Abstract: A method of administering sleep consolidation therapy to a patient to treat a sleep disorder of the patient. The method includes monitoring, via a first number of sensors, a number of characteristics and/or activities of the patient during a number of wake periods of the patient. The method further includes determining, at least in-part from the monitoring of the number of wake periods, a recommended bedtime for the patient for starting a particular sleep period and providing the recommended bedtime for starting the particular sleep period to the patient.

Abstract: A system and method create a framework for personalized sleep hygiene self-experiments to allow users to derive their own discoveries on how the self-experiment has affected their sleep.

Abstract: Some embodiments relate to computer-implemented methods and systems for fidelity improvement of sleep disorder data.

Abstract: A method of providing personalized treatment includes gathering first information (402,404) associated with a user (400), determining a first user profile vector (500) based on first information associated with the user, determining a first treatment plan to move the user from the first user profile vector toward a target user profile vector (506), and providing the first treatment plan to the user.

Abstract: An apparatus and method involve leveraging unobtrusive sleep monitoring technologies, even consumer ones, to predict the phase of a viral infection and is usable for guiding patient treatment and tracking treatment effectiveness. An apparatus and method determine a phase of a viral infection based at least in part upon a data set that is input to an algorithm.

Abstract: A method for cluster-based recommendation generation regarding sleep disorders. A server system transmitting query program code to a client device, wherein the query program code is executable by the client device to transmit one or more response objects encoding a response and further responses to the server system. The server system receiving the one or more response objects from the client device and determining the response and further responses encoded in the response objects. A clustering module of the server system identifying one or more clusters of sleep disorder user data that most closely relate to the determined responses. A recommendation module of the server system identifying a sleep disorder based on the determined responses and clusters. The recommendation module generating one or more recommendations based on the identified sleep disorder, the determined responses and the identified clusters.

Abstract: A method is provided of generating behavior recommendations for a user, and communicating these to a user by means of a linguistic message, and wherein the recommended behavior or properties of the linguistic message are configured based on a measure of circadian inconsistency for the user. The measure of circadian inconsistency is derived by comparing an expected circadian curve of the user (e.g. an average curve derived from historical data for the user) with an empirical circadian curve for a given day. A deviation between the two provides an indication of the circadian inconsistency for the given day, and this is used to inform content, timing, wording, or other properties of the behavior recommendations.

Abstract: A method of determining a sleep phenotype of a subject includes defining a stimulus profile, defining a response profile, administering the stimulus profile to the subject, collecting response data of the subject in accordance with the response profile; comparing the response data to a set of reference data, and determining sleep phenotype based on the comparison of the response data to the reference data. The method is characterized by determining sleep phenotype based on measuring responses to administered stimuli rather than observing typical physiological data observed during periods of sleep.