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.
Citation:
M. N. Ustinin, S. D. Rykunov, M. A. Polikarpov, A. Y. Yurenya, S. P. Naurzakov, A. P. Grebenkin, V. Ya. Panchenko, “Reconstruction of the human hand functional structure based on a magnetomyogram”, Mat. Biolog. Bioinform., 13:2 (2018), 480–489
\Bibitem{UstRykPol18}
\by M.~N.~Ustinin, S.~D.~Rykunov, M.~A.~Polikarpov, A.~Y.~Yurenya, S.~P.~Naurzakov, A.~P.~Grebenkin, V.~Ya.~Panchenko
\paper Reconstruction of the human hand functional structure based on a magnetomyogram
\jour Mat. Biolog. Bioinform.
\yr 2018
\vol 13
\issue 2
\pages 480--489
\mathnet{http://mi.mathnet.ru/mbb350}
\crossref{https://doi.org/10.17537/2018.13.480}
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This publication is cited in the following 6 articles:
Yutong Wei, Yan Chen, Chaofeng Ye, “Neuromuscular disease auxiliary diagnosis using a portable magnetomyographic system”, Physiol. Meas., 45:9 (2024), 095001
S. D. Rykunov, A. I. Boyko, M. N. Ustinin, “Reconstruction of the Electrical Structure of the Human Body Using Spectral Functional Tomography”, Pattern Recognit. Image Anal., 33:4 (2023), 1315
J. Marquetand, T. Middelmann, J. Dax, S. Baek, D. Sometti, A. Grimm, H. Lerche, P. Martin, C. Kronlage, M. Siegel, Ch. Braun, Ph. Broser, “Optically pumped magnetometers reveal fasciculations non-invasively”, Clin. Neurophysiol., 132:10 (2021), 2681–2684
Zuo S., Schmalz J., Ozden M.-O., Gerken M., Su J., Niekiel F., Lofink F., Nazarpour K., Heidari H., “Ultrasensitive Magnetoelectric Sensing System For Pico-Tesla Magnetomyography”, IEEE Trans. Biomed. Circuits Syst., 14:5 (2020), 971–984
Grushko S., Spurny T., Cerny M., “Control Methods For Transradial Prostheses Based on Remnant Muscle Activity and Its Relationship With Proprioceptive Feedback”, Sensors, 20:17 (2020), 4883
Zuo S., Heidari H., Farina D., Nazarpour K., “Miniaturized Magnetic Sensors For Implantable Magnetomyography”, Adv. Mater. Technol., 5:6 (2020), 2000185
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