Математична модель процесу поширення електричного потенціалу в тканинах поля хірургічного втручання та метод її ідентифікації на основі онтологічного підходу

• Дата: 2026
• Автори: Дивак, А.М., Мельник, А.М.
• Формат: Стаття
• Мова: Українська
• Опубліковано: Vinnytsia National Technical University 2026
• Теми: інтервальна модель; поворотний гортанний нерв; інтраопераційний моніторинг; методи ідентифікації; онтологія; інформаційна технологія
• Онлайн доступ: https://oeipt.vntu.edu.ua/index.php/oeipt/article/view/795
• Назва журналу: Optoelectronic Information-Power Technologies

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.