Comparison of filtering methods for extracellular gastric slow wave recordings
Article first published online: 13 SEP 2012
© 2012 Blackwell Publishing Ltd
Neurogastroenterology & Motility
Volume 25, Issue 1, pages 79–83, January 2013
How to Cite
Paskaranandavadivel, N., O’Grady, G., Du, P. and K Cheng, L. (2013), Comparison of filtering methods for extracellular gastric slow wave recordings. Neurogastroenterology & Motility, 25: 79–83. doi: 10.1111/nmo.12012
- Issue published online: 20 DEC 2012
- Article first published online: 13 SEP 2012
- Received: 4 June 2012 Accepted for publication: 14 August 2012
- gastric dysrhythmia;
- gastric electrical activity;
- signal processing
Background Extracellular recordings are used to define gastric slow wave propagation. Signal filtering is a key step in the analysis and interpretation of extracellular slow wave data; however, there is controversy and uncertainty regarding the appropriate filtering settings. This study investigated the effect of various standard filters on the morphology and measurement of extracellular gastric slow waves.
Methods Experimental extracellular gastric slow waves were recorded from the serosal surface of the stomach from pigs and humans. Four digital filters: finite impulse response filter (0.05–1 Hz); Savitzky-Golay filter (0–1.98 Hz); Bessel filter (2–100 Hz); and Butterworth filter (5–100 Hz); were applied on extracellular gastric slow wave signals to compare the changes temporally (morphology of the signal) and spectrally (signals in the frequency domain).
Key Results The extracellular slow wave activity is represented in the frequency domain by a dominant frequency and its associated harmonics in diminishing power. Optimal filters apply cutoff frequencies consistent with the dominant slow wave frequency (3–5 cpm) and main harmonics (up to ∼2 Hz). Applying filters with cutoff frequencies above or below the dominant and harmonic frequencies was found to distort or eliminate slow wave signal content.
Conclusions & Inferences Investigators must be cognizant of these optimal filtering practices when detecting, analyzing, and interpreting extracellular slow wave recordings. The use of frequency domain analysis is important for identifying the dominant and harmonics of the signal of interest. Capturing the dominant frequency and major harmonics of slow wave is crucial for accurate representation of slow wave activity in the time domain. Standardized filter settings should be determined.