Robust EMG pattern recognition in the presence of confounding factors: features, classifiers and adaptive learning.

•Multiple compounding factors are considered during the data-collection.•Donning and doffing the electrodes on different arms is firstly tested.•A variety of features and classifiers are examined to increase the robustness.•New adaptive learning method effectively maintains the classification accuracy.