Methods and apparatus for inferring user intent based on neuromuscular signals

A method of predicting an onset of a motor action, the method comprising

• providing, as input to a trained statistical model, a plurality of neuromuscular signals recorded from a plurality of sensors arranged on or around a part of a user's body, wherein the trained statistical model was trained based, at least in part, on neuromuscular data recorded during at least one previous performance of a motor action by one or more users and result data indicating an outcome of the motor action performed by the one or more users, wherein the trained statistical model is configured to predict the onset of the motor action prior to completion of the motor action;
• predicting, using at least one computer processor, whether an onset of the motor action will occur within a threshold amount of time;
• and
• sending a control signal to at least one device based, at least in part, on the prediction, wherein the control signal is sent to the at least one device prior to completion of the motor action by the user to control an operation of the at least one device.

A computer system for training a statistical model to predict an onset of a motor action based, at least in part, on neuromuscular signal data, the computer system comprising:

• an input interface configured to:
• receive the neuromuscular signal data recorded during performance of a motor action performed by one or more users;
• receive result data indicating an outcome of the motor action performed by the one or more users;
• and
• at least one storage device configured to store a plurality of instructions that, when executed by at least one computer processor perform a method of:
• generating training data based, at least on part, on the received neuromuscular signal data and the received result data;
• training the statistical model using at least some of the generated training data to output a trained statistical model;
• determining an operating threshold used to interpret output of the trained statistical model;
• and
• storing, by the at least one storage device, the trained statistical model and the operating threshold, wherein the trained statistical model is configured to predict the onset of the motor action prior to completion of the motor action by a user.