Intel Corporation

Amazon Technologies, Inc.

Stephanie Moyerman

James Brian Hall

Xue Yang

Zhen Yao

Braxton L Lathrop

Tyler Fetters

Songnan Yang

Jeremy Parra

Haibin Liu

Michael R Rosen

Ryan Paul Thomas

Fletcher Liverance

Melissa M Ortiz

Rita Brugarolas Brufau

Philip Muse

Donald Erik Schneider

Steven Xing

Alex Guazzelli

Naghma Anwar

Nathan Stebor

Shea M Dillon

Donald L Gross

Cody Gabriel

David Said Martinez

Ramesh Sekaran

John Sitar

Karolina Karli Cengija

A respiratory sensor system provides the ability to determine a respiration rate. The respiratory sensor system may include a respiratory sensor and a software solution, where the software solution determines respiration rate from the respiratory sensor (e.g., microphone) located on the bridge of the user's nose. The respiratory sensor may be placed on or near the nose, such as a microphone located in the nosepiece of a pair of glasses. Due to the placement of the microphone and the respiration detection system design, the wearer respiration rate can be determined reliably even with ambient noise and movement. This makes the respiration rate calculation accessible and reliable, both for everyday wear and for extreme situations such as sports.

Respiratory biological sensing

Mouth guard that includes a flexible printed circuit board encapsulated within a base member is provided. The flexible printed circuit board includes multiple separate stiff sections spaced apart from each other within the base member. One or more electronic devices are disposed within the base member. In particular, the one or more electronics are disposed on the base member.

Systems and methods for integrating electronics into a mouth guard

Methods and apparatus for high speed location determinations are disclosed. An example apparatus includes at least two coils arranged along a zone of interest to generate a magnetic field, and a sensor to measure a change in the magnetic field associated with the at least two coils as an object of interest moves within or into the zone of interest. The example apparatus also includes a processor to determine a position of the object of interest based on the measured change.

Methods and apparatus for high speed location determinations

Examples are disclosed to track sport implements and/or objects of interest. An example apparatus includes a first coil to generate a first magnetic field having a first vertical component with a zero magnitude along a first line of interest and a second coil partially overlapped with the first coil, where the second coil is to generate a second magnetic field. The example apparatus also includes a sensor to measure a magnitude of the first magnetic field in the first line of interest and a processor to determine an object of interest has crossed the first line of interest based on the magnitude of the first magnetic field measured by the sensor.

Apparatus and methods to track sport implements

Methods, systems, and computer-readable media for unified code and data management for machine learning models are disclosed. A plurality of dependency graphs, including a first dependency graph and a second dependency graph, are generated. The graphs comprise nodes associated with a software development model or machine learning model, and the nodes represent transforms. One or more transforms of the first dependency graph are used to generate first output corresponding to a node in the second dependency graph. One or more transforms of the second dependency graph are used to generate second output based at least in part on the first output.

Unified code and data management for model development

System and techniques for gesture capture are described herein. A first representation of a sensor array may be collected into a first sensor composition. The first sensor composition may be filtered to output a pose status. Here, the pose status corresponds to a pose in a library of poses. A second representation of the sensor array may be collected into a second sensor composition. A fit of the second sensor composition to a model may be measured. The fit may be provided to a gesture consumer based on the fit and the pose.

Motion gesture capture by selecting classifier model from pose

Illustrative examples of a sports apparatus and methods for manufacturing a sports apparatus for sensing a scoring event, including but not limited to hockey pucks. In some examples, the sports apparatus includes a body formed of a substrate material and an additive embedded in the substrate material. The additive may be used by a sensor array to locate the position of the sports apparatus in relation to a sports goal. Example additives include an electronic object or a doping material.

Sports apparatus and methods including tracking additives

Embodiments of the present disclosure provide techniques and configurations for an apparatus for identifying a maneuver of sports equipment. In one instance, the apparatus may comprise a housing to be attached to the sports equipment; two or more sensors disposed on or in the housing to sense acceleration or rotation of the sports equipment during the motion of the sports equipment, and to output motion data associated with the acceleration or rotation of the sports equipment; and circuitry disposed in the housing and coupled to the sensors to receive the motion data and to identify a maneuver performed using the sports equipment, based on the motion data. Other embodiments may be described and/or claimed.

Sports equipment maneuver detection and classification

Systems and techniques for a sensor network for trick classification are described herein. A first data stream may be received from a first sensor array affixed to a first free-moving body of a sporting device. A second data stream may be received from a second sensor array affixed to a second free-moving body of the sporting device. A trick region of a predetermined length of the first data stream corresponding with an occurrence of a trick may be determined using data from the first data stream. The trick may be classified using a first set of data from the first data stream corresponding with the trick region and a second set of data from the second data stream. The second set of data may be obtained by aligning the trick region of the first data stream with the second data stream.

Sensor network for trick classification

A system for skydiving trajectory and coordination feedback for a user. The system includes a controller coupled to a plurality of sensor inputs. The controller determines a user drag through air based on input data from the plurality of sensor inputs. The controller also receives a user flightpath and determines a projected user trajectory based on the user drag. The controller also determines user drag adjustments to align the projected user trajectory with the received user flightpath. At least one of an aural, haptic, or visual feedback device is coupled to the controller to provide feedback to the user in response to the user drag adjustments.

Growing community of inventors

Phoenix, AZ, United States of America

Stephanie Moyerman