• Chin-Teng Lin, Li-Wei Ko, Meng-Hsiu Chang, Jeng-Ren Duann, Jing-Ying Chen, Tung-Ping Su, and Tzyy-Ping Jung.
• Brain Research Center, National Chiao Tung University, Hsinchu, Taiwan.
• Gerontology. 2010 Jan 1; 56 (1): 112-9.

AbstractBiomedical 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.Copyright 2009 S. Karger AG, Basel.

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