Provided is a biomonitoring device that measures a parameter of a material expelled during use of a toilet by a user. Also provided is a biomonitoring mirror device that identifies a user, detects a febrile illness in a user, dispenses medications/supplements, connects to electrical device accessories in the bathroom, and provides an interactive user interface. Additionally provided is a system for measuring a parameter of a material expelled during use of a toilet by a user. Further provided is a method of determining a physiological parameter of a user.

The disclosed embodiments relate to system, method and apparatus for forming ML sessions so that an AI system can identify, track and diagnose a user through the user's bathroom sessions. As used herein, a session is a period of time during which a user is active in the toilet. The session may include certain inactivity if such inactivity lasts only for a predefined duration. In an exemplary embodiment, a system is configured to capture images of excreta and, using ML algorithms, classifies the toileting session using Digital Biomarkers (DBMs). The ability to create an excreta log to accurately deliver detailed information to doctors and healthcare providers can revolutionize healthcare by notifying when further urine or fecal screening is necessary. The disclosed embodiments of ML and image identification through AI requires no user behavior change and provides a link between medical records and specific excreta patterns.

Provided is a biomonitoring device that measures a parameter of a material expelled during use of a toilet by a user. Also provided is a biomonitoring mirror device that identifies a user, detects a febrile illness in a user, dispenses medications/supplements, connects to electrical device accessories in the bathroom, and provides an interactive user interface. Additionally provided is a system for measuring a parameter of a material expelled during use of a toilet by a user. Further provided is a method of determining a physiological parameter of a user.

The disclosed embodiments relate to system, method and apparatus for forming ML sessions so that an AI system can identify, track and diagnose a user through the user's bathroom sessions. As used herein, a session is a period of time during which a user is active in the toilet. The session may include certain inactivity if such inactivity lasts only for a predefined duration. In an exemplary embodiment, a system is configured to capture images of excreta and, using ML algorithms, classifies the toileting session using Digital Biomarkers (DBMs). The ability to create an excreta log to accurately deliver detailed information to doctors and healthcare providers can revolutionize healthcare by notifying when further urine or fecal screening is necessary. The disclosed embodiments of ML and image identification through AI requires no user behavior change and provides a link between medical records and specific excreta patterns.

Concentrating devices, systems, and methods include those for separating fluids to be sensed (e.g., analytes, such as volatile organic compounds (VOCs) and/or other chemical substances) from other fluid (e.g., a carrier gas, air, etc.) of a fluid mixture received from a target area of a subject's anatomy (e.g., a subject's skin, a wound on a subject, etc.). In some cases, the concentration system may include a housing and a rotor positioned in a compartment of the housing. The housing may receive a fluid mixture in the compartment and rotation of the rotor relative to the housing may separate fluid to be sensed in the fluid mixture from other fluid of the fluid mixture.