Mathematical model of the progress of electric potential propagation in tissues of the field of surgical intervention and method of its identification based on the ontological approach

Authors

  • A.M. Dyvak Western Ukrainian National University
  • A.M. Melnyk Western Ukrainian National University

DOI:

https://doi.org/10.31649/1681-7893-2025-50-2-40-53

Keywords:

interval model, recurrent laryngeal nerve, intraoperative monitoring, identification methods, ontology, information technology

Abstract

The article is devoted to the development and experimental investigation of an information technology for intraoperative neuromonitoring of the recurrent laryngeal nerve, aimed at reducing the risk of its intraoperative injury during surgical interventions on the thyroid and parathyroid glands. The proposed approach is based on a combination of ontological representation of the domain, interval mathematical modeling of electric potential propagation in the tissues of the surgical field, and intelligent analysis methods of intraoperative signals. For the first time, an interval mathematical model of electric potential propagation in the tissues of a surgical wound during stimulation by pulsed electric current and the formation of a vocal cord response in the form of an acoustic signal has been developed. Unlike existing models, it represents the interval distance from the stimulation point to the recurrent laryngeal nerve as a function of the acoustic signal amplitude and the amplitude of its main spectral component, thereby reducing the risk of recurrent laryngeal nerve damage during thyroid surgery. Furthermore, for the first time, a method for identifying the interval mathematical model of electric potential propagation in surgical wound tissues and the formation of the vocal cord response in the form of an acoustic signal has been proposed. In contrast to existing approaches, the method is based on a combination of interval data analysis and an ontological approach, which together reduce the time required to adapt the model to the specific tissue characteristics of an individual patient and enable its use within a hardware–software complex to minimize the risk of recurrent laryngeal nerve injury.

Author Biographies

A.M. Dyvak, Western Ukrainian National University

аспірант

A.M. Melnyk, Western Ukrainian National University

д.т.н., професор

References

Shidlovskyi, Volodymyr O., Oleksandr V. Shidlovskyi, Andrii M. Dyvak, Ihor I. Morozovych, and Volodymyr M. Pryvrotskyy. “Evaluation of Methods for Identifying and Monitoring Laryngeal Nerves.” Clinical Endocrinology and Endocrine Surgery 1 (2025): 27–34. https://doi.org/10.30978/CEES-2025-1-27

Shidlovskyi, Volodymyr O., Oleksandr V. Shidlovskyi, Andrii M. Dyvak, Volodymyr M. Pryvrotskyi, and Ihor I. Morozovych. “Identification and Monitoring of Laryngeal Nerves: Technologies and Problems. Review.” Clinical Endocrinology and Endocrine Surgery 1 (2024): 56–64. https://doi.org/10.30978/CEES-2024-1-56

Dyvak, Mykola, Vasyl Tymets, and Andrii Dyvak. “Multifunctional Stimulation Unit of the Recurrent Laryngeal Nerve for Its Identification.” Optoelectronic Information and Energy Technologies 38, no. 2 (2020): 90–99. https://doi.org/10.31649/1681-7893-2019-38-2-90-99

Dyvak, Mykola P., Andrii V. Pukas, Vasyl I. Tymets, and Andrii M. Dyvak. Method for Identifying the Laryngeal Nerve among Other Tissues of the Surgical Wound during Thyroid Surgery. Ukrainian Utility Model Patent No. 124989, April 25, 2018.

Dyvak, Mykola, Nataliia Kasatkina, Andrii Pukas, and Nataliia Padletska. “Spectral Analysis of the Information Signal in the Task of Identifying the Recurrent Laryngeal Nerve in Thyroid Surgery.” Przegląd Elektrotechniczny 89 (2013): 275–277.

Dyvak, Mykola, Oleksandr Kozak, and Andrii Pukas. “Interval Model for Identification of Laryngeal Nerves.” Przegląd Elektrotechniczny 86 (2010): 139–140.

Dyvak, Mykola, Andrii Pukas, Ihor Oliynyk, and Andrii Melnyk. “Selection of the ‘Saturated’ Block from an Interval System of Linear Algebraic Equations for Recurrent Laryngeal Nerve Identification.” In Proceedings of the 2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP), 444–448. Lviv, Ukraine, August 21–25, 2018. New York: IEEE.

Dyvak, Mykola, and Nataliia Porplytsya. “Formation and Identification of a Model for Recurrent Laryngeal Nerve Localization during Surgery on Neck Organs.” In Advances in Intelligent Systems and Computing III, edited by Mykola Dyvak, vol. 871, 391–404. Cham, Switzerland: Springer, 2019.

