temperature and heat flux sensors may be used to sense and / or detect heat flux conditions and measure the temperature of a portion of the user's skin (e.g., the skin surface) that is in direct contact with the heat flux sensor while the user is seated on the toilet. The measured temperature (or a signal related to the measured temperature) and heat flux data may be transmitted to the processor 120 and fed into a machine learning-based algorithm or artificial intelligence model to determine the user's core body temperature. In one embodiment, the temperature sensor may include a non-contact infrared (IR) thermometer or temperature sensor that can measure temperature based on thermal radiation or blackbody radiation emitted by the object being measured. In some embodiments, the temperature sensors described herein may be similar to the temperature sensors described in U.S. Patent Application Publication No. 2022 / 0361754, incorporated by reference above.

[0021]

[0030] In some embodiments, the sensor 160 of the sensing system 100 may include a camera and / or spectrometer (with optional light source) integrated into the toilet seat, such that the camera and / or spectrometer can be used in addition to the other sensors 110 to determine the identity of a user or to collect additional physiological data, such as a speckle plethysmogram. For example, in some embodiments, the sensor 160 may include a camera disposed on and / or integrated into the surface of the toilet seat that comes into direct contact with a user's skin when the user is seated on the toilet. The processor 120 may be configured to activate the camera to collect one or more images and determine information from the images, for example, related to the skin tone and / or other characteristics of the user seated on the toilet. In some embodiments, the camera may be an infrared skin-transmitting camera and / or spectrometer. The images collected by the camera may be used to determine the identity of a user seated on the toilet.

[0022]

[0031] Additionally or alternatively, the sensor 160 of the sensing system 100 may include two or more electrodes that function as impedance sensors. The impedance electrodes and / or sensors may be incorporated into and / or coupled to the surface of the toilet seat. In some embodiments, the impedance sensor may include two impedance sensors: a first impedance sensor disposed on a first side (e.g., the left or right side) of the toilet seat and a second impedance sensor disposed on a second side of the toilet seat opposite the first side. The first impedance sensor and the second impedance sensor may be positioned on the toilet seat such that the impedance sensors are in direct contact with the user's buttocks (or any adjacent skin surface) when the user is seated on the toilet (e.g., the first impedance sensor contacts the first buttocks and the second impedance sensor contacts the second buttocks). The two impedance sensors may be coupled such that the first impedance sensor and the second impedance sensor can form a closed-loop circuit. The current and / or voltage associated with the closed loop circuit may be measured (e.g., the voltage across the impedance sensors may be measured), processed (e.g., amplified, filtered, digitized), and sent to a processor (e.g., processor 120). The first impedance sensor and the second impedance sensor may be operably coupled to a processor (e.g., processor 120) that can receive signals from the first impedance sensor and the second impedance sensor and determine bioimpedance. When a user places their buttocks on the toilet seat (e.g., left and right buttocks in direct contact with the first impedance sensor and the second impedance sensor), the first impedance sensor and / or electrode may send a signal (e.g., a current) to the second impedance sensor and / or electrode, and the resulting voltage between the two electrodes may be measured to determine the bioimpedance across the user's buttocks.

[0023]

[0032] In some embodiments, sensor 160 of sensing system 100 may include three electrodes that may be configured to function as an impedance sensor or an ECG sensor. For example, the three electrodes may be configured as a three-electrode system. The three-electrode system may include a first electrode and a second electrode that may be and / or function as single-lead signal ECG electrodes, and a third electrode that may be a driven right leg (DRL) electrode that serves as a reference point for the ECG signal. The first electrode, the second electrode, and the third electrode may be operably coupled (e.g., via an on-board chip or integrated circuit) to a processor (e.g., processor 120) that may determine the user's ECG data and / or bioimpedance while the user is seated on the toilet. The on-board chip may be an auxiliary processor configured to receive raw ECG data from the first electrode, the second electrode, and the third electrode, perform one or more pre-processing steps on the raw ECG data (e.g., amplifying, filtering, and / or digitizing the raw ECG data recorded by the first electrode, the second electrode, and the third electrode), and then transmit the pre-processed ECG data to processor 120. In some embodiments, the on-board chip may be a multi-channel ECG chip.

[0024]

[0033] In some embodiments, the sensor 160 of the sensing system 100 may include four electrodes that function as impedance sensors. The electrodes and / or sensors may include a first impedance sensor and a second impedance sensor disposed on a first side (e.g., left or right side) of the toilet base, and a third impedance sensor and a fourth impedance sensor disposed on a second side of the toilet base opposite the first side. The first impedance sensor and the second impedance sensor may be positioned on the toilet base such that the first impedance sensor and the second impedance sensor are in direct contact with the user's buttocks (or any adjacent skin surface, including, for example, the thighs) when the user is seated on the toilet (e.g., the first impedance sensor and the second impedance sensor are in contact with the user's first buttock). The third and fourth impedance sensors may be positioned on the toilet seat such that the third and fourth impedance sensors are in direct contact with the user's other buttocks (or an adjacent skin surface, including, for example, the thigh) when the user is seated on the toilet (e.g., the third and fourth impedance sensors are in contact with the user's second buttocks). The four impedance sensors may be coupled such that the first, second, third, and fourth impedance sensors form and / or configure a Kelvin-like drive circuit and / or a four-electrode configuration. The Kelvin-like drive circuit configuration may facilitate elimination of resistive voltage losses and / or drops caused by current sources, resulting in more accurate impedance measurements. Additionally, the Kelvin-like drive circuit may exhibit reduced sensitivity to specific characteristics and geometric configurations of electrical connections and contact impedances (or changing contact impedances that cause the measured impedance to fluctuate over time).

[0025]

[0034] In some embodiments, the first and third impedance sensors (e.g., one impedance sensor disposed on each side of the toilet seat) may be configured to function and / or operate as excitation electrodes that deliver an excitation signal (e.g., apply an excitation current trough the first and third impedance sensors) when a user is seated on the toilet. The second and fourth impedance sensors (one impedance sensor disposed on each side of the toilet seat) may be configured to function and / or operate as sensing electrodes that sense and / or measure a response signal in response to the excitation signal (e.g., measure a voltage difference, loss, and / or drop across the first and third impedance sensors caused by the excitation current). The first, second, third, and fourth impedance sensors may be operatively coupled to a processor (e.g., processor 120) that can receive signals from the first, second, third, and fourth impedance sensors and determine the user's hip-to-hip bioimpedance.

[0026]

[0035] Additionally and / or alternatively, in some embodiments, the first impedance sensor and the second impedance sensor (e.g., two impedance sensors positioned on either the side of the toilet seat, the first side of the toilet seat, or the second side of the toilet seat) can be positioned such that the tissue of a user's thigh seated on the toilet can be in contact with the first impedance sensor and the second impedance sensor. That is, a first portion of the user's thigh can be in direct contact with the first impedance sensor and / or electrode, and a second portion of the user's thigh can be in direct contact with the second impedance sensor and / or electrode. The first impedance sensor and the second impedance sensor can be coupled such that the first impedance sensor and the second impedance sensor can form a closed loop circuit. A current and / or voltage associated with the closed loop circuit can be measured (e.g., a voltage between the impedance sensors can be measured), processed (e.g., amplified, filtered, digitized), and sent to a processor (e.g., processor 120). As described above, the processor can be configured to determine bioimpedance based on the measured current and / or voltage. When a user contacts one of the user's thighs (the user's left thigh or right thigh) with the first impedance sensor and the second impedance sensor positioned on the toilet seat such that a first portion of the user's thigh contacts the first impedance sensor and a second portion of the user's thigh contacts the second impedance sensor, the first impedance sensor can send a signal (e.g., a current) to the second impedance sensor, and the resulting voltage between the first impedance sensor and the second impedance sensor can be measured to determine the bioimpedance of the user's thigh. Similarly, the third impedance sensor and the fourth impedance sensor can be positioned such that tissue of the user's thigh seated on the toilet can contact the third impedance sensor and the fourth impedance sensor, allowing the bioimpedance of the user's thigh to be measured.In some embodiments, the sensors 160 of the sensing system 100 may be configured to determine the user's hip bioimpedance and the user's thigh impedance.

[0027]

[0036] In some embodiments, the impedance sensor and / or electrode may be configured to generate an excitation signal, measure a response signal, and determine the user's bioimpedance at a predetermined frequency. In some embodiments, the impedance electrode and / or sensor may be configured to determine the user's bioimpedance at multiple frequencies. For example, in some embodiments, the impedance electrode and / or sensor may be configured to determine the user's bioimpedance at multiple frequencies between 40 Hz and 10 MHz. In some embodiments, the impedance electrode and / or sensor may be configured to determine the user's bioimpedance data sequentially (e.g., generating a frequency sweep at one frequency at a time). Alternatively, the impedance electrode and / or sensor may be configured to simultaneously determine the user's bioimpedance data at different frequencies. In some embodiments, the impedance electrode and / or sensor may be configured to continuously determine the user's bioimpedance data while the user is seated on the toilet. In other embodiments, the impedance electrode and / or sensor may be configured to determine the user's bioimpedance data over a random period while the user is seated on the toilet.

[0028]

[0037] In some embodiments, force sensor 130, ECG sensor 140, PPG sensor 150, and / or other sensors may be positioned in spaced relation to one another, for example, at different locations along the toilet ring. In some embodiments, one or more sensors may be positioned adjacent to or near the toilet ring or other toilet component, and other sensors may be positioned on the toilet ring or other toilet component. For example, one or more force sensors of a scale may be positioned adjacent to the toilet, and other force sensors may be positioned on the toilet (e.g., on the ring or a coupling attached to the ring). In some embodiments, one or more of force sensor 130, ECG sensor 140, and / or PPG sensor 150 may be positioned together on a single circuit board or housing.

