title: Power line interference filtering on surface electromyography based on the stationary wavelet packet transform.
abstract: Power line interference is one of the main problems in surface electromyogram signals (EMG) analysis. In this work, a new method based on the stationary wavelet packet transform is proposed to estimate and remove this kind of noise from EMG data records. The performance has been quantitatively evaluated with synthetic noisy signals, obtaining good results independently from the signal to noise ratio (SNR). For the analyzed cases, the obtained results show that the correlation coefficient is around 0.99, the energy respecting to the pure EMG signal is 98-104%, the SNR is between 16.64 and 20.40dB and the mean absolute error (MAE) is in the range of -69.02 and -65.31dB. It has been also applied on 18 real EMG signals, evaluating the percentage of energy respecting to the noisy signals. The proposed method adjusts the reduction level to the amplitude of each harmonic present in the analyzed noisy signals (synthetic and real), reducing the harmonics with no alteration of the desired signal.
authors.affiliation: Dept. Physics, Systems Engineering and Signal Theory, University of Alicante, P.O. Box 99, E-03080 Alicante, Spain. juanjo@dfists.ua.es
authors.forename: J J
authors.initials: JJ
authors.lastname: Galiana-Merino
authors.forename: D
authors.initials: D
authors.lastname: Ruiz-Fernandez
authors.forename: J J
authors.initials: JJ
authors.lastname: Martinez-Espla
mesh_terms: D000328:Adult; D000465:Algorithms; D003198:Computer Simulation; D004559:Electric Wiring; D004574:Electromagnetic Fields / Q000009:adverse effects*; D004576:Electromyography / Q000379:methods*; D004781:Environmental Exposure / Q000009:adverse effects*; D064368:Healthy Volunteers; D006801:Humans; D008875:Middle Aged; D008962:Models, Theoretical; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D012984:Software; D058067:Wavelet Analysis; D055815:Young Adult
keywords: Biological signals filtering; Electromyogram signal (EMG); Power line interference; Stationary wavelet packet transform (SWPT)