Detecting nonlinearity of action surface EMG signal

The action surface EMG (ASEMG) signal contains the electrical properties of limb muscle contraction that undergo many complex transitions in limb different movement states; however, because of the small data nature of this kind signal, it is not clear whether its essence is stochastic or deterministic nonlinear (even chaotic). In this Letter, we show for the first time that ASEMG has deterministic nonlinear character by using the surrogate data method. Furthermore, we study the nonlinear dynamic features of ASEMG by computing its correlation dimension and applying correlation dimension as test statistics. These results indicate that ASEMG is a high-dimension nonlinear signal (even chaotic). In addition, this Letter improves the surrogate data method based on Fourier transform (FT) algorithm to avoid limitations of the previous FT algorithm.