[0029]

[0038] In some embodiments, data measured, recorded, and / or collected by one or more of sensors 110 may be used, alone or in combination with other information, to identify a user, for example, when the user is seated on a toilet. Because individual users tend to have physiological characteristics that differ from those of other users, sensing system 100 may be configured to analyze data indicative of a user's physiological characteristics to identify the user. In some embodiments, sensors 130, 140, 150, and 160 may collectively measure data related to multiple physiological characteristics of a user and provide this measurement data to a processor (e.g., processor 120 or a processor of a separate computing device (see FIGS. 2A-2B)). Processor 120 may be any suitable processing device configured to operate and / or execute a sequence of instructions or code. Processor 120 may be, for example, a general-purpose processor, a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), a digital signal processor (DSP), etc. Processor 120 may be configured to operate and / or execute application processes and / or other modules, processes and / or functions related to system 100 and / or a network associated with system 100 (see Figures 2A-2B).

[0030]

[0039] In some embodiments, the processor 120 may be configured to analyze data measured by one or more sensors 110 to identify a user. For example, the processor may be configured to process the measurement data, e.g., to remove noise, artifacts, and / or other corrupted data. The processor may be configured to extract one of more features from the measurement data and / or determine one or more physiological characteristics of the user (e.g., core body temperature, weight, BCG, ECG, posture, impedance, or other physiological parameters and / or characteristics) based on the measurement data. The processor may be configured to compare the measurement data (or extracted features of the data) with reference data (e.g., previously measured or stored data of one or more users) and determine whether the measurement data is similar to the reference data. Based on the comparison, the processor may be able to identify a user associated with the measurement data. For example, if the measurement data is substantially similar to a reference data set associated with user A, the processor may determine that the measurement data belongs to user A. In some examples, if the measurement data may not be similar to any reference data, the processor may indicate that the user associated with the measurement data is a new user. Further details of this process are provided below with reference to FIG.

[0031]

[0040] In some embodiments, system 100 may perform onboarding of new users. For example, a new user of the restroom may indicate that they are a new user via an input / output device (e.g., an input / output device coupled to communication interface 126). System 100 may record the user's sensor data, including, for example, core body temperature, weight, BCG, ECG, posture, impedance, or other physiological parameters and / or characteristics, via one or more sensors 110 while the user is seated on the restroom. The system may then associate the recorded sensor data with the new user and store the recorded sensor data as reference data for identifying the user during their subsequent use of the restroom. Further details of this process are provided below with reference to FIGS. 4A-4B.

[0032]

[0041] In some embodiments, the processor 120 may be configured to analyze data measured by one or more sensors 110 to monitor and / or assess various physiological data or conditions of the subject. For example, the processor may be configured to process and / or analyze sensor data (e.g., received from the force sensor 130, ECG sensor 140, PPG sensor 150, and / or other sensors 160) to determine the individual's or subject's temperature, weight, BCG, ECG, posture, impedance, or other physiological parameters and / or characteristics. The processor may be configured to monitor these physiological characteristics of the user and / or compare them to predetermined indicators associated with particular conditions. The processor may notify the user (or the user's healthcare provider or caregiver) of changes in such data or conditions that may require specific therapy, treatment, lifestyle changes, etc. Examples of processing and / or measuring sensor data to determine physiological parameters and / or characteristics related to a user and / or subject are described in U.S. Patent No. 10,292,658, U.S. Patent Application Publication No. 2022 / 0378373, U.S. Patent Application Publication No. 2022 / 0364904, U.S. Patent Application Publication No. 2022 / 0361754, and International Application No. PCT / US2023 / 075553, each of which is incorporated by reference above.

[0033]

[0042] Processor 120 may be coupled to a communications interface 126, which may be used to send information to and / or receive information from other devices, as described further herein. The communications interface may be configured to enable bidirectional communication with external devices, including, for example, compute device 270, one or more user devices 280, and / or one or more third-party devices 290, as shown in Figures 2A-2B. The communications interface may include a wired or wireless interface for communicating over a network (e.g., network 204).

[0034]

[0043] Processor 120 may be operatively coupled to memory 122. Memory 122 may be, for example, a random access memory (RAM), a memory buffer, a hard drive, a database, an erasable programmable read-only memory (EPROM), an electrically erasable read-only memory (EEPROM), a read-only memory (ROM), etc. In some embodiments, memory 122 stores instructions that cause processor 120 to execute modules, processes, and / or functions related to processing and / or analyzing sensor data from sensors 110, identifying a subject seated on the toilet based on data measured, recorded, and / or collected by sensors 110, and / or transmitting sensor data to other devices via communication interface 126.

[0035]

[0044] 2A shows a block diagram illustrating sensing system 200 communicating with other devices via network 204, according to an embodiment. In some embodiments, sensing system 200 may be configured to measure physiological data and / or characteristics of a subject seated on a toilet or other commode device. For example, sensing system 200 may be configured to measure one or more of load or force data indicative of body weight or seated weight, BCG data, ECG data, PPG data, core body temperature, bioimpedance, etc. In some embodiments, sensing system 200 is operably coupled to one or more of computing device 270, user device 280, or third-party device 290 and may transmit the measurement data to such devices for further processing and / or analysis. In some embodiments, sensing system 200 or one or more devices coupled to the sensing system (e.g., computing device 270, user device 280, or third-party device 290) may be configured to associate data measured by sensing system 200 with a particular individual or subject. In some embodiments, sensing system 200 or one or more devices coupled to the sensing system (e.g., computing device 270, user device 280, or third-party device 290) may be configured to identify an individual or subject based on data measured by sensing system 200.

[0036]

[0045] Sensing system 200 may include components structurally and / or functionally similar to components of other sensing systems and devices described herein, including, for example, sensing system 100. For example, sensing system 200 may have one or more sensors 210. Sensors 210 may include force sensors, ECG sensors, PPG sensors, and / or other sensors similar to those described with reference to sensing system 100. Sensors 210 may be positioned on, incorporated into, and / or coupled to a toilet seat to measure sensor data representative of physiological parameters and / or characteristics related to the subject.

[0037]

[0046] In some embodiments, sensing system 200 may be configured to communicate with compute device 270, one or more user devices 280, and / or one or more third-party devices 290 via network 204. Network 204 may include one or more networks, which may be any type of network (e.g., a local area network (LAN), a wide area network (WAN), a virtual network, a telecommunications network) implemented as a wired network and / or a wireless network, and may be used to operatively couple any compute device, including sensing system 200, compute device 270, user device 280, and third-party device 290.

[0038]

[0047] In some embodiments, sensing system 200 may be configured to transmit data measured by sensors 210 via communication interface 226 to compute device 270, one or more user devices 280, and / or one or more third-party devices 290. In some embodiments, sensing system 200 may include on-board processing, such as processor 220, implemented as a microprocessor, processing (e.g., filtering, converting, etc.) the sensor data before transmitting it to compute device 270, one or more user devices 280, and / or one or more third-party devices 290. Alternatively, sensing system 200 may be configured to transmit raw sensor data to compute device 270, one or more user devices 280, and / or one or more third-party devices 290. In some embodiments, processor 220 may be configured to analyze the data measured by sensors 210 and / or determine information such as seated weight, BCG data, ECG data, PPG data, or other physiological parameters and / or characteristics of the subject seated on the toilet. In some embodiments, sensing system 200 may be configured to receive information from user device 280, which may be used to determine the identity of the user. For example, in some instances, an unknown user may be seated on the toilet while holding user device 280. User device 280 may include a mobile phone or other portable device, a wearable device such as a necklace, ring, etc., a tablet, a laptop, a personal computer, a smart device, etc. User device 280 may be configured to communicate with computing device 270 over network 204 to transmit user information and / or data such that the computing device can determine the identity of the user seated on the toilet. Sensing system 200 may be configured to receive the identity of the user seated on the toilet from computing device 270.Additionally or alternatively, in some embodiments, the user device 280 may be configured to communicate with the processor 220 of the sensing system 200 to transmit user information and / or data. The sensing system 200 may use the information and / or data received from the user device 280 to determine the identity of the user seated on the toilet.

[0039]

[0048] In some embodiments, processor 220 may be configured to associate the measurement data and / or physiological parameters with a particular individual or subject. In some embodiments, the measurement data and / or physiological parameters may be stored as reference data in a memory (not shown) of sensing system 200. Alternatively, in some embodiments, the measurement data and / or physiological parameters may be stored as reference data in a memory or database coupled to sensing system 200, such as the memory of an external computing device (e.g., computing device 270, user device 280, third-party device 290, and / or other computing device). In some embodiments, processor 220 may be configured to store reference data for multiple known subjects (i.e., subjects of known identities), where the reference data for each subject may be associated with that subject and used to uniquely identify that subject. In particular, processor 220 of sensing system 200 may be configured to receive new data measured by sensor 210 of an unknown subject seated on the toilet and analyze the new data to determine the identity of the unknown subject. For example, processor 220 may be configured to compare new data (or information determined or extracted from the new data) with previously stored data and / or physiological parameters (e.g., reference data) to determine whether the unknown subject is one of multiple subjects known to processor 220. If processor 220 determines that there is a sufficient degree of similarity or overlap between the unknown subject's new measurement data and the known subject's reference data, processor 220 may determine that the unknown subject and the known subject have the same identity. For example, processor 220 may perform cluster analysis or clustering and determine that the unknown subject's new data belongs to the same cluster as data associated with one of the known subjects. If processor 220 is able to identify the unknown subject based on the comparison, processor 220 may associate the new measurement data with the known subject's identity and store such data (e.g., in on-board or external memory) as future reference data.If processor 220 is unable to identify the unknown subject (e.g., due to a lack of similarity with data of known subjects), processor 220 may indicate that the unknown subject cannot be identified and / or prompt the unknown subject to provide identifying information. Further, in some embodiments, if new data of an unknown subject seated on the toilet measured by sensor 210 cannot be linked to the user's identification, sensing system 200 may be configured to store the new measured data in memory of sensing system 200, memory 274 of computing device 270, and / or memory of third-party device 290 as measured data of an unrecognized user. When processor 220 receives new data of an unknown subject measured by sensor 210, the processor may be configured to compare the new data (or information determined or extracted from the new data) with previously stored data and / or physiological parameters (e.g., baseline data) and the data of the unrecognized user. If processor 220 is able to identify the unknown subject based on the comparison with the data of the unrecognized user, the processor may be configured to prompt the unrecognized user to provide identifying information.

