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Reach and grasp by people with tetraplegia using a neurally controlled robotic arm

Hochberg, Leigh R. and Bacher, Daniel and Jarosiewicz, Beata and Masse, Nicolas Y. and Simeral, John D. and Vogel, Joern and Haddadin, Sami and Liu, Jie and Cash, Sydney S. and van der Smagt, Patrick and Donoghue, John P. (2012) Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature, 485 (7398), pp. 372-375. Nature Publishing Group. doi: 10.1038/nature11076.


Official URL: http://www.nature.com/nature/journal/v485/n7398/full/nature11076.html


Paralysis following spinal cord injury, brainstemstroke, amyotrophic lateral sclerosis and other disorders can disconnect the brain from the body, eliminating the ability to perform volitional movements. A neural interface system could restore mobility and independence for people with paralysis by translating neuronal activity directly into control signals for assistive devices. We have previously shown that people with long-standing tetraplegia can use a neural interface system to move and click a computer cursor and to control physical devices. Able-bodied monkeys have used a neural interface system to control a robotic arm, but it is unknown whether people with profound upper extremity paralysis or limb loss could use cortical neuronal ensemble signals to direct useful arm actions. Here we demonstrate the ability of two people with long-standing tetraplegia to use neural interface system-based control of a robotic arm to perform three-dimensional reach and graspmovements. Participants controlled the arm and hand over a broad space without explicit training, using signals decoded from a small, local population of motor cortex (MI) neurons recorded from a 96-channel microelectrode array. One of the study participants, implanted with the sensor 5 years earlier, also used a robotic arm to drink coffee from a bottle. Although robotic reach and grasp actions were not as fast or accurate as those of an able-bodied person, our results demonstrate the feasibility for people with tetraplegia, years after injury to the central nervous system, to recreate useful multidimensional control of complex devices directly from a small sample of neural signals.

Item URL in elib:https://elib.dlr.de/79895/
Document Type:Article
Title:Reach and grasp by people with tetraplegia using a neurally controlled robotic arm
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Hochberg, Leigh R.Brown UniversityUNSPECIFIED
Bacher, DanielBrown UniversityUNSPECIFIED
Jarosiewicz, BeataBrown UniversityUNSPECIFIED
Masse, Nicolas Y.Brown UniversityUNSPECIFIED
Simeral, John D.Brown UniversityUNSPECIFIED
Vogel, JoernJoern.Vogel (at) dlr.deUNSPECIFIED
Haddadin, SamiSami.Haddadin (at) dlr.deUNSPECIFIED
Liu, JieBrown UniversityUNSPECIFIED
Cash, Sydney S.Harvard Medical SchoolUNSPECIFIED
van der Smagt, Patricksmagt (at) dlr.deUNSPECIFIED
Donoghue, John P.Brown UniversityUNSPECIFIED
Date:17 May 2012
Journal or Publication Title:Nature
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
DOI :10.1038/nature11076
Page Range:pp. 372-375
Publisher:Nature Publishing Group
Series Name:Nature
Keywords:Robotics Neuroscience Applied physics Engineering Medical research Technology
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - RMC - Kognitive Intelligenz und Autonomie (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (until 2012)
Deposited By: Vogel, Jörn
Deposited On:19 Dec 2012 11:05
Last Modified:31 Jul 2019 19:39

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