Motion artifact reduction in EEG recordings using multi-channel contact impedance measurements

Abstract

Dry-contact electrodes have paved the way for easy-to-use electroencephalography (EEG) systems with minimal setup time, which are of particular interest in ambulatory as well as real-life environments. However, the presence of motion artifacts forms a major obstacle for such systems. In previous studies, it has been shown that continuous electrode-tissue impedance monitoring can be used to handle motion artifacts. In this paper, we demonstrate that the in-phase and quadrature components of the contact impedance provide complementary information that can be used to improve the prediction of motion artifacts. Furthermore, we demonstrate that the prediction of motion artifacts at one electrode can be further improved by also incorporating the impedance measurements at other electrodes. With this, we propose a motion artifact reduction algorithm based on a multi-channel linear prediction (MLP) filter. Although the MLP filter is not able to completely remove motion artifacts, a substantial reduction can indeed be achieved.