Facebook Technologies, LLC

Meta Platforms Technologies, LLC

Ctrl-labs Corporation

Thomas Reardon

Patrick Kaifosh

Timothy Machado

Erik Schomburg

Adam L Berenzweig

Daniel Z Wetmore

Christopher Osborn

Brett Jurman

Pol Pla I Conesa

Tudor Giurgica-Tiron

Roger Ibars Martinez

Chris Rojas

Joshua Merel

Bryan Sparks

Steven Brian Demers

Emron Jackson Henry

Calvin Tong

Joseph N Bravate

Eric Ma

Vikram Tank

A non-transitory computer-readable storage medium including instructions for distributing tasks between a handheld intermediary processing device (HIPD) and communicatively coupled devices is disclosed. The instructions cause one or more processors to, while a HIPD and a head-wearable device are communicatively coupled and share operational data for performing one or more computational tasks, identify one or more back-end tasks and one or more front-end tasks associated with performing the one or more computational tasks. The instructions further cause performance of the one or more back-end tasks at the HIPD including updating the operational data to create updated operational data. The instructions further cause performance of the one or more front-end tasks at the head-wearable device using the updated operational data such that a representation based on the one or more computational tasks is presented to the user by the head-wearable device.

Intermediary device for offloading processing operations for an artificial-reality system and for enabling interactions and input paradigms, and systems and methods of use thereof

A system comprising a plurality of neuromuscular sensors, each of which is configured to record a time-series of neuromuscular signals from a surface of a user's body; and at least one computer hardware processor programmed to perform: applying a source separation technique to the time series of neuromuscular signals recorded by the plurality of neuromuscular sensors to obtain a plurality of neuromuscular source signals and corresponding mixing information; providing features, obtained from the plurality of neuromuscular source signals and/or the corresponding mixing information, as input to a trained statistical classifier and obtaining corresponding output; and identifying, based on the output of the trained statistical classifier, and for each of one or more of the plurality of neuromuscular source signals, an associated set of one or more biological structures.

Systems and methods for identifying biological structures associated with neuromuscular source signals

A method for determining spatial information for a multi-segment articulated rigid body system having at least an anchored segment and a non-anchored segment coupled to the anchored segment, each segment in the multi-segment articulated rigid body system representing a respective body part of a user, the method comprising: obtaining signals recorded by a first autonomous movement sensor coupled to a body part of the user represented by the non-anchored segment; providing the obtained signals as input to a trained statistical model and obtaining corresponding output of the trained statistical model; and determining, based on the corresponding output of the trained statistical model, spatial information for at least the non-anchored segment of the multi-segment articulated rigid body system. Determining the spatial information may include determining the position and/or orientation of the non-anchored segment relative to the anchor point and/or determining a spatial relationship between the anchored and non-anchored segments.

System and method for measuring the movements of articulated rigid bodies

Methods and apparatus for adapting a control mapping associating sensor signals with control signals for controlling an operation of a device. The method comprises obtaining first state information for an operation of the device, providing the first state information as input to an intention model associated with an operation of the device and obtaining corresponding first intention model output, providing a plurality of neuromuscular signals recorded from a user and/or signals derived from the neuromuscular signals as inputs to a first control mapping and obtaining corresponding first control mapping output, and updating the first control mapping using the inputs provided to the first control mapping and the first intention model output to obtain a second control mapping.

Adaptive system for deriving control signals from measurements of neuromuscular activity

Methods and apparatus for providing a dynamically-updated computerized musculo-skeletal representation comprising a plurality of rigid body segments connected by joints. The method comprises recording, using a plurality of autonomous sensors arranged on one or more wearable devices, a plurality of autonomous signals from a user, wherein the plurality of autonomous sensors include a plurality of neuromuscular sensors configured to record neuromuscular signals. The method further comprises providing as input to a trained statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals. The method further comprises determining, based on an output of the trained statistical model, musculo-skeletal position information describing a spatial relationship between two or more connected segments of the plurality of rigid body segments of the computerized musculo-skeletal representation, and updating the computerized musculo-skeletal representation based, at least in part, on the musculo-skeletal position information.

Methods and apparatus for predicting musculo-skeletal position information using wearable autonomous sensors

Computerized systems, methods, and computer-readable storage media storing code for implementing the methods are described for providing dynamically-updated musculoskeletal information. One such system includes a processor is programmed to: provide, as an input to a trained inference model, information based on a plurality of neuromuscular signals from a user and information based on at least one image of the user; determine, based on an output of the trained inference model, position information describing a spatial relationship between two or more connected musculoskeletal segments of the user and/or force information describing a force exerted by at least one musculoskeletal segment of the user; and output the position information and/or the force information.

Camera-guided interpretation of neuromuscular signals

Computerized systems, methods, and computer-readable storage media storing code for implementing the methods are provided for training an inference model used to generate a musculoskeletal representation. One such system includes a processor programmed to: determine, based on information obtained from at least one image, position information describing a spatial relationship between two or more connected musculoskeletal segments of a user; determine, based on a plurality of neuromuscular signals, force information; associate the position information with the force information; train an inference model to output a musculoskeletal representation consistent with the position information and/or the force information when neuromuscular input signals provided to the inference model have at least one predetermined characteristic, to produce an updated inference model; and cause the updated inference model to be stored in a memory.

Methods and system for predicting the onset of a motor action using neuromuscular signals. The system comprises a plurality of sensors configured to continuously record a plurality of neuromuscular signals from a user and at least one computer processor programmed to provide as input to a trained statistical model, the plurality of neuromuscular signals or information based on the plurality of neuromuscular signals, predict, based on an output of the trained statistical model, whether an onset of a motor action will occur within a threshold amount of time; and send a control signal to at least one device based, at least in part, on the output probability, wherein the control signal is sent to the at least one device prior to completion of the motor action by the user.

Growing community of inventors

New York, NY, United States of America

Thomas Reardon