This study investigated a method of processing muscle activity signals to reduce unwanted noise from the signals.
High-pass filtering (HPF) is a fundamental signal processing method for the attenuation of low-frequency noise contamination, namely baseline noise and movement artefact noise, in human surface electromyography (sEMG) research. Despite this, HPF is largely overlooked in equine sEMG research, with many studies not applying, or failing to describe, the application of HPF. An optimal HPF cut-off frequency maximally attenuates noise while minimally affecting sEMG signal power, but this has not been investigated for equine sEMG signals.
The aim of this study was to determine the optimal cut-off frequency for attenuation of low-frequency noise in sEMG signals from the Triceps Brachii and Biceps Femoris of 20 horses during trot and canter.
sEMG signals were HPF with cut-off frequencies ranging from 0-80 Hz and were subjected to power spectral analysis and enveloped using RMS to calculate spectral peaks, indicative of motion artefact, and signal loss, respectively.
Processed signals consistently revealed a low-frequency peak between 0–20 Hz, which was associated with motion artefact.
Across all muscles and gaits, a 30-40 Hz cut-off fully attenuated the low-frequency peak with the least amount of signal loss and was therefore considered optimal for attenuating low-frequency noise from the sEMG signals explored in this study.