Key result
Multidimensional multiscale parser encoding outperforms wavelet-based schemes in EMG signal compression efficiency.
Why the study?
Effective compression of electromyographic signals is needed, and existing wavelet-based schemes have limitations in performance.
The multidimensional multiscale parser provides an effective method for compressing EMG signals that outperforms existing wavelet-based methods.
In this paper, the multidimensional multiscale parser (MMP) is employed for encoding electromyographic signals. The experiments were carried out with real signals acquired in laboratory and show that the proposed scheme is effective, outperforming even wavelet-based state-of-the-art schemes present in the literature in terms of percent root mean square difference x compression ratio.
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Filho et al. (2008) studied this question. Multidimensional multiscale parser encoding of electromyographic signals outperformed wavelet-based schemes in terms of percent root mean square difference versus compression ratio.
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