Fitbit, Inc.

Belen Lafon

Lindsey Michelle Sunden

Conor Joseph Heneghan

Atiyeh Ghoreyshi

Zachary Todd Beattie

Aniket Sanjay Deshpande

Paul Francis Stetson

Chris Hanrahan Sarantos

Alexandros A Pantelopoulos

Jaclyn Leverett Wasson

Allison Maya Russell

Logan Niehaus

Alexander Statan

Peter Colin Dess

Man-Chi Liu

Philip Foeckler

Amir Bahador Farjadian

Adrienne M Tucker

Derrick Steven Vickers

Elena Perez

James Horng-Kuang Lin

Jacob Antony Arnold

Xi Zhang

Hao-Wei Su

Aravind Natarajan

Delisa Lopez

Allison Shih Wu

Jacob Anthony Arnold

Adrienne Mason Tucker

The present disclosure provides computer-implemented methods, systems, and devices for improved skin temperature monitoring. Accurate estimates of skin and ambient temperature are generated based on determinations and comparisons of skin and internal device temperature sensor measurements contained on or within example devices. The estimates of skin and ambient temperature measurements facilitate monitoring skin and core temperature changes, detecting physiological events of a wearer of example devices, and determining when skin temperature changes are environmentally or physiologically induced.

Methods, systems, and devices for improved skin temperature monitoring

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

Arousal events can be determined for a user associated with a wearable device, such as a user wearing a wearable computing device including one or more sensors. The one or more sensors may obtain EDA information that may determine a sympathetic nervous system response of the user, which may be responsive to an arousal event or an activation. Detection of events that increase the EDA response may provide information to the user regarding arousal events and provide recommendations to the user to address the arousal events to decrease their response.

Detection and response to arousal activations

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San Francisco, CA, United States of America

Belen Lafon