Algorithm and Hardware for Automatic Adjustment of Electric Signal to Identify the Recurrent Laryngeal Nerve

The paper represents the results of developing algorithm and hardware tools for identifying the location of the recurrent laryngeal nerve (RLN). These tools automatically adjust the parameters of the electrical signal to stimulate the tissues of the surgical wound in the most effective way. The introduction of an additional function of automatic adjustment of electrical signal parameters for tissue irritation of a surgical wound is ensured by the use of more productive hardware based on Rasberry Pi-4. The study of the proposed algorithm’s implementation time for setting the pulse signal’s optimal frequency was carried out. It has been established that linear frequency sampling is time-consuming and does not provide an opportunity to obtain optimal signal tuning during a single inhalation or exhalation by the patient during surgery on a surgical wound. It is proposed to implement the algorithm using known Binary Search algorithms. The estimation of the time of adjustment of the frequency of the impulse signal of the tissue stimulation of the surgical wound was carried out with an orientation to the worst case. It has been established that this approach provides sufficient time frames for adjusting the parameters of the electrical stimulation signal within the time frame of inhalation or exhalation by the patient. Further research is aimed at testing the proposed solutions in clinical settings.