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Implementation of EMG- and force-based control interfaces in active elbow supports for men with duchenne muscular dystrophy: a feasiblitity study

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    Abstract

    While there is an extensive number of studies on the development and evaluation of electromyography (EMG)- and force-based control interfaces for assistive devices, no studies have focused on testing these control strategies for the specific case of adults with Duchenne muscular dystrophy (DMD). This paper presents a feasibility study on the use of EMG and force as control interfaces for the operation of active arm supports for men with DMD. We have built an experimental active elbow support, with a threefold objective: 1) to investigate whether adult men with DMD could use EMG- and force-based control interfaces; 2) to evaluate their performance during a discrete position-tracking task; and 3) to examine users' acceptance of the control methods. The system was tested in three adults with DMD (21-22 years). Although none of the three participants had performed any voluntary movements with their arms for the past 3-5 years, all of them were 100% successful in performing the series of tracking tasks using both control interfaces (mean task completion time EMG: 6.8 ± 4.8 s, force: 5.1 ± 1.8 s). While movements with the force-based control were considerably smoother in Subject 3 and faster in Subject 1, EMG based-control was perceived as less fatiguing by all three subjects. Both EMG- and force-based interfaces are feasible solutions for the control of active elbow supports in adults with DMD and should be considered for further investigations on multi-DOF control.
    Original languageEnglish
    Pages (from-to)1179-1190
    Number of pages12
    JournalIEEE transactions on neural systems and rehabilitation engineering
    Volume24
    Issue number11
    DOIs
    Publication statusPublished - 1 Nov 2016

    Keywords

    • 2023 OA procedure
    • Electromyography (EMG) control
    • Arm support
    • Force control
    • Duchenne
    • Assistive devices
    • Human–robot interaction

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