Abstract: An activity classification server receives raw data from one or more activity-tracking devices worn by a user and processes the raw data to classify the user's activities into one or more identifiable states. The activity-tracking devices operate at a given sampling rate to collect the raw data. To optimize power usage, among other things, the activity classification server adjusts the sampling rate of the activity-tracking devices based on the state of the user at any given time. Therefore, the activity-tracking devices collect raw data at different sampling rates depending on the type of activity in which the user wearing those devices is engaged.

Abstract: A wearable device allows the tracking of human movements during activity, such as while exercising or playing a sport. To improve user experience with the wearable device, an activity classification server classifies activities and repetitions of the activity. To further improve user experience, the activity classification server can prompt the user to perform an activity and identify the activity while the user performs the prompted activity. The user can also indicate to the device an election to perform a particular activity without being prompted by the device and the user can classify the activity by indicating to the device what activity the user will perform.