[0040]

[0049] In some embodiments, processor 220 may be configured to present and / or communicate data measured and analyzed by sensor 210 and / or information extracted from that data (e.g., seated weight, BCG data, ECG data, PPG data, or other physiological parameters and / or characteristics) to the subject via an on-board display, audio device, or other output device. In some embodiments, processor 220 may be configured to present and / or communicate to the subject the determined identity of the subject seated on the toilet. In some embodiments, processor 220 may be configured to present and / or communicate to the subject that the processor was unable to identify the subject and / or prompt the subject to provide identifying information.

[0041]

[0050] While the functions and processes described above have been described with reference to processor 220 of sensing system 200, in some embodiments, such functions and processes may be performed or implemented, in whole or in part, by a separate computing device (e.g., computing device 270, user device 280, and / or third-party device 290). In particular, in some embodiments, processor 220 may be configured to transmit data measured by sensor 210 (or information extracted or determined from data measured by sensor 210) to an external device, for example, via communications interface 226. Communications interface 226 may be configured to enable bidirectional communication with one or more external devices, including, for example, computing device 270, one or more user devices 280, and / or one or more third-party devices 290. Communications interface 226 may include a wired or wireless interface for communicating over network 204.

[0042]

[0051] Compute device 270 may be configured to perform various processing tasks including, for example, processing and / or analyzing sensor data measured by sensor 210 (or information extracted or determined from data measured by sensor 210), determining the identity of an unknown subject based on the measured sensor data (or information extracted or determined from the measured sensor data), etc. Compute device 270 may include a processor 272, a memory 274, and input / output devices (input / output) 247 (or a variety of such components).

[0043]

[0052] Memory 274 may be, for example, random access memory (RAM), a memory buffer, a hard drive, a database, erasable programmable read-only memory (EPROM), electrically erasable read-only memory (EEPROM), read-only memory (ROM), etc. In some embodiments, memory 274 stores instructions that cause processor 272 to execute modules, processes, and / or functions related to processing and / or analyzing sensor data from sensing system 200, identifying a subject seated on a toilet, etc.

[0044]

[0053] The processor 272 of the computing device 270 may be any suitable processing device capable of executing the modules, processes, and / or functions stored in the memory 274. For example, the processor 272 may be configured to process and / or analyze sensor data (e.g., measured by the sensor 210) to determine weight, BCG, or other physiological data or condition of an individual. The processor 272 may be configured to associate the sensor data and / or determined physiological data or condition with a particular individual or subject and store this data as reference data. The processor 272 may be configured to identify unknown subjects based on the sensor data, for example, by comparing the unknown subject's measured data with the reference data. The processor 272 may be a general-purpose processor, a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), a digital signal processor (DSP), or the like.

[0045]

[0054] The input / output devices 276 of the computing device 270 may include one or more components (e.g., a communication or network interface) for receiving information and / or transmitting information to other devices (e.g., the sensing system 200, the user device 280, the third-party device 290). In some embodiments, the input / output devices 276 may optionally include or be operably coupled to a display, an audio device, or other output device for presenting information and / or communicating with a user. For example, in some embodiments, the input / output devices 276 may include a vibration motor disposed in the toilet seat to enable tactile communication with the user. In some embodiments, the input / output devices 276 may optionally include or be operably coupled to a touchscreen, a keyboard, or other input device for receiving information from a user.

[0046]

[0055] In some embodiments, compute device 270 may be a nearby compute device (e.g., a local computer, laptop, mobile device, tablet, etc.) that receives sensor data and includes software and / or hardware for processing and / or analyzing the sensor data. In some embodiments, compute device 270 may be a server that is remote from sensing system 200 but can communicate with sensing system 200 over network 204 and / or through another device on network 204 (e.g., user device 280). For example, sensing system 200 may be configured to transmit sensor data to a nearby device (e.g., user device 280), for example, over a wireless network (e.g., Wi-Fi, Bluetooth, Bluetooth low energy, 2G, 3G, 4G / LTE, 5G and / or other cellular networks, Zigbee, etc.), which may then be configured to transmit the sensor data to compute device 270 for further processing and / or analysis.

[0047]

[0056] User device 280 may be a computing device associated with a user or subject using a toilet or other urinal device equipped with sensing system 200. Examples of user device 280 may include a mobile phone or other portable device, a wearable device such as a necklace, ring, etc., a tablet, a laptop, a personal computer, a smart device, etc. In some embodiments, user device 280 may receive sensor data from sensing system 200 and process the sensor data before passing the sensor data to computing device 270. For example, user device 280 may be configured to reduce noise (e.g., filtering, time averaging, etc.) in the raw sensor data. In some embodiments, user device 280 may be configured to analyze the sensor data and present (e.g., via a display) information representing or summarizing the sensor data, the determined identity of the subject, and / or other information (e.g., the reliability of the determined identity, a notification regarding a failure to determine the user's identity, a notification regarding the detection of a significant change in the user's physiological data, etc.). For example, user device 280 may present weight information, ECG information, BCG information, bioimpedance information, etc. to the user. In some embodiments, user device 280 may transmit sensor data to computing device 270 or other external device, which may analyze the sensor data and send information representing or summarizing the sensor data or identifying the user back to user device 280 for presentation to the user (e.g., via a display). For example, in some embodiments, user device 280 may present information about the user to the user, such as heart rate, heart rate variability, left ventricular ejection time, pre-ejection period, flow, pulse wave transit time (e.g., based on ECG or BCG data), blood pressure, cardiac output, cardiac contractility, abnormal cardiac function, blood oxygenation level (e.g., SpO2), respiratory rate, stress level (e.g., from heart rate variability), weight, and / or cardiac waveform characteristics (e.g., amplitude and / or interval).

[0048]

[0057] Third-party device 290 may be a computing device associated with another individual or entity that has requested and / or been provided access to the user's data. For example, third-party device 290 may be associated with medical personnel (e.g., doctors, nurses, therapists) and / or caregivers of the user. The user may choose to allow a particular third party to access the user's health data (e.g., including health data obtained from sensor data collected by sensing system 200). The third party may then track the user's health information to determine whether the user is at risk for a particular condition and / or whether a particular intervention, treatment, or care is required.

[0049]

[0058] Although user device 280 and third party device 290 are not shown with any on-board memory, processing devices, and / or input / output devices, it can be understood that any one of these devices may include components (e.g., memory, processors, input / output devices, etc.) that enable it to perform functions such as, for example, processing and / or analyzing sensor data or using sensor data to determine physiological information about an individual and / or identifying an individual based on determined physiological information (e.g., seated weight, ECG, PPG, BCG, core body temperature, posture, impedance, etc.).

[0050]

[0059] 2B schematically illustrates an example in which sensing system 200 is in communication with computing device 270 to identify multiple unknown and / or unidentified users based on data measured by sensing system 200. More specifically, FIG. 2B illustrates a room with a first unknown user (e.g., user A) optionally associated with a first user device 280 (e.g., user A's device), a second unknown user (user B) optionally associated with a second user device 280 (e.g., user B's device), and a toilet equipped with sensing system 200. Although not illustrated in FIG. 2B, sensing system 200 includes sensor 210, processor 220, and communication interface 226 described above with reference to FIG. 2A. Sensing system 200 can measure new sensor data of one of the unknown users via sensor 210 when the unknown user (e.g., user A or user B) is seated on the toilet. Sensing system 200 may be configured to transmit new sensor data measured by sensors 210 to compute device 270 and / or one or more third-party devices 290 via communication interface 226. In some embodiments, processor 220 may be configured to preprocess (e.g., filter, convert, etc.) the new sensor data before transmitting it to compute device 270 and / or one or more third-party devices 290. Alternatively, in some embodiments, sensing system 200 may be configured to transmit raw new sensor data to compute device 270 and / or one or more third-party devices 290. Compute device 270 may be configured to receive the new sensor data and analyze the new sensor data to determine the identity of the unknown user. For example, in some embodiments, compute device 270 may be configured to receive the new sensor data measured by sensors 210 and determine information such as seated weight, BCG data, ECG data, PPG data, bioimpedance, or other physiological parameters and / or characteristics of the unknown user seated on the toilet.Compute device 270 may further be configured to compare the new sensor data (or information determined or extracted from the new sensor data) with data and / or physiological parameters (e.g., baseline data) of multiple users previously stored either in memory 274 of compute device 270 or in the memory of third-party device 290. Compute device 270 may compare the new sensor data with the baseline data to determine whether the unknown user seated on the toilet is one of multiple users known to compute device 270. If compute device 270 determines that there is a sufficient degree of similarity or overlap between the new sensor data of the unknown user and the baseline data of the known user, compute device 270 may determine that the unknown user and the known subject have the same identity. That is, compute device 270 may determine whether the unknown user seated on the toilet is either User A or User B. Optionally, in some embodiments, processor 220 of sensing system 200 may be configured to receive new sensor data measured by sensors 210, as described above, and analyze the new sensor data to determine the identity of the unknown user.

[0051]

[0060] 2B illustrates a computing device 270 that may optionally be coupled to multiple user devices 280, such as a user A's device and / or a user B's device. In such an embodiment, the processor 272 of the computing device 270 may be configured to determine whether the unknown user seated on the toilet is either user A or user B, and then communicate with the identified user's user device 280 (e.g., user A's device or user B's device) via the network 204 and prompt the identified user to confirm the user's identity. Alternatively, in some embodiments, the processor 220 of the sensing system 200 may be configured to communicate with the identified user's user device 280 (e.g., user A's device or user B's device) via the network 204 and prompt the identified user to confirm the user's identity.

