TY - JOUR
T1 - Review of wireless and wearable electroencephalogram systems and brain-computer interfaces - A mini-review
AU - Lin, Chin-Teng
AU - Ko, Li-Wei
AU - Chang, Meng Hsiu
AU - Duann, Jeng-Ren
AU - Chen, Jing Ying
AU - Su, Tung Ping
AU - Jung, Tzyy Ping
PY - 2010/1/1
Y1 - 2010/1/1
N2 - Biomedical signal monitoring systems have rapidly advanced in recent years, propelled by significant advances in electronic and information technologies. Brain-computer interface (BCI) is one of the important research branches and has become a hot topic in the study of neural engineering, rehabilitation, and brain science. Traditionally, most BCI systems use bulky, wired laboratory-oriented sensing equipments to measure brain activity under well-controlled conditions within a confined space. Using bulky sensing equipments not only is uncomfortable and inconvenient for users, but also impedes their ability to perform routine tasks in daily operational environments. Furthermore, owing to large data volumes, signal processing of BCI systems is often performed off-line using high-end personal computers, hindering the applications of BCI in real-world environments. To be practical for routine use by unconstrained, freely-moving users, BCI systems must be noninvasive, nonintrusive, lightweight and capable of online signal processing. This work reviews recent online BCI systems, focusing especially on wearable, wireless and real-time systems.
AB - Biomedical signal monitoring systems have rapidly advanced in recent years, propelled by significant advances in electronic and information technologies. Brain-computer interface (BCI) is one of the important research branches and has become a hot topic in the study of neural engineering, rehabilitation, and brain science. Traditionally, most BCI systems use bulky, wired laboratory-oriented sensing equipments to measure brain activity under well-controlled conditions within a confined space. Using bulky sensing equipments not only is uncomfortable and inconvenient for users, but also impedes their ability to perform routine tasks in daily operational environments. Furthermore, owing to large data volumes, signal processing of BCI systems is often performed off-line using high-end personal computers, hindering the applications of BCI in real-world environments. To be practical for routine use by unconstrained, freely-moving users, BCI systems must be noninvasive, nonintrusive, lightweight and capable of online signal processing. This work reviews recent online BCI systems, focusing especially on wearable, wireless and real-time systems.
KW - Brain-computer interface
KW - Electroencephalogram
KW - Real-time data analysis
KW - Wearable signal monitoring systems
KW - Wireless data transmission
UR - http://www.scopus.com/inward/record.url?scp=76449112167&partnerID=8YFLogxK
U2 - 10.1159/000230807
DO - 10.1159/000230807
M3 - Review article
C2 - 19641287
AN - SCOPUS:76449112167
SN - 0304-324X
VL - 56
SP - 112
EP - 119
JO - Gerontology
JF - Gerontology
IS - 1
ER -