Ethical approval was granted by our institutional and national review panels. Digital filters were evaluated on raw unipolar recordings acquired using the ActiveTwo system (Biosemi, The Netherlands), at a sampling frequency of 512 Hz. The data acquisition was performed using a large dynamic range (24 bit delta-sigma analog to digital convertor, resolution 31.2 nV) with no high pass filtering, and a low pass filter by the ADC’s decimation filter due to hardware bandwidth limitations (effective bandwidth from DC (0Hz) to 400Hz at -3dB). Recordings were taken from the gastric serosa of a pig and human using flexible arrays (16 (link)) according to our previously published methods (2 (link), 3 (link)), and ten representative data segments were analyzed (855 s for pig, 500 s for human).
Four different filters with distinct specifications were identified from recent literature for comparison: Bandpass FIR (Finite impulse response) filter (0.05–1 Hz) (17 (link), 18 (link)); SG (Savitzky-Golay) filter (low pass filter with cutoff frequency of 1.98 Hz) (9 (link), 13 (link)); Bandpass Bessel filter (2–100 Hz) (15 (link)), and a Bandpass Butterworth filter (5–100 Hz) (15 (link)). These four filters were applied after the removal of baseline wander (via a moving median window of 20 seconds (9 (link))) and notch filters to remove power line interference for consistent comparison. Data processing and analysis was performed in MATLAB v7.11 (Natick, Massachusetts).
After filtering, the resultant signals were evaluated in both the time and frequency domains. Two measures were used to quantify the filter effects: average slow wave amplitude in the time domain, and maximum spectral component in the frequency domain (computed via the Fourier transform). Amplitude in the time domain was computed by the difference between the minimum and maximum of a running window of two minutes and averaged. In the frequency domain, the spectral component with the highest amplitude was acquired. For statistical analyses, t-tests were performed between the amplitude and frequency of the baseline removed signal, and the filtered signals.
Four different filters with distinct specifications were identified from recent literature for comparison: Bandpass FIR (Finite impulse response) filter (0.05–1 Hz) (17 (link), 18 (link)); SG (Savitzky-Golay) filter (low pass filter with cutoff frequency of 1.98 Hz) (9 (link), 13 (link)); Bandpass Bessel filter (2–100 Hz) (15 (link)), and a Bandpass Butterworth filter (5–100 Hz) (15 (link)). These four filters were applied after the removal of baseline wander (via a moving median window of 20 seconds (9 (link))) and notch filters to remove power line interference for consistent comparison. Data processing and analysis was performed in MATLAB v7.11 (Natick, Massachusetts).
After filtering, the resultant signals were evaluated in both the time and frequency domains. Two measures were used to quantify the filter effects: average slow wave amplitude in the time domain, and maximum spectral component in the frequency domain (computed via the Fourier transform). Amplitude in the time domain was computed by the difference between the minimum and maximum of a running window of two minutes and averaged. In the frequency domain, the spectral component with the highest amplitude was acquired. For statistical analyses, t-tests were performed between the amplitude and frequency of the baseline removed signal, and the filtered signals.
