2022, issue 1, p. 28-41

Received 13.06.2022; Revised 26.06.2022; Accepted 28.06.2022

Published 30.06.2022; First Online 03.08.2022

https://doi.org/10.34229/2707-451X.22.1.4

Previous  |  FULL TEXT (in Ukrainian)  |  Next

 

UDC 681.32+537.8

Magnetometric Investigations of Biomagnetic Signals: Magnetocardiography

Mykhailo Primin 1 * ORCID ID favicon Big,   Igor Nedayvoda 1 ORCID ID favicon Big

1 V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine, Kyiv

* Correspondence: This email address is being protected from spambots. You need JavaScript enabled to view it.

 

Introduction. Superconducting magnetometers based on SQUIDs (SQUID- Superconducting QUantum Interference Device) are currently used to register weak magnetic fields generated in various human organs and measured outside the body (in the environment). The creation of information technology, which is a set of methods and software tools combined into a technological chain that ensures registration, storage, pre-processing, analysis of measurement data and automatic diagnostic output, is an essential science-intensive component that determines the possibilities and success of the applied use of non-contact diagnostic systems of the human heart

The purpose. Article presents new algorithms for spatial analysis of cardiomagnetic signal measurement results. The algorithms are based on the inverse problem solution, when the magnetic field source is matched to the spatial distribution of the magnetic signal and the parameters and spatial configuration of the source are determined. A model of the cardiomagnetic source was used in the form of a system of current density vectors, which are distributed in a plane that is parallel to the measurement plane and crosses the volume of the heart.

Results. The inverse problem is solved using the apparatus of two-dimensional integral Fourier transformations. The data transformation algorithm allows to correctly take into account the design of the magnetic flux transformer (the dimensions of the pickup coils, their spatial location and the electrical connection scheme). Algorithm modifications have been developed for most of the known (implemented in existing magnetocardiographs) designs of magnetic flux transformers of the first and second order gradientometers. The operation of the algorithm is modeled on real data of magnetometric investigations of the human heart. Investigations have shown that the application of the proposed algorithms allows obtaining new information about the spatial configuration of the magnetic signal source in the human heart, which can be used in the future for the diagnosis of human heart diseases.

 

Keywords: magnetocardiography, inverse problem of magnetostatics, Fourier transform, SQUID gradientometer.

 

Cite as: Primin M., Nedayvoda I. Magnetometric Investigations of Biomagnetic Signals: Magnetocardiography. Cybernetics and Computer Technologies. 2022. 1. P. 28–41. (in Ukrainian) https://doi.org/10.34229/2707-451X.22.1.4

 

References

           1.     Clarke J., Braginski A.I. SQUID Handbook. Vol I. Berlin: Wiley-VCH 2006. Vol.II. Weinheim: Wiley-VCH. 2004. 634 р. https://doi.org/10.1002/3527603646

           2.     Weinstock H. SQUID Sensors: Fundamentals, Fabrication and Applications. NATO ASI Series, Series E: Applied Sciences. 1995. 329. 703 p. https://doi.org/10.1007/978-94-011-5674-5

           3.     Mansfield P. Snap-shot MRI. Les Prix Nobel, The Nobel Prizes 2003 Nobel Foundation. 2004. P. 266–283. https://doi.org/10.1002/anie.200460078

           4.     Vrba J. Multichannel SQUID biomagnetic systems. In: Weinstock H., editor. Applications of Superconductivity. Dordrecht: Kluwer-Academic. 2000. P. 61–138. http://doi.org/10.1007/978-94-017-0752-7_2

           5.     CTF MEG International Services LP. https://www.ctf.com/products (accessed: 03.05.2021)

           6.     Maslennikov Yu.V., Primin M.A., Slobodchikov V.Yu., Khanin V.V., Nedayvoda I.V., Krymov V.A., Okunev A.V., Moiseenko E.A., Beljaev A.V, Rybkin V.S., Tolcheev A.V., Gapelyuk A.V. The DC-SQUID-based magnetocardiographic systems for clinical use. Physics Procedia. 2012. 36. P. 88–93. https://doi.org/10.1016/j.phpro.2012.06.218

