Methods, systems, and devices for miscarriage identification are described. A system may be configured to receive physiological data associated with a user that is pregnant and collected over a plurality of days, where the physiological data includes at least temperature data. Additionally, the system may be configured to determine a time series of temperature values. The system may then identify that the temperature values are lower than a pregnancy baseline of temperature values for the user and detect an indication of an early pregnancy loss of the user. The system may generate a message for display on a graphical user interface on a user device that indicates the indication of the early pregnancy loss.

Systems and methods are disclosed that employ several or numerous factors in the determination of a glycemic urgency index (GUI), which may be based on a measured blood glucose level as well as other factors. The other factors may include time derivatives of the glucose level and/or other factors, e.g., user-entered data, data measured by other sensors or received from a network source, or historical data. The GUI is then presented to the user in an interesting way, e.g., via a background color or other inconspicuous notifier, e.g., on a mobile device such as a smart phone. The GUI may also be employed in the triggering of actionable alerts and alarms on an electronic device for the user. The GUI, or another index calculated from combinations of the variables and parameters described, may further be employed to drive a medicament delivery device such as a pump.

Embodiments of the present disclosure provide systems, apparatuses and methods for a facility, such as a feedlot, barn, greenhouse, hospital, school or production facility, with synchronous communication and control of LED lights in lighting arrays for the emission of photon pulses to induce the stimulation of desired biological responses. Further provided herein are mobile real time location units to assist the LED lighting arrays to identify the location or status of an organism and to adjust their photon pulse emissions based on the needs of the organism.

Methods, systems, and devices for menstrual cycle onset prediction are described. The method may include receiving physiological data associated with a user from a wearable device, the physiological data including at least temperature data. The method may include fitting the received temperature data to a trigonometric or polynomial function including a plurality of features and calculating a duration between the plurality of features and a corresponding plurality of menstrual cycle onset days. The method may include estimating a future menstrual cycle onset day that the user experiences a first day of a menstrual cycle based on applying the duration to a most recent feature of the trigonometric or polynomial function. In some cases, the method may include causing a graphical user interface of a user device to display an indication of the estimated future menstrual cycle onset day.