The present disclosure provides devices, systems, and methods for the prognosis and management of diseases and conditions. In particular, the present disclosure provides devices, systems, and methods directed to a toilet apparatus for the automatic tracking of a subject's urination and bowel movements to enhance the diagnosis and treatment of various diseases and conditions.

The present disclosure provides devices, systems, and methods for the prognosis and management of diseases and conditions. In particular, the present disclosure provides devices, systems, and methods directed to a toilet apparatus for the automatic tracking of a subject's urination and bowel movements to enhance the diagnosis and treatment of various diseases and conditions.

A an analytical toilet comprising a bowl for receiving excreta comprising a platform for receiving feces; a urine drain; a feces outlet from the bowl; and a urine outlet from the bowl; wherein the platform and drain are separated by a raised hump; at least one first load cell for detecting the weight of the bowl; at least one fecal sensor for detecting at least one property of the feces; and at least one urine sensor for detecting at least one property of the urine is disclosed.

A scale calibration device and method of use. The device may include a base supportable on and movable along a surface to a location. The base further includes a base surface for supporting a scale to be calibrated proximate the location. The device includes a frame assembly connected to the base and operable to support, in a position over the base surface, means for simulating a dead weight, the means being operable to apply a force to the scale supported on the base surface.

A scale calibration device and method of use. The device may include a base supportable on and movable along a surface to a location. The base further includes a base surface for supporting a scale to be calibrated proximate the location. The device includes a frame assembly connected to the base and operable to support, in a position over the base surface, means for simulating a dead weight, the means being operable to apply a force to the scale supported on the base surface.

A method for determining a normalized weight of a non-static item is disclosed. Weight data associated with the non-static item is received from a plurality of load cells. A load cell weight for the non-static item is determined based at least in part on the weight data. The load cell weight for the non-static item is received as an input for a machine learning algorithm. The normalized weight for the non-static item is generated as an output for the machine learning algorithm.

Devices and methods for determining item-specific information for single or multiple items on one or multiple substrates are described. The method includes generating multiple sensor multiple dimensions array (MSMDA) data from multiple sensors, where each of the multiple sensors capture sensor data for one or more items in relation to a substrate. For each item, the method includes determining relationships between the multiple sensors based on characteristics of the MSMDA data, determining a location of the item on the substrate based on at least the determined relationships between the multiple sensors, determining an angular orientation of the item on the substrate based on at least the determined relationships between the multiple sensors, and determining a body position of the subject on the substrate based at least the determined relationships between the multiple sensors, the location of the subject, and the angular orientation of the item.

A system and method for determining the weight gain trend of a user. The weekly weight oscillation is determined, and a future weight trend can be predicted. At least three weeks of weight oscillation trends are typically used to predict future weight trends.

A system and method for determining the weight gain trend of a user. The weekly weight oscillation is determined, and a future weight trend can be predicted. At least three weeks of weight oscillation trends are typically used to predict future weight trends.

An infant sleep device may include a platform for supporting an infant, a base upon which the platform is supported, and one or more weight sensors positioned to measure weight of an infant positioned on the platform.