TY - GEN
T1 - Design and evaluation of a P300 visual brain-computer interface speller in cyrillic characters
AU - Zhumadilova, Arailym
AU - Tokmurzina, Dana
AU - Kuderbekov, Akbay
AU - Abibullaev, Berdakh
N1 - Funding Information:
*This research was supported by Nazarbayev University research grants. All authors are with the Department of Robotics and Mechatronics, Nazarbayev University, Kabanbay Batyr Avenue 53, Astana 010000, Kazakhstan. berdakh.abibullaev@nu.edu.kz Fig. 1. Different components of the presented Cyrillic-BCI speller system. A) A subject pays attention to a specific character of interest in the provided matrix in order to spell a sentence. The BCI system extracts features of EEG P300 waveform in real-time decodes to identify the intended character. b)The EPOC electrode positions on the head approximate the international 10-20 system. c) Example of an ERP-P300 target and non-target waveform.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/8
Y1 - 2017/12/8
N2 - A visual Brain-Computer Interface (BCI) speller is a system which assists disabled persons with severe neu-romuscular diseases to communicate with the external world. It acquires brain signals in response to visual stimuli shown to the person on a screen, and then analyzes in real-time to predict the desired symbol on a single trial basis. To date most BCI design paradigms have been focused on the development of a speller to communicate English or Latin based languages. Due to a lack of BCI spellers for patients speaking Cyrillic-based languages, this study presents the initial design and evaluation of a speller that contains Cyrillic alphanumeric characters. The visual BCI speller was evaluated on five healthy subjects, who showed encouraging results during both the offline training phases, as well as during the real-time BCI spelling experiments. We discuss each steps of the design in detail and share the challenges and limitation of such design approaches with possible solutions.
AB - A visual Brain-Computer Interface (BCI) speller is a system which assists disabled persons with severe neu-romuscular diseases to communicate with the external world. It acquires brain signals in response to visual stimuli shown to the person on a screen, and then analyzes in real-time to predict the desired symbol on a single trial basis. To date most BCI design paradigms have been focused on the development of a speller to communicate English or Latin based languages. Due to a lack of BCI spellers for patients speaking Cyrillic-based languages, this study presents the initial design and evaluation of a speller that contains Cyrillic alphanumeric characters. The visual BCI speller was evaluated on five healthy subjects, who showed encouraging results during both the offline training phases, as well as during the real-time BCI spelling experiments. We discuss each steps of the design in detail and share the challenges and limitation of such design approaches with possible solutions.
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U2 - 10.1109/ROMAN.2017.8172426
DO - 10.1109/ROMAN.2017.8172426
M3 - Conference contribution
AN - SCOPUS:85045856539
T3 - RO-MAN 2017 - 26th IEEE International Symposium on Robot and Human Interactive Communication
SP - 1006
EP - 1011
BT - RO-MAN 2017 - 26th IEEE International Symposium on Robot and Human Interactive Communication
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 26th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2017
Y2 - 28 August 2017 through 1 September 2017
ER -