loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Lukáš Vařeka ; Tomáš Prokop ; Jan Štěbeták and Roman Mouček

Affiliation: University of West Bohemia, Czech Republic

ISBN: 978-989-758-170-0

Keyword(s): Electroencephalography, Event-related Potentials, Brain-Computer Interface, P300, Discrete Wavelet Transform, Multi-layer Perceptron.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Computer Vision, Visualization and Computer Graphics ; Cybernetics and User Interface Technologies ; Devices ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Information and Systems Security ; Medical Image Detection, Acquisition, Analysis and Processing ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods ; Wavelet Transform

Abstract: Although research into brain-computer interfaces is more common in recent years, studies concerning large groups of specific subjects are still lacking. This paper describes a simple brain-computer interface (BCI) experiment that was performed on a group of over 200 school-age children using the technique and methods of event related potentials. In the first phase, experimental data were recorded in various elementary and secondary schools, mainly in the Pilsen region of the Czech Republic. The task was to guess the number between 1 and 9 that the measured subject thinks on. Concurrently, a human expert made a decision about the target number based on averaged P300 waveforms observed on-line. In the second phase, an application for automatic classification was developed for off-line data. A small subset of the data was used for training; the rest of the data was used to evaluate the accuracy of classification. Two feature extraction methods were compared; subsampling and discrete wave let transform for feature extraction. Multi-layer perceptron was used for classification. The human expert achieved the accuracy of 67.6%, while some of the automatic algorithms were able to significantly outperform the expert; the maximum classification accuracy reached 77.2%. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 35.173.234.237

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Vařeka, L.; Prokop, T.; Štěbeták, J. and Mouček, R. (2016). Guess the Number - Applying a Simple Brain-Computer Interface to School-age Children.In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 263-270. DOI: 10.5220/0005801402630270

@conference{biosignals16,
author={Lukáš Va\v{r}eka. and Tomáš Prokop. and Jan Štěbeták. and Roman Mouček.},
title={Guess the Number - Applying a Simple Brain-Computer Interface to School-age Children},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2016)},
year={2016},
pages={263-270},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005801402630270},
isbn={978-989-758-170-0},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2016)
TI - Guess the Number - Applying a Simple Brain-Computer Interface to School-age Children
SN - 978-989-758-170-0
AU - Vařeka, L.
AU - Prokop, T.
AU - Štěbeták, J.
AU - Mouček, R.
PY - 2016
SP - 263
EP - 270
DO - 10.5220/0005801402630270

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.