An ICA-based automatic eye blink artifact eliminator for real-time multi-channel EEG applications
Jui-Chieh Liao, Wai-Chi Fang · 2013
This paper presents an ICA-based automatic eye blink artifact eliminator for real-time multi-channel EEG applications. Since EEG signals are very feeble, they are easy to be contaminated by artifacts. Among all artifacts, eye blink artifact dose the most significant harm. ICA has been shown to separate the artifacts from brain activity sources. After the processing of ICA, the results can be used for further applications such as brain computer interface (BCI). Because the behavior of eye blink artifact might mimic the brain activities which might mislead the operation of BCI, the independent component contained eye blink artifact needs to be removed before further applications. For the availability and feasibility of BCI, a real time ICA algorithm, online recursive ICA (ORICA), is developed. With ORICA, a set of ICA result of each EEG sample time can be accomplished after each EEG acquisition. That will reduce the reaction time of ICA and make the applications of BCI more feasible. In order to take advantage of ORICA completely, a real-time eye blink artifact eliminator which can detect the existence of eye blink artifact for every single set of ICA result is needed. The proposed eliminator is designed using TSMC 90nm CMOS technology. The validity of the proposed eliminator is also given in this paper.