Paralysis following spinal cord injury, brainstem stroke, amyotrophic lateral sclerosis and other disorders can disconnect the brain from the body, eliminating the ability to perform volitional movements. A neural interface system1,2,3,4,5 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 devices6,7,8. Able-bodied monkeys have used a neural interface system to control a robotic arm9, 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 grasp movements. 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.
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We thank participants S3 and T2 for their dedication to this research. We thank M. Black for initial guidance in the BrainGate–DLR research. We thank E. Gallivan, E. Berhanu, D. Rosler, L. Barefoot, K. Centrella and B. King for their contributions to this research. We thank G. Friehs and E. Eskandar for their surgical contributions. We thank K. Knoper for assistance with illustrations. We thank D. Van Der Merwe and DEKA Research and Development for their technical support. The contents do not represent the views of the Department of Veterans Affairs or the United States Government. The research was supported by the Rehabilitation Research and Development Service, Office of Research and Development, Department of Veterans Affairs (Merit Review Awards B6453R and A6779I; Career Development Transition Award B6310N). Support was also provided by the National Institutes of Health: NINDS/NICHD (RC1HD063931), NIDCD (R01DC009899), NICHD-NCMRR (N01HD53403 and N01HD10018), NIBIB (R01EB007401), NINDS-Javits (NS25074); a Memorandum of Agreement between the Defense Advanced Research Projects Agency (DARPA) and the Department of Veterans Affairs; the Doris Duke Charitable Foundation; the MGH-Deane Institute for Integrated Research on Atrial Fibrillation and Stroke; Katie Samson Foundation; Craig H. Neilsen Foundation; the European Commission’s Seventh Framework Programme through the project The Hand Embodied (grant 248587). The pilot clinical trial into which participant S3 was recruited was sponsored in part by Cyberkinetics Neurotechnology Systems (CKI).
This file contains Supplementary Movie 1 which shows neuronal ensemble control of the DLR robot arm and hand for three-dimensional reach and grasp by a woman with tetraplegia, trial day 1959.
This file contains Supplementary Movie 2 which shows neuronal ensemble control of the DEKA prosthetic arm and hand by a woman with tetraplegia, trial day 1974.
This file contains Supplementary Movie 3 which shows neuronal ensemble control of the DEKA prosthetic arm and hand by a gentleman with tetraplegia (Participant T2), trial day 166.
This file contains Supplementary Movie 4 which shows BrainGate-enabled drinking from a bottle by S3, using neurally-controlled 2-D movement and hand state control of the DLR robot arm, trial day 1959.
About this article
Scientific Reports (2018)