Isolating gait-related movement artifacts in electroencephalography during human walking

Julia E Kline,Helen J Huang,Daniel P Ferris,Kristine L Snyder

doi:10.1088/1741-2560/12/4/046022

Julia E Kline, Helen J Huang + Show 2 more

Open Access

https://doi.org/10.1088/1741-2560/12/4/046022

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Abstract

Objective. High-density electroencephelography (EEG) can provide an 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 to 1.6 m s−1. 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 removal of EEG movement artifact to advance the field.

Highlights

Measuring brain activity during human walking has the potential to advance both basic neuroscience and functional technologies
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
The correlation coefficients were greatest for the vertical head acceleration and the movement artifact signals recorded in the EEG electrodes compared to the mediolateral and anterior-posterior accelerations (Figure 3(b))

Summary

Introduction

Measuring brain activity during human walking has the potential to advance both basic neuroscience and functional technologies. Mobile brain imaging devices would provide valuable information about the brain activity patterns of individuals with neural disorders. For these goals to be achieved during locomotion, it is imperative to: 1) be able to identify specific brain sources, which requires good spatial resolution, 2) be able to observe split-second neural changes within a stride, which requires good temporal resolution, and 3) be able to extract strictly neural signals. Other groups have proved the feasibility of measuring scalp electrocortical signals during human walking, at speeds ranging from 0.42 m/s to 1.9 m/s, to provide insight into brain function (Gramann et al, 2010; Cheron et al, 2012; Lau et al, 2012; Severens et al, 2012; Wagner et al, 2012; Seeber et al, 2014; Seeber et al, 2015)

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