The use of FIR vs. IIR filters is discussed elsewhere at length:

• Pitfalls of Filtering the EEG Signal by Sapiens Lab

• Difference between IIR and FIR filters: a practical design guide by Advanced Solutions Nederland

For fast, lightweight computation—most applicable to closed-loop applications—the IIR is ideal (see also, A Fast EEG Forecasting Algorithm for Phase-Locked Transcranial Electrical Stimulation of the Human Brain). Using the CMSIS DSP library is probably the fastest way to implement such a filter on equipped ARM hardware. The key to implementing the filter is generating the filter coefficients which end up being part of the arm_biquad_cascade_df2T_instance_f32 struct.

Matteo posted a great toolset for GNU Octave which I ported to MATLAB. However, the lines of code to get the coefficients is rather simple and straight forward. It comes down to the second-order section (SOS) digital filter, specified as an L-by-6 matrix, where L is the number of second-order sections (see sosfilt() in MATLAB).

In this example, I generate a low-pass elliptical filter. This code can be generated by the Filter Design Tool in MATLAB.

Hd.sosMatrix contains the SOS matrix. You can derive the SOS matrix in other ways, like using ellip() followed by zp2sos(). To use the coefficients with an ARM device, the fourth column is removed, the last two columns undergo a sign reversal, and the matrix is flattened.

Implementing on ARM

There is a CMSIS example of using an FIR filter which I have used as a model (caveats discussed below). I have combined the boilerplate from Matteo with this example for my final implementation; note that this initializes the filter instance manually (without the init function), but shows how to filter the signal in blocks, like the example. The input signal is found in SWAsignal.h.

I suspect that the example uses a for-loop, block-filtering approach because it is adaptable to larger input signal buffers and can be optimized for a particular architecture. However, I found that a 1,024 point buffer has an 80 microsecond advantage from being run in one line while eliminating a lot of code complexity.

arm_biquad_cascade_df2T_f32(&filtInst, inputSignal, filtSignal, SIG_SAMPLES);