Electromyogram Signal Compression Using Pre/De-emphasis- Based Smoothing Technique

Today, there is a great tendency to store long-term recordings of electromyogram (EMG) signals; thus, showing the importance and necessity of effective compression of this type of biomedical signals. In this paper, regarding to the relatively rapid variation of EMG instantaneous amplitudes and thus having rather high frequency components, we have proposed a compression approach in which a smooth and reversible version of the input EMG signal is generated to be compressed instead of the original one; thus, improving the compression efficiency. We have used the pre/de-emphasis technique in the Fourier domain to produce a smooth signal from the input EMG signal. The smoothed signal is then simply converted to the corresponding 2D image and finally, compressed by the Wavelet transform and Set Partitioning In Hierarchical Trees (SPIHT) codec. The proposed method is evaluated by two sets of criteria, measuring the compression efficiency (including the PRD and CF measures) and capability of preserving the clinical information (including four spectral parameters). The results show the superiority of the proposed method compared to most of existing approaches.