Apple Inc.

Hengliang Zhang

Alan C Dye

Hung A Pham

Karthik Jayaraman Raghuram

Xiaoyuan Tu

Alexander Singh Alvarado

Umamahesh Srinivas

Xing Tan

Yann Jerome Julien Renard

Sheena Sharma

Huayu Ding

Harshavardhan Mylapilli

Geoffrey Louis Chi-Johnston

Vivek Garg

Parisa Dehleh Hossein Zadeh

Ben-Heng Juang

Adam S Howell

Gunes Dervisoglu

Hue Duc Tran

Patrick L Coffman

Christopher Patrick Foss

Jeffrey L Robbin

Craig Michael Federighi

Grant R Paul

Darin Benjamin Adler

Caelan G Stack

Steven J Falkenburg

Heena Ko

Charles Hugo Ying

Sam H Gharabally

Reza Abbasian

Ada Y Chan

Pallavika Ramaswamy

Yongjun Zhang

Edith Merle Arnold

Grant Ritchie

Keith P Kowalczykowski

Nahir A Khan

Mark M Xue

Dana J Dubois

Brian Erik Goldberg

Xiaoyue Zhang

James S Savage

Matthew Sibson

Charles B Etzel

Kenneth Arthur Abraham Ferry

Nicholas Stephen Doherty

Rishab Mehra

Luming Yin

Parisa Deleh Hossein Zadeh

Dana J DuBois

Gurshamnjot Singh

Ada Chan

Steven Falkenburg

In an example method, a mobile device obtains a signal indicating an acceleration measured by a sensor over a time period. The mobile device determines an impact experienced by the user based on the signal. The mobile device also determines, based on the signal, one or more first motion characteristics of the user during a time prior to the impact, and one or more second motion characteristics of the user during a time after the impact. The mobile device determines that the user has fallen based on the impact, the one or more first motion characteristics of the user, and the one or more second motion characteristics of the user, and in response, generates a notification indicating that the user has fallen.

Detecting falls using a mobile device

The present disclosure generally relates to user interfaces for enabling an activity using a computer system. In some embodiments, exemplary user interfaces for invoking an activity associated with an application are described. In some embodiments, exemplary user interfaces for customizing displayed content based on circumstances under which the content was invoked are described. In some embodiments, exemplary user interfaces for managing applications that were used to enable activities are described. In some embodiments, exemplary user interfaces for managing settings for applications used to enable activities are described.

User interfaces for enabling an activity

A method and a system for determining an energy expenditure of a user by detecting unmeasurable loads using heart rate and work rate are described. Time-stamped heart rate data and work rate data can be collected by one or more sensing modules. A processor circuit can calculate a heart rate-based energy expenditure and a work rate-based energy expenditure. The processor circuit can output a hybrid energy expenditure based on a heart rate confidence parameter, an exercise type, a fraction of heart rate reserve, and a hear rate-based metabolic equivalents of task.

Detecting unmeasurable loads using heart rate and work rate

In some implementations, a mobile device can analyze motion sensor data and proximity sensor data during a voice call to determine whether the mobile device is on a stationary object or worn on a user's body (e.g., in the lap or pocket of a user of the mobile device). The mobile device can adjust the transmit power level of the telephony transceiver during the voice call based on the determination.

Determination of device body location

Implementations are disclosed for using magnetometer measurements to estimate bias for angular rate measurements provided by an angular rate sensor (e.g., a gyro sensor). In some implementations, a bias estimator running on a device is configured to determine if the device is rotating based on the magnetometer measurements. If the device is not rotating, a dynamic bias is calculated and added to a temperature compensated static bias to provide a total angular rate measurement bias. The total angular rate measurement bias can be provided to an attitude estimation system where it is used to update an attitude (orientation) of the device. In some implementations, the angular rate measurements are used to determine if the device is oscillating according to a threshold value. If the device is not rotating and the device is oscillating according to a threshold value, the static bias is updated in a calibration table.

Using magnetometer data to calculate angular rate measurement bias

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San Jose, CA, United States of America

Hengliang Zhang