TY - GEN
T1 - A wearable real-time BCI system based on mobile cloud computing
AU - Blondet, Maria V.Ruiz
AU - Badarinath, Adarsha
AU - Khanna, Chetan
AU - Jin, Zhanpeng
PY - 2013
Y1 - 2013
N2 - Pervasive and wearable brain-computer interface (BCI) systems show great potential for effectively understanding human mental activities and intentions in their daily life. In this paper, we propose a real-time BCI system based on mobile devices and cloud computing to detect and recognize the user's mental states. A proof-of-concept prototype is developed based on a wearable, commercially available EEG headset, an Android smartphone, and a multi-core computing server. We demonstrate an integrated Android app containing three built-in functional modules. Specifically, a graphical window can receive and display continuous EEG data acquired from the headset in a real-time manner; a facial expression interface can indicate the user's mental states according to the analysis of EEG data on the server; and a retrospective analysis tool to investigate the mental behaviors over a long period of time.
AB - Pervasive and wearable brain-computer interface (BCI) systems show great potential for effectively understanding human mental activities and intentions in their daily life. In this paper, we propose a real-time BCI system based on mobile devices and cloud computing to detect and recognize the user's mental states. A proof-of-concept prototype is developed based on a wearable, commercially available EEG headset, an Android smartphone, and a multi-core computing server. We demonstrate an integrated Android app containing three built-in functional modules. Specifically, a graphical window can receive and display continuous EEG data acquired from the headset in a real-time manner; a facial expression interface can indicate the user's mental states according to the analysis of EEG data on the server; and a retrospective analysis tool to investigate the mental behaviors over a long period of time.
UR - https://www.scopus.com/pages/publications/84897729917
U2 - 10.1109/NER.2013.6696040
DO - 10.1109/NER.2013.6696040
M3 - Conference contribution
AN - SCOPUS:84897729917
SN - 9781467319690
T3 - International IEEE/EMBS Conference on Neural Engineering, NER
SP - 739
EP - 742
BT - 2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
T2 - 2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
Y2 - 6 November 2013 through 8 November 2013
ER -