title: Digital Butterworth filter for subtracting noise from low magnitude surface electromyogram.
abstract: This work presents a digital filter designed to delimitate the frequency band of surface electromyograms (EMG) and remove the mains noise and its harmonics, focusing the signal analysis during reduced muscle activity. A Butterworth filter was designed as the frequency-domain product of a second order, high-pass filter with cutoff frequency 10 Hz, an eighth order low-pass filter, with cutoff at 400 Hz and six stop-band filters, second order, centered at the 60 Hz mains noise and its harmonics until 360 Hz. The resulting filter was applied in both direct and reverse directions of the signals to avoid phase distortions. The performance was evaluated with a simulated EMG signal with additive noise in multiples of 60 Hz. A qualitative assessment was made with real EMG data, acquired from 16 subjects, with age from 20 to 32 years. Subjects were positioned in orthostatic position during 21s, being only the last second analyzed to assure stationarity. EMG were collected by Ag/AgCl electrodes on right lateral gastrocnemius, amplified with gain 5000, filtered in the band from 10 Hz to 1 kHz, and thus digitized with 2ksamples/s. The filter effectively removed the mains noise components, with attenuations greater than 96.6%. The attenuation of the simulated signal at frequencies below 15 Hz and at 60 Hz caused only a small reduction of total power, preserving the original spectrum. Thus, the filter resulted suitable to the proposed application.
authors.affiliation: Biomedical Engineering Program-COPPE, Federal University of Rio de Janeiro, P.O. Box 68510, 21941-972 Rio de Janeiro, RJ, Brazil. roger@peb.ufrj.br
authors.forename: Roger G T
authors.initials: RG
authors.lastname: Mello
authors.forename: Liliam F
authors.initials: LF
authors.lastname: Oliveira
authors.forename: Jurandir
authors.initials: J
authors.lastname: Nadal
mesh_terms: D000328:Adult; D000465:Algorithms; D001938:Brazil; D004576:Electromyography / Q000379:methods*; D006801:Humans; D008297:Male; D009622:Noise / Q000517:prevention & control*; D012815:Signal Processing, Computer-Assisted