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Proceedings Paper

Quality improvement of diagnosis of the electromyography data based on statistical characteristics of the measured signals
Author(s): Karina G. Selivanova; Oleg G. Avrunin; Sergii M. Zlepko; Sergii O. Romanyuk; Natalia I. Zabolotna; Andrzej Kotyra; Paweł Komada; Saule Smailova
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Paper Abstract

Research and systematization of motor disorders, taking into account the clinical and neurophysiologic phenomena, are important and actual problem of neurology. The article describes a technique for decomposing surface electromyography (EMG), using Principal Component Analysis. The decomposition is achieved by a set of algorithms that uses a specially developed for analyze EMG. The accuracy was verified by calculation of Mahalanobis distance and Probability error.

Paper Details

Date Published: 28 September 2016
PDF: 7 pages
Proc. SPIE 10031, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2016, 100312R (28 September 2016); doi: 10.1117/12.2248953
Show Author Affiliations
Karina G. Selivanova, Kharkiv National Univ. of Radio Electronics (Ukraine)
Oleg G. Avrunin, Kharkiv National Univ. of Radio Electronics (Ukraine)
Sergii M. Zlepko, Vinnytsia National Technical Univ. (Ukraine)
Sergii O. Romanyuk, Vinnytsia National Technical Univ. (Ukraine)
Natalia I. Zabolotna, Vinnytsia National Technical Univ. (Ukraine)
Andrzej Kotyra, Lublin Univ. of Technology (Poland)
Paweł Komada, Lublin Univ. of Technology (Poland)
Saule Smailova, D. Serikbayev East Kazakhstan State Technical Univ. (Kazakhstan)


Published in SPIE Proceedings Vol. 10031:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2016
Ryszard S. Romaniuk, Editor(s)

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