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9 April 2020 The recurrence plot analysis in the processing of experimental biomedical data
Anastasiya Runnova, Anton Selskii, Maksim Zhuravlev, Elizaveta Emelyanova, Elena Selskaya
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Proceedings Volume 11459, Saratov Fall Meeting 2019: Computations and Data Analysis: from Nanoscale Tools to Brain Functions; 114590F (2020) https://doi.org/10.1117/12.2564365
Event: Saratov Fall Meeting 2019: VII International Symposium on Optics and Biophotonics, 2019, Saratov, Russian Federation
Abstract
In this article, we proposed a method for identifying the individual characteristics of motor activity based on recurrence analysis as applied to encepholography of the human brain. The analysis was carried out according to the real and imaginary (for the MEG only by imaginary) movements of the subjects and was compared with the background recording when the subject was at rest. This approach allows us to identify channels for each subject in which the frequency increases at the moment of motor activity and / or a stable pattern is formed that corresponds to this movement. The proposed method has a large number of applied applications in medicine and neurophysiology.
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Anastasiya Runnova, Anton Selskii, Maksim Zhuravlev, Elizaveta Emelyanova, and Elena Selskaya "The recurrence plot analysis in the processing of experimental biomedical data", Proc. SPIE 11459, Saratov Fall Meeting 2019: Computations and Data Analysis: from Nanoscale Tools to Brain Functions, 114590F (9 April 2020); https://doi.org/10.1117/12.2564365
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KEYWORDS
Electroencephalography
Brain
Magnetoencephalography
Visualization
Motion analysis
Biological research
Signal processing
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