Time domain analysis on myoelectric activity of masseter muscles in resting and chewing conditions

• Published in: Network modeling and analysis in health informatics and bioinformatics (Wien) Vol. 9; no. 1; p. 18
• Main Authors: Arockia Sukanya, S., Kamalanand, K., Thayumanavan, B., Emmanuel, C., Rajnikanth, V.
• Format: Journal Article
• Language: English
• Published: Vienna Springer Vienna 01.12.2020; Springer Nature B.V
• Subjects: Abnormalities; Applications of Graph Theory and Complex Networks; Bioinformatics; Chewing; Computational Biology/Bioinformatics; Computer Science; Electrodes; Electromyography; Fast Fourier transformations; Food; Fourier transforms; Health Informatics; Jaw; Kurtosis; Masseter muscle; Mastication; Muscle fatigue; Muscles; Myoelectricity; Original Article; Parameters; Peak frequency; Personal computers; Physiology; Skewness; Statistics; Time domain analysis; Mastication; Electromyograms; Hjorth parameters; Masseter muscle; Fast Fourier transform; Surface electrodes
• DOI: 10.1007/s13721-020-0224-2
• ISSN: 2192-6662

Masseter is a type of muscle which involves in the process of chewing. Any disorder in the masseter muscle creates dysfunction of the entire mastication process and leads to neuromuscular problems. Electromyograms (EMGs) act as a diagnostic tool in detecting any abnormalities present in the nervous and muscular system. The objective of this work is to record and analyze the electrical activity of the masseter muscle of healthy subjects during resting and chewing conditions. In this work, the electrical activity of the masseter muscle was recorded form healthy volunteers of different age, using non invasive surface electrodes. The EMG signals are recorded from left as well as right sides in resting and chewing conditions. The characteristics of the EMG signals in resting and chewing conditions are analyzed using various statistical measures, Fast Fourier Transforms (FFT) and Hjorth parameters such as complexity, activity, and mobility. Results demonstrate that the EMG signals acquired at resting conditions of different subjects have equal peak frequencies in the FFT. However, there is a significant shift in the peak frequency of the EMG signals during chewing activity. Furthermore, it is observed that there are variations in both the Hjorth parameters as well as the statistical parameters of EMG signals recorded during resting and chewing conditions. Results show that there is a significant change in the electrical activity of masseter muscle in the resting and chewing conditions. This work appears to be of high clinical significance, since the electrical activity of masseter muscle can provide diagnostic information for the analysis of various diseases in the oral structures.