Palo Alto Research Center Inc.

Yahoo! Inc.

Physera, Inc.

Oath Inc.

Conduent Business Services, LLC

Shane Patrick Ahern

Michael Roberts

Rahul Nair

Simon P King

Mor Naaman

Yigal Dan Rubinstein

Cameron Marlow

Jonathan D Chang

Victoria M E Bellotti

Daniel Matthew Merl

Todd Riley Norwood

Oliver Brdiczka

Jonathan Rubin

Peter L T Pirolli

Lester D Nelson

Simon Tucker

Gregory Michael Youngblood

Jeannie Hui-I Yang

Ashwin Ram

Jesse Vig

Marc Eliot Davis

Ashish V Pattekar

Daniel Gureasko Bobrow

Doron Kletter

Christian Fritz

Evgeniy Bart

Hoda M A Eldardiry

Paul Hammond

Simon Willison

Tom Coates

David Garcia

Christina Pavlopoulou

Alexander B Jaffe

Rui Abreu

Anselm Hook

Honglu Du

David Gunning

Peter L Pirolli

Hoda MA Eldardiry

An exercise feedback system receives exercise data such as images or video captured by client devices of users performing exercises. The exercise feedback system may access a machine learning model trained using image of a population of users. The images used for training may be labeled, for example, as having proper or improper musculoskeletal form. The exercise feedback system may determine a metrics describing the musculoskeletal form of a user by applying the trained machine learning model to images of the user as input features. The exercise feedback system may generate feedback for a certain exercise using the metrics based on output predictions of the model. The feedback can be provided to a client device of the user or a physical therapist for presentation.

Classification of musculoskeletal form using machine learning model

A computer-implemented system and method for distributed activity detection is provided. Contextual data collected for a user performing an activity is processed on a mobile computing device. The mobile computing device extracts features from the contextual data and compares the features with a set of models. Each model represents an activity. A confidence score is assigned to each model based on the comparison with the features and the mobile computing device transmits the features to a server when the confidence scores for the models are low. The server trains a new model using the features and sends the new model to the mobile computing device.

Computer-implemented system and method for distributed activity detection

An exercise feedback system receives exercise data captured by client devices of users performing musculoskeletal exercises. The exercise feedback system may provide captured images to a client device of a physical trainer (PT) who remotely provides feedback on the users' exercise performances, for example, by labeling images as indicative of proper or improper musculoskeletal form. A PT may track multiple users using a central feed, which includes content displayed in an order based on ranking of users by a model. Additionally, the exercise feedback system may provide an augmented reality (AR) environment. For instance, an AR graphic indicating a target musculoskeletal form for an exercise is overlaid on a video feed displayed by a client device. Responsive to detecting that a user's form is aligned to the AR graphic, the exercise feedback system may notify the user and trigger the start of the exercise.

Augmented reality guided musculoskeletal exercises

A computer-implemented system and method for predicting activity outcome based on user attention is provided. Sensor data is collected for a user, and an activity performed by a user is identified based on the sensor data. Features of the user are collected while performing the activity and a subject of focus of the user is determined based on the collected features. An outcome of the activity performed by the user is predicted based on the features and the determined subject of focus.

Computer-implemented system and method for predicting activity outcome based on user attention

Customizing content for musculoskeletal exercise feedback

Exercise feedback system for musculoskeletal exercises

A computer-implemented system and method for providing contextually relevant task recommendations to qualified users is provided. Sensor data is collected for a user. The user's location is determined and subsequently, an activity of the user is determined based on the sensor data and the location. Two or more recommendable items are scored based on the activity and one or more of the recommendable items with the highest scores are selected. Finally, one or more recipients qualified to perform each of the recommendable items are identified.

Computer-implemented system and method for providing contextually relevant task recommendations to qualified users

A method and system for generating a personalized health management recommendation for a user. During operation, the system obtains first physiological data generated by a wearable device worn by the user that indicates a physiological condition of the user. The system then generates a prediction model for the user based on the first physiological data. Next, the system obtains real-time physiological data generated by the wearable device. The system may generate a prediction by analyzing the real-time physiological data to determine whether the user's physiological condition exceeds a threshold parameter according to the prediction model. Upon determining that the threshold parameter has been exceeded, the system may select a recommendation and send the recommendation message to the user's mobile device.

