Isolating gait-related movement artifacts in electroencephalography during human walking

Abstract

Objective High-density electroencephelography (EEG) can provide insight into human brain function during real-world activities with walking. Some recent studies have used EEG to characterize brain activity during walking, but the relative contributions of movement artifact and electrocortical activity have been difficult to quantify. We aimed to characterize movement artifact recorded by EEG electrodes at a range of walking speeds and to test the efficacy of artifact removal methods. We also quantified the similarity between movement artifact recorded by EEG electrodes and a head-mounted accelerometer. Approach We used a novel experimental method to isolate and record movement artifact with EEG electrodes during walking. We blocked electrophysiological signals using a nonconductive layer (silicone swim cap) and simulated an electrically conductive scalp on top of the swim cap using a wig coated with conductive gel. We recorded motion artifact EEG data from nine young human subjects walking on a treadmill at speeds from 0.4–1.6 m/s. We then tested artifact removal methods including moving average and wavelet-based techniques. Main Results Movement artifact recorded with EEG electrodes varied considerably, across speed, subject, and electrode location. The movement artifact measured with EEG electrodes did not correlate well with head acceleration. All of the tested artifact removal methods attenuated low-frequency noise but did not completely remove movement artifact. The spectral power fluctuations in the movement artifact data resembled data from some previously published studies of EEG during walking. Significance Our results suggest that EEG data recorded during walking likely contains substantial movement artifact that: cannot be explained by head accelerations; varies across speed, subject, and channel; and cannot be removed using traditional signal processing methods. Future studies should focus on more sophisticated methods for removing of EEG movement artifact to advance the field.

Neuroimaging of Human Balance Control: A Systematic Review

“…Furthermore, the signal correlation varied for each of the three EEG electrode locations (Cz, Oz, T8), suggesting that a uniform filtering method could not be used across all scalp electrodes (Castermans et al, 2014). Kline et al (2015) and Snyder et al (2015) used a silicone swim cap to block all electrocortical activity, thus measuring only movement artifact while subjects walked on a treadmill at different speeds. Like Castermans et al (2014) and Kline et al (2015) collected accelerometer data, however, there was poor correlation between the EEG and accelerometer signals.…”

Concealed, Unobtrusive Ear-Centered EEG Acquisition: cEEGrids for Transparent EEG

“…Note that physiological artifacts caused by electrical activity of the muscles are unavoidable, but may be relatively easy to deal with by temporal filter application and other post-processing procedures (Reis et al, 2014). Motion of sensors, and motion of parts of the measurement system, however, may contribute strong interference and corrupt signals to an extend that the underlying brain activity cannot be recovered (Kline et al, 2015). New hardware solutions that account for sensor motion (Yazicioglu et al, 2010; Reis et al, 2014; Cömert and Hyttinen, 2015; Goverdovsky et al, 2015) and miniaturized amplifier solutions featuring shielding and active amplification (Metting van Rijn et al, 1990) may help to alleviate this problem further.…”

Distinct β Band Oscillatory Networks Subserving Motor and Cognitive Control during Gait Adaptation

“…Two recent studies (Castermans et al, 2014;Kline et al, 2015) investigated movementrelated artifacts in the EEG during upright walking and found contamination of the EEG data at frequencies from 1 to 150 Hz. Castermans et al (2014) found similar time/frequency properties in accelerometer signals recorded from the head during walking and in EEG for frequency bands extending up to 150 Hz.…”