A comprehensive nonlinear analysis of electromyogram

To test whether electromyogram (EMG) is nonlinear deterministic signal or just random noise, we comprehensively analyze four EMGs of an adult woman. At first, we calculate the correlation time, L-Z complexity, approximate entropy (ApEn), maximum Lyapunov exponent (Ly₁) and correlation dimension (D_corr) of each EMG data and its ten surrogate data. We find that all the results are quite different between each original EMG and its ten surrogate data, i.e. EMG is not a linear random noise, but a nonlinear deterministic signal (though it does not like a low dimensional chaos). EMG is also assessed with recurrence plot analysis (RPA), iterated function system (FS) clumpiness test, singular-value decomposition, and Pearson product-moment correlation coefficient (Pearson´s correlation). All the results of these assessments show that EMG is different from noise. Thus we conclude that EMG is a signal of high dimensional (D_corr range from 4 to 6) chaos.