Fitbit, Inc.

Jacob Antony Arnold

Allison Maya Russell

Shelten Gee Jao Yuen

Subramaniam Venkatraman

Yeqing Cheng

Yasaman Baiani

Zachariah Lord Wasson, Ii

Jung Ook Hong

Delisa Lopez

Conor Joseph Heneghan

Alexandros A Pantelopoulos

Atiyeh Ghoreyshi

Nicholas Myers

Belen Lafon

Zachary Todd Beattie

Philip Foeckler

Adrienne M Tucker

Alan McLean

Adrienne Mason Tucker

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.

Sedentary period detection using a wearable electronic device

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.

Automatic detection of user's periods of sleep and sleep stage

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.

Systems and techniques for tracking sleep consistency and sleep goals

A system, computer-readable storage medium, and a method capable of, directly or indirectly, estimating sleep states of a user based on sensor data from movement sensors and/or optical sensors.

Methods and systems for labeling sleep states

Selecting and presenting messages to user of an activity/health monitoring platform. The health/activity monitoring platform may receive physiological data for a user. The health/activity monitoring platform may identify a set of messages based on the physiological data. The health/activity monitoring platform may also determine a set of scores for the set of messages. Each score from the set of scores may be associated with a message from the set of messages and each score from the set of scores may be indicative of whether a respective message should be presented to the user. The health/activity monitoring platform may also identify a first message from a set of messages based on the set of scores and cause the first message to be presented via a display of a computing device of the user. The health/activity monitoring platform may also update a first set of penalties associated with the first message in response to causing the first message to be presented. The first set of penalties decreases a first likelihood that the first message will be presented to the user again.

Presenting health related messages to users of an activity/health monitoring platform

Sedentary period detection utilizing a wearable electronic device

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.

Periodic inactivity alerts and achievement messages

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.

Fitness monitoring device with user engagement metric functionality

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.

Growing community of inventors

Fremont, CA, United States of America

Jacob Antony Arnold