           7.     Primin M.A., Nedaivoda I.V., Maslennikov Yu.V., Gulyaev Yu.V. Software for the Magnetocardiographic Complex for the Early Diagnostics and Monitoring of Heart Diseases. J. Commun. Technol. Electron. 2010. 55. No.10. P. 1169–1186. https://doi.org/10.1134/S1064226910100116

           8.     Faley M.I., Dammers J., Maslennikov Y.V., Schneiderman J.F., Winkler D., Koshelets V.P., Shah N.J., Dunin-Borkowski R.E. High-Tc SQUID biomagnetometers. Supercond. Sci. Technol. 2017. 30. P. 083001. https://doi.org/10.1088/1361-6668/aa73ad

           9.     Faley M.I., Poppe U., Dunin-Borkowski R.E., Schiek M., Boers F., Chocholacs H., Dammers J., Eich E., Shah N.J., Ermakov A.B., Slobodchikov V.Yu., Maslennikov Yu.V., Koshelets V.P. High-Tc DC SQUIDs for Magnetoencephalography. IEEE Trans. on Appl. Supercond. 2013. 23. No. 3. P. 1600705. http://doi.org/10.1109/TASC.2012.2229094

       10.     Sheng D., Li S., Dural N., Romalis M.V. Subfemtotesla Scalar Atomic Magnetometry Using Multipass Cells. Phys. Rev. Lett. 2013. 110. P. 160802. https://doi.org/10.1103/PhysRevLett.110.160802

       11.     Nedayvoda I.V., Primin M.A., Vasylyev V.E., Voytovych I.D. Supersensitive Magnetocardiographic System for Early Identification and Monitoring of Heart Diseases (Software). УсиМ. 2005. 2. С. 43–56.

       12.     Chaikovsky I., Primin M., Nedayvoda I., Kazmirchuk A., Frolov Yu., Boreyko M., New metrics to asses the subtle changes of the heart electromagnetic field. in: Advanced Methods in Biomedical Signal Processing and Analysis, Editors: K.Pal, S.Ari, A.Bit, S.Bhattacharyya. Academic Press 2022, Paperback. ISBN: 9780323859554

       13.     Primin M.A., Maslennikov Yu.V., Nedayvoda I.V., Gulyaev Yu.V. Magnetocardiographic technology for studying the human heart. Biomedical radioelectronics. 2016. No. 2. P. 14–33. (in Russian)

       14.     Primin M., Nedayvoda I. Mathematical model and measurement algorithms for a dipole source location. Int. J. Applied Elektromagn. In. Mechanics. 1997. No. 8. P. 119–131.

       15.     Primin M., Nedayvoda I. Inverse problem solution algorithms in magnetocardiography: new analytical approaches and some results. Int. J.Applied Electromagn. Mechanics. 2009. 29 (2). P. 65–81. https://doi.org/10.3233/JAE-2009-1001

       16.     Korn G., Korn T. Handbook of mathematics for scientists and engineers. M.: Nauka, 1970. 720 p. (in Russian)

       17.     Primin M., Gumeniuk-Sychevskij V., Nedayvoda I. Mathematical models and algorithms of information conversion in spatial analysis of weak magnetic fields. Int. J. Applied Elektromagn. In. Materials .1994. No. 5. P. 311–319.

       18.     Roth B., Sepulveda N., Wikswo J.Jr. Using a magnetometer to image a two-dimensional current distribution. J. Appl. Phys.1989. 65. P. 361–372. https://doi.org/10.1063/1.342549

       19.     Voitovych I.D., Primin M.A., Sosnytskyy V.N. Application of SQUIDs for registration of biomagnetic signals. Low Temperature Physics. 2012. 38. P. 311–320. https://doi.org/10.1063/1.3699954

       20.     Chaikovsky I., Primin M., Nedayvoda I., Budnyk M. Magnetocardiography in Unshielded Setting: Heart Electrical Image Based on 2-D and 3-D Data in Comparison with Perfusion Image Based on PET Results-Clinical Cases. In: Coronary Artery Diseases, Edited by Illya Chaikovsky and Nataliia N. Sydorova. 2012. InTech, Croatia. P. 43–58. http://dx.doi.org/10.5772/30122

 

 

ISSN 2707-451X (Online)

ISSN 2707-4501 (Print)

Previous  |  FULL TEXT (in Ukrainian)  |  Next

 

 

 

© Website and Design. 2019-2022,

V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine,

National Academy of Sciences of Ukraine.