Techniques for anonymizing neuromuscular signal data
First Claim
1. A computerized system for anonymizing neuromuscular signals used to generate a musculoskeletal representation, the system comprising:
- a plurality of neuromuscular sensors configured to continuously record a plurality of neuromuscular signals from a user, wherein the plurality of neuromuscular sensors are arranged on one or more wearable devices; and
at least one computer processor programmed to;
provide as input to a statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals, wherein;
the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals provided as input to the statistical model includes a first personal characteristic of the user, andthe statistical model is trained to remove the first personal characteristic of the user from the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals; and
generate the musculoskeletal representation based, at least in part, on position estimates and/or force estimates output from the trained statistical model, wherein;
the musculoskeletal representation is an anonymized musculoskeletal representation from which the first personal characteristic of the user has been removed, andthe statistical model has been trained using an adversarial training approach to remove the first personal characteristic of the user while predicting the position estimates and/or the force estimates associated with the musculoskeletal representation.
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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.
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Citations
25 Claims
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1. A computerized system for anonymizing neuromuscular signals used to generate a musculoskeletal representation, the system comprising:
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a plurality of neuromuscular sensors configured to continuously record a plurality of neuromuscular signals from a user, wherein the plurality of neuromuscular sensors are arranged on one or more wearable devices; and at least one computer processor programmed to; provide as input to a statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals, wherein; the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals provided as input to the statistical model includes a first personal characteristic of the user, and the statistical model is trained to remove the first personal characteristic of the user from the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals; and generate the musculoskeletal representation based, at least in part, on position estimates and/or force estimates output from the trained statistical model, wherein; the musculoskeletal representation is an anonymized musculoskeletal representation from which the first personal characteristic of the user has been removed, and the statistical model has been trained using an adversarial training approach to remove the first personal characteristic of the user while predicting the position estimates and/or the force estimates associated with the musculoskeletal representation. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A computerized system for anonymizing neuromuscular signals used to generate a musculoskeletal representation, the system comprising:
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a plurality of neuromuscular sensors configured to continuously record a plurality of neuromuscular signals from a user, wherein the plurality of neuromuscular sensors are arranged on one or more wearable devices; and at least one computer processor programmed to; provide as input to a trained statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals; generate the musculoskeletal representation based, at least in part, on an output of the trained statistical model, wherein the output of the trained statistical model comprises; position estimates and/or force estimates associated with the musculoskeletal representation, wherein the position estimates and/or the force estimates include at least one personal characteristic of the user; and render a visual representation based on the musculoskeletal representation, wherein; the musculoskeletal representation includes the at least one personal characteristic of the user, and rendering the visual representation comprises removing the at least one personal characteristic of the user during rendering of the visual representation. - View Dependent Claims (15, 16, 17, 18)
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19. A method for anonymizing neuromuscular signals used to generate a musculoskeletal representation, the method comprising:
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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 statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals, wherein; the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals provided as input to the statistical model includes at least one personal characteristic of the user, and the statistical model is trained to remove the at least one personal characteristic of the user from 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 position estimates and/or force estimates output from the trained statistical model, wherein; the musculoskeletal representation is an anonymized musculoskeletal representation from which the at least one personal characteristic of the user has been removed, and the statistical model has been trained using an adversarial training approach to remove the at least one personal characteristic of the user while predicting the position estimates and/or the force estimates associated with the musculoskeletal representation. - View Dependent Claims (20)
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21. A method for anonymizing neuromuscular signals used to generate a musculoskeletal representation, the method comprising:
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providing as input to a trained statistical model, a plurality of neuromuscular signals recorded from a user by a plurality of neuromuscular sensors and/or information based on the plurality of neuromuscular signals; generating the musculoskeletal representation based, at least in part, on an output of the trained statistical model, wherein the output of the trained statistical model comprises; position estimates and/or force estimates associated with the musculoskeletal representation, wherein the position estimates and/or the force estimates include at least one personal characteristic of the user; and rendering a visual representation based on the musculoskeletal representation, wherein; the musculoskeletal representation includes the at least one personal characteristic of the user, and rendering the visual representation comprises removing the at least one personal characteristic of the user during rendering of the visual representation. - View Dependent Claims (22, 23, 24, 25)
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Specification