Temperature sensors are configured to sense a temperature for the sleeper and transmit temperature readings. A controller is configured to receive temperature readings; and send to a heating subsystem instructions to initiate a warming process that raises a distal temperature of the sleeper more than a proximal temperature of the sleeper. The heating subsystem that may include a heating element that, when engaged, can raise the distal temperature of the sleeper more than the proximal temperature of the sleeper.

A system includes a memory storing a user profile for a user of the system and machine-readable instructions and a control system including one or more processors configured to execute the machine-readable instructions to receive physiological data associated with the user during a sleep session, determine, based at least in part on the received physiological data, a set of sleep-related parameters for the sleep session, subsequent to the sleep session, select one of the set of sleep-related parameters as a targeted parameter, the selection of the targeted parameter being based at least in part on the stored user profile, the set of sleep-related parameters, or both, and cause information to be communicated to the user via a user device, the information being indicative of the targeted parameter, a recommendation associated with improving the targeted parameter for the user in one or more subsequent sleep sessions, or both.

A system includes an electronic contact lens that obtains sensor measurements from integrated motion sensors or other types of sensors and a processing module that estimates a mental state of an individual based on the sensor measurements. The processing module identifies patterns of eye movements and analyzes how these patterns change over time. Based on anatomical relationships between eye movement and mental state, the processing module estimates characteristics of the individual such as fatigue, intoxication, injury, or a medical condition that have known effects on eye movement patterns. The electronic contact lens system generates an output indicative of the estimated mental state to alert the individual to the detected condition or to initiate an automated action.

The various embodiments of the method of the present invention include a method to improving or expanding the capacity of a sleep analysis unit or laboratory, a method sleep analysis testing a patient admitted for diagnosis or treatment of another primary medical condition while being treated or diagnosed for that condition, a method of sleep analysis testing a patient that cannot be easily moved or treated in a sleep analysis unit or laboratory and other like methods.

A method includes receiving physiological data associated with a user during a sleep session. The method also includes determining a sleep-wake signal for the user during the sleep session based at least in part on the received physiological data. The method also includes determining one or more sleep-related parameters for the user during the sleep session based at least in part on the sleep-wake signal. The method also includes determining that the user experienced insomnia during the sleep session based at least in part on at least one of the one or more sleep-related parameters. The method also includes identifying a type for the insomnia experienced by the user based at least in part on the one or more sleep-related parameters.

A method for uterine activity monitoring may include: acquiring a plurality of signals from a plurality of sensors during uterine activity; processing the plurality of signals to extract a plurality of uterine electrical activity characteristics; analyzing the plurality of uterine electrical activity characteristics; and classifying the uterine activity as one of: a preterm labor contraction, a labor contraction, a Braxton-Hicks contraction, and a state of no contraction. A method of assessing over time a pre-term birth risk of a pregnant female may include: calculating a baseline pre-term birth risk score based on a user input; acquiring, over time, a signal from a sensor; analyzing the signal to extract a parameter of interest, such that the parameter of interest comprises a physiological parameter; and calculating an instant pre-term birth risk score based, at least in part, on the parameter of interest and the user input.

Computer implemented biometric methods and systems incorporate sensing biophysical phenomena, translating the phenomena into digital data and transmitting the data to a series of servers operating in an open feedback loop to generate a module. A biometric networking system can include a biometric monitoring cloud computing platform with AI/machine learning augmented models are generated to make user assessments, programs and confidence scores to the healthcare provider systems. The AI/machine learning models can be used by the biometric monitoring network to generate health-related AI processes that analyze relationships treatment techniques and outcomes. AI techniques can be used to calculate movement modeling and confidence scoring including support vector machines, neural networks, and decision trees. The biophysical phenomena may include biometric parameters based on data, such as medical history, exertion, sleep, temperature, cardiovascular events, respiratory events, and muscle and blood pH.

A dynamic wake-up alarm is provided-for, including a clock, a contactless biometric sensor, a processor, memory, and a speaker. The processor may be configured to receive a wake-up rule based on at least two wake-up criteria including a time from the clock and data from the biometric sensor, and evaluate whether the criteria are met to activate an alarm.

A load cell apparatus for use with a bed includes a housing having a top portion and a bottom portion, and a load cell device held by the bottom portion of the housing. The load cell device is structured to generate a signal having a magnitude that is proportional to a first force being applied to the load cell device. The load cell apparatus also includes a button member held by the housing in a manner wherein the button member is structured to engage the load cell device and apply the first force to the load cell device in response to a second force being applied to the top portion of the housing. Also, various systems for monitoring parameters such as weight, sleep quality, fall risk, and/or pressure sore risk that may incorporate such a load cell apparatus.

A patient health management platform accesses a metabolic profile for a patient and biosignals recorded for the patient during a current time period comprising sensor data and/or lab test data collected for the patient. The platform receives patient data recorded during the current time period comprising food items consumed, medications taken, and symptoms experienced by the patient. The platform implements a machine-learned metabolic model to determine a metabolic state of the patient at a conclusion of the current time period by comparing a true representation of the metabolic state and a prediction of the metabolic state. The true representation and the prediction are determined based on the recorded biosignals and the recorded patient data, respectively. The platform generates a patient-specific treatment recommendation outlining instructions for the patient to improve their metabolic state and provides the patient-specific treatment recommendation to the patient device for display to the patient.