The Difficulty of Recognizing Grasps from sEMG during Activities of Daily Living

The application of machine learning to recognize hand movements from surface electromyography has led to promising academic results. Unfortunately, it has proven difficult to translate these results in better control methods for the end-users of upper-limb prostheses. Recent studies have pointed out that common offline performance metrics, such as classification accuracy, are not correlated with real controllability of the prosthesis. In this...