brain/bodycomputer Interface (BBCI) technology facilitates research in human cognition and assistive technologies. BBCI acquires and analyzes physiological signals from human body/brain such as electroencephalography...
详细信息
ISBN:
(纸本)9781450345354
brain/bodycomputer Interface (BBCI) technology facilitates research in human cognition and assistive technologies. BBCI acquires and analyzes physiological signals from human body/brain such as electroencephalography (EEG) to observe human physiological states and potentially enable external control. BBCI devices require accurate data acquisition systems with sufficient dynamic range for various brain/body signals. Also, embedded processing is desirable for real-time interaction and flexible deployment. However, most off-the-shelf BBCI devices are very costly, e.g. g. USBamp at $ 15K and do not offer embedded processing. Hence, an open embedded device for BBCI acquisition and processing is needed to foster the BBCI research. This paper proposes EEGu2 as a portable embedded BBCI device. Based on a BeagleBone Black (BBB), EEGu2 integrates a custom-designed cape including 2 PCBs: an acquisition board for 16-channel 24-bit acquisition up to 1KHz sampling frequency and a power board for wall charging and powering mobile operations. EEGu2 measurement shows a high acquisition accuracy with 25dB signal-to-noise ratio and 0.785 mu V peak-to-peak input referred noise. At maximum performance, the cape consumes 101.2 mW while BBB consumes 1850 mW. With two lithium batteries, EEGu2 operates independently 12 hours. We demonstrate the flexibility and portability of EEGu2 in the context of Human-in-the-Loop Cyber-Physical Systems (HiLCPS) that augments human interaction with physical world through BBCI. The EEGu2 firmware is integrated into the HiLCPS Framework to enable the location transparent access via the MATLAB interface. EEGu2 empowers rapid embedded BBCI application deployment and we show the flexibility of EEGu2 with a BCI Speller application that acquires real-time EEG signals and infers the user spelling based on Steady State Visually Evoked Potential.
暂无评论