Affiliation:
1. Department of Sports Medicine, Medical University of Lublin, 20-093 Lublin, Poland
Abstract
Surface electromyography (sEMG) is a technique for measuring and analyzing the electrical signals of muscle activity using electrodes placed on the skin’s surface. The aim of this paper was to outline the history of the development and use of surface electromyography in dentistry, to show where research and technical solutions relating to surface electromyography currently lie, and to make recommendations for further research. sEMG is a diagnostic technique that has found significant application in dentistry. The historical section discusses the evolution of sEMG methods and equipment, highlighting how technological advances have influenced the accuracy and applicability of this method in dentistry. The need for standardization of musculoskeletal testing methodology is highlighted and the needed increased technical capabilities of sEMG equipment and the ability to specify parameters (e.g., sampling rates, bandwidth). A higher sampling rate (the recommended may be 2000 Hz or higher in masticatory muscles) allows more accurate recording of changes in the signal, which is essential for accurate analysis of muscle function. Bandwidth is one of the key parameters in sEMG research. Bandwidth determines the range of frequencies effectively recorded by the sEMG system (the recommended frequency limits are usually between 20 Hz and 500 Hz in masticatory muscles). In addition, the increased technical capabilities of sEMG equipment and the ability to specify electromyographic parameters demonstrate the need for a detailed description of selected parameters in the methodological section. This is necessary to maintain the reproducibility of sEMG testing. More high-quality clinical trials are needed in the future.
Reference203 articles.
1. Konrad, P. (2005). The Abc of Emg—A Practical Introduction to Kinesiological Electromyography, Noraxon Inc.
2. Raez, M.B.I., Hussain, M.S., and Mohd-Yasin, F. (2006). Techniques of EMG Signal Analysis: Detection, Processing, Classification and Applications. Biol. Proced. Online, 8.
3. del Olmo, M., and Domingo, R. (2020). EMG Characterization and Processing in Production Engineering. Materials, 13.
4. Chrysafides, S.M., Bordes, S.J., and Sharma, S. (2023). StatPearls, StatPearls Publishing.
5. Ehrenwerth, J., Eisenkraft, J.B., and Berry, J.M. (2013). Anesthesia Equipment, W.B. Saunders. [2nd ed.].
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