Error Control for Performance Improvement of Brain-Computer Interface: Reliability-Based Automatic Repeat Request

Hiromu TAKAHASHI; Tomohiro YOSHIKAWA; Takeshi FURUHASHI

doi:10.1587/transinf.E94.D.1243

Error Control for Performance Improvement of Brain-Computer Interface: Reliability-Based Automatic Repeat Request

Hiromu TAKAHASHI, Tomohiro YOSHIKAWA, Takeshi FURUHASHI

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Brain-Computer Interfaces (BCIs) are systems that translate one's thoughts into commands to restore control and communication to severely paralyzed people, and they are also appealing to healthy people. One of the challenges is to improve the performance of BCIs, often measured by the accuracy and the trial duration, or the information transfer rate (ITR), i.e., the mutual information per unit time. Since BCIs are communications between a user and a system, error control schemes such as forward error correction and automatic repeat request (ARQ) can be applied to BCIs to improve the accuracy. This paper presents reliability-based ARQ (RB-ARQ), a variation of ARQ designed for BCIs, which employs the maximum posterior probability for the repeat decision. The current results show that RB-ARQ is more effective than the conventional methods, i.e., better accuracy when trial duration was the same, and shorter trial duration when the accuracy was the same. This resulted in a greater information transfer rate and a greater utility, which is a more practical performance measure in the P300 speller task. The results also show that such users who achieve a poor accuracy for some reason can benefit the most from RB-ARQ, which could make BCIs more universal.

Publication: IEICE TRANSACTIONS on Information Vol.E94-D No.6 pp.1243-1252

Publication Date: 2011/06/01

Publicized

Online ISSN: 1745-1361

DOI: 10.1587/transinf.E94.D.1243

Type of Manuscript: PAPER

Category: Rehabilitation Engineering and Assistive Technology

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Hiromu TAKAHASHI, Tomohiro YOSHIKAWA, Takeshi FURUHASHI, "Error Control for Performance Improvement of Brain-Computer Interface: Reliability-Based Automatic Repeat Request" in IEICE TRANSACTIONS on Information, vol. E94-D, no. 6, pp. 1243-1252, June 2011, doi: 10.1587/transinf.E94.D.1243.
Abstract: Brain-Computer Interfaces (BCIs) are systems that translate one's thoughts into commands to restore control and communication to severely paralyzed people, and they are also appealing to healthy people. One of the challenges is to improve the performance of BCIs, often measured by the accuracy and the trial duration, or the information transfer rate (ITR), i.e., the mutual information per unit time. Since BCIs are communications between a user and a system, error control schemes such as forward error correction and automatic repeat request (ARQ) can be applied to BCIs to improve the accuracy. This paper presents reliability-based ARQ (RB-ARQ), a variation of ARQ designed for BCIs, which employs the maximum posterior probability for the repeat decision. The current results show that RB-ARQ is more effective than the conventional methods, i.e., better accuracy when trial duration was the same, and shorter trial duration when the accuracy was the same. This resulted in a greater information transfer rate and a greater utility, which is a more practical performance measure in the P300 speller task. The results also show that such users who achieve a poor accuracy for some reason can benefit the most from RB-ARQ, which could make BCIs more universal.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E94.D.1243/_p

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@ARTICLE{e94-d_6_1243,
author={Hiromu TAKAHASHI, Tomohiro YOSHIKAWA, Takeshi FURUHASHI, },
journal={IEICE TRANSACTIONS on Information},
title={Error Control for Performance Improvement of Brain-Computer Interface: Reliability-Based Automatic Repeat Request},
year={2011},
volume={E94-D},
number={6},
pages={1243-1252},
abstract={Brain-Computer Interfaces (BCIs) are systems that translate one's thoughts into commands to restore control and communication to severely paralyzed people, and they are also appealing to healthy people. One of the challenges is to improve the performance of BCIs, often measured by the accuracy and the trial duration, or the information transfer rate (ITR), i.e., the mutual information per unit time. Since BCIs are communications between a user and a system, error control schemes such as forward error correction and automatic repeat request (ARQ) can be applied to BCIs to improve the accuracy. This paper presents reliability-based ARQ (RB-ARQ), a variation of ARQ designed for BCIs, which employs the maximum posterior probability for the repeat decision. The current results show that RB-ARQ is more effective than the conventional methods, i.e., better accuracy when trial duration was the same, and shorter trial duration when the accuracy was the same. This resulted in a greater information transfer rate and a greater utility, which is a more practical performance measure in the P300 speller task. The results also show that such users who achieve a poor accuracy for some reason can benefit the most from RB-ARQ, which could make BCIs more universal.},
keywords={},
doi={10.1587/transinf.E94.D.1243},
ISSN={1745-1361},
month={June},}

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TY - JOUR
TI - Error Control for Performance Improvement of Brain-Computer Interface: Reliability-Based Automatic Repeat Request
T2 - IEICE TRANSACTIONS on Information
SP - 1243
EP - 1252
AU - Hiromu TAKAHASHI
AU - Tomohiro YOSHIKAWA
AU - Takeshi FURUHASHI
PY - 2011
DO - 10.1587/transinf.E94.D.1243
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E94-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2011
AB - Brain-Computer Interfaces (BCIs) are systems that translate one's thoughts into commands to restore control and communication to severely paralyzed people, and they are also appealing to healthy people. One of the challenges is to improve the performance of BCIs, often measured by the accuracy and the trial duration, or the information transfer rate (ITR), i.e., the mutual information per unit time. Since BCIs are communications between a user and a system, error control schemes such as forward error correction and automatic repeat request (ARQ) can be applied to BCIs to improve the accuracy. This paper presents reliability-based ARQ (RB-ARQ), a variation of ARQ designed for BCIs, which employs the maximum posterior probability for the repeat decision. The current results show that RB-ARQ is more effective than the conventional methods, i.e., better accuracy when trial duration was the same, and shorter trial duration when the accuracy was the same. This resulted in a greater information transfer rate and a greater utility, which is a more practical performance measure in the P300 speller task. The results also show that such users who achieve a poor accuracy for some reason can benefit the most from RB-ARQ, which could make BCIs more universal.
ER -