Abstract: An example technique may include tracking motion of a user wearing the wearable device using at least first sensors of one or more sensors of the wearable device. The technique may also include tracking a physical state of the user using at least second sensors of the one or more sensors of the wearable device. The technique may also include determining whether an application of the wearable device has been launched. The technique may also include determining an action category of the user based at least in part on at least one of the motion of the user, the physical state of the user, or whether the application has been launched. The technique may also include collecting heartrate data of the user. The technique may also include categorizing the heartrate data based at least in part on the determined action category.

Abstract: Techniques are provided for tracking heartrate metrics using different operating modes associated with different contexts of a wearable device. For example, a heartrate sensor of the wearable device may be operated in a first operating mode when an activity is being tracked within an application session of a particular application. The heartrate sensor may be operated in a second operating mode after detecting conclusion of the activity within the activity session (e.g., during sedentary time).

Abstract: A user domain concept (UDC) node of a personalized data graph may be generated by a user device. The UDC node may include customized information that represents some user-customized portion of health data, e.g., data obtained from an electronic health record (EHR) system. The UDC node may be generated based on a customization request, e.g., a request from a user to customize the portion of the health data and/or other aspects. The UDC node may store relationship information between nodes and be used to improve the functioning of a user interface that presents the health data. This may be achieved, at least in part, by providing user customization of the user interface (e.g., favoriting records, adding records to lists, giving records nicknames).

Abstract: Techniques are provided for tracking heartrate metrics using different operating modes associated with different contexts of a wearable device. For example, a heartrate sensor of the wearable device may be operated in a first operating mode when an activity is being tracked within an application session of a particular application. The heartrate sensor may be operated in a second operating mode after detecting conclusion of the activity within the activity session (e.g., during sedentary time).

Abstract: Embodiments of the present disclosure can provide systems, methods, and computer-readable medium for tracking the heartrate of a user using different techniques associated with different contexts. For example, motion of a user wearing a wearable device can be tracked using at least first sensors of the one or more sensors. The physical state of the user can also be tracked using at least second sensors of the one or more sensors. In some cases it can be determines whether an application of the wearable device has been launched. Additionally, an activity category of the user can be determined based at least in part on the motion of the user, the physical state of the user, and/or whether the application has been launched. Heartrate data of the user can be collected, and the heartrate data can be categorized based at least in part on the determined category.

Abstract: Embodiments of the present disclosure can provide systems, methods, and computer-readable medium for tracking the heartrate of a user using different techniques associated with different contexts. For example, motion of a user wearing a wearable device can be tracked using at least first sensors of the one or more sensors. The physical state of the user can also be tracked using at least second sensors of the one or more sensors. In some cases it can be determines whether an application of the wearable device has been launched. Additionally, an activity category of the user can be determined based at least in part on the motion of the user, the physical state of the user, and/or whether the application has been launched. Heartrate data of the user can be collected, and the heartrate data can be categorized based at least in part on the determined category.