Abstract: Most impedance-based walking controllers for powered knee–ankle prostheses use a finite state machine with dozens of user-specific parameters that require manual tuning by technical experts.

Does one of these scenarios sounds familiar to you? You are working on your own side-project in NLP, but you don't have enough labeled data to train a good model. You are working in a team and already ...