Oura Health

Abstract Methods, systems, and devices for controlling external devices are described. A method may include receiving physiological data associated with a user from a wearable device, and identifying one or more physiological states, physical activities, or both, associated with the user based on the physiological data. Physiological states may include physiological states associated with waking up, falling asleep, anxiety, relaxation, and the like. The method may further include transmitting an instruction to one or more external devices based on the one or more physiological states, physical activities, or both, where the instruction is configured to selectively modify one or more operational parameters associated with the one or more external devices.

Abstract Methods, systems, and devices for menstrual cycle phase identifier are described. A system may be configured to receive physiological data collected over a plurality of days, where the physiological data includes at least temperature data. Additionally, the system may be configured to determine a time series of temperature values taken over the plurality of days where the time series includes a plurality of menstrual cycles for the user. The system may then identify morphological features in the time series and identify menstrual cycle phases in the time series based on the morphological features. The system may cause the graphical user interface to display the identified menstrual cycle phases.

Abstract Methods, systems, and devices for adaptive sensors are described. A system may acquire physiological data from a user via multiple optical channels of a wearable device, where each optical channel includes a light-emitting component and a photodetector. The system may determine respective measurement quality metrics and respective power consumption metrics associated with each optical channel based on the physiological data. Additionally, the system may select one or more optical channels of the multiple optical channels of the wearable device based on a comparison of the respective measurement quality metrics and the respective power consumption metrics associated with each optical channel. The system may acquire additional physiological data using the one or more optical channels based on the selecting.

Abstract Methods, systems, and devices for menstrual cycle onset prediction are described. The method may include receiving physiological data associated with a user from a wearable device, the physiological data including at least temperature data. The method may include fitting the received temperature data to a trigonometric or polynomial function including a plurality of features and calculating a duration between the plurality of features and a corresponding plurality of menstrual cycle onset days. The method may include estimating a future menstrual cycle onset day that the user experiences a first day of a menstrual cycle based on applying the duration to a most recent feature of the trigonometric or polynomial function. In some cases, the method may include causing a graphical user interface of a user device to display an indication of the estimated future menstrual cycle onset day.

Abstract Methods, systems, and devices for adjusting power consumption of a wearable device based on heart rate data are described. The method may include acquiring first physiological data from a user in accordance with a first measurement configuration associated with a first power consumption and determining a heart rate of the user based on the first physiological data. Further, the method may include comparing the heart rate to a set of heart rate ranges associated with the user and selecting a second measurement configuration associated with a second power consumption based on the heart rate of the user falling into a second heart rate range. Moreover, the method may include acquiring second physiological data in accordance with the second measurement configuration.

Abstract Methods, systems, and devices for ring-shaped housing alignment features are described. The wearable ring device may include an inner shell and a printed circuit board. The inner shell may include a plurality of apertures, a first set of alignment features including planar regions that are formed into an arcuate ridge of the inner shell, and a second set of alignment features. The plurality of apertures may be aligned within the planar regions. The printed circuit board may include optoelectronic components and rigid regions. The rigid regions are configured to engage with the first set of alignment features to align the optoelectronic components in a first direction, and one or more features of the printed circuit board are configured to engage with the second set of alignment features to align the optoelectronic components in other directions such that the optoelectronic components are aligned with the plurality of apertures.

Abstract Methods, systems, and devices for wearing detection are described. A method may include directing light from a first light emitting element to a first light detecting element via an optical interface, at least one of the first light emitting element or the first light detecting element dedicated to detecting a level of surface contact at the optical interface. The method may include measuring, via the first light detecting element, an amount of escaped light which escaped the optical interface, where the amount of escaped light is indicative of the level of surface contact. The method may further include controlling an activation of a second light emitting element and a second light detecting element based on the level of surface contact, at least one of the second light emitting element or the second light detecting element dedicated to measuring a physiological phenomenon at a user of the wearable device.

Abstract Methods, systems, and devices for estimating skin tone using a machine learning (ML) model are described. A wearable device may transmit light using a light-emitting component, and generate a signal based on the light received at a photodetector. In some examples, a strength of the received signal may be maintained within a signal strength band. The wearable device may identify a data set pair based on the signal, the data set pair including the signal strength band and a transmit power parameter that corresponds to the signal strength band. The data set pair may be inputted into an ML model and the ML model may output a skin tone metric for the user. The estimated skin tone metric may then be used to adjust measurement parameters used by the wearable device to improve a quality of physiological data, or validate algorithms used by the wearable device across skin tones.