Simultaneous and Proportional Myocontrol of a Hand Exoskeleton for Spinal Muscular Atrophy: A Preliminary Evaluation

Abstract

Spinal Muscular Atrophy (SMA) is a neuromuscular disease characterized by the degeneration of the $\alpha$-motor neurons in the spinal cord, resulting in progressive proximal muscle weakness and paralysis. It is the second most common fatal autosomal recessive disorder after cystic fibrosis in the world. In the context of assistive robotics for SMA, in this work the authors have preliminarily assessed the feasibility of using low-cost electromyography pattern recognition and simultaneous/proportional myocontrol to enforce smooth, intuitive control of an assistive hand exoskeleton system. A target achievement control test has involved ten healthy subjects. Synthetic noise has been added to their surface ElectroMyoGraphic (sEMG) signals in order to reach a signal-to-noise ratio similar to that of sEMG signals gathered from a SMA patient. The results indicate that, even neglecting any learning effect, an SMA patient could reach an average success rate of up to 82% through the proposed approach.

This work was partially supported by the German Research Society project Deep-Hand (DFG Sachbeihilfe CA-1389/1-2), The authors would like to thank Annette Hagengruber and Jörn Vogel of the DLR for useful insights and for making available to us sEMG signals recorded from a SMA patient.