Fitbit, Inc.

Verily Life Sciences LLC

Atiyeh Ghoreyshi

Shelten Gee Jao Yuen

James Park

Anjian Wu

Conor Joseph Heneghan

Belen Lafon

Zachary Todd Beattie

Chris Hanrahan Sarantos

Alexandros A Pantelopoulos

Jaclyn Leverett Wasson

Allison Maya Russell

Logan Niehaus

Peter Colin Dess

Philip Foeckler

Delisa Lopez

Amir Bahador Farjadian

Allison Shih Wu

Adrienne M Tucker

Jacob Antony Arnold

Jacob Anthony Arnold

Adrienne Mason Tucker

A temperature measurement device for determining a body temperature of a subject includes a first temperature sensor configured to measure a plurality of skin temperatures of the subject at a plurality of time instants, a second temperature sensor spaced apart from the first temperature sensor and configured to measure a plurality of ambient temperatures at the plurality of time instants, a thermal insulation material between the first temperature sensor and the second temperature sensor, a memory device configured to store the plurality of skin temperatures and the plurality of ambient temperatures, and a controller configured to estimate, using a prediction model, the body temperature of the subject based on the plurality of skin temperatures and the plurality of ambient temperatures.

Core temperature estimation from skin and ambient temperature sensors using a dynamic model

Health information for a woman can be used to predict timing of events related to the woman's menstrual cycle. If available, historical cycle information for a woman can be used to predict upcoming cycle events, such as the start and stop of menstruation. To improve the accuracy of those predictions, one or more health metrics are monitored for the woman that can be correlated with the menstrual cycle. These can include, for example, the resting heart rate (RHR), blood oxygen concentration (SpO) level, and hemoglobin concentration, among other such options. The metrics are monitored over time to determine patterns that can be correlated with menstrual cycle. This information can then be used to update the predictive model, as well as to update individual event predictions. Information about the predictions, and updates to the predictions, can be surfaced accordingly.

Menstrual cycle tracking

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

The disclosure relates to methods, devices, and systems to identify a user of a wearable fitness monitor using data obtained using the wearable fitness monitor. Data obtained from motion sensors of the wearable fitness monitor and data obtained from heartbeat waveform sensors of the wearable fitness monitor may be used to identify the user.

User identification via motion and heartbeat waveform data

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San Francisco, CA, United States of America

Atiyeh Ghoreyshi