DocumentCode :
1513605
Title :
VEP-based brain-computer interfaces: time, frequency, and code modulations [Research Frontier]
Author :
Bin, Guangyu ; Gao, Xiaorong ; Wang, Yijun ; Hong, Bo ; Gao, Shangkai
Author_Institution :
Tsinghua Univ., Beijing, China
Volume :
4
Issue :
4
fYear :
2009
fDate :
11/1/2009 12:00:00 AM
Firstpage :
22
Lastpage :
26
Abstract :
A brain computer interface (BCI) translates human intentions into control signals to establish a direct communication channel between the human brain and external devices. Because a BCI does not depend on the brain´s normal output pathways of peripheral nerves and muscles, it can provide a new communication channel to people with severe motor disabilities. Electroencephalograms (EEGs) recorded from the surface of the scalp are widely used in current BCIs for their non-invasive nature and easy applications. Among EEG based BCIs, systems based on visual evoked potentials (VEPs) have received widespread attention in recent decades. We described the three stimulus modulation approaches used in current VEP based BCIs: time modulation (t-VEP), frequency modulation (f-VEP), and pseudorandom code modulation (c-VEP). We then carried out a detailed comparison of system performance between an f-VEP BCI and a c-VEP BCI. The results show that an f-VEP BCI has the advantage of little or no training and simple system configuration, while the c-VEP based BCI has a higher communication speed. The stimulus modulation design is the crux of VEP based BCI systems.
Keywords :
brain-computer interfaces; electroencephalography; frequency modulation; medical signal processing; visual evoked potentials; EEG; brain-computer interface; communication channel; electroencephalogram; frequency modulation; human brain; pseudorandom code modulation; severe motor disability; stimulus modulation; time modulation; visual evoked potential; Brain computer interfaces; Communication channels; Communication system control; Electroencephalography; Frequency modulation; Humans; Modulation coding; Muscles; Scalp; System performance;
fLanguage :
English
Journal_Title :
Computational Intelligence Magazine, IEEE
Publisher :
ieee
ISSN :
1556-603X
Type :
jour
DOI :
10.1109/MCI.2009.934562
Filename :
5294934
Link To Document :
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