[0052]

[0061] 3A-3C illustrate top, side, and bottom views, respectively, of a sensing device or system (e.g., as described with reference to FIGS. 1 and 2) for monitoring signals associated with various physiological data or conditions of an individual, according to an embodiment. As shown in FIGS. 3A-3C, the sensing device is implemented as a toilet seat 301. The toilet seat 301 may be a toilet ring or other component of a toilet on which an individual or subject sits. The toilet seat 301 may be disposed on a base (e.g., the top of a toilet bowl) such that the toilet seat 301 defines a centrally located opening 312 therethrough for receiving, for example, bodily fluids, feces, etc. The shape and / or dimensions of the toilet seat 301 may be circular, oval, elliptical, and / or any other closed annular shape (e.g., a rounded or "o" shaped toilet seat). Alternatively, in some embodiments, the shape and / or dimensions of the toilet seat 901 may correspond to an open shape, such as, for example, a "U" shaped toilet seat (not shown in FIGS. 3A-3C). In such embodiments, the toilet seat 901 may include one or more openings that provide and / or create a space and / or gap between the toilet seat and bowl that facilitates a user, particularly a male user, to sit on the toilet without directly contacting the bowl with their genitals. For example, in some embodiments, the toilet seat 901 may include an opening located in a front portion of the toilet seat 901. This opening, which may be referred to as a front opening of the toilet 901, can create a location for urine to splash and facilitate rapid cleaning of the toilet when the toilet is installed, for example, in a public washroom and / or bathroom.

[0053]

[0062] The toilet base 301 may include multiple sensors, including, for example, one or more force sensors 330, ECG sensors 340, and PPG sensors 350. The sensors 310 may be the same or similar in form and / or function as the sensors 110 and 210 described above with reference to FIGS. 1 and 2. The sensors 310 included in and / or incorporated into the toilet base 301 may be configured to measure multiple signals (e.g., PPG signals, ECG signals, and loads and / or forces) present on the toilet base 301, for example, when an individual is seated on the toilet seat 301. Although not shown, the toilet base 301 may also include a processor, memory, and communication interface similar to those described with reference to FIGS. 1 and 2. Alternatively, the toilet base 301 may be operably coupled to a processor, memory, and / or communication interface not located in the toilet seat, such as one located within another component of the toilet (e.g., the toilet base) or located on an external device (e.g., the computing device 270). In some embodiments, the toilet seat 301 may be configured to transmit sensor data collected by the force sensor 330, the ECG sensor 340, and the PPG sensor 350 to a processor (e.g., processor 120, 220, 272) such that the processor can process and / or analyze the sensor data as described above with reference to Figure 2. In some embodiments, the sensing device shown in Figure 3 may be installed in an existing toilet, for example, by retrofitting the existing toilet.

[0054]

[0063] 9A and 9B show top views of two exemplary sensing devices or systems (e.g., as described with reference to FIGS. 1, 2A-2B, and 3A-3C) for monitoring signals associated with various physiological data or conditions of an individual, according to embodiments of the present disclosure. As shown in FIGS. 9A and 9B, the sensing device is implemented as a toilet seat 901. The toilet seat 901 may be a toilet ring or other component of a toilet on which an individual or subject sits. The toilet seat 901 may be disposed on a base (e.g., the top of a toilet bowl) such that the toilet seat 901 defines a centrally located opening 912 therethrough for receiving, for example, bodily fluids, feces, etc. The shape and / or dimensions of the toilet seat 901 may be circular, oval, elliptical, and / or any other closed annular shape (e.g., a rounded or "o" shaped toilet seat). As mentioned above, in some embodiments, the shape and / or dimensions of the toilet seat 901 may correspond to an open shape, such as, for example, a "U" shaped toilet seat. For example, in some embodiments, the toilet seat 901 may include an opening located in a front portion of the toilet seat 901. This opening, which may also be referred to as the front opening of the toilet 901, can create a location where urine may splash, facilitating quick cleaning of the toilet when the toilet is installed, for example, in a public washroom and / or bathroom.

[0055]

[0064] The toilet base 901 may include multiple sensors 910, including a PPG sensor 950 and four sensors 960, which may be four electrodes. The four sensors and / or electrodes 960 may be configured to function as impedance sensors and / or ECG sensors. The PPG sensor 950 shown in FIGS. 9A and 9B may be the same or similar in form and / or function to the PPG sensor 150 and PPG sensor 350 described above with reference to FIGS. 1 and 3A, respectively. Additionally or alternatively, in some embodiments, the sensor 910 may also include a force sensor (not shown in FIGS. 9A-9B) configured to record and / or collect, for example, a force or load present on the toilet. The sensor 910 included in and / or incorporated into the toilet base 901 may be configured to measure multiple signals (e.g., a PPG signal, a bioimpedance signal, an ECG signal, and load and / or force) present on the toilet seat 901, for example, when an individual is seated on the toilet seat 901. Although not shown, the toilet base 901 may also include a processor, memory, and communication interface similar to those described with reference to Figures 1 and 2A-2B. Alternatively, the toilet base 901 may be operably coupled to a processor, memory, and / or communication interface not located in the toilet base, such as one located within another component of the toilet (e.g., the toilet base) or in an external device (e.g., computing device 270). In some embodiments, the toilet base 901 may be configured to transmit sensor data collected by sensors 910 included in the toilet base 901 to a processor (e.g., processor 120, 220, 272) so that the processor can process and / or analyze the sensor data as described above with reference to Figures 2A-2B. In some embodiments, the sensing devices shown in Figures 9A-9B can be installed in an existing toilet, for example, by retrofitting the existing toilet.

[0056]

[0065] FIG. 9A illustrates a toilet base 901 including four sensors and / or electrodes 960 that can be configured to function as impedance sensors. The four impedance sensors 960 can be coupled such that a first impedance sensor 960, a second impedance sensor 960, a third impedance sensor 960, and a fourth impedance sensor 960 form and / or configure a Kelvin-like drive circuit and / or a four-electrode configuration. FIG. 9A illustrates that the first impedance sensor 960 and the second impedance sensor 960 can be disposed on a first side of the toilet base 901. More specifically, the first impedance sensor can be disposed on a rear portion of the first side of the toilet (e.g., see impedance sensor A), and the second impedance sensor can be disposed on a front portion of the first side of the toilet (e.g., see impedance sensor B). In use, the first impedance sensor and the second impedance sensor are placed in direct contact with the user's buttocks (or any adjacent skin surface, including, for example, the thighs) while the user is seated on the toilet. 9A also shows that a third impedance sensor 960 and a fourth impedance sensor 960 may be positioned on a second side of the toilet seat opposite the first side toilet. The third impedance sensor may be positioned on a rear portion of the second side of the toilet (e.g., see impedance sensor C), and the fourth impedance sensor is positioned on a front portion of the second side of the toilet (e.g., see impedance sensor D). In use, the third impedance sensor and the fourth impedance sensor are placed in direct contact with the user's other buttocks (or adjacent skin surfaces, including, for example, thighs) when the user is seated on the toilet. In some implementations, the first impedance sensor and the third impedance sensor (e.g., rear impedance sensors A and C) may be configured to function and / or operate as excitation electrodes that deliver excitation signals by applying an excitation current through the first impedance sensor and the third impedance sensor when the user is seated on the toilet.In such implementations, the second and fourth impedance sensors (e.g., front impedance sensors B and D) may be configured to function and / or operate as sensing electrodes that sense and / or measure a response signal in response to an excitation signal (e.g., measure a voltage difference, loss, and / or drop across the first and third impedance sensors caused by an excitation current). Alternatively, in some implementations, the first and third impedance sensors (e.g., rear impedance sensors A and C) may be configured to function and / or operate as sensing electrodes, and the second and fourth impedance sensors (e.g., front impedance sensors B and D) are configured to function and / or operate as excitation electrodes. The Kelvin-like drive circuit configuration described above can facilitate elimination of resistive voltage losses and / or drops caused by current sources, resulting in more accurate impedance measurements. The above-mentioned first impedance sensor, second impedance sensor, third impedance sensor, and fourth impedance sensor may be operably coupled to a processor (e.g., processor 120, 220, and / or 272) that can receive signals from the first impedance sensor, second impedance sensor, third impedance sensor, and fourth impedance sensor and determine bioimpedance between the user's hips.

[0057]

[0066] Additionally or alternatively, in some embodiments, the first impedance sensor 960 and the second impedance sensor 960 (e.g., impedance sensors A and B) shown in FIG. 9A may be positioned such that the first impedance sensor and the second impedance sensor can contact the tissue of a user's thigh while the user is seated on the toilet. That is, a first portion of the user's thigh can be in direct contact with the first impedance sensor (impedance sensor A), and a second portion of the user's thigh can be in direct contact with the second impedance sensor (impedance sensor B). The first impedance sensor and the second impedance sensor can be coupled such that the first impedance sensor and the second impedance sensor can form a closed loop circuit. The current and / or voltage associated with the closed loop circuit can be measured (e.g., the voltage between the first impedance sensor and the second impedance sensor can be measured), processed (e.g., amplified, filtered, digitized), and sent to a processor (e.g., processors 120, 220, and / or 272). As described above, the processor may be configured to determine bioimpedance based on the measured current and / or voltage. When a user contacts one of the user's thighs with the first and second impedance sensors disposed on the toilet seat such that a first portion of the user's thigh contacts the first impedance sensor (impedance sensor A) and a second portion of the user's thigh contacts the second impedance sensor (impedance sensor B), the first impedance sensor can transmit a signal (e.g., a current) to the second impedance sensor, and the voltage generated between the first and second impedance sensors can be measured to determine the bioimpedance of the user's thigh. Similarly, the third and fourth impedance sensors (e.g., impedance sensors C and D) may be positioned such that the tissue of the user's thigh seated on the toilet can be brought into contact with the third and fourth impedance sensors, thereby measuring the bioimpedance of the user's thigh.In some embodiments, the impedance sensor 960 shown in FIG. 9A may be configured to determine the user's hip bioimpedance and the user's thigh impedance.

