Facebook Technologies, LLC

Meta Platforms Technologies, LLC

Ctrl-labs Corporation

Timothy Machado

Patrick Kaifosh

Thomas Reardon

Erik Schomburg

Tudor Giurgica-Tiron

Joshua Merel

Steven Brian Demers

Calvin Tong

Steven Demers

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

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.

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Palo Alto, CA, United States of America

Timothy Machado