Systems and methods for autoconfiguration of pattern-recognition controlled myoelectric prostheses

A system for training a prosthesis comprising:

• a prosthesis;
• a plurality of sensors associated with the prosthesis operable to detect electromyographic activity generated in response to a sequence of automated joint movements of the prosthesis, such electromyographic activity representing mimicking of the automated joint movements, and generate electromyographic signal data from the electromyographic activity;
• a processor in communication with the prosthesis to:
• receive the electromyographic signal data from the plurality of sensors;
• and
• determine, based on the electromyographic signal data, a motion intent for the prosthesis during real-time operation of the prosthesis, by
• generating calibration classifier parameters, by:
• extracting, at the processor, at least one signal feature from the electromyographic signal data, and
• applying, using the processor, at least one machine learning algorithm to the at least one signal feature.