docs: def _thres_norm_reg(threshold_level, signal, pre_smooth_signal):
      """
      Regression function that with a percent input gives an absolute value of the threshold
      level (used in the muscular activation detection algorithm).
      Converts a relative threshold level to an absolute value.
  
      ----------
      Parameters
      ----------
      threshold_level : int
          Percentage value that defines the absolute threshold level relatively to the maximum value
          of signal.
      signal : list
          List of EMG smoothed signal samples.
      pre_smooth_signal : list
          Original EMG samples.
  
      Returns
      -------
      out : float
          Threshold level in absolute format.
  
       """
      avg_signal = numpy.average(pre_smooth_signal)
      std_signal = numpy.std(pre_smooth_signal)
  
      threshold_0_perc_level = (-avg_signal) / float(std_signal)
      threshold_100_perc_level = (numpy.max(signal) - avg_signal) / float(std_signal)
  
      slope, b_coeff = linregress([0, 100], [threshold_0_perc_level, threshold_100_perc_level])[:2]
      return slope * threshold_level + b_coeff