Abstract: A controller of a bed is configured to receive one or more different types of sleep data, determine a sleep regularity factor for the user and a chronotype of the user, access, a machine learning model trained to determine a sleep onset time for the user, the machine learning model being trained based on (i) the one or more different types of sleep data including data that is representative of historic sleep times and historic wake time for the user, (ii) the sleep regularity factor of the user, and (iii) the chronotype of the user, determine e, based on an output of the machine learning model, a sleep onset time for the user, determine a target time to communicate a bedtime reminder notification to the user, and responsive to determining a target time to communicate a bedtime reminder notification to the user, communicate the bedtime reminder notification to the user.

Abstract: Some aspects provide an approach for optimizing sleep quality by addressing several components of sleep: falling asleep, maintaining sleep, and waking up refreshed. Some aspects include example systems, devices, and techniques that describe the significance of distal and core body temperatures to achieve these sleep components. For example, by facilitating an increase in distal skin temperature, the example systems, devices, and techniques promote a decrease in core body temperature, which can be associated with reduced sleep onset latency. Maintaining a steady decrease in core body temperature during the initial sleep cycle can support prolonged sleep maintenance. As users approach their wake time, an increase in core body temperature can be encouraged to enhance alertness and improve the waking experience. These example systems, devices, and techniques allow for a tailored sleep environment (e.g.

Abstract: This document describes systems, methods, devices, and other techniques used for improving a sleeper's body thermoregulation during sleep. One aspect is a system, comprising a bed with a heating element and a cooling element and a controller configured to receive a current sleep state of a sleep stage sequence for a user in the bed, when the current sleep state is a non-rapid eye movement (NREM) state, activating the heating element to increase a skin temperature of the user, and when the current sleep state is a rapid eye movement (REM) state, activating the cooling element to decrease the skin temperature of the user.

Abstract: A method for detecting body position or posture of a user is provided. The method includes arranging a plurality of temperature sensors at a plurality of locations on a sleeping surface. The method includes collecting a plurality of sensor outputs from the plurality of temperature sensors. The method includes determining a plurality of associations between the plurality of locations and the plurality of sensor outputs. The method includes determining, based on the plurality of associations, the body position or posture of the user. Also provided is a system for detecting body position or posture of a user. The system includes a sleeping surface, a plurality of temperature sensors arranged at a plurality of locations on the sleeping surface, and a processor communicatively coupled to the plurality of temperature sensors.

Abstract: One or more sensors are configured to sense physiological phenomena of a user of the bed; and generate one or more data streams based on the sensing of the physiological phenomena of the user. A computing system may include at least one processor and computer memory, the computing-system configured to: receive the one or more data streams for a plurality of night's sleep for the same user; generate, using the one or more data streams, digital cognitive behavioral therapy for insomnia (dCBTI) parameters for the user; and cause a computing device to operate a dCBTI treatment for the user according to the dCBTI parameters.

Abstract: One general aspect includes a bed having a mattress. The system also includes one or more sensors configured to: sense physiological phenomenon of a user of the bed and generate one or more data streams based on the sensing of the physiological phenomenon of the user. The system also includes a computing system that may include at least one processor and computer memory, the computing-system configured to: receive the one or more data streams and generate, using the one or more data streams, an insomnia-risk metric for the user reflective of risk that the user will or is experiencing symptoms may include with insomnia.