# Muscle synergy analysis with musclesyneRgies

    library(musclesyneRgies)

## Analysis functions

For example, one can measure the full width at half maximum (FWHM) of the activation patterns or their centre of activity (CoA).

    # Load a typical activation pattern of 30 cycles (from locomotion)
    data("act_pattern")

    # Reduce activation pattern to the first cycle
    act_sub <- act_pattern$signal[1:which(act_pattern$time == max(act_pattern$time))[1]]

    # Calculate FWHM of the first cycle
    act_sub_FWHM <- FWHM(act_sub)
    # Calculate CoA of the first cycle
    act_sub_CoA <- CoA(act_sub)

    # Half maximum (for the plots)
    hm <- min(act_sub) + (max(act_sub) - min(act_sub)) / 2
    hm_plot <- act_sub
    hm_plot[which(hm_plot > hm)] <- hm
    hm_plot[which(hm_plot < hm)] <- NA

    # Plots
    plot(act_sub, ty = "l", xlab = "Time", ylab = "Amplitude")
    lines(hm_plot, lwd = 3, col = 2) # FWHM (horizontal, in red)
    graphics::abline(v = act_sub_CoA, lwd = 3, col = 4) # CoA (vertical, in blue)

Or perhaps one might want to investigate the nonlinear behaviour of a long activation pattern.

    act <- act_pattern$signal

    # Calculate the local complexity or Higuchi's fractal dimension (HFD)
    nonlin_HFD <- HFD(act)$Higuchi
    # Calculate the global complexity or Hurst exponent (H)
    nonlin_H <- Hurst(act, min_win = max(act_pattern$time))$Hurst

    message("Higuchi's fractal dimension: ", round(nonlin_HFD, 3))
    #> Higuchi's fractal dimension: 1.047
    message("Hurst exponent: ", round(nonlin_H, 3))
    #> Hurst exponent: 0.338