Abstract: Methods, techniques, apparatuses, and systems for setting up and tracking sleep consistency goals of users are provided. In one example, a computing system for setting a sleep schedule of a user of a biometric monitoring device may obtain sleep data derived from sensor data generated by the biometric monitoring device, store the sleep data in a sleep log data store as one or more sleep logs associated with an account assigned to the user, and calculate a target bedtime based on a scheduled waketime of the user and a sleep efficiency derived, at least in part, from the sleep data for one or more users stored in the sleep log data store. The computing system may also be configured to provide a number of personalized user interfaces to an individual for the purposes of setting a sleep schedule. Such interfaces may include parameters that are tailored to the individual sleep needs and/or characteristics of the individual's sleep.

Abstract: Methods, techniques, apparatuses, and systems for setting up and tracking sleep consistency goals of users are provided. In one example, a computing system for setting a sleep schedule of a user of a biometric monitoring device may obtain sleep data derived from sensor data generated by the biometric monitoring device, store the sleep data in a sleep log data store as one or more sleep logs associated with an account assigned to the user, and calculate a target bedtime based on a scheduled waketime of the user and a sleep efficiency derived, at least in part, from the sleep data for one or more users stored in the sleep log data store. The computing system may also be configured to provide a number of personalized user interfaces to an individual for the purposes of setting a sleep schedule. Such interfaces may include parameters that are tailored to the individual sleep needs and/or characteristics of the individual's sleep.

Abstract: Methods, apparatuses, and systems are provided for interacting with a user to promote engagement with a fitness monitoring device configured to measure a fitness parameter of the user, which may include determining, by one or more processors in at least one of the fitness monitoring device or a device in communication with the fitness monitoring device, that user engagements with the fitness monitoring device have occurred on multiple occasions, in which each user engagement produces at least one measurement of the fitness parameter; receiving, by the one or more processors, information indicating a level of engagement metric for the user based, at least in part, on multiple detected the multiple user engagements with the fitness monitoring device; and generating, by the one or more processors and based on the level of engagement metric, a notification containing information relating to at least a level of user engagement with the fitness monitoring device or the fitness parameter.

Abstract: Aspects of generating movement measures that quantify motion data samples generated by a wearable electronic device are discussed herein. For example, in one aspect, an embodiment may obtain motion data samples generated by the set of motion sensors in a wearable electronic device. The wearable electronic device may then generate a first movement measure based on a quantification of the first set of motion data samples. The wearable electronic device may also generate a second movement measure based on a quantification of the second set of the motion data samples. The wearable electronic device may then cause the non-transitory machine readable storage medium to store the first movement measure and the second movement measure as time series data.

Abstract: Methods, systems, and computer programs are presented for holding the generation of alarm and congratulatory messages. One method includes an operation for capturing motion data using an activity tracking device. Intervals during a day are identified, each interval including a start and an end time, and a near-end time being defined between the start and end times. Another operation is for generating a first notification for display on the activity tracking device when the near-end time of the current interval is reached and the steps taken by the user during the current interval is less than a goal of a predetermined number of steps. Further, the method includes operations for receiving a hold command with a hold period, and for suspending the generation of the first notification during the hold period. After the hold period expires, the generation of the first notification is resumed without requiring user input.

Abstract: Methods, systems, and computer programs are presented for generating alarms and congratulatory messages to reduce sedentary time. One method includes an operation for capturing motion data using an activity tracking device. The method further includes operations for storing the motion data in memory, and for identifying one or more intervals during a day. Each interval includes a start time and an end time, and a near-end time is defined between the start and the end time. For each interval, the number of steps taken during the interval is determined, and the number of steps is compared against a goal defined by a number of steps to be taken during the interval. A first notification is displayed when the number of steps is less than the goal and the near-end time has been reached. A second notification is displayed congratulating the user if the interval goal is reached.

Abstract: Methods, systems, and computer programs are presented for reporting information regarding hourly steps. One method includes operations for capturing motion data using an activity tracking device, and for identifying a plurality of intervals during a day. Each interval includes a start time, an end time, and an interval goal, which is the number of steps to be taken during the interval. The method includes an operation for determining the number of steps taken during the current interval. Responsive to determining that the steps taken during the current interval is less than the interval goal, a first message is presented on the activity tracking device indicating the steps taken during the current interval. Further, responsive to determining that the user meets the interval goal during the current interval, a second message is presented indicating in how many intervals of the current day the interval goal was reached.

