Smart Threshold
Like the threshold calculation, the Smart Threshold calculation determines the intervals where the Data Series exceeds a specified threshold. The result is a new Data Series of the same length with zeros indicating samples that did not exceed the threshold and ones indicating samples that did exceed the threshold.
Refer to the Threshold calculation documentation for details in how the pre- and post-processing options work. The smart threshold differs from the basic threshold calculation in how the threshold level is determined. Generally, it is specified to be Baseline Level multiplied by the RMS value of the baseline noise of the signal. This is very useful for EMG data, where each channel may have a slightly different baseline level.
The baseline estimation is performed by taking finding the RMS of data in n windows throughout the data. The Number of Windows and Window Length parameters determine the count and size of these windows. The smallest RMS value found is taken to be the baseline of the signal, and multiplied by the Baseline Level parameter to produce the threshold level. The windows are selected randomly, in a manner that is repeatable within the particular data series.
Parameters