S-EMG Signal Compression in One-Dimensional and Two-Dimensional Approaches

This paper presents algorithms designed for one-dimensional (1-D) and 2-D surface electromyographic (S-EMG) signal compression. The 1-D approach is a wavelet transform based encoder applied to isometric and dynamic S-EMG signals. An adaptive estimation of the spectral shape is used to carry out dyna...

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Bibliographic Details
Published in:IEEE journal of biomedical and health informatics 2018-07, Vol.22 (4), p.1104-1113
Main Authors: Trabuco, Marcel H., Costa, Marcus V. C., Macchiavello, Bruno, de O. Nascimento, Francisco Assis
Format: Article
Language:English
Subjects:
Algorithms
Bit rate
Codec
Coders
Coding
Compression
Data banks
Dynamic bit allocation
Electromyography
Encoding
Entropy
HEVC encoder
Isometric
Performance assessment
Quantization (signal)
Redundancy
S-EMG signal compression
Spectral shape
transform-based encoder
Two dimensional displays
Vector quantization
wavelet transform
Wavelet transforms
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Description
Summary:This paper presents algorithms designed for one-dimensional (1-D) and 2-D surface electromyographic (S-EMG) signal compression. The 1-D approach is a wavelet transform based encoder applied to isometric and dynamic S-EMG signals. 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 2-D approach algorithm, the isometric or dynamic S-EMG signal is properly segmented and arranged to build a 2-D representation. The high efficient 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 paper, where the proposed methods have outperformed other efficient encoders reported in the literature.
ISSN:2168-2194
2168-2208
DOI:10.1109/JBHI.2017.2765922