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 diff erent movement states; however, because of the small data nature of this ki nd signal, it is not clear whether its essence is stochastic or determinist ic nonlinear seven chaotic). In this Letter, we show for the first time tha t ASEMG has deterministic nonlinear character by using the surrogate data m ethod. Furthermore, we study the nonlinear dynamic features of ASEMG by com puting its correlation dimension and applying correlation dimension as test statistics. These results indicate that ASEMG is a high-dimension nonlinea r signal (even chaotic). In addition, this Letter improves the surrogate da ta method based on Fourier transform (FT) algorithm to avoid limitations of the previous FT algorithm. (C) 2001 Elsevier Science B.V. All rights reser ved.