Methods and apparatus for predicting musculo-skeletal position information using wearable autonomous sensors

A method of providing a dynamically-updated computerized musculo-skeletal representation comprising a plurality of rigid body segments connected by joints, the method comprising:

• recording, using a plurality of autonomous sensors arranged on one or more wearable devices, a plurality of autonomous signals from a user, wherein the plurality of autonomous sensors comprise a plurality of neuromuscular sensors configured to record a plurality of neuromuscular signals;
• providing as input to a trained statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals;
• determining, based on an output of the trained statistical model, musculo-skeletal position information describing a spatial relationship between two or more connected segments of the plurality of rigid body segments of the computerized musculo-skeletal representation;
• and
• updating the computerized musculo-skeletal representation based, at least in part, on the musculo-skeletal position information.

A computer system for training a statistical model to predict musculo-skeletal position information based, at least in part, on autonomous signals recorded by a plurality of autonomous sensors, wherein the plurality of autonomous sensors include a plurality of neuromuscular sensors configured to record a plurality of neuromuscular signals, the computer system comprising:

• an input interface configured to:
• receive the neuromuscular signals recorded during performance of a task performed by one or more users;
• receive position information indicating a position of a plurality of rigid body segments of a computerized musculo-skeletal representation during performance of the task 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 signals and the received position information;
• training the statistical model using at least some of the generated training data to output a trained statistical model;
• and
• storing, by the at least one storage device, the trained statistical model, wherein the trained statistical model is configured to predict musculo-skeletal position information based, at least in part on continuously recorded signals from the neuromuscular sensors.