Recurrence quantification analysis of electrically evoked surface EMG signal

Area of Science:

• Dynamical Systems and Chaos Theory
• Biomedical Signal Processing
• Time-Series Analysis

Background:

• Recurrence Plots (RP) are valuable for analyzing time-series data, particularly for detecting unstable periodic orbits in chaotic systems.
• Recurrence Quantification Analysis (RQA) provides quantitative measures from Recurrence Plots.
• Surface electromyography (sEMG) signals are complex and can exhibit chaotic behavior.

Purpose of the Study:

• To introduce the structure and generation of Recurrence Plots.
• To define methods for quantifying Recurrence Plots.
• To investigate the application of RQA to analyze electrical stimulation-evoked surface EMG and its relationship with stimulation intensity.

Main Methods:

• Detailed explanation of Recurrence Plot construction.
• Definition and application of Recurrence Quantification Analysis (RQA) metrics.
• Experimental analysis of surface EMG signals during varying electrical stimulation intensities.

Main Results:

• The study details the fundamental structures and formation of Recurrence Plots.
• Recurrence Quantification Analysis (RQA) metrics were defined for quantitative analysis.
• A significant finding was the increase in percent determination as electrical stimulation intensity rose.

Conclusions:

• Recurrence Plots and RQA are effective tools for analyzing complex time-series data like sEMG.
• The percent determination metric in RQA correlates positively with electrical stimulation intensity.
• This suggests RQA can quantify changes in muscle response to varying stimulation levels.