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Performance measurement for brain–computer or brain–machine interfaces: a tutorial

David Thompson, Lucia Quitadamo, Luca Mainardi, Khalil ur Rehman Laghari, Shangkai Gao, Pieter-Jan Kindermans, John Simeral, Reza Fazel-Rezai, Matteo Matteucci, Tiago Falk, et al. (2014) JOURNAL OF NEURAL ENGINEERING. 11(3).
abstract
Objective. Brain–computer interfaces (BCIs) have the potential to be valuable clinical tools. However, the varied nature of BCIs, combined with the large number of laboratories participating in BCI research, makes uniform performance reporting difficult. To address this situation, we present a tutorial on performance measurement in BCI research. Approach. A workshop on this topic was held at the 2013 International BCI Meeting at Asilomar Conference Center in Pacific Grove, California. This paper contains the consensus opinion of the workshop members, refined through discussion in the following months and the input of authors who were unable to attend the workshop. Main results. Checklists for methods reporting were developed for both discrete and continuous BCIs. Relevant metrics are reviewed for different types of BCI research, with notes on their use to encourage uniform application between laboratories. Significance. Graduate students and other researchers new to BCI research may find this tutorial a helpful introduction to performance measurement in the field.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
VISUAL SPELLER, INITIAL TESTS, CORTICAL CONTROL, REAL-TIME FMRI, COMMUNICATION, WHEELCHAIR, ATTENTION, DESIGN, TETRAPLEGIA, ENVIRONMENT, brain-computer interface, brain-machine interface, performance measurement, metrics
journal title
JOURNAL OF NEURAL ENGINEERING
volume
11
issue
3
article number
035001
pages
13 pages
Web of Science type
Article
Web of Science id
000336964700002
JCR category
ENGINEERING, BIOMEDICAL
JCR impact factor
3.295 (2014)
JCR rank
14/76 (2014)
JCR quartile
1 (2014)
ISSN
1741-2560
DOI
10.1088/1741-2560/11/3/035001
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
4425489
handle
http://hdl.handle.net/1854/LU-4425489
date created
2014-06-20 10:27:41
date last changed
2016-12-21 15:42:47
@article{4425489,
  abstract     = {Objective. Brain--computer interfaces (BCIs) have the potential to be valuable clinical tools. However, the varied nature of BCIs, combined with the large number of laboratories participating in BCI research, makes uniform performance reporting difficult. To address this situation, we present a tutorial on performance measurement in BCI research. Approach. A workshop on this topic was held at the 2013 International BCI Meeting at Asilomar Conference Center in Pacific Grove, California. This paper contains the consensus opinion of the workshop members, refined through discussion in the following months and the input of authors who were unable to attend the workshop. Main results. Checklists for methods reporting were developed for both discrete and continuous BCIs. Relevant metrics are reviewed for different types of BCI research, with notes on their use to encourage uniform application between laboratories. Significance. Graduate students and other researchers new to BCI research may find this tutorial a helpful introduction to performance measurement in the field.},
  articleno    = {035001},
  author       = {Thompson, David and Quitadamo,  Lucia and Mainardi,  Luca and Laghari, Khalil ur Rehman and Gao, Shangkai and Kindermans, Pieter-Jan and Simeral, John  and Fazel-Rezai, Reza  and Matteucci, Matteo  and Falk, Tiago and Bianchi, Luigi and Chestek, Cynthia and Huggins, Jane},
  issn         = {1741-2560},
  journal      = {JOURNAL OF NEURAL ENGINEERING},
  keyword      = {VISUAL SPELLER,INITIAL TESTS,CORTICAL CONTROL,REAL-TIME FMRI,COMMUNICATION,WHEELCHAIR,ATTENTION,DESIGN,TETRAPLEGIA,ENVIRONMENT,brain-computer interface,brain-machine interface,performance measurement,metrics},
  language     = {eng},
  number       = {3},
  pages        = {13},
  title        = {Performance measurement for brain--computer or brain--machine interfaces: a tutorial},
  url          = {http://dx.doi.org/10.1088/1741-2560/11/3/035001},
  volume       = {11},
  year         = {2014},
}

Chicago
Thompson, David, Lucia Quitadamo, Luca Mainardi, Khalil ur Rehman Laghari, Shangkai Gao, Pieter-Jan Kindermans, John Simeral, et al. 2014. “Performance Measurement for Brain–computer or Brain–machine Interfaces: a Tutorial.” Journal of Neural Engineering 11 (3).
APA
Thompson, David, Quitadamo, L., Mainardi, L., Laghari, K. ur R., Gao, S., Kindermans, P.-J., Simeral, J., et al. (2014). Performance measurement for brain–computer or brain–machine interfaces: a tutorial. JOURNAL OF NEURAL ENGINEERING, 11(3).
Vancouver
1.
Thompson D, Quitadamo L, Mainardi L, Laghari K ur R, Gao S, Kindermans P-J, et al. Performance measurement for brain–computer or brain–machine interfaces: a tutorial. JOURNAL OF NEURAL ENGINEERING. 2014;11(3).
MLA
Thompson, David, Lucia Quitadamo, Luca Mainardi, et al. “Performance Measurement for Brain–computer or Brain–machine Interfaces: a Tutorial.” JOURNAL OF NEURAL ENGINEERING 11.3 (2014): n. pag. Print.