S-EMG Signal Compression in 1D and 2D Approaches.
This work presents algorithms designed for 1D (one-dimensional) and 2D (two-dimensional) surface electromyographic (S-EMG) signal compression. The 1D approach is a wavelet transform-based encoder. An adaptive estimation of the spectral shape is used to carry out dynamic bit allocation for vector quantization of transformed coefficients. Thus, an entropy coding is applied to minimize redundancy in quantized coefficient vector and to pack the data. In the 2D approach algorithm, the isometric or dynamic S-EMG signal is properly segmented and arranged to build a two-dimensional representation. The HEVC video codec is used to encode the signal, using 16 bit-depth precision, all possible Coding/Prediction Unit sizes and all Intra coding modes. The encoders are evaluated with objective metrics, and a real signal data bank is used. Furthermore, performance comparisons are also shown in this work, where the proposed methods have outperformed other efficient encoders reported in the literature.