Interactive remote patient monitoring and condition management intervention system

One embodiment provides a system that facilitates access control. During operation, the system generates, by a first mobile computing device associated with a first user, a request to record information of a second user associated with a second mobile computing device. In response to receiving, from the second mobile computing device, an acceptance of the request, the system records, by the first mobile computing device, the information of the second user based on recording-related preferences of the second user. In response to receiving, from the second mobile computing device, a rejection of the request, the system precludes the first mobile computing device from recording the information of the second user, thereby facilitating intuitive and socially aligned access control.

System and method for intuitive and socially aligned access control

Apparatuses and methods for location-based visualization of geo-reference content are provided. Apparatus may include logic for causing a display of a map having at least one tag displayed therewith, and logic for causing the display of a set of content objects in response to selection of the tag, the set of content objects associated with the tag and the geographical location of the map. The content objects may be displayed in a viewing window adjacent the map and selectable by a user. The content objects may be filtered by a user, e.g., indicating that a content object is incorrectly tagged or geo-referenced. The apparatus may dynamically update the content based on user interaction. The set of tags and content objects displayed may vary based on a particular zoom level and associated tags may be displayed in response to selection of a tag and/or a content object.

Location-based visualization of geo-referenced context

One embodiment provides a system that facilitates optimization of passenger pick-up. During operation, the system generates, by a first mobile computing device associated with a passenger at a first location, a request for a target location at which to meet with a vehicle. The system receives the target location and a planned passenger route for the passenger to the target location, which are calculated based on a location, facing direction, and direction of movement, if any, of the vehicle, and wherein the target location is different from the first location, thereby facilitating optimization of a time duration and route the passenger takes to meet the vehicle.

System and method for optimizing passenger pick-up

One embodiment of the present invention provides a system for creating a health/wellness program on a generic health/wellness platform. During operation, the system receives, at the generic health/wellness platform, a set of definitions for the health/wellness program, constructs a program model for the health/wellness program, generates a program instance to be executed on the generic health/wellness platform, and associates the program instance to a number of health/wellness modules provided by the health/wellness platform.

Method and a system for providing hosted services based on a generalized model of a health/wellness program

One embodiment of the present invention provides a system for generating a message. During operation, the system receives user interaction event data. The user interaction event data describes explicit or implicit interactions of a user with a web application and/or mobile application. Next, the system modifies a graph describing the user's current context associated with the user based on an analysis of the user interaction event data, as interpreted by the system learning from previous processing of user interaction event data. The context graph includes information about the user's state, behavior, and interests, and some or all portions of the context graph may be shared between users. The system determines a set of rules associated with a group of users that includes the user, and then applies the determined set of rules to any context graph associated with the user to generate the message.

Rule-based messaging and dialog engine

One embodiment of the present invention provides a system for automatically reporting progress in completing objectives and goals of a plan. During operation, the system receives data indicating user selection and/or configuration of a plan with one or more goals, objectives, and/or milestones. The system obtains data generated by sensors in a sensing device and/or a mobile device. The sensors generate physiological data or data from detecting activity or environment associated with the user. Next, the system analyzes the data to determine whether the user has completed an objective, milestone, or goal of the plan. If the system determines that the user has completed an objective, milestone, or goal of the plan, the system pushes an alert to the mobile device indicating that the user has completed the objective, milestone, or goal.

System and method for automatic objective reporting via wearable sensors

One embodiment of the present invention provides a recommendation system. During operation, the system receives context information associated with the user, updates a plurality of user models based on the received context information, and identifies at least one spatial data structure that stores a plurality of items. A respective item is stored within the spatial data structure based on a vector value associated with the item. The system then queries the spatial data structure to obtain a first set of recommendable items that have vector values within a predetermined range, calculates a score for each item within the set of recommendable items based on the plurality of the user models and a characterization vector associated with each item, ranks the items within the set of recommendable items based on calculated scores, and recommends one or more top-ranked items to the user.

Generalized graph, rule, and spatial structure based recommendation engine

Growing community of inventors

Belmont, CA, United States of America

Shane Patrick Ahern