Apple Inc.

Gunes Dervisoglu

Hung A Pham

Ronald Keryuan Huang

Adam S Howell

Karthik Jayaraman Raghuram

James P Ochs

Alexander Singh Alvarado

Umamahesh Srinivas

Craig H Mermel

Jonathan M Beard

Sunny K Chow

Vinay R Majjigi

Bharath Narasimha Rao

Xing Tan

Adeeti V Ullal

Anh N Phan

Xiaoyuan Tu

Ben-Heng Juang

Edith Merle Arnold

Hengliang Zhang

Hue Duc Tran

Sunny Kai Pang Chow

Rami Y Hindiyeh

Robin T Guers

Srinivasan Nimmala

Tang Yew Tan

Erik L Wang

Tyler S Bushnell

Emily Clark Schubert

Indranil S Sen

Venkateswara Rao Manepalli

Ryan David Shelby

Robert Caston Curtis

Anil K Kandangath

Richard B Warren

Andrew M Wadycki

Vijay Kumar Ramamurthi

Lili Cao

Pejman Lotfali Kazemi

Digvijay Arjunrao Jadhav

Andre M Boule

Kenneth Waters

Jonathan C King

Richard Channing Moore, Iii

Maulik V Choksi

Christopher D Guichet

Xiao Xiao

John D Blackwell

Christopher E Balcells

Alexander Joshua Wiens

Erin Paeng

Dan Marvin Trietsch

Chintan S Parikh

Theodore Lao

Bor-rong Chen

Lucie A Huet

Disclosed embodiments include wearable devices and techniques for detecting the end of hiking activities. By accurately and promptly detecting the end of hiking activities automatically, the disclosure enables wearable devices to accurately calculate user performance information when users forget to start and/or stop recording a hiking activity.

Detecting the end of hiking activities on a wearable device

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

Disclosed embodiments include wearable devices and techniques for detecting walking workouts. By accurately and promptly detecting the start of walking workouts activities and automatically distinguishing between walking workout and causal walking activities, the disclosure enables wearable devices to accurately calculate user performance information when users forget to start and/or stop recording walking workouts.

Detecting outdoor walking workouts on a wearable device

A method for calibrating a magnetometer of an electronic device can include detecting a change in a magnetism of the electronic device, collecting a first magnetic field data from the magnetometer at sampling frequency of at least 1 hertz, generating an elliptical calibration model based at least partially on the collected first magnetic field data, collecting a second magnetic field data from the magnetometer, and fitting the collected second magnetic field data to a sphere using the elliptical calibration model.

In-field soft magnetic distortion hardware compensation

Systems and methods of analyzing a user's motion during a swimming session are described. One or more motions sensors can collect motion data of the user. A processor circuit can make motion analysis based on the motion data. The processor circuit can determine if the user's arm swing is a genuine swim stroke. The processor circuit can also determine whether the user is swimming or turning. The processor circuit can also classify the user's swim stroke style. The processor circuit can also determine the user's swim stroke phase. The processor circuit can also determine the user's stroke orbit consistency.

Systems and methods of swimming analysis

In an example method, a mobile device connects a voice call for a user. The voice call causes one or more radio frequency transmitters of the mobile device to transmit radio waves at a first power level. Motion data describing movement of the mobile device is obtained, and the orientation of the mobile device is determined based on the motion data. A determination whether the mobile device is on the user's body or on an inanimate object is made based on the orientation of the mobile device over the period of time. The transmit power level is adjusted based on the determination.

Determination of device placement using pose angle

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

Systems, methods, and computer-readable media for managing or classifying movement states of an electronic device are provided that may utilize communications circuitry data from one or more communications circuitries when determining a current or future movement state of an electronic device.

Management of movement states of an electronic device using communications circuitry data

In one aspect, the present disclosure relates to a method including obtaining, by a heart rate sensor of a fitness tracking device, a heart rate measurement of a user of the fitness tracking device; obtaining, by at least one motion sensor, motion data of the user; analyzing, by the fitness tracking device, the motion data of the user to estimate a step rate of the user; estimating, by the fitness tracking device, a load associated with a physical activity of the user by comparing the heart rate measurement with the step rate of the user; and estimating, by the fitness tracking device, an energy expenditure rate of the user using the load and at least one of the heart rate measurement and the step rate.

Latent load calibration for calorimetry using sensor fusion

Systems, methods, devices and computer-readable mediums are disclosed for parking event detection and location estimation. In some implementations, a method comprises: determining, by a processor of a mobile device, a first activity state indicative of a possible parking event; obtaining, by the processor, a speed of the mobile device from a global navigation satellite system (GNSS) of the mobile device; obtaining, by the processor, pedometer data from a digital pedometer of the mobile device; determining, by the processor, a second activity state indicative of a possible parking event based at least in part on the GNSS speed and pedometer data; and responsive to the second activity state, estimating, by the processor, a location of the vehicle.

Parking event detection and location estimation

A calibration track to use for pedometer calibration can be automatically selected based on detecting sustained locomotion activity and an ability to obtain and maintain a reliable location fix over a calibration period. Calibration tracks can be generated, rated for quality, and used to compute calibration parameters to convert accelerometer data to stride length and/or distance traveled. Quality of a calibration can be assessed, and old and new calibration parameter sets can be combined based on quality weights assigned to each. Calibration parameters can be separately maintained for different locomotion activities and/or different on-body locations of the pedometers. Pedometer devices can also cooperatively calibrate each other.

Automatic track selection for calibration of pedometer devices

Growing community of inventors

Santa Clara, CA, United States of America

Gunes Dervisoglu