[0058]

[0067] FIG. 9B illustrates a toilet base 901 including four sensors and / or electrodes 960 that can be configured to function as impedance sensors. The four impedance sensors 960 can be coupled such that a first impedance sensor 960, a second impedance sensor 960, a third impedance sensor 960, and a fourth impedance sensor 960 form and / or configure a Kelvin-like drive circuit and / or a four-electrode configuration. FIG. 9B illustrates that the first impedance sensor 960 and the second impedance sensor 960 can be positioned side by side on a first side of the toilet base 901. That is, the first impedance sensor can be positioned in an outer region near the outer edge of the first side of the toilet base 901 (see, e.g., impedance sensor A), and the second impedance sensor can be positioned in an inner region near the opening 912 (see, e.g., impedance sensor B). In use, the first impedance sensor and the second impedance sensor are placed in direct contact with the user's buttocks (or any adjacent skin surface, including, for example, the thighs) while the user is seated on the toilet. 9B also shows that a third impedance sensor 960 and a fourth impedance sensor 960 may be positioned side by side on a second side of the toilet seat opposite the first side toilet. The third impedance sensor may be positioned in an inner region near the opening 912 (see, e.g., impedance sensor C), and the fourth impedance sensor may be positioned in an outer region near the outer edge of the second side of the toilet seat 901 (see, e.g., impedance sensor D). In use, the third impedance sensor and the fourth impedance sensor are placed in direct contact with the user's other buttocks (or adjacent skin surface, including, for example, the thigh) when the user is seated on the toilet.

[0059]

[0068] In some implementations, the first and fourth impedance sensors (e.g., impedance sensors A and D in the outer region of FIG. 9B ) may be configured to function and / or operate as excitation electrodes, and the second and third impedance sensors (e.g., impedance sensors B and C in the inner region of FIG. 9B ) may be configured to function and / or operate as sensing electrodes. Alternatively, in some implementations, the positions of the excitation and sensing electrodes may be reversed. That is, the first and fourth impedance sensors (e.g., impedance sensors A and D in the outer region of FIG. 9B ) may be configured to function and / or operate as sensing electrodes, and the second and third impedance sensors (e.g., impedance sensors B and C in the inner region of FIG. 9B ) may be configured to function and / or operate as excitation electrodes. In still other implementations, the first and third impedance sensors (e.g., impedance sensors A and C in FIG. 9B ) may be configured to function and / or operate as excitation electrodes, and the second and fourth impedance sensors (e.g., impedance sensors B and D) may be configured to function and / or operate as sensing electrodes. Additionally, in some implementations, the positions of the excitation and sensing electrodes may be reversed. For example, the first and third impedance sensors (e.g., impedance sensors A and C in FIG. 9B ) may be configured to function and / or operate as sensing electrodes, and the second and fourth impedance sensors (e.g., impedance sensors B and D) may be configured to function and / or operate as excitation electrodes. The Kelvin-like drive circuit configuration described above can facilitate elimination of resistive voltage losses and / or drops caused by current sources, resulting in more accurate impedance measurements.The above-mentioned first impedance sensor, second impedance sensor, third impedance sensor, and fourth impedance sensor may be operably coupled to a processor (e.g., processor 120, 220, and / or 272) that can receive signals from the first impedance sensor, second impedance sensor, third impedance sensor, and fourth impedance sensor and determine bioimpedance between the user's hips.

[0060]

[0069] Additionally or alternatively, in some embodiments, the first impedance sensor 960 and the second impedance sensor 960 (e.g., impedance sensors A and B) shown in FIG. 9B may be positioned such that the tissue of a user's thigh while seated on the toilet can be in contact with the first impedance sensor and the second impedance sensor. That is, a first portion of the user's thigh can be in direct contact with the first impedance sensor (impedance sensor A), and a second portion of the user's thigh can be in direct contact with the second impedance sensor (impedance sensor B). The first impedance sensor and the second impedance sensor may be coupled such that the first impedance sensor and the second impedance sensor can form a closed loop circuit. The current and / or voltage associated with the closed loop circuit may be measured (e.g., the voltage between the first impedance sensor and the second impedance sensor may be measured), processed (e.g., amplified, filtered, digitized), and sent to a processor (e.g., processors 120, 220, and / or 272). As described above, the processor may be configured to determine bioimpedance based on the measured current and / or voltage. When a user contacts one of the user's thighs with the first and second impedance sensors disposed on the toilet seat such that a first portion of the user's thigh contacts the first impedance sensor (impedance sensor A) and a second portion of the user's thigh contacts the second impedance sensor (impedance sensor B), the first impedance sensor can transmit a signal (e.g., a current) to the second impedance sensor, and the voltage generated between the first and second impedance sensors can be measured to determine the bioimpedance of the user's thigh. Similarly, the third and fourth impedance sensors (e.g., impedance sensors C and D) may be positioned such that the tissue of the user's thigh seated on the toilet can be brought into contact with the third and fourth impedance sensors, thereby measuring the bioimpedance of the user's thigh.In some embodiments, the impedance sensor 960 shown in FIG. 9B may be configured to determine the user's hip bioimpedance and the user's thigh impedance.

[0061]

[0070] In some embodiments, the impedance sensors and / or electrodes described above with reference to FIGS. 9A-9B may be configured to generate an excitation signal, measure a response signal, and determine a user's bioimpedance at a predetermined frequency. In some embodiments, the impedance electrodes and / or sensors described above may be configured to determine a user's bioimpedance at multiple frequencies. For example, in some embodiments, the impedance electrodes and / or sensors may be configured to determine a user's bioimpedance at multiple frequencies between 40 Hz and 10 MHz. In some embodiments, the impedance electrodes and / or sensors may be configured to determine a user's bioimpedance data sequentially (e.g., generating a frequency sweep at one frequency at a time). Alternatively, the impedance electrodes and / or sensors may be configured to simultaneously determine a user's bioimpedance data at different frequencies. In some embodiments, the impedance electrodes and / or sensors may be configured to continuously determine a user's bioimpedance data while the user is seated on the toilet. In other embodiments, the impedance electrodes and / or sensors may be configured to determine a user's bioimpedance data over a random period while the user is seated on the toilet.

[0062]

[0071] 9A or 9B may be configured to function as ECG sensors. In such embodiments, two of the sensors 960 (e.g., sensors A and C, sensors B and D, sensors A and D, or sensors B and C) may be configured to measure signals representative of the user's and / or subject's cardiac electrical activity caused by depolarization of the heart and cardiac muscle tissue conductive pathways during each cardiac cycle, as described above with reference to ECG sensors 140 and 340 of FIGS. 1 and 3A-3C.

[0063]

[0072] 9A or 9B may be configured to function as ECG sensors. In such embodiments, the three sensors and / or electrodes 960 may be configured as a three-electrode system. The three-electrode system may include a first electrode and a second electrode (e.g., electrode A and electrode C) that may be and / or function as single-lead signal ECG electrodes, and a third electrode (electrode B) that may be a driven right leg electrode that serves as a reference point for the ECG signal. The first electrode, the second electrode, and the third electrode may be operably coupled to a processor (e.g., processor 120) that can receive signals from the first electrode, the second electrode, and the third electrode and determine the user's ECG data and / or bioimpedance while the user is seated on the toilet.

[0064]

[0073] The systems and devices described herein, including those depicted in FIGS. 1-3 and 9, can actively and / or passively determine the identity of an individual or subject seated on a toilet seat or other toilet device. In some embodiments, the systems and devices described herein may implement an initial setup or onboarding process for a new individual to enable subsequent identification of the same individual. In particular, the systems and devices described herein may acquire sensor data of a user (e.g., during a training period or under different conditions) and associate the sensor data with the subject. Such associated data may then be stored and used as reference data for identifying the user at a future time. In some embodiments, such associated data may represent a biological profile or biometric identification of the user that can be referenced at a future time to identify the user. FIGS. 4A-4B provide an example of an initiation or onboarding process 400 according to one embodiment. Process 400 may be performed by a processor, including, for example, a processor on-board the sensing system or device (e.g., a processor similar to processor 120 and / or processor 220 described above with reference to Figures 1 and 2) or a processor of a remote computing device to which the sensing system is coupled (e.g., processor 272 of computing device 270 described above with reference to Figures 2A-2B).

[0065]

[0074] As shown in FIG. 4A , onboarding process 400 may optionally begin at step 401 by prompting the user to provide identifying information. In some embodiments, the processor may communicate with the user through a communication interface of the sensing system (e.g., communication interface 126 or communication interface 226). For example, the communication interface may include an output device that can present a prompt to the user (e.g., via audio or video). Alternatively, the communication interface may communicate the prompt to an external device (e.g., user device 280, compute device 270, and / or third-party device 290), causing the external device to present the prompt to the user. The processor may prompt the user to provide identifying information, such as, for example, name, date of birth, username or user identifier, or other information that can be used to identify the user. If the user is a new user, the user may create a user account and associate their identity with the username or user identifier of the account.

[0066]

[0075] At step 402, the onboarding process 400 may optionally include prompting the user's caregiver to provide identifying information. In some embodiments, the processor may communicate with a caregiver, a medical professional, and / or a third party associated with the user via a communication interface of the sensing system (e.g., communication interface 126 or communication interface 226) to prompt and / or request the caregiver, medical professional, or third party to provide identifying information for the user. In some examples, the caregiver may enter all identifying information remotely (e.g., at a location different from where the user and the sensing system are located) on behalf of the user of the sensing system 200. Furthermore, in some embodiments, the caregiver, medical professional, or third party may register the user's information before the user is introduced to the sensing system 200.

[0067]

[0076] Method 400 includes performing one or more recordings of a user or subject seated on a toilet or other toilet bowl device. For example, at reference numeral 403, a sensing system (e.g., sensing system 100, 200, or 300) can measure and record sensor data while the user is seated on the toilet. As described above, the sensing system can include sensors configured to measure and record data about the user. A processor (e.g., an on-board processor or a remote processor) can receive the measurement data from the sensing system. In some embodiments, the processor can be configured to analyze the sensor data to determine physical and / or physiological information about the user, including, for example, seated weight, total weight, ECG characteristics, PPG characteristics, bioimpedance, etc.

