Semi-supervised adaptation in ssvep-based brain-computer interface using tri-training

Thomas Bender; Troels W Kjaer; Carsten E Thomsen; Helge B D Sorensen; Sadasivan Puthusserypady

doi:10.1109/EMBC.2013.6610491

Semi-supervised adaptation in ssvep-based brain-computer interface using tri-training

Thomas Bender, Troels W Kjaer, Carsten E Thomsen, Helge B D Sorensen, Sadasivan Puthusserypady

Department of Clinical Neurophysiology

3 Citations (Scopus)

Abstract

This paper presents a novel and computationally simple tri-training based semi-supervised steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI). It is implemented with autocorrelation-based features and a Naïve-Bayes classifier (NBC). The system uses nine characters presented on a 100 Hz CRT-monitor, three scalp electrodes for signal acquisition, a gUSB-amp for preamplification and two PCs for data-processing and stimulus control respectively. Preliminary test results of the system on nine healthy subjects, with and without tri-training, indicates that the accuracy improves as a result of tri-training.

Original language	English
Journal	Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
Volume	2013
Pages (from-to)	4279-82
Number of pages	4
ISSN	2375-7477
DOIs	https://doi.org/10.1109/EMBC.2013.6610491
Publication status	Published - 2013

Access to Document

10.1109/EMBC.2013.6610491

Cite this

Bender, T., Kjaer, T. W., Thomsen, C. E., Sorensen, H. B. D., & Puthusserypady, S. (2013). Semi-supervised adaptation in ssvep-based brain-computer interface using tri-training. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2013, 4279-82. https://doi.org/10.1109/EMBC.2013.6610491

Semi-supervised adaptation in ssvep-based brain-computer interface using tri-training. / Bender, Thomas; Kjaer, Troels W; Thomsen, Carsten E et al.
In: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, Vol. 2013, 2013, p. 4279-82.

Research output: Contribution to journal › Journal article › Research › peer-review

Bender, T, Kjaer, TW, Thomsen, CE, Sorensen, HBD & Puthusserypady, S 2013, 'Semi-supervised adaptation in ssvep-based brain-computer interface using tri-training', Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, vol. 2013, pp. 4279-82. https://doi.org/10.1109/EMBC.2013.6610491

Bender T, Kjaer TW, Thomsen CE, Sorensen HBD, Puthusserypady S. Semi-supervised adaptation in ssvep-based brain-computer interface using tri-training. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference. 2013;2013:4279-82. doi: 10.1109/EMBC.2013.6610491

@article{9de936813ded485cb143585cbbe78ca4,

title = "Semi-supervised adaptation in ssvep-based brain-computer interface using tri-training",

abstract = "This paper presents a novel and computationally simple tri-training based semi-supervised steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI). It is implemented with autocorrelation-based features and a Na{\"i}ve-Bayes classifier (NBC). The system uses nine characters presented on a 100 Hz CRT-monitor, three scalp electrodes for signal acquisition, a gUSB-amp for preamplification and two PCs for data-processing and stimulus control respectively. Preliminary test results of the system on nine healthy subjects, with and without tri-training, indicates that the accuracy improves as a result of tri-training.",

author = "Thomas Bender and Kjaer, \{Troels W\} and Thomsen, \{Carsten E\} and Sorensen, \{Helge B D\} and Sadasivan Puthusserypady",

year = "2013",

doi = "10.1109/EMBC.2013.6610491",

language = "English",

volume = "2013",

pages = "4279--82",

journal = "Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference",

issn = "2375-7477",

publisher = "IEEE",

}

TY - JOUR

T1 - Semi-supervised adaptation in ssvep-based brain-computer interface using tri-training

AU - Bender, Thomas

AU - Kjaer, Troels W

AU - Thomsen, Carsten E

AU - Sorensen, Helge B D

AU - Puthusserypady, Sadasivan

PY - 2013

Y1 - 2013

N2 - This paper presents a novel and computationally simple tri-training based semi-supervised steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI). It is implemented with autocorrelation-based features and a Naïve-Bayes classifier (NBC). The system uses nine characters presented on a 100 Hz CRT-monitor, three scalp electrodes for signal acquisition, a gUSB-amp for preamplification and two PCs for data-processing and stimulus control respectively. Preliminary test results of the system on nine healthy subjects, with and without tri-training, indicates that the accuracy improves as a result of tri-training.

AB - This paper presents a novel and computationally simple tri-training based semi-supervised steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI). It is implemented with autocorrelation-based features and a Naïve-Bayes classifier (NBC). The system uses nine characters presented on a 100 Hz CRT-monitor, three scalp electrodes for signal acquisition, a gUSB-amp for preamplification and two PCs for data-processing and stimulus control respectively. Preliminary test results of the system on nine healthy subjects, with and without tri-training, indicates that the accuracy improves as a result of tri-training.

UR - https://www.scopus.com/pages/publications/84886483574

U2 - 10.1109/EMBC.2013.6610491

DO - 10.1109/EMBC.2013.6610491

M3 - Journal article

C2 - 24110678

SN - 2375-7477

VL - 2013

SP - 4279

EP - 4282

JO - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference

JF - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference

ER -

Semi-supervised adaptation in ssvep-based brain-computer interface using tri-training

Abstract

Access to Document

Other files and links

Fingerprint

Cite this