Browse by author
Lookup NU author(s): Dr Luke BashfordORCiD
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
© 2023 IOP Publishing Ltd. Objective. Invasive brain-computer interfaces (BCIs) have shown promise in restoring motor function to those paralyzed by neurological injuries. These systems also have the ability to restore sensation via cortical electrostimulation. Cortical stimulation produces strong artifacts that can obscure neural signals or saturate recording amplifiers. While front-end hardware techniques can alleviate this problem, residual artifacts generally persist and must be suppressed by back-end methods. Approach. We have developed a technique based on pre-whitening and null projection (PWNP) and tested its ability to suppress stimulation artifacts in electroencephalogram (EEG), electrocorticogram (ECoG) and microelectrode array (MEA) signals from five human subjects. Main results. In EEG signals contaminated by narrow-band stimulation artifacts, the PWNP method achieved average artifact suppression between 32 and 34 dB, as measured by an increase in signal-to-interference ratio. In ECoG and MEA signals contaminated by broadband stimulation artifacts, our method suppressed artifacts by 78%-80% and 85%, respectively, as measured by a reduction in interference index. When compared to independent component analysis, which is considered the state-of-the-art technique for artifact suppression, our method achieved superior results, while being significantly easier to implement. Significance. PWNP can potentially act as an efficient method of artifact suppression to enable simultaneous stimulation and recording in bi-directional BCIs to biomimetically restore motor function.
Author(s): Lim J, Wang PT, Bashford L, Kellis S, Shaw SJ, Gong H, Armacost M, Heydari P, Do AH, Andersen RA, Liu CY, Nenadic Z
Publication type: Article
Publication status: Published
Journal: Journal of Neural Engineering
Year: 2023
Volume: 20
Issue: 5
Print publication date: 01/10/2023
Online publication date: 22/09/2023
Acceptance date: 04/09/2023
ISSN (print): 1741-2560
ISSN (electronic): 1741-2552
Publisher: Institute of Physics
URL: https://doi.org/10.1088/1741-2552/acf68b
DOI: 10.1088/1741-2552/acf68b
PubMed id: 37666246
Altmetrics provided by Altmetric
