The impact of head movements on EEG and contact impedance: An adaptive filtering solution for motion artifact reduction

Abstract

Designing and developing a comfortable and convenient EEG system for daily usage that can provide reliable and robust EEG signal, encompasses a number of challenges. Among them, the most ambitious is the reduction of artifacts due to body movements. This paper studies the effect of head movement artifacts on the EEG signal and on the dry electrode-tissue impedance (ETI), monitored continuously using the imec's wireless EEG headset. We have shown that motion artifacts have huge impact on the EEG spectral content in the frequency range lower than 20 Hz. Coherence and spectral analysis revealed that ETI is not capable of describing disturbances at very low frequencies (below 2 Hz). Therefore, we devised a motion artifact reduction (MAR) method that uses a combination of a band-pass filtering and multi-channel adaptive filtering (AF), suitable for real-time MAR. This method was capable of substantially reducing artifacts produced by head movements.

Review on Latest Multichannel EEG Acquisition and Artifact Filtering Methods

“…Adaptive filtering scheme [26,28,37,38], Blind source Separation scheme [32,36], Transform based methods [27,30,33,39,40], Empirical mode decomposition techniques [29,31] and combination methods [30,34,35,37,38,41].These methods are suggested by worldwide researchers for getting clean EEG signal for proper diagnosis.…”

“…Motion artifacts and eye blink artifacts are considered for removal using adaptive filtering and EMD approach. This method combines the band-pass and adaptive filtering to cope with the limitations of the reference ETI signal [28].…”

“…Therefore, a motion artifact reduction (MAR) method that consists of combination of a band-pass filters and multi-channel adaptive filtering (AF), suitable for real-time MAR is devised. This method was capable of substantially reducing artifacts produced by head movements [28].…”

“…Electrodes movements may occur with different speed and in different directions, so the shape of electrodes movement artifacts varies a lot. In the frequency domain, Alpha wave measurement and detection will seriously be influenced by the electrodes movement artifacts [17,28].…”

Comparison of Preprocessing Algorithms using an Affordable EEG Headset

“…Then, the signals were filtered by Sinc band pass filter (order 5) to get the frequency band from 0.2 Hz to 45 Hz. The obtained frequency band is the band that is more informative according to [10] that shows the substantial is increasing in the EEG spectral content below the frequency of 5Hz (delta band brain activity), a medium increase in the range of 5-20Hz (alpha and low beta bands), and a smaller increase of spectra in the higher frequency range can be observed. These EEG data were recorded from Emotiv EPOC which it has 14 electrodes only and 2 reference electrodes (CMS and DRL).…”