Real-time myoelectric control of wrist/hand motion in Duchenne muscular dystrophy: A case study

Frontiers in Robotics and AI

Robotics and AI

Bart F. J. M. Koopman¹  Anıl Ayvaz¹  Massimo Sartori¹  Noortje H. M. Rijken²  Kostas Nizamis³ 

[1] Neuromechanical Modelling and Engineering lab, Department of Biomechanical Engineering, Faculty of Engineering Technology, University of Twente, Enschede, Netherlands;Research Group Smart Health, Saxion University of Applied Sciences, Enschede, Netherlands;Systems Engineering and Multidisciplinary Design Group, Department of Design, Production, and Management, Faculty of Engineering Technology, University of Twente, Enschede, Netherlands;

关键词: admittance;    Duchenne muscular dystrophy;    forearm;    intention decoding;    myoelectric control;    pattern recognition;    surface electromyography;    wrist;   

DOI  :  10.3389/frobt.2023.1100411

 received in 2022-11-16, accepted in 2023-03-21,  发布年份 2023

来源: Frontiers

【 摘 要 】

Introduction: Duchenne muscular dystrophy (DMD) is a genetic disorder that induces progressive muscular degeneration. Currently, the increase in DMD individuals' life expectancy is not being matched by an increase in quality of life. The functioning of the hand and wrist is central for performing daily activities and for providing a higher degree of independence. Active exoskeletons can assist this functioning but require the accurate decoding of the users' motor intention. These methods have, however, never been systematically analyzed in the context of DMD.Methods: This case study evaluated direct control (DC) and pattern recognition (PR), combined with an admittance model. This enabled customization of myoelectric controllers to one DMD individual and to a control population of ten healthy participants during a target-reaching task in 1- and 2- degrees of freedom (DOF). We quantified real-time myocontrol performance using target reaching times and compared the differences between the healthy individuals and the DMD individual.Results and Discussion: Our findings suggest that despite the muscle tissue degeneration, the myocontrol performance of the DMD individual was comparable to that of the healthy individuals in both DOFs and with both control approaches. It was also evident that PR control performed better for the 2-DOF tasks for both DMD and healthy participants, while DC performed better for the 1-DOF tasks. The insights gained from this study can lead to further developments for the intuitive multi-DOF myoelectric control of active hand exoskeletons for individuals with DMD.

【 授权许可】

Unknown   
Copyright © 2023 Nizamis, Ayvaz, Rijken, Koopman and Sartori.