Abstract: Methods, systems, and computer programs are presented for reporting sedentary time information. One method includes operations for capturing motion data using one or more sensors of an activity tracking device, and for determining one or more sedentary time periods associated where the user is sedentary. Further, the method includes an operation for determining a first set of one or more time intervals when the user is asleep, and for determining a second set of one or more time intervals when the user is not wearing the activity tracking device. The longest sedentary period for a day where the user is sedentary, awake, and wearing the activity tracking device, is calculated based on excluding the first and the second sets of one or more time intervals from the one or more sedentary time periods. Information describing the longest sedentary period is displayed on the activity tracking device.

Abstract: Systems and methods for determining a sedentary state of a user are described. Sensor data is collected and analyzed to calculate metabolic equivalent of task (MET) measures for a plurality of moments of interest. Based on the MET measures and a time period for which the MET measures exceed a threshold value, it is determined whether the user is in a sedentary state. If the user is in the sedentary state, the user is provided a notification to encourage the user to perform a non-sedentary activity.

Abstract: Aspects of changing power consumption of a sensor of a wearable electronic device worn by a user are discussed herein. For example, in one aspect, based on detecting that a state of the user, as tracked by the wearable electronic device, has transitioned into an asleep state, an embodiment may decrease power consumption of at least one sensor from the set of sensors. Additionally, based on detecting that the state of the user, as tracked by the wearable electronic device, has transitioned out of the asleep state, the embodiment may reverse the decrease of power consumption of the at least one sensor.

Abstract: Systems and methods for determining a sedentary state of a user are described. Sensor data is collected and analyzed to calculate metabolic equivalent of task (MET) measures for a plurality of moments of interest. Based on the MET measures and a time period for which the MET measures exceed a threshold value, it is determined whether the user is in a sedentary state. If the user is in the sedentary state, the user is provided a notification to encourage the user to perform a non-sedentary activity.

Abstract: Methods, apparatuses, and systems are provided for interacting with a user to promote engagement with a fitness monitoring device configured to measure a fitness parameter of the user, which may include determining, by one or more processors in at least one of the fitness monitoring device or a device in communication with the fitness monitoring device, that user engagements with the fitness monitoring device have occurred on multiple occasions, in which each user engagement produces at least one measurement of the fitness parameter; receiving, by the one or more processors, information indicating a level of engagement metric for the user based, at least in part, on multiple detected the multiple user engagements with the fitness monitoring device; and generating, by the one or more processors and based on the level of engagement metric, a notification containing information relating to at least a level of user engagement with the fitness monitoring device or the fitness parameter.

Abstract: Aspects of automatically detecting periods of sleep of a user of a wearable electronic device are discussed herein. For example, in one aspect, an embodiment may obtain a set of features for periods of time from motion data obtained from a set of one or more motion sensors in the wearable electronic device or data derived therefrom. The wearable electronic device may then classify the periods of time into one of a plurality of statuses of the user based on the set of features determined for the periods of time, where the statuses are indicative of relative degree of movement of the user. The wearable electronic device may also derive blocks of time each covering one or more of the periods of time during which the user is in one of a plurality of states, wherein the states include an awake state and an asleep state.

Abstract: Aspects of automatically determining a period of time when a wearable electronic device is not being worn are discussed herein. For example, in one aspect, an embodiment may automatically determine a period of time when the wearable electronic device is not being worn based on a comparison of the motion data and a not-worn profile that specifies a pattern of motion data that is indicative of when the wearable electronic device is not being worn by a user. The wearable electronic device also stores in the non-transitory machine readable storage medium, data associating the period of time with a not-worn state.

Abstract: Aspects of changing power consumption of a sensor of a wearable electronic device worn by a user are discussed herein. For example, in one aspect, based on detecting that a state of the user, as tracked by the wearable electronic device, has transitioned into an asleep state, an embodiment may decrease power consumption of at least one sensor from the set of sensors. Additionally, based on detecting that the state of the user, as tracked by the wearable electronic device, has transitioned out of the asleep state, the embodiment may reverse the decrease of power consumption of the at least one sensor.

Abstract: Aspects of generating movement measures that quantify motion data samples generated by a wearable electronic device are discussed herein. For example, in one aspect, an embodiment may obtain motion data samples generated by the set of motion sensors in a wearable electronic device. The wearable electronic device may then generate a first movement measure based on a quantification of the first set of motion data samples. The wearable electronic device may also generate a second movement measure based on a quantification of the second set of the motion data samples. The wearable electronic device may then cause the non-transitory machine readable storage medium to store the first movement measure and the second movement measure as time series data.

Abstract: Methods, apparatuses, and systems are provided for determining a level of user engagement with a fitness monitoring device and, when a level of engagement metric for the fitness monitoring device for a person meets certain criteria, encouraging user engagement with the fitness monitoring device.

Abstract: Methods, apparatuses, and systems are provided for determining a level of user engagement with a fitness monitoring device and, when a level of engagement metric for the fitness monitoring device for a person meets certain criteria, encouraging user engagement with the fitness monitoring device.