Comparative analysis of the accuracy of classification of electromyographic signals by second-order difference graphs for differentiating types of pain in the lower back

Authors

  • T. Zhemchuzhkina Kharkiv National University of Radio Electronics Kharkiv

DOI:

https://doi.org/10.31649/1681-7893-2025-49-1-217-226

Keywords:

chaos theory, classification, classification ensemble, electromyography, k-nearest neighbors, low back pain, neural network, second order difference plot

Abstract

Low back pain is the main cause of disability. From the pathophysiological point of view, there are functional and dysfunctional types of pain. Functional pain has a specific organic cause in the form of direct tissue damage and activation of peripheral pain receptors or damage that affects the somatosensory system. Dysfunctional pain is formed as a result of neurodynamic disorders in the central nervous system. As a rule, when examining patients with dysfunctional pain, it is not possible to identify organic diseases that could explain the occurrence of the pain syndrome. This work is devoted to studying the possibilities of classification methods for differentiating functional and dysfunctional pain based on the second-order difference plot of the electromyographic signal. Electromyographic signals have extremely complex characteristics that resemble chaotic processes in nature. The second-order difference plot allows to analyze the degree of variability or chaos in a set of electromyographic data.

Author Biography

T. Zhemchuzhkina, Kharkiv National University of Radio Electronics Kharkiv

Ph.D., Associate Professor

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Published

2025-06-18

How to Cite

[1]
T. Zhemchuzhkina, “Comparative analysis of the accuracy of classification of electromyographic signals by second-order difference graphs for differentiating types of pain in the lower back”, Опт-ел. інф-енерг. техн., vol. 49, no. 1, pp. 217–226, Jun. 2025.

Issue

Vol. 49 No. 1 (2025)

Section

Biomedical Optical And Electronic Systems And Devices

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