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Lim J, Wang PT, Bashford L, Kellis S, Shaw SJ, Gong H, Armacost M, Heydari P, Do AH, Andersen RA, Liu CY, Nenadic Z. Suppression of cortical electrostimulation artifacts using pre-whitening and null projection. J Neural Eng 2023; 20:056018. [PMID: 37666246 DOI: 10.1088/1741-2552/acf68b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 09/04/2023] [Indexed: 09/06/2023]
Abstract
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.
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Affiliation(s)
- Jeffrey Lim
- Department of Biomedical Engineering, University of California Irvine (UCI), Irvine, CA 92697, United States of America
| | - Po T Wang
- Department of Biomedical Engineering, University of California Irvine (UCI), Irvine, CA 92697, United States of America
| | - Luke Bashford
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, United States of America
| | - Spencer Kellis
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, United States of America
- Department of Neurological Surgery, Keck School of Medicine of University of Southern California (USC), Los Angeles, CA 90033, United States of America
- USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA 90033, United States of America
| | - Susan J Shaw
- Department of Neurology, Rancho Los Amigos National Rehabilitation Center, Downey, CA 90242, United States of America
- Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA 90033, United States of America
| | - Hui Gong
- Department of Neurology, Rancho Los Amigos National Rehabilitation Center, Downey, CA 90242, United States of America
- Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA 90033, United States of America
| | - Michelle Armacost
- Department of Neurology, Rancho Los Amigos National Rehabilitation Center, Downey, CA 90242, United States of America
- Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA 90033, United States of America
| | - Payam Heydari
- Department of Biomedical Engineering, University of California Irvine (UCI), Irvine, CA 92697, United States of America
- Department of Electrical Engineering and Computer Science, UCI, Irvine, CA 92697, United States of America
| | - An H Do
- Department of Neurology, UCI, Irvine, CA 92697, United States of America
| | - Richard A Andersen
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, United States of America
| | - Charles Y Liu
- Department of Neurological Surgery, Keck School of Medicine of University of Southern California (USC), Los Angeles, CA 90033, United States of America
- USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA 90033, United States of America
- Department of Neurosurgery, Rancho Los Amigos National Rehabilitation Center, Downey, CA 90242, United States of America
| | - Zoran Nenadic
- Department of Biomedical Engineering, University of California Irvine (UCI), Irvine, CA 92697, United States of America
- Department of Electrical Engineering and Computer Science, UCI, Irvine, CA 92697, United States of America
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Sohn WJ, Wang PT, Kellis S, Andersen RA, Liu CY, Heydari P, Nenadic Z, Do AH. A Prototype of a Fully-Implantable Charge-Balanced Artificial Sensory Stimulator for Bi-directional Brain-Computer-Interface (BD-BCI). ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:3083-3085. [PMID: 33018656 DOI: 10.1109/embc44109.2020.9176718] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Bi-directional brain-computer interfaces (BD-BCI) to restore movement and sensation must achieve concurrent operation of recording and decoding of motor commands from the brain and stimulating the brain with somatosensory feedback. Previously we developed and validated a benchtop prototype of a fully implantable BCI system for motor decoding. Here, a prototype artificial sensory stimulator was integrated into the benchtop system to develop a prototype of a fully-implantable BD-BCI. The artificial sensory stimulator incorporates an active charge balancing mechanism based on pulse-width modulation to ensure safe stimulation for chronically interfaced electrodes to prevent damage to brain tissue and electrodes. The feasibility of the BD-BCI system's active charge balancing was tested in phantom brain tissue. With the charge-balancing, the removal of the residual charges on an electrode was evident. This is a critical milestone toward fully-implantable BD-BCI systems.
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Lim J, Wang PT, Shaw SJ, Armacost M, Gong H, Liu CY, Do AH, Heydari P, Nenadic Z. Pre-whitening and Null Projection as an Artifact Suppression Method for Electrocorticography Stimulation in Bi-Directional Brain Computer Interfaces. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:3493-3496. [PMID: 33018756 DOI: 10.1109/embc44109.2020.9175760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Electrocorticography (ECoG)-based bi-directional (BD) brain-computer interfaces (BCIs) are a forthcoming technology promising to help restore function to those with motor and sensory deficits. A major problem with this paradigm is that the cortical stimulation necessary to elicit artificial sensation creates strong electrical artifacts that can disrupt BCI operation by saturating recording amplifiers or obscuring useful neural signal. Even with state-of-the-art hardware artifact suppression methods, robust signal processing techniques are still required to suppress residual artifacts that are present at the digital back-end. Herein we demonstrate the effectiveness of a pre-whitening and null projection artifact suppression method using ECoG data recorded during a clinical neurostimulation procedure. Our method achieved a maximum artifact suppression of 21.49 dB and significantly increased the number of artifact-free frequencies in the frequency domain. This performance surpasses that of a more traditional independent component analysis methodology, while retaining a reduced complexity and increased computational efficiency.
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Pu H, Lim J, Kellis S, Liu CY, Andersen RA, Do AH, Heydari P, Nenadic Z. Optimal artifact suppression in simultaneous electrocorticography stimulation and recording for bi-directional brain-computer interface applications. J Neural Eng 2020; 17:026038. [PMID: 32208379 DOI: 10.1088/1741-2552/ab82ac] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
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.
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Affiliation(s)
- Haoran Pu
- Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, 92697, United States of America
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