Digital Butterworth filter for subtracting noise from low magnitude surface electromyogram
Computer Methods and Programs in Biomedicine
The Generalized Wavelets Based on Meyer Wavelet
ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part I
Computer Methods and Programs in Biomedicine
| Hi-index | 0.00 |
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.