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Elife. 2017 Feb 21;6. pii: e18554. doi: 10.7554/eLife.18554.

High performance communication by people with paralysis using an intracortical brain-computer interface.

Pandarinath C1,2,3,4,5, Nuyujukian P1,3,6,7, Blabe CH1, Sorice BL8, Saab J9,10,11, Willett FR12,13, Hochberg LR8,9,10,11,14, Shenoy KV2,3,6,15,16,17, Henderson JM1,3.

Author information

1
Department of Neurosurgery, Stanford University, Stanford, United States.
2
Electrical Engineering, Stanford University, Stanford, United States.
3
Stanford Neurosciences Institute, Stanford University, Stanford, United States.
4
Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, United States.
5
Department of Neurosurgery, Emory University, Atlanta, United States.
6
Department of Bioengineering, Stanford University, Stanford, United States.
7
School of Medicine, Stanford University, Stanford, United States.
8
Department of Neurology, Massachusetts General Hospital, Boston, United States.
9
School of Engineering, Brown University, Providence, United States.
10
Brown Institute for Brain Science, Brown University, Providence, United States.
11
Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Department of VA Medical Center, Providence, United States.
12
Department of Biomedical Engineering, Case Western Reserve University, Cleveland, United States.
13
Cleveland Functional Electrical Stimulation (FES) Center of Excellence, Louis Stokes VA Medical Center, Cleveland, United States.
14
Department of Neurology, Harvard Medical School, Boston, United States.
15
Neurosciences Program, Stanford University, Stanford, United States.
16
Department of Neurobiology, Stanford University, Stanford, United States.
17
Howard Hughes Medical Institute, Stanford University, Stanford, United States.

Abstract

Brain-computer interfaces (BCIs) have the potential to restore communication for people with tetraplegia and anarthria by translating neural activity into control signals for assistive communication devices. While previous pre-clinical and clinical studies have demonstrated promising proofs-of-concept (Serruya et al., 2002; Simeral et al., 2011; Bacher et al., 2015; Nuyujukian et al., 2015; Aflalo et al., 2015; Gilja et al., 2015; Jarosiewicz et al., 2015; Wolpaw et al., 1998; Hwang et al., 2012; Spüler et al., 2012; Leuthardt et al., 2004; Taylor et al., 2002; Schalk et al., 2008; Moran, 2010; Brunner et al., 2011; Wang et al., 2013; Townsend and Platsko, 2016; Vansteensel et al., 2016; Nuyujukian et al., 2016; Carmena et al., 2003; Musallam et al., 2004; Santhanam et al., 2006; Hochberg et al., 2006; Ganguly et al., 2011; O'Doherty et al., 2011; Gilja et al., 2012), the performance of human clinical BCI systems is not yet high enough to support widespread adoption by people with physical limitations of speech. Here we report a high-performance intracortical BCI (iBCI) for communication, which was tested by three clinical trial participants with paralysis. The system leveraged advances in decoder design developed in prior pre-clinical and clinical studies (Gilja et al., 2015; Kao et al., 2016; Gilja et al., 2012). For all three participants, performance exceeded previous iBCIs (Bacher et al., 2015; Jarosiewicz et al., 2015) as measured by typing rate (by a factor of 1.4-4.2) and information throughput (by a factor of 2.2-4.0). This high level of performance demonstrates the potential utility of iBCIs as powerful assistive communication devices for people with limited motor function.Clinical Trial No: NCT00912041.

KEYWORDS:

ALS; assistive technology; brain-machine interface; human; human biology; medicine; neural prosthesis; neuroscience

PMID:
28220753
PMCID:
PMC5319839
DOI:
10.7554/eLife.18554
[Indexed for MEDLINE]
Free PMC Article

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