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Makeyev O, Ye-Lin Y, Prats-Boluda G, Garcia-Casado J. Finite element method modeling to confirm the results of comprehensive optimization of the tripolar concentric ring electrode based on its finite dimensions model. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:7244-7247. [PMID: 34892770 DOI: 10.1109/embc46164.2021.9629784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Concentric ring electrodes are noninvasive and wearable sensors for electrophysiological measurement capable of estimating the surface Laplacian (second spatial derivative of surface potential) at each electrode. Significant progress has been made toward optimization of inter-ring distances (distances between the recording surfaces of the electrode), maximizing the accuracy of the surface Laplacian estimate based on the negligible dimensions model of the electrode. However, novel finite dimensions model offers comprehensive optimization including all of the electrode parameters simultaneously by including the radius of the central disc and the widths of the concentric rings into the model. Recently, such comprehensive optimization problem has been solved analytically for the tripolar electrode configuration. This study, for the first time, introduces a finite dimensions model based finite element method model (as opposed to the negligible dimensions model based one used in the past) to confirm the analytic results. Specifically, finite element method modeling results confirmed that previously proposed linearly increasing inter-ring distances and constant inter-ring distances configurations of tripolar concentric ring electrodes correspond to an almost two-fold and more than three-fold increases in relative and normalized maximum errors of Laplacian estimation when directly compared to the optimal tripolar concentric ring electrode configuration of the same size.Clinical Relevance- This study assesses and confirms the electrode configuration that maximizes the accuracy of the estimated Laplacian recorded via concentric ring electrodes. Therefore, it is potentially useful for designing future concentric ring electrodes for diagnostic purposes such as localization of epileptic foci.
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Makeyev O, Ye-Lin Y, Prats-Boluda G, Garcia-Casado J. Comprehensive Optimization of the Tripolar Concentric Ring Electrode Based on Its Finite Dimensions Model and Confirmed by Finite Element Method Modeling. SENSORS 2021; 21:s21175881. [PMID: 34502772 PMCID: PMC8434583 DOI: 10.3390/s21175881] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 08/13/2021] [Accepted: 08/28/2021] [Indexed: 11/16/2022]
Abstract
The optimization performed in this study is based on the finite dimensions model of the concentric ring electrode as opposed to the negligible dimensions model used in the past. This makes the optimization problem comprehensive, as all of the electrode parameters including, for the first time, the radius of the central disc and individual widths of concentric rings, are optimized simultaneously. The optimization criterion used is maximizing the accuracy of the surface Laplacian estimation, as the ability to estimate the Laplacian at each electrode constitutes primary biomedical significance of concentric ring electrodes. For tripolar concentric ring electrodes, the optimal configuration was compared to previously proposed linearly increasing inter-ring distances and constant inter-ring distances configurations of the same size and based on the same finite dimensions model. The obtained analytic results suggest that previously proposed configurations correspond to almost two-fold and more than three-fold increases in the Laplacian estimation error compared with the optimal configuration proposed in this study, respectively. These analytic results are confirmed using finite element method modeling, which was adapted to the finite dimensions model of the concentric ring electrode for the first time. Moreover, the finite element method modeling results suggest that optimal electrode configuration may also offer improved sensitivity and spatial resolution.
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Affiliation(s)
- Oleksandr Makeyev
- School of STEM, Diné College, Tsaile, AZ 86556, USA
- Correspondence: ; Tel.: +1-928-724-6960
| | - Yiyao Ye-Lin
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, 46022 Valencia, Spain; (Y.Y.-L.); (G.P.-B.); (J.G.-C.)
| | - Gema Prats-Boluda
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, 46022 Valencia, Spain; (Y.Y.-L.); (G.P.-B.); (J.G.-C.)
| | - Javier Garcia-Casado
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, 46022 Valencia, Spain; (Y.Y.-L.); (G.P.-B.); (J.G.-C.)
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Huggins JE, Guger C, Aarnoutse E, Allison B, Anderson CW, Bedrick S, Besio W, Chavarriaga R, Collinger JL, Do AH, Herff C, Hohmann M, Kinsella M, Lee K, Lotte F, Müller-Putz G, Nijholt A, Pels E, Peters B, Putze F, Rupp R, Schalk G, Scott S, Tangermann M, Tubig P, Zander T. Workshops of the Seventh International Brain-Computer Interface Meeting: Not Getting Lost in Translation. BRAIN-COMPUTER INTERFACES 2019; 6:71-101. [PMID: 33033729 PMCID: PMC7539697 DOI: 10.1080/2326263x.2019.1697163] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 10/30/2019] [Indexed: 12/11/2022]
Abstract
The Seventh International Brain-Computer Interface (BCI) Meeting was held May 21-25th, 2018 at the Asilomar Conference Grounds, Pacific Grove, California, United States. The interactive nature of this conference was embodied by 25 workshops covering topics in BCI (also called brain-machine interface) research. Workshops covered foundational topics such as hardware development and signal analysis algorithms, new and imaginative topics such as BCI for virtual reality and multi-brain BCIs, and translational topics such as clinical applications and ethical assumptions of BCI development. BCI research is expanding in the diversity of applications and populations for whom those applications are being developed. BCI applications are moving toward clinical readiness as researchers struggle with the practical considerations to make sure that BCI translational efforts will be successful. This paper summarizes each workshop, providing an overview of the topic of discussion, references for additional information, and identifying future issues for research and development that resulted from the interactions and discussion at the workshop.
