| Popis: |
Surface-electromyography (sEMG) is a kind of weak physiological signals. During the sEMG signals measurement, the motion noise caused by body movement can easily affect measurement accuracy. In order to prevent the noise, we designed a method to adaptive noise cancellation combined with wavelet transform for sEMG signal filter. Through the decomposition and reconstitution of the Surface-electromyography signal using wavelet transform, we extracted motion interference signal, as the reference input signal of adaptive noise canceller, to offset motion noise of the original sEMG signal. Without the loss of useful sEMG information, this method can suppress motion noise interference and improve the SNR of the measurement system. It laid a solid foundation for EMG feature extraction and pattern recognition. |
