Using Mechanomyograms for Estimating Median Frequency and Root Mean Square of Electromyograms With Hybrid Deep Neural Network and CatBoost Model

• Published in: IEEE access Vol. 12; pp. 190629 - 190639
• Main Authors: Liu, Shing-Hong, Chen, Wenxi, Chang, Kang-Ming, Pan, Kuo-Li
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accelerometers; Artificial neural networks; Correlation coefficients; Electrodes; Electromyogram; Electromyography; Fatigue; Frequency measurement; hybrid deep neural network; Kurtosis; mechanomyogram; median frequency; Motors; Muscle function; Muscles; Muscular function; Neural networks; root mean square; Skin; Urban areas

The aim of this study is to estimate the median frequency (MDF) and root mean square (RMS) of surface electromyogram (sEMG) signal using a hybrid deep neural network (DNN) and CatBoost model from mechanomyogram (MMG) signal as a simple alternative approach. sEMG is measured from the skin over muscle...