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: 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: The disclosed systems and methods are generally directed to interpreting neuromuscular signals. The system includes (A) a plurality of neuromuscular sensors that detect a plurality of neuromuscular signals from a user and (B) at least one multiplexer in communication with the plurality of neuromuscular sensors and that is capable of dynamically adjusting neuromuscular sensor processing based on neuromuscular signal characteristics. A computer processor is programmed to (i) receive a set of neuromuscular signals from the plurality of neuromuscular sensors, (ii) determine, via a real-time system, at least one signal characteristic included in a neuromuscular signal, where the neuromuscular signal is associated with a first neuromuscular sensor included in the plurality of neuromuscular sensors; and (iii) dynamically reconfigure the processing of neuromuscular signals from the plurality of neuromuscular sensors based on an output from the multiplexer.

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: 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: 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 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: 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: 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 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: 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: 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: 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: Methods and apparatus for mitigating neuromuscular signal artifacts are described. The method comprises detecting in real-time, by at least one computer processor, one or more artifacts in a plurality of neuromuscular signals recorded by a plurality of neuromuscular sensors, determining, based at least in part, on the detected one or more artifacts, a plurality of derived neuromuscular signals to mitigate the one or more artifacts, and providing, as input to one or more trained statistical models, the plurality of derived neuromuscular signals.

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.