Calibration techniques for handstate representation modeling using neuromuscular signals

A method of calibrating performance of one or more statistical models used to generate a musculoskeletal representation, the method comprising:

• recording a plurality of neuromuscular signals using a plurality of neuromuscular sensors arranged on at least one wearable device;
• processing 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;
• determining 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;
• initiating a calibration session in response to determining that calibration is needed;
• updating 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;
• processing at least some of the plurality of neuromuscular signals using the updated statistical model to generate an updated musculoskeletal representation;
• determining, 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
• ending the calibration session in response to determining that further calibration is not needed.

A computerized system configured to calibrate performance of one or more statistical models used to generate a musculoskeletal representation, the system comprising:

• a user interface configured to instruct a user to perform at least one gesture while wearing a wearable device having a plurality of neuromuscular sensors arranged thereon;
• and
• at least one computer processor programmed to:
• control presentation of instructions via the user interface to instruct the user to perform the at least one gesture;
• update at least one parameter of the one or more statistical models based, at least in part, on a plurality of neuromuscular signals recorded by the plurality of neuromuscular sensors during performance of the at least one gesture by the user;
• identify, based on at least one aspect of the musculoskeletal representation generated based, at least in part, on joint angle estimates and/or force estimates output from the one or more statistical models, a plurality of gesture characteristics that the one or more statistical models is poor at estimating;
• select a new gesture for the user to perform that includes the identified plurality of gesture characteristics;
• control presentation of instructions via the user interface to instruct the user to perform the new gesture;
• and
• update at least one parameter of the one or more statistical models based, at least in part, on the plurality of neuromuscular signals recorded by the neuromuscular sensors during performance of the new gesture by the user.

A method of calibrating performance of one or more statistical models used to generate a musculoskeletal representation, the method comprising:

• instructing, via a user interface, a user to perform at least one gesture while wearing a wearable device having a plurality of neuromuscular sensors arranged thereon;
• controlling presentation of instructions via the user interface to instruct the user to perform the at least one gesture;
• 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 the plurality of neuromuscular sensors during performance of the at least one gesture by the user;
• identifying, based on at least one aspect of the musculoskeletal representation generated based, at least in part, on joint angle estimates and/or force estimates output from the one or more statistical models, a plurality of gesture characteristics that the one or more statistical models is poor at estimating;
• selecting a new gesture for the user to perform that includes the identified plurality of gesture characteristics;
• controlling presentation of instructions via the user interface to instruct the user to perform the new gesture;
• and
• updating at least one parameter of the one or more statistical models based, at least in part, on the plurality of neuromuscular signals recorded by the neuromuscular sensors during performance of the new gesture by the user.