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 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 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: 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: 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: 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: System and methods are provided for providing a dynamically-updated musculoskeletal representation of a hand. The system includes a plurality of neuromuscular 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 and temporally smooth in real-time an output of the trained statistical model. The system is also programmed to determine, based on the smoothed output of the trained statistical model, position information describing a spatial relationship between two or more connected segments of the musculoskeletal representation, force information describing a force exerted by at least one segment of the musculoskeletal representation, and update the musculoskeletal representation of the hand based, at least in part, on the position information and the force information.

Abstract: Arrangements for improving neuromuscular recording electrode contact with a body surface are described. According to some aspects, a sensor assembly may include a housing and one or more electrodes that are moveable relative to the housing. The electrodes may rotate and/or translate relative to the housing and/or have at least two degrees of freedom relative to the housing. The sensor may include a spring element that stores potential energy and biases the electrodes toward a starting position in which the electrodes extend at least partially out of the sensor housing. In some embodiments, application of a contact force to one or more of the electrodes of the sensor compresses the spring element, causing the spring element to store potential energy.

Abstract: Systems, devices and methods that enable a user to access and interact with content displayed on a portable electronic display in an inconspicuous, hands-free manner are described. There is disclosed a completely wearable system comprising a wearable muscle interface device and a wearable head-mounted display, as well as methods for using the wearable system to effect interactions between the user and content displayed on the wearable head-mounted display. The wearable muscle interface device includes muscle activity sensors worn on an arm of the user to detect muscle activity generated when the user performs a physical gesture. The wearable system is adapted to recognize a plurality of gestures made by the user and, in response to each recognized gesture, to effect one or more interaction(s) with content displayed on the wearable head-mounted display.

Abstract: Methods and apparatus for authenticating a user based on neuromuscular signals. 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; deriving a neuromuscular signature for the user from the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals, wherein the neuromuscular signature is indicative of at least one personal characteristic of the user detected in the plurality of neuromuscular signals; and authenticating the user based on the derived neuromuscular signature.

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: Techniques for shielding wearable surface electromyography (sEMG) devices are described. According to some aspects, an sEMG device may comprise amplification circuitry comprising at least a first differential amplifier and at least two sEMG electrodes electrically connected to the amplification circuitry. The device may further comprise at least one auxiliary conductor not electrically connected to the amplification circuitry, wherein the at least one auxiliary conductor is configured to be electrically coupled to a wearer of the wearable device, and an electromagnetic shield surrounding the wearable device at least in part and electrically connected to the at least one auxiliary conductor.

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 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 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: Systems and methods for text input based on neuromuscular information. 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 obtain the plurality of neuromuscular signals from the plurality of neuromuscular sensors, provide as input to the one or more trained statistical models, 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, one or more linguistic tokens.

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: System and methods are provided for providing a dynamically-updated musculoskeletal representation of a hand. The system includes a plurality of neuromuscular 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 and temporally smooth in real-time an output of the trained statistical model. The system is also programmed to determine, based on the smoothed output of the trained statistical model, position information describing a spatial relationship between two or more connected segments of the musculoskeletal representation, force information describing a force exerted by at least one segment of the musculoskeletal representation, and update the musculoskeletal representation of the hand based, at least in part, on the position information and the force information.