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EDAN: An EMG-controlled Daily Assistant to Help People With Physical Disabilities

Jörn Vogel, Annette Hagengruber, Maged Iskandar, Gabriel Quere, Ulrike Leipscher, Samuel Bustamante, Alexander Dietrich, Hannes Höppner, Daniel Leidner, Alin Albu‐Schäffer

202046 citationsDOI

Abstract

Injuries, accidents, strokes, and other diseases can significantly degrade the capabilities to perform even the most simple activities in daily life. A large share of these cases involves neuromuscular diseases, which lead to severely reduced muscle function. However, even though affected people are no longer able to move their limbs, residual muscle function can still be existent. Previous work has shown that this residual muscular activity can suffice to apply an EMG-based user interface. In this paper, we introduce DLR's robotic wheelchair EDAN (EMG-controlled Daily Assistant), which is equipped with a torque-controlled, eight degree-of-freedom light-weight arm and a dexterous, five-fingered robotic hand. Using electromyography, muscular activity of the user is measured, processed and utilized to control both the wheelchair and the robotic manipulator. This EMG-based interface is enhanced with shared control functionality to allow for efficient and safe physical interaction with the environment.

Topics & Concepts

WheelchairElectromyographyPhysical medicine and rehabilitationTorqueComputer scienceInterface (matter)Work (physics)ResidualSimulationRobotHuman–computer interactionEngineeringArtificial intelligenceMedicineMechanical engineeringMaximum bubble pressure methodThermodynamicsAlgorithmBubbleParallel computingPhysicsWorld Wide WebGaze Tracking and Assistive TechnologyEEG and Brain-Computer InterfacesMuscle activation and electromyography studies
EDAN: An EMG-controlled Daily Assistant to Help People With Physical Disabilities | Litcius