Towards classification of patients based on surface EMG data of temporomandibular joint muscles using self-organising maps

Mateusz Troka; Wiktoria Wojnicz; Katarzyna Szepietowska; Marek Podlasiński; Sebastian Walerzak; Konrad Walerzak; Izabela Lubowiecka

doi:10.1016/j.bspc.2021.103322

Towards classification of patients based on surface EMG data of temporomandibular joint muscles using self-organising maps

Abstrakt

The study considers the need for an effective method of classification of patients with a temporomandibular joint disorder (TMD). The self-organising map method (SOM) was applied to group patients and used together with the cross-correlation approach to interpret the processed (rectified and smoothed by using root mean square (RMS) algorithm) surface electromyography signal (sEMG) obtained from testing the muscles (two temporal muscles and two masseters) of the temporomandibular joint (TMJ) during selected jaw movements. SOM’s Unified distance matrix (U-matrix) maps consist of formed clusters that correspond to similarities in input datasets. The results showed that SOM was able to encode muscular responses and create clusters. Information about the level of similarity between the activity of right, left, ipsilateral, and contralateral pairs of muscles was provided by intra cross-correlation coefficient (CC). A low intra CC value may indicate instability of the TMJ function. Information about the level of similarity between the sEMG signals of the same muscles tested in two different patients was provided by inter CC. SOM analysis can be used to interpret the activation of muscular systems, and by comparing the results of different individuals also to identify their TMJ health. Using the cross-correlation approach, one can find similarities in the sEMG data of different patients that can be used to provide clinically useful information. Such findings could be used to improve the clinical diagnosis of TMD and assess muscle activity during treatment.

Cytowania

1 2

CrossRef
0

Web of Science
1 1

Scopus

Autorzy (7)

Mateusz Troka
Wiktoria Wojnicz dr hab. inż.
Katarzyna Szepietowska dr inż.
Marek Podlasiński
- NZOZ Centrum Leczenia Wad Zgryzu
Sebastian Walerzak
- NZOZ Centrum Leczenia Wad Zgryzu
Konrad Walerzak
- NZOZ Centrum Leczenia Wad Zgryzu
Izabela Lubowiecka dr hab. inż.

Cytuj jako

Pełna treść

pobierz publikację

pobrano 89 razy

Wersja publikacji: Accepted albo Published Version
DOI:: Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1016/j.bspc.2021.103322
Licencja: otwiera się w nowej karcie

Słowa kluczowe

Informacje szczegółowe

Kategoria:

Publikacja w czasopiśmie

Typ:

artykuły w czasopismach

Opublikowano w:

Biomedical Signal Processing and Control nr 72,
ISSN: 1746-8094

Język:

angielski

Rok wydania:

2022

Opis bibliograficzny:

Troka M., Wojnicz W., Szepietowska K., Podlasiński M., Walerzak S., Walerzak K., Lubowiecka I.: Towards classification of patients based on surface EMG data of temporomandibular joint muscles using self-organising maps// Biomedical Signal Processing and Control -Vol. 72,iss. Part B (2022), s.103322-

DOI: