ASRE: Adaptive Spatial Resolution Wearable EEG

Abstract

Electroencephalography (EEG) has been used as a gold standard in various clinical and research applications including disease diagnoses and cognitive understanding. It is also being used as brain-machine interfaces in robotics and assistive technologies. Wearable EEG systems provide a good solution for out-of-hospital recording; however, they are still not suitable for long-term monitoring due to the bulky placement of electrodes over the scalp. The goal of this study is to develop an adaptive spatial resolution framework for wearable EEG systems that can use a limited number of EEG electrodes to achieve high spatial resolution detection. It also shows the high feasibility for achieving high-density and ultra-high-density EEG from traditional 10-20 or 10-10 systems. The proposed method utilized the matrix completion technique to recover high-resolution EEG field from only a limited number of electrodes, which enables simplification of hardware design for wearable EEG that can achieve a compatible performance of P300 detection. The results show that 75% reduced electrodes can achieve a comparable performance as regular EEG with the RMSE under 5%.