Abstract: Methods, systems, and devices for emotional well-being correlation are described. A system may receive physiological data associated with a user from a wearable device worn by the user, environmental data including characteristics of an environment of the user, and feedback data from the user indicating a physical state or a psychological state of the user when experiencing the at least one environmental characteristic. The system may additionally determine a set of relationships between the received environmental data and the received feedback data, the received physiological data, or both. Additionally, the system may generate a message for the user based on the set of relationships and display the message to the user via a graphical user interface (GUI) of a user device. The message may include instructions for regulating the physical state of the user, the psychological state of the user, or both, when experiencing the characteristics of the environment.

Abstract: Methods, systems, and devices for determining a circadian rhythm chronotype are described. A system may be configured to receive a first set of physiological data collected over a period of time and receive a second set of physiological data collected over a previous sleep day. Additionally, the system may be configured to classify, using a machine learning model, the first set of physiological data into the circadian rhythm chronotype. The system may then compare the determined circadian rhythm chronotype and the received second set of physiological data. The system may cause a graphical user interface of the user device to display a message associated with the comparison, the determined circadian rhythm chronotype, the received second set of physiological data, or a combination thereof.

Abstract: Methods, systems, and devices for providing health-related mini-insights using wearable devices are described. Baseline physiological data is collected from a user via a wearable device, where the baseline physiological data is associated with any physiological parameter, including heart rate data, restorative time, temperature, respiratory rate, blood oxygen saturation, and the like. Additional physiological data is then collected from the user via the wearable device and compared to the user’s baseline physiological data for the respective physiological parameter(s). Based on the comparison, a satisfaction of a trigger condition for providing a health-related insight associated with one or more physiological parameters is identified, and the health-related insight is displayed to the user via a graphical user interface (GUI).

Abstract: Methods, systems, and devices for temperature analysis are described. The method may include receiving physiological data associated with a user collected via a first set of sensors of a wearable device. The physiological data may include skin temperature data. The method may include receiving surrounding temperature data associated with an environment surrounding the user. The surrounding temperature data may be collected via the first set of sensors, a second set of sensors, or both. The method may additionally include identifying one or more physiological characteristics associated with the user based at least in part on a comparison of the skin temperature data and the surrounding temperature data, and causing a graphical user interface (GUI) of a user device to display an indication of the one or more physiological characteristics, a message or alert associated with the one or more physiological characteristics, or both.

Abstract: Methods, systems, and devices for sleep analysis are described. The method may include receiving, at a first application, physiological data associated with a user that is collected via a set of sensors of a wearable device. The method may include receiving, at the first application and from a second application, information indicating a wakeup time restriction for the user. In some cases, the method may include determining, by the first application, a bedtime for the user based on the physiological data and the wakeup time restriction for the user. In some other cases, the method may include identifying, by the first application, sleep staging information for the user while the user is sleeping based on the physiological data, and further include determining a wakeup time for the user based on the sleep staging information and the wakeup time restriction for the user from the second application.

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.