Assisted Grasping in Individuals with Tetraplegia: Improving Control through Residual Muscle Contraction and Movement

Bibliographic Details
Title: Assisted Grasping in Individuals with Tetraplegia: Improving Control through Residual Muscle Contraction and Movement
Authors: Lucas Fonseca, Wafa Tigra, Benjamin Navarro, David Guiraud, Charles Fattal, Antônio Bó, Emerson Fachin-Martins, Violaine Leynaert, Anthony Gélis, Christine Azevedo-Coste
Source: Sensors, Vol 19, Iss 20, p 4532 (2019)
Publisher Information: MDPI AG, 2019.
Publication Year: 2019
Collection: LCC:Chemical technology
Subject Terms: spinal cord injury, tetraplegia, fes-assisted grasping, inertial measurement unit interface, electromyography interface, Chemical technology, TP1-1185
More Details: Individuals who sustained a spinal cord injury often lose important motor skills, and cannot perform basic daily living activities. Several assistive technologies, including robotic assistance and functional electrical stimulation, have been developed to restore lost functions. However, designing reliable interfaces to control assistive devices for individuals with C4−C8 complete tetraplegia remains challenging. Although with limited grasping ability, they can often control upper arm movements via residual muscle contraction. In this article, we explore the feasibility of drawing upon these residual functions to pilot two devices, a robotic hand and an electrical stimulator. We studied two modalities, supra-lesional electromyography (EMG), and upper arm inertial sensors (IMU). We interpreted the muscle activity or arm movements of subjects with tetraplegia attempting to control the opening/closing of a robotic hand, and the extension/flexion of their own contralateral hand muscles activated by electrical stimulation. Two groups were recruited: eight subjects issued EMG-based commands; nine other subjects issued IMU-based commands. For each participant, we selected at least two muscles or gestures detectable by our algorithms. Despite little training, all participants could control the robot’s gestures or electrical stimulation of their own arm via muscle contraction or limb motion.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1424-8220
Relation: https://www.mdpi.com/1424-8220/19/20/4532; https://doaj.org/toc/1424-8220
DOI: 10.3390/s19204532
Access URL: https://doaj.org/article/213485b203934e568df466804c1aeaca
Accession Number: edsdoj.213485b203934e568df466804c1aeaca
Database: Directory of Open Access Journals
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More Details
ISSN:14248220
DOI:10.3390/s19204532
Published in:Sensors
Language:English