Enhancing practical multifunctional myoelectric applications through implicit motor control training systems

Despite holding promise for advances in prostheses and robot teleoperation, myoelectric controlled interfaces have had limited impact in commercial applications. Simultaneous multifunctional controls are desired, but often lead to frustration by users who cannot easily control the devices using state-of-the-art control schemes. This paper proposes and validates the use of implicit motor control training systems (IM-CTS) to achieve practical implementations of multifunctional myoelectric applications. Subjects implicitly develop muscle synergies needed to control a robotic application through an analogous visual interface without the associated physical constraints which may hinder learning. The learning then naturally transfers to perceived intuitive and robust control of the robotic device. The efficacy of the method is tested by comparing performance between two groups learning controls implicitly via the visual interface and explicitly via the robotic interface, respectively. The groups achieved comparable performance when performing tasks with the robotic device a week later. Moreover, the initial performance of the experimental group was significantly better than the control group achieved after up to 75 minutes of training. These findings support the use of IMCTS to achieve practical multifunctional control of a wide range of myoelectric applications without limiting them to intuitive mappings nor anthropomorphic devices.