Chaos, Fractal and Recurrence Quantification Analysis of Surface Electromyography in Muscular Dystrophy

Elio Conte, Ken Ware, Riccardo Marvulli, Giancarlo Ianieri, Marisa Megna, Sergio Conte, Leonardo Mendolicchio, Enrico Pierangeli
2015 World Journal of Neuroscience  
We analyze muscular dystrophy recorded by sEMG and use standard methodologies and nonlinear chaotic methods here including the RQA. We reach sufficient evidence that the sEMG signal contains a large chaotic component. We have estimated the correlation dimension (fractal measure), the largest Lyapunov exponent, the LZ complexity and the %Rec and %Det of the RQA demonstrating that such indexes are able to detect the presence of repetitive hidden patterns in sEMG which, in turn, senses the level
more » ... senses the level of MU synchronization within the muscle. The results give also an interesting methodological indication in the sense that it evidences the manner in which nonlinear methods and RQA must be arranged and applied in clinical routine in order to obtain results of clinical interest. We have studied the muscular dystrophy and evidence that the continuous regime of chaotic transitions that we have in muscular mechanisms may benefit in this pathology by the use of the NPT treatment that we have considered in detail in our previous publications.
doi:10.4236/wjns.2015.54022 fatcat:facw6ff4tzfgzgi5botifk5cfy