Brain-computer interface advance allows paralyzed people to type almost as fast as some smartphone users

Coming next: controlling personal computers, phones, and tablets --- and reaching out via the internet
February 24, 2017

Typing with your mind. You are paralyzed. But now, tiny electrodes have been surgically implanted in your brain to record signals from your motor cortex, the brain region controlling muscle movement. As you think of mousing over to a letter (or clicking to choose it), those electrical brain signals are transmitted via a cable to a computer (replacing your spinal cord and muscles). There, advanced algorithms decode the complex electrical brain signals, converting them instantly into screen actions. (credit: Chethan Pandarinath et al./eLife)

Stanford University researchers have developed a brain-computer interface (BCI) system that can enable people with paralysis* to type (using an on-screen cursor) at speeds and accuracy levels of about three times faster than reported to date.

Simply by imagining their own hand movements, one participant was able to type 39 correct characters per minute (about eight words per minute); the other two participants averaged 6.3 and 2.7 words per minute, respectively — all without auto-complete assistance (so it could be much faster).

Those are communication rates that people with arm and hand paralysis would also find useful, the researchers suggest. “We’re approaching the speed at which you can type text on your cellphone,” said Krishna Shenoy, PhD, professor of electrical engineering, a co-senior author of the study, which was published in an open-access paper online Feb. 21 in eLife.

Braingate and beyond

The three study participants used a brain-computer interface called the “BrainGate Neural Interface System.” On KurzweilAI, we first discussed Braingate in 2011, followed by a 2012 clinical trial that allowed a paralyzed patient to control a robot.

Braingate in 2012 (credit: Brown University)

The new research, led by Stanford, takes the Braingate technology way further**. Participants can now move a cursor (by just thinking about a hand movement) on a computer screen that displays the letters of the alphabet, and they can “point and click” on letters, computer-mouse-style, to type letters and sentences.

The new BCI uses a tiny silicon chip, just over one-sixth of an inch square, with 100 electrodes that penetrate the brain to about the thickness of a quarter and tap into the electrical activity of individual nerve cells in the motor cortex.

As the participant thinks of a specific hand-to-mouse movement (pointing at or clicking on a letter), neural electrical activity is recorded using 96-channel silicon microelectrode arrays implanted in the hand area of the motor cortex. These signals are then filtered to extract multiunit spiking activity and high-frequency field potentials, then decoded (using two algorithms) to provide “point-and-click” control of a computer cursor.

What’s next

The team next plans is to adapt the system so that brain-computer interfaces can control commercial computers, phones and tablets — perhaps extending out to the internet.

Beyond that, Shenoy predicted that a self-calibrating, fully implanted wireless BCI system with no required caregiver assistance and no “cosmetic impact” would be available in five to 10 years from now (“closer to five”).

Perhaps a future wireless, noninvasive version could let anyone simply think to select letters, words, ideas, and images — replacing the mouse and finger touch — along the lines of Elon Musk’s neural lace concept?

* Millions of people with paralysis reside in the U.S.

** The study’s results are the culmination of the long-running multi-institutional BrainGate consortium, which includes scientists at Massachusetts General Hospital, Brown University, Case Western University, and the VA Rehabilitation Research and Development Center for Neurorestoration and Neurotechnology in Providence, Rhode Island. The study was funded by the National Institutes of Health, the Stanford Office of Postdoctoral Affairs, the Craig H. Neilsen Foundation, the Stanford Medical Scientist Training Program, Stanford BioX-NeuroVentures, the Stanford Institute for Neuro-Innovation and Translational Neuroscience, the Stanford Neuroscience Institute, Larry and Pamela Garlick, Samuel and Betsy Reeves, the Howard Hughes Medical Institute, the U.S. Department of Veterans Affairs, the MGH-Dean Institute for Integrated Research on Atrial Fibrillation and Stroke and Massachusetts General Hospital.


Stanford | Stanford researchers develop brain-controlled typing for people with paralysis


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

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.