Literature DB >> 30074489

Dual-electrode motion artifact cancellation for mobile electroencephalography.

Andrew D Nordin1, W David Hairston, Daniel P Ferris.   

Abstract

OBJECTIVE: Our purpose was to evaluate the ability of a dual electrode approach to remove motion artifact from electroencephalography (EEG) measurements. APPROACH: We used a phantom human head model and robotic motion platform to induce motion while collecting scalp EEG. We assembled a dual electrode array capturing (a) artificial neural signals plus noise from scalp EEG electrodes, and (b) electrically isolated motion artifact noise. We recorded artificial neural signals broadcast from antennae in the phantom head during continuous vertical sinusoidal movements (stationary, 1.00, 1.25, 1.50, 1.75, 2.00 Hz movement frequencies). We evaluated signal quality using signal-to-noise ratio (SNR), cross-correlation, and root mean square error (RMSE) between the ground truth broadcast signals and the recovered EEG signals. MAIN
RESULTS: Signal quality was restored following noise cancellation when compared to single electrode EEG measurements collected with no phantom head motion. SIGNIFICANCE: We achieved substantial motion artifact attenuation using secondary electrodes for noise cancellation. These methods can be applied to studying electrocortical signals during human locomotion to improve real-world neuroimaging using EEG.

Entities:  

Mesh:

Year:  2018        PMID: 30074489     DOI: 10.1088/1741-2552/aad7d7

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  15 in total

1.  Corrigendum: Multimodal Imaging of Brain Activity to Investigate Walking and Mobility Decline in Older Adults (Mind in Motion Study): Hypothesis, Theory, and Methods.

Authors:  David J Clark; Todd M Manini; Daniel P Ferris; Chris J Hass; Babette A Brumback; Yenisel Cruz-Almeida; Marco Pahor; Patricia A Reuter-Lorenz; Rachael D Seidler
Journal:  Front Aging Neurosci       Date:  2020-03-04       Impact factor: 5.750

2.  Combined head phantom and neural mass model validation of effective connectivity measures.

Authors:  Steven M Peterson; Daniel P Ferris
Journal:  J Neural Eng       Date:  2018-12-04       Impact factor: 5.379

Review 3.  Wearable EEG and beyond.

Authors:  Alexander J Casson
Journal:  Biomed Eng Lett       Date:  2019-01-04

4.  Human electrocortical dynamics while stepping over obstacles.

Authors:  Andrew D Nordin; W David Hairston; Daniel P Ferris
Journal:  Sci Rep       Date:  2019-03-18       Impact factor: 4.379

5.  Faster Gait Speeds Reduce Alpha and Beta EEG Spectral Power From Human Sensorimotor Cortex.

Authors:  Andrew D Nordin; W David Hairston; Daniel P Ferris
Journal:  IEEE Trans Biomed Eng       Date:  2019-06-13       Impact factor: 4.538

6.  Human myoelectric spatial patterns differ among lower limb muscles and locomotion speeds.

Authors:  Bryan R Schlink; Andrew D Nordin; Daniel P Ferris
Journal:  Physiol Rep       Date:  2020-12

7.  Absence Seizure Detection Algorithm for Portable EEG Devices.

Authors:  Pawel Glaba; Miroslaw Latka; Małgorzata J Krause; Sławomir Kroczka; Marta Kuryło; Magdalena Kaczorowska-Frontczak; Wojciech Walas; Wojciech Jernajczyk; Tadeusz Sebzda; Bruce J West
Journal:  Front Neurol       Date:  2021-06-29       Impact factor: 4.003

8.  Cortical Correlates of Locomotor Muscle Synergy Activation in Humans: An Electroencephalographic Decoding Study.

Authors:  Hikaru Yokoyama; Naotsugu Kaneko; Tetsuya Ogawa; Noritaka Kawashima; Katsumi Watanabe; Kimitaka Nakazawa
Journal:  iScience       Date:  2019-04-10

9.  More Reliable EEG Electrode Digitizing Methods Can Reduce Source Estimation Uncertainty, but Current Methods Already Accurately Identify Brodmann Areas.

Authors:  Seyed Yahya Shirazi; Helen J Huang
Journal:  Front Neurosci       Date:  2019-11-06       Impact factor: 4.677

10.  Measurement of stretch-evoked brainstem function using fMRI.

Authors:  Andrea Zonnino; Andria J Farrens; David Ress; Fabrizio Sergi
Journal:  Sci Rep       Date:  2021-06-15       Impact factor: 4.379

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