Abstract: A device may include: a bed. A sensor may be configured to configured to: sense pressure applied to the bed; and transmit a pressure stream. A plurality of temperature sensors arranged across the bed can be configured to: sense temperature in a particular location of the bed; and transmit a datastream of the sensed temperature. A computing system comprising can be configured to: receive the pressure stream; receive each of the datastreams; identify an apnea event; generate a sequence of heart rate values for the user for cardiac activity; generate a sequence of skin temperature values for the user; determine a change in heart rate; determine a change in skin temperature within the second time window; determine a relationship between the change in heart rate and the change in skin temperature; and determine a severity score for the apnea event based on the relationship.

Abstract: A bed receives one or more data streams. The bed can provide, as input, sleep-data for the user to a disorder-risk classifier and receive, as output, a disorder-risk metric. The disorder-risk classifier can include a model defining relationships between sleep-data and disorder risk. The bed can use the disorder-risk metric for the user reflective of risk that the user will or is experiencing symptoms consistent with a disorder. The bed can intermittently update, after generating the disorder-risk metric, the disorder-risk metric using the data streams by changing the model.

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.

Abstract: Disclosed are systems and techniques for determining biometrics of a user of a bed system based on force data. A bed system can include a support element having at least one leg, at least one force sensor of the at least one leg, the force sensor being configured to sense a force applied to the bed system or the leg, and a controller. The controller can receive at least one force data-stream from the at least one force sensor, the at least one force data-stream representing a force sensed by the force sensor, determine a biometric parameter of a user on the bed system at predetermined time intervals based on processing the at least one force data-stream, generate an aggregate biometric parameter of the user based on aggregating the biometric parameters for the predetermined time intervals, and return the aggregate biometric parameter of the user.