Abstract: A system for development of an algorithm for analysis of sensor data includes one or more wearable sensor devices, a smart device, and a cloud computing platform. The sensors in the wearable sensor device produce sensor data (e.g., physiological data) from a user that can be processed by a software algorithm in the wearable sensor device or by a connected smart device (e.g., a smartphone) via cloud computing, producing an algorithm output. The raw sensor data along with other information, such as the algorithm output and sensor data features can be sent to the cloud computing platform for storage and to enable developers to access the data in order to modify the software algorithms. The wearable sensor device can be configured to send more or less data to the cloud computing platform according to the performance of the software algorithm.

Abstract: This invention relates to systems and methods for treating sleep apnea, which include a first dry electrode for detecting EEG signals of a user, positioned at or near a head of a user; a sleep stage processor for determining a sleep stage of the user based, at least in part, on the EEG signals detected by the first dry electrode, and a pressure delivery device for delivering a controllable stream of air to at least one of a nose and a mouth of the user, the stream of air having a pressure selected based, at least in part, on the sleep stage determined by the sleep stage processor.

Abstract: Systems and methods for monitoring EEG signals include dry electrodes that can be used in sleep monitoring systems. In one aspect, a system for sleep stage monitoring and measurement includes a first dry electrode for detecting EEG signals of a user, a housing, and a sleep stage processor disposed within the housing. The first dry electrode is positioned at or near a head of the user. The sleep stage processor processes the EEG signals to determine a sleep stage of the user.

Abstract: A device and a method for waking a user in a desired sleep state. The device may predict an occurrence when the user will be in the desired sleep state, such as light sleep, and wake the user during that predicted occurrence. In one embodiment, a user may set a wake-up time representing the latest possible time that the user would like to be awakened. The occurrence closest to the wake-up time when the user will be in light sleep may be predicted, thereby allowing the user to sleep as long as possible, while awakening in light sleep. To predict when the user will be in the desired sleep state, the user's sleep state may be monitored during the night or sleep experience and the monitored information may be used in predicting when the user will be in the desired sleep state.