[0068]

[0077] In some embodiments, instead of prompting the user for identifying information at step 401 or step 402, the processor may automatically compare the user's measured sensor data to previously collected and stored sensor data of known users at step 404. If the processor determines (e.g., via statistical and / or machine learning algorithms) based on the comparison that the user's sensor data is similar to the sensor data of known users, at reference numeral 405, the processor may determine that the user is a known user. The processor may then obtain a user identifier associated with the known user. Further details of how users may be identified based on sensor data are described below with reference to FIG. 5.

[0069]

[0078] At reference numeral 406, the processor may then associate the user's sensor data (e.g., raw or filtered) with a user identifier associated with that user. As described above, the user identifier may have been entered by the user or created by the user or the user's caregiver at step 401 or step 402, or the user identifier may be obtained by the processor after the processor identifies the user as a known user at reference numeral 405. In some embodiments, the processor may determine or extract information from the user's sensor data (e.g., information about one or more physiological characteristics, parameters, or conditions of the user) and associate such determined or extracted information with the user instead of or in addition to the raw or filtered sensor data.

[0070]

[0079] In some embodiments, if the processor does not prompt the user to provide or create a user identifier and the processor does not determine that the sensor data is similar to previously collected sensor data of a known user, then at reference numeral 407 the processor may create a new user identifier for the user and associate the sensor data of the user with the new user identifier.

[0071]

[0080] Optionally, process 400 may include collecting sensor data of the user under different conditions. For example, as shown in FIG. 4B , in step 410, the processor may be configured to collect sensor data of the user while the user is sitting on the toilet seat in different positions. At reference numeral 411, the user may be instructed to adjust their position and remain in each position for a predetermined time (e.g., several seconds, one minute, or several minutes) so that the sensing system can measure the user's data in each position. In some embodiments, the processor may communicate with the user via a communication interface of the sensing system and instruct the user to hold each of the multiple positions for the predetermined time. In some embodiments, the processor may send a message to an external device (e.g., a user device, a computing device, and / or a third-party device) instructing the user to hold each of the multiple positions for the predetermined time. The external device may be configured to receive the message from the sensing system and present it to the user, for example, via a display, an audio device, or other output component of the external device. Examples of positions the user may be instructed to assume include sitting on the toilet with their upper body leaning forward so that more of their weight is on the front of the toilet, sitting on the toilet with their upper body leaning back, sitting on the toilet with their upper body leaning to the right or left, sitting on the toilet with their upper body upright or as straight as possible, etc. In another example, the sensing system may present the user with a message instructing the user to sit on the toilet with their upper body leaning forward.

[0072]

[0081] At reference numeral 412, the sensing system may record sensor data of the user in different postures (e.g., postures instructed to the user at reference numeral 411). At reference numeral 413, the processor may associate the sensor data recorded in the different postures with the user, for example, by associating it with the user's user identifier.

[0073]

[0082] After associating the sensor data with a user identifier at reference numeral 407 or reference numeral 413, the processor may be configured to store the sensor data in memory (e.g., on-board memory or a remote memory or database coupled to the processor). This stored sensor data may then be used as reference data (or biological profile) for comparison with newly acquired sensor data to facilitate identification of future unknown users, as described further herein.

[0074]

[0083] Optionally, process 400 may include collecting sensor data related to a user's patterns while seated on the toilet. These patterns, which may be referred to as reach patterns, correspond to different positions and / or orientations a user may assume while seated on the toilet. In some embodiments, the user's reach patterns may be recorded by a processor and used to determine the user's identity. As shown in FIG. 4B , the processor may be configured to collect sensor data of a user's reach patterns as the user sits on the toilet seat in step 420. The user may be instructed to stand up and then sit on the toilet, and may approach the toilet according to different orientations, positions, and / or postures. For example, the user may be instructed to approach the toilet from the front of the toilet and sit on the toilet while assuming a forward-leaning orientation. Alternatively, the user may be instructed to approach the toilet from different orientations (e.g., diagonally or sideways) while assuming different orientations. The user may be instructed to repeat instructing the user to stand up and sit on the toilet multiple times in step 421 so that the sensing system can measure sufficient data for the user at each reach.

[0075]

[0084] At reference numeral 422, the sensing system can record sensor data of the user's sitting pattern (e.g., the repeated standing and sitting as instructed to the user at reference numeral 421). At reference numeral 423, the processor can associate the sensor data of the user's sitting pattern, for example, by associating it with the user's user identifier.

[0076]

[0085] After associating the sensor data with a user identifier at reference numeral 407 or reference numeral 413, the processor may be configured to store the sensor data in memory (e.g., on-board memory or a remote memory or database coupled to the processor). This stored sensor data may then be used as reference data (or biological profile) for comparison with newly acquired sensor data to facilitate identification of future unknown users, as described further herein.

[0077]

[0086] While the onboarding process shown in FIGS. 4A-4B indicates that a single measurement of the user or multiple measurements taken in different positions may be collected, it can be understood that any number of measurements of the user may be collected during the onboarding process. For example, the user may be instructed to sit on the toilet for an extended period of time, during which time n measurements of data may be taken. In some embodiments, the onboarding process may continue over several seated sessions. For example, the user may be asked to identify themselves during multiple seated sessions on the toilet (e.g., the first 3-10 sessions, etc.) so that the processor can associate the data measured during those multiple sessions with the user. Having multiple data sets of the user collected can increase the processor's robustness in identifying the user at a later point in time.

[0078]

[0087] 5 shows a flowchart of a process 500 for identifying a user based on measured user sensor data, according to an embodiment. Process 500 may be performed by a processor, including, for example, a processor on-board a sensing system or device (e.g., a processor similar to processor 120 and / or processor 220 described above with reference to FIGS. 1 and 2) or a processor of a remote computing device to which the sensing system is coupled (e.g., processor 272 described above with reference to FIGS. 2A-2B).

[0079]

[0088] 5, several different types of sensor data, such as force data, ECG data, PPG data, and / or impedance data, may be recorded by a sensing system (e.g., sensing systems 100, 200, or 300). In some embodiments, only a single type of sensor data may be recorded, while in other embodiments, two or more types of sensor data may be recorded.

[0080]

[0089] At reference numeral 501, a sensing system can record force data of a user sitting on the toilet. In particular, the sensing system can include force sensors positioned around the toilet ring, which can capture force data of the user as the user sits on the toilet ring. The force data can be provided to a processor for further processing and / or analysis. In some embodiments, the processor can process the raw force data to remove artifacts and / or noise. In some embodiments, the processor can process the raw data to provide BCG data of the user. In some embodiments, the processor can optionally use the force data at reference numeral 502 to determine one or more BCG-related features and / or the user's posture or dynamic weight. The BCG-related features can include, for example, an ejection wave (e.g., an I ejection wave and / or a J ejection wave) and one or more pre-systolic peaks, systolic peaks, and / or diastolic peaks. In particular, the processor can determine the distribution of the user's weight, which indicates how the user's weight is concentrated around the toilet seat. Such weight distribution can indicate the user's posture (e.g., whether the user is leaning forward, whether the user is leaning back, whether the user is leaning to the left, whether the user is leaning to the right, or whether the user is sitting upright). In some embodiments, the sensing system (or a separate sensing system) can include one or more force sensors disposed on the scale assembly. The force sensors in the scale assembly, together with force sensors in the toilet ring, can provide more comprehensive weight distribution data of the user. In such embodiments, the processor can determine the user's posture and / or weight distribution based on force data captured along the toilet ring and by the scale assembly. For example, if more of the user's weight is concentrated on the toilet ring, the processor may determine that the user is leaning back or sitting backward on the toilet. Alternatively, if more of the user's weight is concentrated on the scale assembly, the processor may determine that the user is leaning forward (e.g., in a reading position).In some embodiments, the processor can optionally determine the user's seated weight and / or the user's BCG waveform at reference numeral 503. For example, the processor can segment the raw or filtered BCG signal into fixed or time-varying windows and then average the segmented BCG signal over the windows to determine the user's average BCG waveform. The processor can determine the user's partial seated weight from force data collected by sensors along the toilet ring. At reference numeral 504, the processor can compare the user's force data and / or one or more determined characteristics with stored reference data of known users. For example, the processor can use one or more statistical models (e.g., log-likelihood function, joint Gaussian distribution) to determine correlations between the user's force data and stored force data of multiple known users. In some embodiments, the processor can process the user's force data using a trained classification model that classifies the user as either a known user or an unknown user. The classification model may have been previously trained using force data and / or other data of known users. The processor may then evaluate, at reference numeral 550, whether the correlation or classification indicates that the user is one of the known users (e.g., based on the strength of the correlation, the confidence level, etc.).

