Apple Inc.

Other

Adeeti V Ullal

Karthik Jayaraman Raghuram

Hung A Pham

Xing Tan

Alexander Singh Alvarado

Umamahesh Srinivas

Vinay R Majjigi

Craig H Mermel

Ronald Keryuan Huang

Stephen P Jackson

Yann Jerome Julien Renard

Daniel M Trietsch

Bharath Narasimha Rao

Adam S Howell

Gunes Dervisoglu

James P Ochs

Edith Merle Arnold

Sunny K Chow

Telford Earl Forgety, Iii

Robin T Guers

Thomas G Salter

Thomas J Moore

Ioana Negoita

Richard Channing Moore, Iii

Mrinal Agarwal

Rami Y Hindiyeh

Allison L Gilmore

James J Dunne

Katherine E Niehaus

Alexander G Bruno

Matthew S DeMers

Nicholas D Felton

Matthew Wagner Crowley

Asif Khalak

Ruchi Goswami

Sheena Sharma

Xiaoyue Zhang

Ava Baunoo Rezvani

William R Powers, Iii

Gabriel A Blanco

Maryam Etezadi-Amoli

Irida Mance

Maxsim L Gibiansky

Britni A Crocker

Kyle A Reed

Sumayah F Rahman

Vinay R Majigi

Dan Marvin Trietsch

Embodiments are disclosed for a biomechanical trigger for improved responsiveness in grade estimation. In some embodiments, a method comprises: obtaining, from a wearable device worn by a user, cadence data, speed data and elevation data, determining a grade of a surface on which the user is traveling based on a ratio of a change in elevation based on the elevation data and a change in speed data; determining that the grade satisfies a first condition indicative of a horizontal speed compensation by the user at a grade onset; determining that the grade satisfies a second condition indicative of a rapid elevation increase or decrease at a grade onset; and confirming that the grade is a valid estimate based on either the first condition or the second condition being satisfied.

Biomechanical triggers for improved responsiveness in grade estimation

In an example method, a mobile device obtains sample data generated by one or more sensors over a period of time, where the one or more sensors are worn by a user. The mobile device determines that the user has fallen based on the sample data, and determines, based on the sample data, a severity of an injury suffered by the user. The mobile device generates one or more notifications based on the determination that the user has fallen and the determined severity of the injury.

Detecting falls using a mobile device

A method includes: presenting a posture summary interface including: a representation of the user, a visualization of a current accumulated strain value for the user, and a first affordance for initiating an animated posture summary associated with the accumulated strain value for the user over a respective time window; and in response to detecting a user input directed to the first affordance within the posture summary interface, presenting an animation of the representation of the user over the respective time window that corresponds to one or more instances in which head pose information changes associated with the user caused an increase or a decrease to the accumulated strain value greater than a significance threshold, wherein an appearance of the visualization of the current accumulated strain value for the user changes to represent the accumulated strain value for the user over the respective time window.

Method and device for surfacing accumulated strain information

The present disclosure relates to methods and systems of determining swimming metrics of a user during a swimming session. The method can include receiving, by a processor circuit of a user device, motion information from one or more motion sensors of the user device; determining, by the processor circuit using the motion information, a first set of rotational data of the user device, wherein the first set of rotational data is expressed in a first frame of reference; converting, by the processor circuit, the first set of rotational data into a second set of rotational data, wherein the second set of rotational data is expressed in a second frame of reference; determining, by the processor circuit, one or more swimming metrics of the user; and outputting the one or more swimming metrics.

Systems and methods for determining swimming metrics

One or more electronic device may use motion and/or activity sensors to estimate a user's 6 minute walking distance. In particular, because users typically walk at less than their maximum output and in imperfect conditions, control circuitry within the device(s) may rely on walks of shorter distances to estimate the 6 minute walking distance. For example, the control circuitry may gather activity information for the user, such as heart rate, calories burned, and step count, and analyze a distance component and a speed component for periods in which the user has walked. Individual 6 minute walk distance estimates may be generated based on each of the activity information, distance component, and speed component. The distance and speed estimates may be corrected for walking behaviors that deviate from an ideal testing environment, and may then be fused with the activity estimate to generate a final 6 minute walk distance estimate.

Electronic devices with 6 minute walk distance estimates

In an example method, a mobile device receives motion data obtained by one or more sensors over a time period, where the one or more sensors are worn by a user, The mobile device determines, based on the motion data, an impact experienced by the user during the time of period, and determines one or more of characteristics of the user. The mobile device determines, based on the motion data and the one or more characteristics of the user, a likelihood that the user requires assistance subsequent to the impact, and generates one or more notifications based on likelihood.

In an example method, a mobile device receives motion data obtained by one or more sensors worn by a user. The mobile device determines, based on the motion data, that the user has fallen at a first time and whether the user has moved between a second time and a third time subsequent to the first time. Upon determining that the user has not moved between the second time and the third time, the mobile device initiates a communication to an emergency response service at a fourth time after the third time. The communication includes an indication that the user has fallen and a location of the user.

The present disclosure generally relates to user interfaces for health applications. In some embodiments, exemplary user interfaces for managing health and safety features on an electronic device are described. In some embodiments, exemplary user interfaces for managing the setup of a health feature on an electronic device are described. In some embodiments, exemplary user interfaces for managing background health measurements on an electronic device are described. In some embodiments, exemplary user interfaces for managing a biometric measurement taken using an electronic device are described. In some embodiments, exemplary user interfaces for providing results for captured health information on an electronic device are described. In some embodiments, exemplary user interfaces for managing background health measurements on an electronic device are described.

User interfaces for health applications

A method and a system for determining an energy expenditure of a user while practicing yoga are described. A heart rate sensing module can measure the user's heart rate. A temperature sensing module can measure ambient temperature. A motion sensing module can collect user's motion data. In some embodiments, a hot yoga session can be detected based on measured ambient temperature. In some embodiments, a yoga type can be detected based on the motion data. In some embodiments, an energy expenditure model can be applied based on the determined yoga type.

Pose and heart rate energy expenditure for yoga

The present disclosure relates to a system and method of detecting activity by a wheelchair user. In one aspect, a method comprises collecting motion data of a user device located on an appendage of the user; detecting, by a processor circuit, that one or more activities by the wheelchair user occurred based on the motion data; calculating, by a processor circuit, an energy expenditure by the user based the one or more activities by the wheelchair user occurred; and outputting, by a processor circuit, the energy expenditure estimation.

Detecting activity by a wheelchair user

The present disclosure relates to systems and methods of estimating energy expenditure of a user while swimming. A processor circuit of a user device can estimate a speed of the user based on a stroke rate and a stroke length. The processor circuit can estimate an efficiency of the user. The processor circuit can classify a swimming style of the user. The processor circuit can determine energy expenditure of the user based on the speed, the efficiency, and the style. The processor circuit can also detect glides of the user and adjust the energy expenditure.

Systems and methods of swimming calorimetry

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Mountain View, CA, United States of America

Adeeti V Ullal