NDLI: The portable P300 dialing system based on tablet and Emotiv Epoc headset

Content Provider	IEEE Xplore Digital Library
Author	Tong Jijun Zhang Peng Xiao Ran Ding Lei
Copyright Year	2015
Description	Author affiliation: Sch. of Inf. Sci. & Technol., Zhejiang Sci-Tech Univ., Hangzhou, China (Tong Jijun; Zhang Peng) \|\| Sch. of Electr. & Comput. Eng., Univ. of Oklahoma, Norman, OK, USA (Xiao Ran; Ding Lei)
Abstract	A Brain-computer interface (BCI) is a novel communication system that translates brain signals into a control signal. Now with the appearance of the commercial EEG headsets and mobile smart platforms (tablet, smartphone), it is possible to develop the mobile BCI system, which can greatly improve the life quality of patients suffering from motor disease, such as amyotrophic lateral scleroses (ALS), multiple sclerosis, cerebral palsy and head trauma. This study adopted a 14-channel Emotiv EPOC headset and Microsoft surface pro 3 to realize a dialing system, which was represented by 4×3 matrices of alphanumeric characters. The performance of the online portable dialing system based on P300 is satisfying. The average classification accuracy reaches 88.75±10.57% in lab and 73.75±16.94% in metro, while the information transfer rate (ITR) reaches 7.17±1.80 and 5.05±2.17 bits/min respectively. This means the commercial EEG headset and tablet has good prospect in developing real time BCI system in realistic environments.
Starting Page	566
Ending Page	569
File Size	890592
Page Count	4
File Format	PDF
ISSN	1557170X
e-ISBN	9781424492718
DOI	10.1109/EMBC.2015.7318425
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Headphones Accuracy Mobile communication Brain-computer interfaces Visualization Computers
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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