TY - GEN
T1 - Brain computer interface to answer yes-no questions
AU - Roman-Gonzalez, Avid
AU - Vargas-Cuentas, Natalia I.
AU - Hoyos, Miguel
AU - Diaz, Joel
AU - Zimic, Mirko
N1 - Funding Information:
This work was supported by FONDECYT – ‘01-2013-Fondecyt Financiamiento de Subvención para Investigación Postdoctoral’.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/11/3
Y1 - 2017/11/3
N2 - The aim of this work is to design, implement and validate a primary communication system based on a brain-computer interface. There are people who-for various reasons-are affected in their ability to externalize their communication, however, they receive and process information from different sources. This system would allow basic communication-allowing the user to answer closed questions-through thought. The system was implemented by analyzing and interpreting electrical signals from brain activity, collected through electrodes attached to the scalp. The analog electrical signals were received by a data acquisition system and digitized for computer analysis. We implemented different signal processing techniques, pattern analysis, and classification and discrimination methods. By analyzing these signals and interpreting the electrical patterns, was achieved understand answers to simple questions. The system has been validated testing with healthy volunteers in the laboratory, obtaining good results.
AB - The aim of this work is to design, implement and validate a primary communication system based on a brain-computer interface. There are people who-for various reasons-are affected in their ability to externalize their communication, however, they receive and process information from different sources. This system would allow basic communication-allowing the user to answer closed questions-through thought. The system was implemented by analyzing and interpreting electrical signals from brain activity, collected through electrodes attached to the scalp. The analog electrical signals were received by a data acquisition system and digitized for computer analysis. We implemented different signal processing techniques, pattern analysis, and classification and discrimination methods. By analyzing these signals and interpreting the electrical patterns, was achieved understand answers to simple questions. The system has been validated testing with healthy volunteers in the laboratory, obtaining good results.
KW - BCI
KW - EEG
KW - brain-computer interface
KW - communication system
KW - yes-no questions
UR - http://www.scopus.com/inward/record.url?scp=85040537614&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85040537614&partnerID=8YFLogxK
U2 - 10.1109/BIOSMART.2017.8095323
DO - 10.1109/BIOSMART.2017.8095323
M3 - Conference contribution
AN - SCOPUS:85040537614
T3 - BioSMART 2017 - Proceedings: 2nd International Conference on Bio-Engineering for Smart Technologies
BT - BioSMART 2017 - Proceedings
A2 - Nait-Ali, Amine
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Bio-Engineering for Smart Technologies, BioSMART 2017
Y2 - 30 August 2017 through 1 September 2017
ER -