Optimization of electrode channels in brain computer interfaces

M. Kamrunnahar, N. S. Dias, S. J. Schiff

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

What is the optimal number of electrodes one can use in discrimination of tasks for a Brain Computer Interface (BCI)? To address this question, the number and location of scalp electrodes in the acquisition of human electroencephalography (EEG) and discrimination of motor imagery tasks were optimized by using a systematic optimization approach. The systematic analysis results in the most reliable procedure in electrode optimization as well as a validating means for the other feature selection techniques. We acquired human scalp EEG in response to cue-based motor imagery tasks. We employed a systematic analysis by using all possible combinations of the channels and calculating task discrimination errors for each of these combinations by using linear discriminant analysis (LDA) for feature classification. Channel combination that resulted in the smallest discrimination error was selected as the optimum number of channels to be used in BCI applications. Results from the systematic analysis were compared with another feature selection algorithm: forward stepwise feature selection combined with LDA feature classification. Our results demonstrate the usefulness of the fully optimized technique for a reliable selection of scalp electrodes in BCI applications.

Original languageEnglish (US)
Title of host publicationProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEngineering the Future of Biomedicine, EMBC 2009
PublisherIEEE Computer Society
Pages6477-6480
Number of pages4
ISBN (Print)9781424432967
DOIs
StatePublished - Jan 1 2009
Event31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 - Minneapolis, MN, United States
Duration: Sep 2 2009Sep 6 2009

Publication series

NameProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009

Other

Other31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
CountryUnited States
CityMinneapolis, MN
Period9/2/099/6/09

Fingerprint

Brain-Computer Interfaces
Brain computer interface
Electrodes
Scalp
Feature extraction
Imagery (Psychotherapy)
Discriminant Analysis
Discriminant analysis
Electroencephalography
Cues
Discrimination (Psychology)

All Science Journal Classification (ASJC) codes

  • Cell Biology
  • Developmental Biology
  • Biomedical Engineering
  • Medicine(all)

Cite this

Kamrunnahar, M., Dias, N. S., & Schiff, S. J. (2009). Optimization of electrode channels in brain computer interfaces. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 (pp. 6477-6480). [5333585] (Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009). IEEE Computer Society. https://doi.org/10.1109/IEMBS.2009.5333585
Kamrunnahar, M. ; Dias, N. S. ; Schiff, S. J. / Optimization of electrode channels in brain computer interfaces. Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. IEEE Computer Society, 2009. pp. 6477-6480 (Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009).
@inproceedings{b6d9816258bf4faca08463ceb21f4414,
title = "Optimization of electrode channels in brain computer interfaces",
abstract = "What is the optimal number of electrodes one can use in discrimination of tasks for a Brain Computer Interface (BCI)? To address this question, the number and location of scalp electrodes in the acquisition of human electroencephalography (EEG) and discrimination of motor imagery tasks were optimized by using a systematic optimization approach. The systematic analysis results in the most reliable procedure in electrode optimization as well as a validating means for the other feature selection techniques. We acquired human scalp EEG in response to cue-based motor imagery tasks. We employed a systematic analysis by using all possible combinations of the channels and calculating task discrimination errors for each of these combinations by using linear discriminant analysis (LDA) for feature classification. Channel combination that resulted in the smallest discrimination error was selected as the optimum number of channels to be used in BCI applications. Results from the systematic analysis were compared with another feature selection algorithm: forward stepwise feature selection combined with LDA feature classification. Our results demonstrate the usefulness of the fully optimized technique for a reliable selection of scalp electrodes in BCI applications.",
author = "M. Kamrunnahar and Dias, {N. S.} and Schiff, {S. J.}",
year = "2009",
month = "1",
day = "1",
doi = "10.1109/IEMBS.2009.5333585",
language = "English (US)",
isbn = "9781424432967",
series = "Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009",
publisher = "IEEE Computer Society",
pages = "6477--6480",
booktitle = "Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society",
address = "United States",

}

Kamrunnahar, M, Dias, NS & Schiff, SJ 2009, Optimization of electrode channels in brain computer interfaces. in Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009., 5333585, Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009, IEEE Computer Society, pp. 6477-6480, 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009, Minneapolis, MN, United States, 9/2/09. https://doi.org/10.1109/IEMBS.2009.5333585

Optimization of electrode channels in brain computer interfaces. / Kamrunnahar, M.; Dias, N. S.; Schiff, S. J.

Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. IEEE Computer Society, 2009. p. 6477-6480 5333585 (Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Optimization of electrode channels in brain computer interfaces

AU - Kamrunnahar, M.

AU - Dias, N. S.

AU - Schiff, S. J.

PY - 2009/1/1

Y1 - 2009/1/1

N2 - What is the optimal number of electrodes one can use in discrimination of tasks for a Brain Computer Interface (BCI)? To address this question, the number and location of scalp electrodes in the acquisition of human electroencephalography (EEG) and discrimination of motor imagery tasks were optimized by using a systematic optimization approach. The systematic analysis results in the most reliable procedure in electrode optimization as well as a validating means for the other feature selection techniques. We acquired human scalp EEG in response to cue-based motor imagery tasks. We employed a systematic analysis by using all possible combinations of the channels and calculating task discrimination errors for each of these combinations by using linear discriminant analysis (LDA) for feature classification. Channel combination that resulted in the smallest discrimination error was selected as the optimum number of channels to be used in BCI applications. Results from the systematic analysis were compared with another feature selection algorithm: forward stepwise feature selection combined with LDA feature classification. Our results demonstrate the usefulness of the fully optimized technique for a reliable selection of scalp electrodes in BCI applications.

AB - What is the optimal number of electrodes one can use in discrimination of tasks for a Brain Computer Interface (BCI)? To address this question, the number and location of scalp electrodes in the acquisition of human electroencephalography (EEG) and discrimination of motor imagery tasks were optimized by using a systematic optimization approach. The systematic analysis results in the most reliable procedure in electrode optimization as well as a validating means for the other feature selection techniques. We acquired human scalp EEG in response to cue-based motor imagery tasks. We employed a systematic analysis by using all possible combinations of the channels and calculating task discrimination errors for each of these combinations by using linear discriminant analysis (LDA) for feature classification. Channel combination that resulted in the smallest discrimination error was selected as the optimum number of channels to be used in BCI applications. Results from the systematic analysis were compared with another feature selection algorithm: forward stepwise feature selection combined with LDA feature classification. Our results demonstrate the usefulness of the fully optimized technique for a reliable selection of scalp electrodes in BCI applications.

UR - http://www.scopus.com/inward/record.url?scp=77951013660&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77951013660&partnerID=8YFLogxK

U2 - 10.1109/IEMBS.2009.5333585

DO - 10.1109/IEMBS.2009.5333585

M3 - Conference contribution

C2 - 19964437

AN - SCOPUS:77951013660

SN - 9781424432967

T3 - Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009

SP - 6477

EP - 6480

BT - Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society

PB - IEEE Computer Society

ER -

Kamrunnahar M, Dias NS, Schiff SJ. Optimization of electrode channels in brain computer interfaces. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. IEEE Computer Society. 2009. p. 6477-6480. 5333585. (Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009). https://doi.org/10.1109/IEMBS.2009.5333585