Abstract: The disclosed method may include receiving neuromuscular activity data over a first time series from a first sensor on a wearable device donned by a user receiving ground truth data over a second time series from a second sensor that indicates a body part state of a body part of the user, generating one or more training datasets by time-shifting at least a portion of the neuromuscular activity data over the first time series relative to the second time series, to associate the neuromuscular activity data with at least a portion of the ground truth data, and training one or more inferential models based on the one or more training datasets. Various other related methods and systems are also disclosed.

Abstract: Methods and apparatus for generating a control signal based on sub-muscular activation. Information for a first sub-muscular control channel of a plurality of sub-muscular control channels is derived from the plurality of neuromuscular signals. Each of the plurality of sub-muscular control channels is configured to process information associated with activation of one or more sub-muscular structures. A control signal is generated based on the derived information for the first sub-muscular control channel and the control signal is provided to a control interface to control an operation of a device.

Abstract: 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.

Abstract: Methods and apparatus for calibrating performance of one or more statistical models used to generate a musculoskeletal representation. The method comprises controlling presentation of instructions via a user interface to instruct the user to perform the at least one gesture and updating at least one parameter of the one or more statistical models based, at least in part on a plurality of neuromuscular signals recorded by a plurality of neuromuscular sensors during performance of the at least one gesture by the user.

Abstract: Methods and apparatus for enabling a user or third-party to select or adjust parameters of one or more statistical models used to generate a musculoskeletal representation. The method comprises providing as input to the statistical model(s), a plurality of neuromuscular signals recorded by a plurality of neuromuscular sensors during performance of at least one gesture by a user, wherein the at least one gesture is performed by the user while wearing a wearable device having the plurality of neuromuscular sensors arranged thereon, rendering at least one visual representation based on an output of the statistical model(s), and receiving user or third-party input to adjust parameters of the statistical model(s) based on the rendered at least one visual representation, the user input including a selection of a particular statistical model of the statistical model(s) and/or an adjustment of parameters associated with the particular statistical model.

Abstract: Methods and apparatus for anonymizing neuromuscular signals used to generate a musculoskeletal representation. The method comprises recording, using a plurality of neuromuscular sensors arranged on one or more wearable devices, a plurality of neuromuscular signals from a user, providing as input to a trained statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals; and generating, the musculoskeletal representation based, at least in part, on an output of the trained statistical model, wherein the musculoskeletal representation is an anonymized musculoskeletal representation from which at least one personal characteristic of the user has been removed.

Abstract: Methods and apparatus for controlling a physical object in an environment based, at least in part, on neuromuscular signals. The method comprises recording a plurality of neuromuscular signals from a plurality of neuromuscular sensors arranged on one or more wearable devices worn by a user, receiving a selection of a physical object within the environment, and controlling, based at least in part on the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals, an operation of the selected object within the environment.

Abstract: Systems and methods for using neuromuscular information to improve speech recognition. The system includes a plurality of neuromuscular sensors, arranged on one or more wearable devices, wherein the plurality of neuromuscular sensors is configured to continuously record a plurality of neuromuscular signals from a user, at least one storage device configured to store one or more trained statistical models, and at least one computer processor programmed to provide as an input to the one or more trained statistical models, the plurality of neuromuscular signals or signals derived from the plurality of neuromuscular signals, determine based, at least in part, on an output of the one or more trained statistical models, at least one instruction for modifying an operation of a speech recognizer, and provide the at least one instruction to the speech recognizer.

Abstract: Computerized systems, methods, and computer-readable storage media storing code for implementing the methods are provided, in which camera information is used to calibrate one or more inference models used to generate a musculoskeletal representation. One such system includes at least one camera configured to capture at least one image, a plurality of neuromuscular sensors configured to sense and record a plurality of neuromuscular signals from a user, and at least one computer processor. The plurality of neuromuscular sensors are arranged on one or more wearable devices structured to be worn by the user to obtain the plurality of neuromuscular signals. The at least one computer processor is programmed to calibrate the one or more inference models by updating at least one parameter associated with the one or more inference models based, at least in part, on the plurality of neuromuscular signals and the at least one image.

