Performance Assessment of Jaw Muscle Electromyography in the Detection of Temporomandibular Joint Disorder

Temporomandibular Joint Disorder (TMD), one of the most chronic muscular disorders affecting adults and adolescents whose signs and symptoms are complex. It is estimated that about 60% to 70% of the population has at least one symptom. Although it is prevalent in the general population, females are more prone to this condition. A simple electromyography test is commonly used to visualize and diagnose jaw muscles disorders such as TMD. In this study, the researchers used the wavelet decomposition technique to denoise the surface electromyographic (EMG) signal and extract the various features of the same. They were able to use the classification models to extract the results. After testing the model optimization features, the output values indicated when it came to TMD detection, the Adaboost model outperformed the other techniques. The null hypothesis is disproved by data analysis, demonstrating that there is a significant difference between the EMG activity of the control and study groups.