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A direct spinal cord-computer interface enables the control of the paralysed hand in spinal cord injury.
Oliveira, Daniela Souza; Ponfick, Matthias; Braun, Dominik I; Osswald, Marius; Sierotowicz, Marek; Chatterjee, Satyaki; Weber, Douglas; Eskofier, Bjoern; Castellini, Claudio; Farina, Dario; Kinfe, Thomas Mehari; Del Vecchio, Alessandro.
Afiliación
  • Oliveira DS; Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91052 Erlangen, Germany.
  • Ponfick M; Querschnittzentrum Rummelsberg, Krankenhaus Rummelsberg GmbH, 90592 Schwarzenbruck, Germany.
  • Braun DI; Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91052 Erlangen, Germany.
  • Osswald M; Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91052 Erlangen, Germany.
  • Sierotowicz M; Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91052 Erlangen, Germany.
  • Chatterjee S; Institute of Robotics and Mechatronics, German Aerospace Center (DLR), 82234 Oberpfaffenhofen, Germany.
  • Weber D; Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91052 Erlangen, Germany.
  • Eskofier B; Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
  • Castellini C; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
  • Farina D; Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91052 Erlangen, Germany.
  • Kinfe TM; Translational Digital Health Group, Institute of AI for Health, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany.
  • Del Vecchio A; Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91052 Erlangen, Germany.
Brain ; 147(10): 3583-3595, 2024 Oct 03.
Article en En | MEDLINE | ID: mdl-38501612
ABSTRACT
Paralysis of the muscles controlling the hand dramatically limits the quality of life for individuals living with spinal cord injury (SCI). Here, with a non-invasive neural interface, we demonstrate that eight motor complete SCI individuals (C5-C6) are still able to task-modulate in real-time the activity of populations of spinal motor neurons with residual neural pathways. In all SCI participants tested, we identified groups of motor units under voluntary control that encoded various hand movements. The motor unit discharges were mapped into more than 10 degrees of freedom, ranging from grasping to individual hand-digit flexion and extension. We then mapped the neural dynamics into a real-time controlled virtual hand. The SCI participants were able to match the cue hand posture by proportionally controlling four degrees of freedom (opening and closing the hand and index flexion/extension). These results demonstrate that wearable muscle sensors provide access to spared motor neurons that are fully under voluntary control in complete cervical SCI individuals. This non-invasive neural interface allows the investigation of motor neuron changes after the injury and has the potential to promote movement restoration when integrated with assistive devices.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Parálisis / Traumatismos de la Médula Espinal / Mano Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Brain Año: 2024 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Parálisis / Traumatismos de la Médula Espinal / Mano Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Brain Año: 2024 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Reino Unido