Abstract: 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.

Abstract: 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.

Abstract: Methods and apparatus for substantially real-time detection of spike events in neuromuscular data. The method comprises receiving a plurality of neuromuscular signals from a plurality of neuromuscular sensors arranged on one or more wearable devices worn by a user, detecting, based on the plurality of neuromuscular signals or information derived from the plurality of neuromuscular signals, at least one spike event corresponding to firing of an action potential in at least one motor unit, determining, based on the plurality of neuromuscular signals or the information derived from the plurality of neuromuscular signals, a biological source of the detected at least one spike event, and generating at least one output based, at least in part, on the detected at least one spike event and/or the determined biological source of the detected at least one spike event.

Abstract: Methods and apparatus for anonymizing neuromuscular signals used to generate a musculoskeletal representation. The method comprises recording, using a plurality of neuromuscular sensors arranged on one or more wearable devices, a plurality of neuromuscular signals from a user, providing as input to a trained statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals; and generating, the musculoskeletal representation based, at least in part, on an output of the trained statistical model, wherein the musculoskeletal representation is an anonymized musculoskeletal representation from which at least one personal characteristic of the user has been removed.

Abstract: Methods and apparatus for calibrating performance of one or more statistical models used to generate a musculoskeletal representation. The method comprises controlling presentation of instructions via a user interface to instruct the user to perform the at least one gesture and updating at least one parameter of the one or more statistical models based, at least in part on a plurality of neuromuscular signals recorded by a plurality of neuromuscular sensors during performance of the at least one gesture by the user.

Abstract: Methods and apparatus for generating a control signal based on sub-muscular activation. Information for a first sub-muscular control channel of a plurality of sub-muscular control channels is derived from the plurality of neuromuscular signals. Each of the plurality of sub-muscular control channels is configured to process information associated with activation of one or more sub-muscular structures. A control signal is generated based on the derived information for the first sub-muscular control channel and the control signal is provided to a control interface to control an operation of a device.

Abstract: Methods and apparatus for enabling a user or third-party to select or adjust parameters of one or more statistical models used to generate a musculoskeletal representation. The method comprises providing as input to the statistical model(s), a plurality of neuromuscular signals recorded by a plurality of neuromuscular sensors during performance of at least one gesture by a user, wherein the at least one gesture is performed by the user while wearing a wearable device having the plurality of neuromuscular sensors arranged thereon, rendering at least one visual representation based on an output of the statistical model(s), and receiving user or third-party input to adjust parameters of the statistical model(s) based on the rendered at least one visual representation, the user input including a selection of a particular statistical model of the statistical model(s) and/or an adjustment of parameters associated with the particular statistical model.

Abstract: 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.

Abstract: Systems and methods for using neuromuscular information to improve speech recognition. The system includes a plurality of neuromuscular sensors, arranged on one or more wearable devices, wherein the plurality of neuromuscular sensors is configured to continuously record a plurality of neuromuscular signals from a user, at least one storage device configured to store one or more trained statistical models, and at least one computer processor programmed to provide as an input to the one or more trained statistical models, the plurality of neuromuscular signals or signals derived from the plurality of neuromuscular signals, determine based, at least in part, on an output of the one or more trained statistical models, at least one instruction for modifying an operation of a speech recognizer, and provide the at least one instruction to the speech recognizer.

Abstract: Systems and methods for using neuromuscular information to improve speech recognition. The system includes a plurality of neuromuscular sensors arranged on one or more wearable devices and configured to continuously record a plurality of neuromuscular signals from a user, at least one storage device configured to store one or more trained statistical models for determining text based on audio input and the plurality of neuromuscular signals, at least one input interface configured to receive the audio input, and at least one computer processor programmed to obtain the audio input and the plurality of neuromuscular signals, provide as input to the one or more trained statistical models, the audio input and the plurality of neuromuscular signals or signals derived from the plurality of neuromuscular signals, and determine based, at least in part, on an output of the one or more trained statistical models, the text.

Abstract: 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.