CNR ExploRA

Articolo in rivista, 2022, ENG, 10.1016/j.bspc.2022.104042

Feasibility of recurrence quantification analysis (RQA) in quantifying dynamical coordination among muscles

Zhao, Kunkun; Wen, Haiying; Guo, Yiming; Scano, Alessandro; Zhang, Zhisheng

Southeast Univ; Nanjing Univ Sci & Technol; Italian Natl Res Council CNR

Surface electromyography (EMG) signal is a powerful tool to investigate motor control. However, due to the non -linearity and non-stationarity of EMG signals, linear methods hardly quantify the dynamical coordination among muscles. To quantify the dynamical characteristics and promote the applications of nonlinear methods in motor neuroscience and neurorehabilitation, this study assessed the feasibility of a nonlinear approach, recurrence quantification analysis (RQA), in quantifying the dynamical muscle coordination by calculating four RQA measurements, recurrence rate (RR), determinism (DET), entropy (ENT), and laminarity (LAM) of each trial, movement, and subject. By analyzing the variability of four RQA measurements, the results showed the feasi-bility of using RQA to quantify dynamic characteristics among muscles during reaching movements. Especially, DET and LAM had less variation among trials, indicating they were more appropriate for dynamical analysis. The results also reported significant differences of each measurement among subjects and among movements, and inter-subject variability was larger than inter-movement. It suggests that future studies should focus more on dynamical variations of one person rather than comparisons between subjects and/or movements. This study provides a dynamic perspective to research motor control and clinical diagnoses and assessment in future work.

Biomedical signal processing and control (Print) 79