Title :
A wearable real-time BCI system based on mobile cloud computing
Author :
Blondet, Maria V. Ruiz ; Badarinath, Adarsha ; Khanna, Chetan ; Zhanpeng Jin
Author_Institution :
Dept. of Bioeng., Binghamton Univ., Binghamton, NY, USA
Abstract :
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.
Keywords :
brain-computer interfaces; cloud computing; electroencephalography; medical signal processing; mobile computing; smart phones; Android app; Android smartphone; EEG headset; brain-computer interface system; continuous EEG data analysis; electroencephalography; facial expression interface; graphical window; human mental activities; mobile cloud computing; mobile devices; multicore computing server; pervasive BCI system; wearable real-time BCI system; Electroencephalography; Headphones; Humanoid robots; Mobile communication; Mobile handsets; Real-time systems; Servers;
Conference_Titel :
Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on
Conference_Location :
San Diego, CA
DOI :
10.1109/NER.2013.6696040