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Optimal artifact suppression in simultaneous electrocorticography stimulation and recording for bi-directional brain-computer interface applications

Pu, Haoran and Lim, Jeffrey and Kellis, Spencer and Liu, Charles Y. and Andersen, Richard A. and Do, An H. and Heydari, Payam and Nenadic, Zoran (2020) Optimal artifact suppression in simultaneous electrocorticography stimulation and recording for bi-directional brain-computer interface applications. Journal of Neural Engineering, 17 (2). Art. No. 026038. ISSN 1741-2560. doi:10.1088/1741-2552/ab82ac.

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Objective. Electrocorticogram (ECoG)-based brain-computer interfaces (BCIs) are a promising platform for the restoration of motor and sensory functions to those with neurological deficits. Such bi-directional BCI operation necessitates simultaneous ECoG recording and stimulation, which is challenging given the presence of strong stimulation artifacts. This problem is exacerbated if the BCI's analog front-end operates in an ultra-low power regime, which is a basic requirement for fully implantable medical devices. In this study, we developed a novel method for the suppression of stimulation artifacts before they reach the analog front-end. Approach. Using elementary biophysical considerations, we devised an artifact suppression method that employs a weak auxiliary stimulation delivered between the primary stimulator and the recording grid. The exact location and amplitude of this auxiliary stimulating dipole were then found through a constrained optimization procedure. The performance of our method was tested in both simulations and phantom brain tissue experiments. Main Results. The solution found through the optimization procedure matched the optimal canceling dipole in both simulations and experiments. Artifact suppression as large as 28.7 dB and 22.9 dB were achieved in simulations and brain phantom experiments, respectively. Significance. We developed a simple constrained optimization-based method for finding the parameters of an auxiliary stimulating dipole that yields optimal artifact suppression. Our method suppresses stimulation artifacts before they reach the analog front-end and may prevent the front-end amplifiers from saturation. Additionally, it can be used along with other artifact mitigation techniques to further reduce stimulation artifacts.

Item Type:Article
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URLURL TypeDescription
Pu, Haoran0000-0002-6787-5907
Kellis, Spencer0000-0002-5158-1058
Andersen, Richard A.0000-0002-7947-0472
Additional Information:© 2020 IOP Publishing Ltd. Received 26 October 2019; Revised 15 February 2020; Accepted 24 March 2020; Accepted Manuscript online 24 March 2020.
Funding AgencyGrant Number
Issue or Number:2
Record Number:CaltechAUTHORS:20200330-151432453
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Official Citation:Haoran Pu et al 2020 J. Neural Eng. 17 026038
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:102174
Deposited By: Tony Diaz
Deposited On:30 Mar 2020 22:24
Last Modified:16 Nov 2021 18:09

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