Abstract: A system and method to determine a sleep disorder in a patient is disclosed. A storage device stores a digital image including a face and a neck of the patient. A database stores previously identified phenotypes and dimensions of facial and neck features. A sleep disorder analysis engine is coupled to the storage device and the database. The sleep disorder analysis engine is operable to identify features of the face and the neck from the image by determining landmarks on the image. The sleep disorder analysis engine classifies at least one phenotype from the image based on comparisons with the database. The sleep disorder analysis engine correlates the at least one phenotype and at least one feature with a sleep disorder. The sleep disorder analysis engine determines a risk score of the sleep disorder based on the correlation of the phenotype and the feature.

Abstract: A method includes receiving physiological data associated with a sleep session of a user. The method also includes identifying a triggering event based at least in part on the physiological data. The method also includes generating image data in response to identifying the triggering event, the image data being reproducible as one or more images of at least a portion of the user during the sleep session. The method also includes causing at least a portion of the image data to be communicated to the user subsequent to the sleep session.

Abstract: A method includes receiving first data associated with a first sleep session of a user. The method also includes determining a first set of sleep-related parameters associated with the first sleep session of the user based at least in part on the first data. The method also includes receiving second data associated with a second sleep session of the user. The method also includes determining a second set of sleep-related parameters associated with the second sleep session of the user based at least in part on the second data. The method also includes receiving third data associated with a variable condition. The method also includes causing one or more indications associated with the variable condition and the first sleep session, the second sleep session, or both to be communicated to the user.

Abstract: A system and method to determine symptoms of respiratory ailments is disclosed. The system includes a transceiver operable to receive data from a monitor attached to a patient. The monitor includes a plurality of sensors, each of the plurality of sensors outputting physiological data related to respiration of the patient. An analytics platform is coupled to the transceiver to analyze the physiological data to determine the occurrence of a symptom of a respiratory condition, disorder or ailment in the patient.