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Identification of Microrecording Artifacts with Wavelet Analysis and Convolutional Neural Network: An Image Recognition Approach Cover

Identification of Microrecording Artifacts with Wavelet Analysis and Convolutional Neural Network: An Image Recognition Approach

Measurement Science Review
Volume 19 (2019): Issue 5 (October 2019)
By: Ondřej Klempíř,  Radim Krupička,  Eduard Bakštein and  Robert Jech  
Open Access
|Oct 2019

Authors

Ondřej Klempíř

klempond@gmail.com

Department of Biomedical Informatics, Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno

Radim Krupička

Department of Biomedical Informatics, Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno

Eduard Bakštein

Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague
National Institute of Mental Health, Klecany

Robert Jech

Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine and General University Hospital, Charles University, Prague
DOI: https://doi.org/10.2478/msr-2019-0029 | Journal eISSN: 1335-8871
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Language: English
Page range: 222 - 231
Submitted on: Mar 20, 2019
|
Accepted on: Aug 30, 2019
|
Published on: Oct 7, 2019
Published by: Slovak Academy of Sciences, Institute of Measurement Science
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
Artifacts detection,
convolutional neural networks,
Parkinson’s disease,
deep brain stimulation,
microrecording,
wavelet analysis
Related subjects:
Engineering,
Electrical engineering,
Control engineering, metrology and testing

© 2019 Ondřej Klempíř, Radim Krupička, Eduard Bakštein, Robert Jech, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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