Evidence map›Paper›PMID 33746239›Full record

ArticleProceedings of the IEEE. Institute of Electrical and Electronics Engineers2017

A Non-Human Primate Brain-Computer Typing Interface.

Paul Nuyujukian, Jonathan C Kao, Stephen I Ryu, Krishna V Shenoy

Abstract read
In one paragraph

Article in Proceedings of the IEEE. Institute of Electrical and Electronics Engineers, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Review
  7. Neural Decoding for Intracortical Brain-Computer Interfaces.Cyborg and bionic systems (Washington, D.C.) · 2023
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Paul NuyujukianNeurosurgery Department, the Electrical Engineering Department, the Bioengineering Department, and Stanford Neurosciences Institute, Stanford University, Stanford, CA 94305 USA.
Jonathan C KaoElectrical Engineering Department, Stanford University, Stanford, CA 94305 USA.
Stephen I RyuElectrical Engineering Department, Stanford University, Stanford, CA 94305 USA and also with Palo Alto Medical Foundation, Palo Alto, CA 94550 USA.
Krishna V ShenoyElectrical Engineering Department, the Bioengineering Department, the Neurobiology Department, and Stanford Neurosciences Institute, Stanford University, Stanford, CA 94305 USA and also with Howard Hughes Medical Institute, Chevy Chase, MD 20815 USA.

Funding

Engaging new cognitive and motor signals to improve communication prosthesesR01DC014034 · NIDCD · STANFORD UNIVERSITY · PI JAIMIE M HENDERSON · 2015 to 2026
$8.2M
Fully Implantable and Programmable Spike-based Codecs for NeuroprostheticsR01NS076460 · NINDS · STANFORD UNIVERSITY · PI BOAHEN, KWABENA · 2011 to 2015
$4.4M
Toward an Animal Model of Freely Moving HumansR01NS066311 · NINDS · STANFORD UNIVERSITY · PI BLACK, MICHAEL J, SHENOY, KRISHNA V · 2009 to 2012
$2.9M
Next generation wireless neural interfaces for chronic and acute applicationsR01NS064318 · NINDS · UNIVERSITY OF UTAH · PI SOLZBACHER, FLORIAN · 2009 to 2010
$2.8M
Toward an Animal Model of Freely Moving HumanDP1OD006409 · OD · STANFORD UNIVERSITY · PI SHENOY, KRISHNA V · 2009 to 2011
$2.5M
CRCNS: Extracting Dynamical Structure Embedded in Motor Preparatory ActivityR01NS054283 · NINDS · STANFORD UNIVERSITY · PI SHENOY, KRISHNA V · 2005 to 2009
$1.7M
Toward an Animal Model of Freely Moving HumanDP1HD075623 · NICHD · STANFORD UNIVERSITY · PI SHENOY, KRISHNA V · 2012 to 2013
$1.6M
NICHD NIH HHS DP1 HD075623NIDCD NIH HHS R01 DC014034NIH HHS DP1 OD006409NINDS NIH HHS R01 NS054283NINDS NIH HHS R01 NS064318NINDS NIH HHS R01 NS066311NINDS NIH HHS R01 NS076460
6 · The paper itself

Abstract

Brain-computer interfaces (BCIs) record brain activity and translate the information into useful control signals. They can be used to restore function to people with paralysis by controlling end effectors such as computer cursors and robotic limbs. Communication neural prostheses are BCIs that control user interfaces on computers or mobile devices. Here we demonstrate a communication prosthesis by simulating a typing task with two rhesus macaques implanted with electrode arrays. The monkeys used two of the highest known performing BCI decoders to type out words and sentences when prompted one symbol/letter at a time. On average, Monkeys J and L achieved typing rates of 10.0 and 7.2 words per minute (wpm), respectively, copying text from a newspaper article using a velocity-only two dimensional BCI decoder with dwell-based symbol selection. With a BCI decoder that also featured a discrete click for key selection, typing rates increased to 12.0 and 7.8 wpm. These represent the highest known achieved communication rates using a BCI. We then quantified the relationship between bitrate and typing rate and found it approximately linear: typing rate in wpm is nearly three times bitrate in bits per second. We also compared the metrics of achieved bitrate and information transfer rate and discuss their applicability to real-world typing scenarios. Although this study cannot model the impact of cognitive load of word and sentence planning, the findings here demonstrate the feasibility of BCIs to serve as communication interfaces and represent an upper bound on the expected achieved typing rate for a given BCI throughput.

Identifiers

PMID33746239
PMCPMC7970827

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.