Apple Inc.

Christian Schroeder

Kevin M Lynch

Jay Kriz Blahnik

Erno H Klaassen

Evan Russell Doll

Stephen J Waydo

Ian R Shapiro

Jason B Morley

Zhe Li

Roxanne B Brittain

Mark E Pennell

David W Padgett

Divya Padmanabhan

Joefrey S Kibuule

Alexa VanHattum

Jorge Fernando Pozas Trevino

John P Clark

Brian A Carlsen

Jeffrey D LaMarche

Patrick L Coffman

Ronald Keryuan Huang

Stephen J Rhee

Erik C Neuenschwander

Krishna M Behara

Matthew B Ball

Adam M Driscoll

Jessica Aranda

Brandon J Van Ryswyk

Christopher C Foster

Charles D Deets

Siraj T Abidi

Maria Ryen

Shuli Zhou

Alexa M Vanhattum

A user device can be used to generate medical term expressions, which represent medical terms of a health record. The user device can identify a medical concept present in the health record based on a medical term expression. The user device can generate a node in a personalized relational graph that corresponds to the medical concept. One or more sub-nodes can be added to the node. Responsive to a request, a user interface is presented that identifies the medical concept and some of the additional information.

Techniques for anonymized searching of medical providers

An example technique may include tracking motion of a user wearing the wearable device using at least first sensors of one or more sensors of the wearable device. The technique may also include tracking a physical state of the user using at least second sensors of the one or more sensors of the wearable device. The technique may also include determining whether an application of the wearable device has been launched. The technique may also include determining an action category of the user based at least in part on at least one of the motion of the user, the physical state of the user, or whether the application has been launched. The technique may also include collecting heartrate data of the user. The technique may also include categorizing the heartrate data based at least in part on the determined action category.

Heartrate tracking techniques

A term base can be used to index a raw medical term (e.g., a text string from an electronic health record) to generate a computational expression of the raw medical term. The computational expression of the raw medical term can be used to generate a uniform medical term for the raw medical term. The computational expression can be compared with other computational expressions to organize the electronic health record, filter the electronic health record, and provide a uniform presentation of raw medical terms from different events in the electronic health record.

Normalization of medical terms

Techniques are provided for tracking heartrate metrics using different operating modes associated with different contexts of a wearable device. For example, a heartrate sensor of the wearable device may be operated in a first operating mode when an activity is being tracked within an application session of a particular application. The heartrate sensor may be operated in a second operating mode after detecting conclusion of the activity within the activity session (e.g., during sedentary time).

A location control subsystem is provided that allows a user of an electronic device to define the granularity used to provide location coarseness. A user can define a coarse location granularity for an application. When a coarse device location is reported to an application, the location can be provided with at least a minimum degree of variable specificity based on the selected location coarseness. When an application is granted a coarse location, the application is to interpret the provided location indicating that the user may be anywhere within a geographic region of variable specificity, as opposed to being close to a center point with a horizontal accuracy based on the precision of the location fix, as when a fine granularity location is provided. In addition to reducing the spatial resolution of the location that is reported to the application, the temporal resolution may also be reduced.

User selectable location granularity

A term base can be used to index a raw term (e.g., a text string from an electronic health record) to generate a computational expression of the raw term. As part of doing so, portions of the raw term including personally identifying information can be removed and/or replaced with de-identified information. The computational expression of the raw term can be used to generate a version of the raw term that is devoid of the personally identifying information.

Index-based deidentification

Embodiments of the present disclosure can provide systems, methods, and computer-readable medium for tracking the heartrate of a user using different techniques associated with different contexts. For example, motion of a user wearing a wearable device can be tracked using at least first sensors of the one or more sensors. The physical state of the user can also be tracked using at least second sensors of the one or more sensors. In some cases it can be determines whether an application of the wearable device has been launched. Additionally, an activity category of the user can be determined based at least in part on the motion of the user, the physical state of the user, and/or whether the application has been launched. Heartrate data of the user can be collected, and the heartrate data can be categorized based at least in part on the determined category.

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Palo Alto, CA, United States of America

Christian Schroeder