Power Spectral Density, Higuchi's Fractal Dimension and Detrended Fluctuation Analysis of sEMG at Varying Weights

Our muscle cells produce rhythmical potentials that get totalized as millions of cells discharge simultaneously and represent as a waveform, the recording of this waveform is known as Electromyogram (EMG). The device is used this recording is called Electromyograph and process of this recording is known as Electromyography. The primary objective of this work is to see the changes in muscles dynamics when a person lifts various weights. This study used power spectral density (PSD) for linear analysis of surface EMG (sEMG) signal and total powers of the muscles were evaluated. This study used HFD (Higuchi's Fractal Dimension) analysis to estimate fractal dimension of the sEMG signal during biceps and forearm muscles activities. Using Detrended Fluctuation Analysis (DFA) nonlinear analysis the change in the pattern of the sEMG signals was observed with varying weights. Surface electrodes with required signal collection circuitry were used for the experiments, and signal data was acquired using a laptop and processed using MATLAB 2013 platform. The signal was also subjected to frequency domain analysis to measure muscle power at varying weights conditions. The fractal dimension measured varies depending on the applied weights. The investigation of the nonlinear nature of the sEMG signal at various weight situations might yield substantial results as time-based quantitative monitoring of muscle durability and regeneration.