TY - GEN
T1 - Brain-computer interfaces by electrical cortex activity: Challenges in creating a cognitive system for mobile devices using steady-state visually evoked potentials
AU - Morais, Pedro
AU - Pereira, Carla Maria Quintão
AU - Vieira, Pedro
N1 - sem pdf.
PY - 2016
Y1 - 2016
N2 - The research field of Brain-Computer Interfaces (BCI) emerged in an attempt to enable communication between paralyzed patients and technology. Identifying an individual’s mental state, through his brain’s electric activity, a typical BCI system assigns to it a particular action in the computer. It is known that when the visual cortex is stimulated with a certain frequency, it shows activity with the same frequency. This Steady-State Visually Evoked Potential (SSVEP) activity can be used to achieve the aforementioned communication goal. In this work, we first analyze the spontaneous electrical activity of the brain, to distinguish two mental sates (concentration/meditation). Then, following an SSVEP type of approach, we divide the stimulating screen in four areas, each of which flickering at a distinct frequency. By observing the responding frequency from the occipital lobe of the subject, we can then estimate the 2 bit decision he made. We observe that such a setup is efficient for real time BCI, and can be easily integrated in mobile devices. Besides, the user is able to change voluntarily her/his decisions, interacting with the system in a natural manner.
AB - The research field of Brain-Computer Interfaces (BCI) emerged in an attempt to enable communication between paralyzed patients and technology. Identifying an individual’s mental state, through his brain’s electric activity, a typical BCI system assigns to it a particular action in the computer. It is known that when the visual cortex is stimulated with a certain frequency, it shows activity with the same frequency. This Steady-State Visually Evoked Potential (SSVEP) activity can be used to achieve the aforementioned communication goal. In this work, we first analyze the spontaneous electrical activity of the brain, to distinguish two mental sates (concentration/meditation). Then, following an SSVEP type of approach, we divide the stimulating screen in four areas, each of which flickering at a distinct frequency. By observing the responding frequency from the occipital lobe of the subject, we can then estimate the 2 bit decision he made. We observe that such a setup is efficient for real time BCI, and can be easily integrated in mobile devices. Besides, the user is able to change voluntarily her/his decisions, interacting with the system in a natural manner.
KW - BCI
KW - EEG
KW - Mobile device
KW - Smartphone
KW - SSVEP
KW - Tablet
UR - http://www.scopus.com/inward/record.url?scp=84962097607&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-31165-4_14
DO - 10.1007/978-3-319-31165-4_14
M3 - Conference contribution
AN - SCOPUS:84962097607
SN - 978-3-319-31164-7
T3 - IFIP Advances in Information and Communication Technology
SP - 135
EP - 141
BT - Technological Innovation for Cyber-Physical Systems - 7th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2016, Proceedings
A2 - Camarinha-Matos, L. M.
A2 - Falcão, A. J.
A2 - Vafaei, N.
A2 - Najdi, S.
PB - Springer
CY - Cham
T2 - 7th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2016
Y2 - 11 April 2016 through 13 April 2016
ER -