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JOURNALS // Matematicheskaya Biologiya i Bioinformatika // Archive

Mat. Biolog. Bioinform., 2018 Volume 13, Issue 2, Pages 480–489 (Mi mbb350)

This article is cited in 5 papers

Information and Computer Technologies in Biology and Medicine

Reconstruction of the human hand functional structure based on a magnetomyogram

M. N. Ustinina, S. D. Rykunova, M. A. Polikarpovb, A. Y. Yurenyabc, S. P. Naurzakovb, A. P. Grebenkinb, V. Ya. Panchenkobc

a Keldysh Institute of Applied Mathematics RAS, Moscow, Russian Federation
b National Research Center “Kurchatov Institute”, Moscow, Russian Federation
c Faculty of Physics, Lomonosov Moscow State University, Moscow, Russian Federation

Abstract: The new method of magnetomyography data analysis is proposed. The method is based on the Fourier transform of prolonged time series and on the massive solution of the inverse problem for all spectral components. For the method testing the following experiment was proposed. The subject clenched and relaxed the hand for five minutes, holding the handle, fixed on the table. Magnetomyograms were registered near the hand using the 7-channel SQUID-magnetometer based on the axial second-order gradiometers. The subject and experimental setup were placed inside a thick-walled aluminum camera, designed for shielding from an alternating electromagnetic field. No shielding from static magnetic field was used. Magnetomyograms with amplitude 20 picoTesla were registered in broad frequency band (up to 500 Hz), signal to noise ratio was more than 20. After filtering and extracting of clench/relax periods two synthetic 135 seconds myograms were formed. The multichannel spectra were calculated, and the functional tomograms were estimated. In case of the relaxed hand, no significant object was reconstructed. In case of the clenched hand, the 3D-object was extracted, representing the functional structure of the muscles, tensed in this experiment. The method can be used for diagnostics and study of the human muscle system.

Key words: magnetomyography, Fourier transform, frequency-pattern data analysis, inverse problem, functional tomography.

UDC: 57.085+611.976+51-76

Received 02.11.2018, Published 09.12.2018

DOI: 10.17537/2018.13.480



© Steklov Math. Inst. of RAS, 2024