A comparative analysis of co-contraction indices using synthetic EMG data: Implications for selection and interpretation - Hannah D. Carey; Friedl De Groote; Andrew Sawers (PLoS ONE, 2026)
Co-contraction—the simultaneous activation of opposing muscles—influences movement efficiency, joint stability, and motor learning. While consensus exists for EMG acquisition and processing, comparable guidance for quantifying co-contraction is lacking. This study evaluated the behavior and interrelationships of six commonly used co-contraction indices (CCIs) to develop practical recommendations for their selection, calculation, and interpretation. Synthetic EMG-like signals were generated and used to evaluate CCI behavior across a range of conditions that would be difficult to achieve experimentally. Based on their formulas and observed behavior, CCIs were sorted into three categories: shape-based, amplitude-driven, and temporal indices. Shape-based CCIs increase when two EMG signals have similar shapes, regardless of amplitudes. Amplitude-driven CCIs increase when activation is high in both muscles. Temporal CCIs increase as the duration of EMG overlap increases, regardless of signal shape or amplitude. Correlation analyses showed stronger associations within-category than between-category, supporting the proposed classification scheme. CCI behavior yielded three principal findings, each paired with a practical recommendation. First, EMG amplitude normalization techniques altered co-contraction estimates, and the effect varied by index. Researchers should therefore test whether their conclusions hold across normalization methods. Second, because CCIs differ in scale and theoretical maxima, their values are not directly comparable across indices. Comparisons should instead focus on relative trends interpreted within each index’s bounds. Third, each CCI category was sensitive to different EMG features (e.g., amplitude versus shape). The choice of CCI should therefore align with hypothesized differences in EMG signals—use shape-based CCIs when waveform similarity is of interest, and amplitude-driven CCIs when differences in activation magnitude are expected. These results provide initial guidance for selecting, calculating, and interpretating CCIs, and they establish a framework for testing the robustness of these theoretical findings using experimental EMG from diverse tasks, muscle pairs, and populations.