Abstract

Brain-computer interfaces (BCIs) [1], [2] have recently been shown to be the most promising conduits for individuals with disabilities or reduced mobility to allow communication with the external environment or to trigger surrounding devices. BCIs have also been shown to be successful in a wide range of applications, such as personal authentication or identification [3], [4], assessment of emotional disorders [5], games [6], and accident prevention [7], [8]. However, several technical issues in signal acquisition, signal preprocessing, feature extraction, and signal translation must be addressed to facilitate the transition of laboratory-oriented neuroscience research to practical BCI devices (Figure 1).

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