Abstract: In one implementation, a method is performed for tiered posture awareness. The method includes: while presenting a three-dimensional (3D) environment, via the display device, obtaining head pose information for a user associated with the computing system; determining an accumulated strain value for the user based on the head pose information; and in accordance with a determination that the accumulated strain value for the user exceeds a first posture awareness threshold: determining a location for virtual content based on a height value associated with the user and a depth value associated with the 3D environment; and presenting, via the display device, the virtual content at the determined location while continuing to present the 3D environment via the display device.

Abstract: In some implementations, a method includes: while presenting a 3D environment, obtaining user profile and head pose information for a user; determining locations for visual cues within the 3D environment for a first portion of a guided stretching session based on the user profile and head pose information; presenting the visual cues at the determined locations within the 3D environment and a directional indicator; and in response to detecting a change to the head pose information: updating a location for the directional indicator based on the change to the head pose information; and in accordance with a determination that the change to the head pose information satisfies a criterion associated with a first visual cue among the visual cues, providing at least one of audio, haptic, or visual feedback indicating that the first visual cue has been completed for the first portion of the guided stretching session.

Abstract: A method and a system for determining an energy expenditure of a user while practicing yoga are described. A heart rate sensing module can measure the user's heart rate. A temperature sensing module can measure ambient temperature. A motion sensing module can collect user's motion data. In some embodiments, a hot yoga session can be detected based on measured ambient temperature. In some embodiments, a yoga type can be detected based on the motion data. In some embodiments, an energy expenditure model can be applied based on the determined yoga type.

Abstract: Improved techniques and systems are disclosed for determining the components of resistance experienced by a wearer of a wearable device engaged in an activity such as bicycling or running. By monitoring data using the wearable device, improved estimates can be derived for various factors contributing to the resistance experienced by the user in the course of the activity. Using these improved estimates, data sampling rates may be reduced for some or all of the monitored data.

Abstract: Improved techniques and systems are disclosed for determining the components of resistance experienced by a wearer of a wearable device engaged in an activity such as bicycling or running. By monitoring data using the wearable device, improved estimates can be derived for various factors contributing to the resistance experienced by the user in the course of the activity. Using these improved estimates, data sampling rates may be reduced for some or all of the monitored data.

Abstract: A method and a system for determining an energy expenditure of a user while practicing yoga are described. A heart rate sensing module can measure the user's heart rate. A temperature sensing module can measure ambient temperature. A motion sensing module can collect user's motion data. In some embodiments, a hot yoga session can be detected based on measured ambient temperature. In some embodiments, a yoga type can be detected based on the motion data. In some embodiments, an energy expenditure model can be applied based on the determined yoga type.

Abstract: Improved techniques and systems are disclosed for determining the components of resistance experienced by a wearer of a wearable device engaged in an activity such as bicycling or running. By monitoring data using the wearable device, improved estimates can be derived for various factors contributing to the resistance experienced by the user in the course of the activity. Using these improved estimates, data sampling rates may be reduced for some or all of the monitored data.