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Calibration techniques for handstate representation modeling using neuromuscular signals

  • US 10,496,168 B2
  • Filed: 01/25/2019
  • Issued: 12/03/2019
  • Est. Priority Date: 01/25/2018
  • Status: Active Grant
First Claim
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1. A computerized system configured to calibrate performance of one or more statistical models used to generate a musculoskeletal representation, the system comprising:

  • a plurality of neuromuscular sensors configured to continuously record a plurality of neuromuscular signals, wherein the plurality of neuromuscular sensors are arranged on at least one wearable device; and

    at least one computer processor programmed to;

    process at least some of the plurality of neuromuscular signals using a statistical model to generate based, at least in part, on joint angle estimates and/or force estimates output from the statistical model, the musculoskeletal representation;

    determine based, at least in part, on at least one aspect of the musculoskeletal representation, that calibration of the statistical model used to generate the musculoskeletal representation is needed;

    initiate a calibration session in response to determining that calibration is needed;

    update a statistical model configuration based, at least in part, on a plurality of neuromuscular signals recorded by the plurality of neuromuscular sensors and ground-truth data representing position information and/or force information recorded during the calibration session to produce an updated statistical model;

    process at least some of the plurality of neuromuscular signals using the updated statistical model to generate an updated musculoskeletal representation;

    determine, based, at least in part, on the at least one aspect of the updated musculoskeletal representation whether further calibration of the statistical model is needed; and

    end the calibration session in response to determining that further calibration is not needed.

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