IIR vs. FIR filters
IIR filters are much more efficient than FIR filters, but can introduce linear phase distortions. The IIR filters in BIOPAC hardware are emulated by the software IIR filters.
- IIR filters can be set up as online calculation channels for real-time digital filtering.
- IIR filters have a variable Q setting that defines the filter response pattern (but FIR filters do not have a Q component).
- The optimal Q of an IIR filter is 0.707, with lower values resulting in a flatter response and higher values resulting in a more peaked response. By definition, any single order bi-quad filter with a Q of 0.707 is a Butterworth filter.
- The default Q for low pass and high pass IIR filters in AcqKnowledge is 0.707. The Q for band pass and band stop filters is 5. These values are appropriate for nearly all filter applications.
FIR filters require more computing power than IIR filters. Their filter response can be adjusted so that it is superior to IIR filters (i.e., they can be tweaked to do a better job at attenuating particular frequencies).
- FIR filters are available only in the software; in AcqKnowledge versions older than 4.4, they cannot be set up as calculation channels and must be applied as transformations once the acquisition is over.
- Number of coefficients for FIR filters—The following rule of thumb will help to determine the correct number of coefficients to use when setting up an FIR filter: The number of coefficients should be greater than or equal to four times the sampling rate divided by the lowest cutoff frequency specified. Additional coefficients will improve the response.
- For example, if running a low pass filter at 1Hz on data sampled at 100Hz, choose at least (4 x 100/1) or 400 coefficients in the filter. Select the “Show Filter Response” option to see the filter response (a graph of attenuation vs. frequency).
Page last modified 29Dec2014