[0081]

[0090] At reference numeral 520, a sensing system can record ECG data of a user seated on the toilet. In particular, the sensing system can include an ECG sensor disposed on the top surface of the toilet ring. The ECG sensor can contact the user's buttocks or legs while the user is seated on the toilet, allowing the sensor to capture the user's ECG data. Alternatively, in some embodiments, the sensing system can include an ECG sensor disposed on the toilet seat, a wall positioned near the toilet, and / or one or more handles mounted in any suitable location so that the user can hold the handles while seated on the toilet. The user can hold and / or grasp the handles so that the ECG sensors can contact one or both of the user's hands, allowing the sensors to capture the user's ECG data. The ECG data can be provided to a processor for further processing and / or analysis. In some embodiments, the processor can process the raw ECG data to remove artifacts and / or noise. In some embodiments, the processor may optionally determine one or more ECG-related features at reference numeral 521, including, for example, R-peak amplitude, RR interval, ECG power, heart rate, etc., or averages thereof. In some embodiments, the processor may optionally determine the user's ECG waveform at reference numeral 522. For example, the processor may segment raw or filtered ECG signals into fixed or time-varying windows and then perform averaging or other statistical measurements (e.g., higher-order statistics, peak amplitude, slope, area under the curve, etc.) on the segmented ECG signals over the windows to determine an average ECG waveform or other ECG data for the user. In some embodiments, the process may segment one or more regions of the ensemble mean or ensemble median ECG based on time windows and / or features (e.g., QRS complexes) and then average (or perform other statistical measurements) the ECG signals within those regions.At reference numeral 524, the processor may compare the user's ECG data and / or one or more determined characteristics to stored reference data of known users. For example, the processor may use one or more statistical models to determine correlations between the user's ECG data and stored ECG data of multiple known users. In some embodiments, the processor may process the user's ECG data using a trained classification model that classifies the user as either a known user or an unknown user. The classification model may have been previously trained using the ECG data and / or other data of known users. The processor may then evaluate at reference numeral 550 whether the correlation or classification indicates that the user is one of the known users (e.g., based on the strength of the correlation, confidence level, etc.).

[0082]

[0091] At reference numeral 530, a sensing system can record PPG data of a user seated on the toilet. In particular, the sensing system can include a PPG sensor disposed within the toilet ring. The PPG sensor can detect light reflected by the user's buttocks or legs while the user is seated on the toilet and capture PPG waveform data. In some embodiments, the sensor can detect light reflected by the buttocks corresponding to one or more specific wavelengths. For example, in some embodiments, the sensor can detect reflected red light, infrared light, and / or green light. The PPG data can be provided to a processor for further processing and / or analysis. In some embodiments, the processor may process the raw PPG data to remove artifacts and / or noise. In some embodiments, the processor can optionally determine one or more PPG-related features, including, for example, DC amplitude, peak systolic (SP) amplitude, SP-SP interval, heart rate, etc., or an average thereof, at reference numeral 531. In some embodiments, the processor may determine PPG-related features from multiple wavelengths of reflected light (e.g., red light, infrared light, and / or green light) and combine these PPG-related features to generate new features that facilitate user identification. For example, in some embodiments, the processor may determine DC amplitude from reflected red light and DC amplitude from reflected infrared light. The processor may then determine a DC amplitude ratio (e.g., DC red light / DC infrared) that can be used to distinguish users. In some embodiments, the processor may optionally determine the user's PPG waveform at reference numeral 532. For example, the processor may segment the raw or filtered PPG signal into fixed or time-varying windows and then perform averaging or other statistical measurements (e.g., higher-order statistics, peak amplitude, slope, area under the curve, etc.) on the segmented PPG signal over the window to determine an average PPG waveform or other PPG data for the user.In some embodiments, the process may segment one or more regions of the ensemble average PPG based on time windows and / or features (e.g., systolic peak, diastolic peak, etc.) and then average the PPG signals within those regions (or perform other statistical measurements). At reference numeral 534, the processor may compare the user's PPG data and / or one or more determined characteristics with stored reference data of known users. For example, the processor may use one or more statistical models to determine correlations between the user's PPG data and stored PPG data of multiple known users. In some embodiments, the processor may process the user's PPG data using a trained classification model that classifies the user as either a known user or an unknown user. The classification model may have been previously trained using the PPG data and / or other data of known users. The processor may then evaluate, at reference numeral 550, whether the correlation or classification indicates that the user is one of the known users (e.g., based on the strength of the correlation, confidence level, etc.).

[0083]

[0092] At reference numeral 540, the sensing system can record impedance data of a user seated on the toilet. In particular, the sensing system can include electrodes or conductive elements capable of measuring impedance associated with the user when the user's skin is in contact with the conductive elements. The conductive elements can form a closed circuit with a portion of the user's anatomy (e.g., thigh-to-thigh, foot-to-foot) to measure the user's bioimpedance. The bioimpedance data can be provided to a processor for further processing and / or analysis. At reference numeral 544, the processor can compare the user's bioimpedance data and / or one or more determined characteristics with stored reference data of known users. For example, the processor can use one or more statistical models to determine correlations between the user's bioimpedance data and stored bioimpedance data of multiple known users. The bioimpedance data can include amplitude and frequency information, which can be used to identify the user. For example, in some embodiments, the processor can compare the user's average impedance at a predetermined frequency with stored average impedances of known users at the predetermined frequency to identify the user. In some embodiments, the processor can process the user's bioimpedance data using a trained classification model that classifies the user as either a known user or an unknown user. The classification model may have been previously trained using the bioimpedance data and / or other data of known users. The processor can then evaluate 550 whether the correlation or classification indicates that the user is one of the known users (e.g., based on the strength of the correlation, confidence, etc.).

[0084]

[0093] In response to determining whether the correlation meets one or more predetermined criteria at reference numeral 550, the processor may identify the user. For example, if the correlation with reference data of a known user is sufficiently high (e.g., above a predetermined threshold), or if multiple types of data are sufficiently highly correlated (e.g., above one or more predetermined thresholds), the processor may identify the user as the known user at reference numeral 551. If the correlation is low or does not meet the predetermined criteria, the processor may indicate to the user that the user could not be identified at reference numeral 552 and / or prompt the user to provide identifying information (e.g., similar to that described with respect to step 401 or step 402 of FIG. 4A).

[0085]

[0094] For illustrative purposes, FIG. 7 shows an example of different users' data points plotted on a scatter plot, according to an embodiment. Each data point may represent or indicate one or more physiological characteristics, conditions, and / or other information of a user. For example, a scatter plot may be a technique for visualizing a user's physiological characteristics, conditions, and / or other information, in which multiple features associated with the user's physiological characteristics, conditions, and / or other information are assigned to different axes, and each user's data is plotted on those axes accordingly. Each data point may be associated with a different measurement of the user taken, for example, using a sensing system or device described herein. For example, each data point may be associated with a measurement of the user taken at a different time when the user used a toilet or other urinal device (e.g., during a different seated session on the toilet). Alternatively or additionally, for a user who may have been instructed to go through an initiation process such as that described above in FIGS. 4A-4B , one or more data points for that user may be associated with a different stage of the initiation process (e.g., when the user is instructed to sit in a different position or when the user is instructed to take n measurements, as described above). As shown in Figure 7, a first user (e.g., an intended user) may have multiple data points that can be grouped together, for example, based on cluster analysis. Similarly, a second user (e.g., another regular seated person) may have multiple data points that can be grouped together, for example, based on cluster analysis. Given the grouping of both users' data points, the systems and devices described herein may be configured to determine whether new data points of the unknown user are sufficiently similar (e.g., correlated) with data points of either user to identify the unknown user as the first user, the second user, or a new user. While data for two users is shown in Figure 7, it may be understood that data for any number of users may be stored by the systems and devices described herein and referenced to identify a user when new data for that user is measured.

[0086]

[0095] Referring again to FIG. 5 , while subprocesses 501-504, 520-524, 530-534, and 540-544 are shown as separate subprocesses, it can be understood that one or more of these processes can be performed together, e.g., sequentially and / or simultaneously. Furthermore, in some embodiments, one or more of the force data (including BCG data), ECG data, PPG data, bioimpedance data, and / or characteristics determined therefrom can be combined or evaluated together and used to determine the identity of the user (e.g., by comparing or correlating with reference data). For example, in some embodiments, seated weight and weight or posture distribution can be evaluated together to determine the identity of the user. In some embodiments, the user's seated weight and bioimpedance can be evaluated together to determine the identity of the user. In some embodiments, the user's seated weight and ECG can be evaluated together to determine the identity of the user.

[0087]

[0096] In some embodiments, a user's sensor data measured during a live session may be associated with the identified user (e.g., associated with the user's user identifier) ​​and stored to be used as future baseline data for that user. For many users, physiological data may change over time, for example, based on changes in circumstances and / or health status. Thus, unobtrusive health monitoring systems with which users typically interface, such as toilets or other toilet devices, may be well-suited to track changes in such users' physiological data.

[0088]

[0097] 6 illustrates a processor 600 for identifying a user, according to an embodiment, where the processor tracks the user's data and can passively adapt the user's biological profile or biometric identity over time. Process 600 may be performed by a processor, including, for example, a processor on-board a sensing system or device (e.g., a processor similar to processor 120 and / or processor 220 described above with reference to FIGS. 1 and 2A-2B) or a processor of a remote computing device to which the sensing system is coupled (e.g., processor 272 described above with reference to FIG. 2). Process 600 may include one or more portions similar to process 400 and / or process 500 described above. Accordingly, specific details of these portions will not be provided again in detail herein.

[0089]

[0098] At reference numeral 601, a sensing system (e.g., sensing system 100, 200, or 300) can record sensor data (e.g., force data, BCG data, ECG data, temperature data, PPG data, impedance data, etc.) while a user is seated on the toilet, for example, similar to that described with reference to reference numeral 401 of process 400. The sensing system can provide this data to a processor. At reference numeral 602, the processor can optionally extract one or more features (e.g., posture, dynamic weight, seated weight, ECG, BCG, PPG, bioimpedance, etc.) from the sensor data. At reference numeral 603, the processor can automatically compare the user's sensor data and / or one or more extracted features from the sensor data with previously measured and stored sensor data and / or extracted features, for example, similar to that described with reference to reference numerals 403 and 404 of process 400 and / or reference numerals 504, 524, 534, and 544 of process 500. As described above, in some embodiments, the processor may perform the comparison by assessing the correlation between the user's sensor data or extracted features and reference data of one or more known users. Alternatively or additionally, in some embodiments, the processor may perform the comparison by processing the data using one or more machine learning algorithms (e.g., classification algorithms).

[0090]

[0099] At reference numeral 604, the processor may identify whether the sensor data and / or extracted features are likely to be of the known user based on the output of the comparison, e.g., similar to what was described with reference to reference numeral 404 of process 400 and / or reference numeral 550 of process 500. The processor may then associate the sensor data and / or extracted features with the known user at reference numeral 605, e.g., similar to what was described with reference to reference numeral 404 of processor 405.