Porplytsya, Nataliia, Mykola Dyvak, Ivan Spivak, and Ihor Voytyuk. “Mathematical and Algorithmic Foundations for Implementation of the Method for Structure Identification of Interval Difference Operator Based on Functioning of Bee Colony.” In Proceedings of the 13th International Conference on the Experience of Designing and Application of CAD Systems in Microelectronics, 196–199. Lviv, Ukraine, February 24–27, 2015. New York: IEEE.

Husson, Raoul. Étude des phénomènes physiologiques et acoustiques fondamentaux de la voix chantée. Paris, 1952.

Husson, Raoul. Physiologie de la phonation. Paris: Masson, 1962.

Malcharek, Michael, and Hans J. Priebe. “Anesthesia and IONM.” In Intraoperative Neuromonitoring: Fundamentals, Possibilities, Limitations, 143–157. Cham, Switzerland: Springer, 2024.

Valenzuela-Fuenzalida, Juan J., Victor Baeza-Garrido, María F. Navia-Ramírez, Cristian Cariseo-Ávila, Andrés Bruna-Mejías, Álvaro Becerra-Farfan, Esteban Lopez, Marco Orellana Donoso, and Waldo Loyola-Sepulveda. “Systematic Review and Meta-Analysis: Recurrent Laryngeal Nerve Variants and Their Implication in Surgery and Neck Pathologies Using the Anatomical Quality Assurance (AQUA) Checklist.” Life 13 (2023): 1077.

Brunet, Alexandre, Albert Rovira, Marc Quer, Antonio Sanabria, Orlando Guntinas-Lichius, Mark E. Zafereo, Dominique M. Hartl, Ana Coca-Pelaz, Ashok R. Shaha, Jean-Pierre Marie, et al. “Recurrent Laryngeal Nerve Intraoperative Neuromonitoring Indications in Non-Thyroid and Non-Parathyroid Surgery.” Journal of Clinical Medicine 13 (2024): 2221.

Thomas, Alexander M., Dima K. Fahim, and John M. Gemechu. “Anatomical Variations of the Recurrent Laryngeal Nerve and Implications for Injury Prevention during Surgical Procedures of the Neck.” Diagnostics 10 (2020): 670.

Gumus, Sercan, Cagri Yuksel, Hakan Pulat, Cengiz Akyuz, and Mehmet O. Gul. “Inferior-to-Superior Dissection for Recurrent Laryngeal Nerve Identification in Redo Thyroid Surgery: Enhanced Safety and Reduced Injuries.” Journal of Clinical Medicine 13 (2024): 7364.

Tabriz, Nima, Sebastian Muehlbeyer, Dietmar Weyhe, and Volker Uslar. “Risk Factors for Recurrent Laryngeal Nerve Palsy in Thyroid Surgery: A Single-Center Experience of 1147 Procedures with Intermittent Intraoperative Neuromonitoring.” Journal of Personalized Medicine 14 (2024): 714.

Mykola Dyvak, Andriy Melnyk, Artur Rot, Marcin Hernes, Andriy Pukas, “Ontology of mathematical modelling based on interval data,” Complexity, vol. 2022, Article ID 8062969, 24 pages, 2022.

A. Melnyk, I. Shcherbiak, R. Shevchuk, A. Shevchuk, O. Huhul and Y. Franko, “Software Architecture for Mathematical Modelling Based on Interval and Ontology Approach,” 2022 12th International Conference on Advanced Computer Information Technologies (ACIT), Ruzomberok, Slovakia, 2022, pp. 101 - 105, doi: https://doi.org/10.1109/ACIT54803.2022.9913108

Dyvak, M., Melnyk, A., Mazepa, S., Stetsko, M. ( 2022 ). An Ontological Approach to Detecting Irrelevant and Unreliable Information on Web-Resources and Social Networks. In: Klymash, M., Beshley, M., Luntovskyy, A. (eds) Future Intent-Based Networking. Lecture Notes in Electrical Engineering, vol 831. Springer, Cham. https://doi.org/10.1007/978-3-030-92435-5_27.

Kryvonosov, V., Avrunin, O., Sander, S., Pavlov, V., etc. (2023). A usage of the impedance method for detecting circulatory disorders to determine the degree of limb ischemia. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 13(4), 5–10.

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Published

2026-01-12

How to Cite

[1]
A. Dyvak and A. Melnyk, “Mathematical model of the progress of electric potential propagation in tissues of the field of surgical intervention and method of its identification based on the ontological approach”, Опт-ел. інф-енерг. техн., vol. 50, no. 2, pp. 40–53, Jan. 2026.

Issue

Vol. 50 No. 2 (2025)

Section

OptoElectronic/Digital Methods and Systems for Image/Signal Processing

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