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Affiliation(s)
- Jane E Huggins
- Department of Physical Medicine and Rehabilitation, Department of Biomedical Engineering, Neuroscience Graduate Program, University of Michigan, Ann Arbor, Michigan, United States, 325 East Eisenhower, Room 3017; Ann Arbor, Michigan 48108-5744
| | - Christoph Guger
- g.tec medical engineering GmbH/Guger Technologies OG, Austria, Sierningstrasse 14, 4521 Schiedlberg, Austria
| | - Erik Aarnoutse
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Brendan Allison
- Dept. of Cognitive Science, Mail Code 0515, University of California at San Diego, La Jolla, United States
| | - Charles W Anderson
- Department of Computer Science, Molecular, Cellular and Integrative Neurosience Program, Colorado State University, Fort Collins, CO 80523
| | - Steven Bedrick
- Center for Spoken Language Understanding, Oregon Health & Science University, Portland, OR 97239
| | - Walter Besio
- Department of Electrical, Computer, & Biomedical Engineering and Interdisciplinary Neuroscience Program, University of Rhode Island, Kingston, Rhode Island, USA, CREmedical Corp. Kingston, Rhode Island, USA
| | - Ricardo Chavarriaga
- Defitech Chair in Brain-Machine Interface (CNBI), Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne - EPFL, Switzerland
| | - Jennifer L Collinger
- University of Pittsburgh, Department of Physical Medicine and Rehabilitation, VA Pittsburgh Healthcare System, Department of Veterans Affairs, 3520 5th Ave, Pittsburgh, PA, 15213
| | - An H Do
- UC Irvine Brain Computer Interface Lab, Department of Neurology, University of California, Irvine
| | - Christian Herff
- School of Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Matthias Hohmann
- Max Planck Institute for Intelligent Systems, Department for Empirical Inference, Max-Planck-Ring 4, 72074 Tübingen, Germany
| | - Michelle Kinsella
- Oregon Health & Science University, Institute on Development & Disability, 707 SW Gaines St, #1290, Portland, OR 97239
| | - Kyuhwa Lee
- Swiss Federal Institute of Technology in Lausanne-EPFL
| | - Fabien Lotte
- Inria Bordeaux Sud-Ouest, LaBRI (Univ. Bordeaux/CNRS/Bordeaux INP), 200 avenue de la vieille tour, 33405, Talence Cedex, France
| | | | - Anton Nijholt
- Faculty EEMCS, University of Twente, Enschede, The Netherlands
| | - Elmar Pels
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Betts Peters
- Oregon Health & Science University, Institute on Development & Disability, 707 SW Gaines St, #1290, Portland, OR 97239
| | - Felix Putze
- University of Bremen, Germany, Cognitive Systems Lab, University of Bremen, Enrique-Schmidt-Straße 5 (Cartesium), 28359 Bremen
| | - Rüdiger Rupp
- Spinal Cord Injury Center, Heidelberg University Hospital
| | - Gerwin Schalk
- National Center for Adaptive Neurotechnologies, Wadsworth Center, NYS Dept. of Health, Dept. of Neurology, Albany Medical College, Dept. of Biomed. Sci., State Univ. of New York at Albany, Center for Medical Sciences 2003, 150 New Scotland Avenue, Albany, New York 12208
| | - Stephanie Scott
- Department of Media Communications, Colorado State University, Fort Collins, CO 80523
| | - Michael Tangermann
- Brain State Decoding Lab, Cluster of Excellence BrainLinks-BrainTools, Computer Science Dept., University of Freiburg, Germany, Autonomous Intelligent Systems Lab, Computer Science Dept., University of Freiburg, Germany
| | - Paul Tubig
- Department of Philosophy, Center for Neurotechnology, University of Washington, Savery Hall, Room 361, Seattle, WA 98195
| | - Thorsten Zander
- Team PhyPA, Biological Psychology and Neuroergonomics, Technische Universität Berlin, Berlin, Germany, 7 Zander Laboratories B.V., Amsterdam, The Netherlands
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