[0091]

[0100] By constantly or repeatedly associating a new user's sensor data with the user (e.g., by associating new sensor data with the user's identifier), the processor may be configured to adapt the user's biological profile or biometric identification over time. At reference numeral 606, the processor may be configured to update the reference user's data over time. For example, as exemplarily shown in FIG. 8, the data points associated with a user may move over time. FIG. 8 shows an example of a user's data points plotted on a scatter plot, similar to FIG. 7. Each data point may represent or indicate one or more physiological characteristics, conditions, and / or other information of the user. Over time (e.g., over multiple seated sessions), a user's condition may change due to, for example, weight loss, new medication, new environment, etc., and these changes will be reflected in the user's data points.

[0092]

[0101] Referring again to FIG. 6 , the processor may be configured at 606 to track these physiological changes of the user over time and update one or more baseline characteristics of the user. In some embodiments, the processor may be configured at 607 to monitor and detect degree of disease risk over time. For example, the processor may be configured to compare the user's sensor data (or information extracted therefrom) to predetermined indicators indicative of various health conditions. When the user's data moves toward a predetermined threshold or other indicator indicative of a health condition, the processor may be configured to notify the user of such movement. In some embodiments, the processor may be configured at 608 to communicate with one or more other computing devices (e.g., the user device or a third-party device) to inform the user or a third-party clinician or caregiver of the user's condition.

[0093]

[0102] Although the systems, devices, and methods are described herein with respect to a toilet seat or toilet bowl, it will be understood that the systems, devices, and methods described herein may be implemented in other types of devices. For example, the systems, devices, and methods may perform user identification in other types of sensing systems, including wearable devices (e.g., armbands, wristbands, headbands, glasses, etc.), scales, exercise equipment, etc.

[0094]

[0103] While various inventive embodiments have been described and illustrated herein, those skilled in the art will readily envision various other means and / or structures for performing the functions and / or results and / or obtaining one or more of the advantages described herein. Each such variation and / or modification is deemed to be within the scope of the inventive embodiments described herein. More generally, those skilled in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are exemplary, and that the actual parameters, dimensions, materials, and / or configurations will depend on the particular application or applications for which the inventive teachings are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific inventive embodiments described herein. Accordingly, the foregoing embodiments are presented by way of example only, and it should be understood that, within the scope of the appended claims and their equivalents, inventive embodiments may be practiced other than as specifically described and claimed. Inventive embodiments of the present disclosure are directed to each individual feature, system, article, material, and / or method described herein. Furthermore, any combination of two or more of such features, systems, articles, materials, and / or methods, if such features, systems, articles, materials, and / or methods are not mutually inconsistent, is included within the inventive scope of the present disclosure.

[0095]

[0104] Also, various inventive concepts may be embodied as one or more methods, examples of which are provided. The actions performed as part of a method may be ordered in any suitable manner. Thus, embodiments may be constructed in which actions are performed in an order different from that illustrated, and these embodiments may include performing some actions simultaneously although shown as sequential actions in the illustrated embodiments.

Claims

1. an array of sensors coupled to the waste receptacle and disposed on a seat including a surface on which a user can sit, the array of sensors configured to measure sensor data present on the seat when the user is sitting on the seat; a processor operably coupled to the series of sensors, the processor comprising: receiving a signal indicative of the measured sensor data; responsive to receiving the signal, determining one or more physiological characteristics related to the user based on the measured sensor data; correlating the determined one or more physiological characteristics with historical user baseline data stored in memory; Identifying the user as one of the past users based on the correlation. a processor configured to: a sensing system including:

2. The sensing system of claim 1 , wherein the series of sensors includes force sensors configured to collectively measure forces present on the seat when the user is seated on the seat.

3. 3. The sensing system of claim 2, wherein the series of sensors further includes a scale device configured to measure a force present on the scale device when the user is seated on the seat and one or more of the user's feet are resting on the scale device.

4. The sensing system of claim 2 or 3, wherein the one or more physiological characteristics include at least one of seated weight, ballistocardiogram (BCG), or posture of the user.

5. the one or more force sensors a first force sensor and a second force sensor located near a front end of the seat; a third force sensor and a fourth force sensor located near a rear end of the seat; The sensing system according to claim 2 or 3, comprising:

6. The sensing system of claim 1 , wherein the series of sensors further comprises a temperature sensor configured to measure the core body temperature of the user.

7. The sensing system of claim 1 , wherein the series of sensors further comprises an electrocardiogram (ECG) sensor.

8. The ECG sensor a first lead electrode configured to contact the user's thigh; a second lead electrode configured to contact a first portion of another thigh of the user; a driven right leg (DRL) electrode configured to contact a second portion of the other thigh of the user; The sensing system of claim 7 , comprising:

9. The sensing system of claim 1 , wherein the series of sensors further comprises a photoplethysmography (PPG) sensor.

10. The sensing system of any one of claims 1 to 9, wherein the series of sensors further comprises one or more impedance sensors disposed on the seat.

11. The one or more impedance sensors a first electrode; a second electrode; and a circuit coupled to the first electrode and the second electrode, Passing a current between the first electrode and the second electrode; outputting a signal indicative of the voltage between the first electrode and the second electrode; a circuit configured as follows: Including, The processor is further configured to determine a bioimpedance of the user based on the signal. The sensing system of claim 10.

12. 11. The sensing system of claim 10, wherein the one or more impedance sensors include four impedance sensors, the four impedance sensors forming a drive circuit configured to determine the bioimpedance of the user when the user is seated on the seat.

13. The four impedance sensors are: a first impedance sensor and a second impedance sensor disposed on a first portion of the seat; a third impedance sensor and a fourth impedance sensor disposed on a second portion of the seat, the second portion being on an opposite side of the seat from the first portion; The sensing system of claim 12 , comprising:

14. the first impedance sensor and the third impedance sensor are disposed in a rear portion of the seat and are configured to operate as excitation electrodes; the second impedance sensor and the fourth impedance sensor are disposed in a front portion of the seat and configured to operate as sensing electrodes; The sensing system of claim 13.

15. the first impedance sensor and the fourth impedance sensor are disposed near an outer edge of the seat and configured to operate as excitation electrodes; the second impedance sensor and the third impedance sensor are positioned near an interior region of the seat adjacent an opening of the waste receptacle and configured to operate as sensing electrodes; The sensing system of claim 13.

16. recording sensor data of a user seated on the toilet with a sensing system including an array of sensors positioned on the toilet seat; extracting, by a processor operatively coupled to the series of sensors, one or more features of the recorded sensor data; comparing, by the processor, the sensor data or the one or more characteristics to reference data of a plurality of known users; determining, by the processor and based on the comparing, an identity of the user seated on the toilet; A method comprising:

17. Determining the identity of the user includes: determining a correlation between the sensor data or the one or more features of the recorded sensor data and the reference data of the plurality of known users; evaluating whether the correlation indicates that the user is one of the plurality of known users based on a statistical model; and 17. The method of claim 16, comprising:

18. 17. The method of claim 16, wherein the series of sensors includes a force sensor, and the sensor data includes a force present on the seat measured by the force sensor when the user is seated on the seat.

19. 20. The method of claim 18, wherein the series of sensors further includes a scale device, and the sensor data includes a force present on the scale device measured by the scale device when the user is seated on the seat and one or more of the user's feet are resting on the scale device.

20. 20. The method of claim 18 or 19, wherein the one or more features of the recorded sensor data include at least one of seated weight, ballistocardiogram (BCG), or posture of the user.

21. The method of any one of claims 16 to 20, wherein the set of sensors further comprises a temperature sensor, and the sensor data comprises the user's core body temperature measured by the temperature sensor.

22. The method of any one of claims 16 to 21, wherein the series of sensors further comprises an electrocardiogram (ECG) sensor.

23. 23. The method of any one of claims 16 to 22, wherein the series of sensors further comprises a photoplethysmography (PPG) sensor.

24. The method of any one of claims 16 to 23, wherein the series of sensors further comprises one or more impedance sensors.

25. The one or more impedance sensors a first electrode; a second electrode; and a circuit coupled to the first electrode and the second electrode, Passing a current between the first electrode and the second electrode; outputting a signal indicative of the voltage between the first electrode and the second electrode; a circuit configured as follows: Including, The processor is further configured to determine a bioimpedance of the user based on the signal.

25. The method of claim 24.

26. 25. The method of claim 24, wherein the one or more impedance sensors include four impedance sensors, the four impedance sensors forming a drive circuit configured to determine the bioimpedance of the user when the user is seated in the seat.

27. The four impedance sensors are: a first impedance sensor and a second impedance sensor disposed on a first portion of the seat; a third impedance sensor and a fourth impedance sensor disposed on a second portion of the seat, the second portion being on an opposite side of the seat from the first portion; 27. The method of claim 26, comprising:

28. the first impedance sensor and the third impedance sensor are disposed in a rear portion of the seat and are configured to operate as excitation electrodes; the second impedance sensor and the fourth impedance sensor are disposed in a front portion of the seat and configured to operate as sensing electrodes; 28. The method of claim 27.

29. the first impedance sensor and the fourth impedance sensor are disposed near an outer edge of the seat and configured to operate as excitation electrodes; the second impedance sensor and the third impedance sensor are positioned near an interior region of the seat adjacent an opening of a waste receptacle and configured to operate as sensing electrodes; 27. The method of claim 26.

30. 25. The method of claim 24, wherein the comparing comprises correlating at least one of the user's BCG data, ECG data, or PPG data with the reference data of known users.

31. 25. The method of claim 24, wherein the comparing comprises correlating the user's bioimpedance with reference data of known users.

32. 25. The method of claim 24, wherein the comparing further comprises correlating at least one of the user's bioimpedance, PPG, or ECG with reference data of known users.

33. The method of claim 16 , wherein the processor is a processor of a computing device operatively coupled to the set of sensors over a network.

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