SEMG signal compression based on two-dimensional techniques.

Background: Recently, two-dimensional techniques have been successfully employed for compressing surface electromyographic (SEMG) records as images, through the use of image and video encoders. Such schemes usually provide specific compressors, which are tuned for SEMG data, or employ preprocessing...

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Publicado en:BioMedical Engineering OnLine Vol. 15; pp. 1 - 32
Autores principales: Carneiro de Melo, Wheidima, Batista de Lima Filho, Eddie, Sabino da Silva Júnior, Waldir, de Melo, Wheidima Carneiro, de Lima Filho, Eddie Batista, da Silva Júnior, Waldir Sabino
Formato: research tables/charts Journal Article
Publicado: BioMed Central 4/18/2016
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 4/18/2016
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      pub: BioMed Central
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        10.1186/s12938-016-0158-1
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        114755691
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        atl: SEMG signal compression based on two-dimensional techniques.
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        au:
          Carneiro de Melo, Wheidima
          Batista de Lima Filho, Eddie
          Sabino da Silva Júnior, Waldir
          de Melo, Wheidima Carneiro
          de Lima Filho, Eddie Batista
          da Silva Júnior, Waldir Sabino
        affil: State University of Amazonas, Av. Darcy Vargas, 1200, Parque 10, 69050-020 Manaus, Brazil
      sug:
        subj:
          Image Processing, Computer Assisted Methods
          Signal Processing, Computer Assisted
          Electromyography
          Algorithms
      ab: Background: Recently, two-dimensional techniques have been successfully employed for compressing surface electromyographic (SEMG) records as images, through the use of image and video encoders. Such schemes usually provide specific compressors, which are tuned for SEMG data, or employ preprocessing techniques, before the two-dimensional encoding procedure, in order to provide a suitable data organization, whose correlations can be better exploited by off-the-shelf encoders. Besides preprocessing input matrices, one may also depart from those approaches and employ an adaptive framework, which is able to directly tackle SEMG signals reassembled as images.Methods: This paper proposes a new two-dimensional approach for SEMG signal compression, which is based on a recurrent pattern matching algorithm called multidimensional multiscale parser (MMP). The mentioned encoder was modified, in order to efficiently work with SEMG signals and exploit their inherent redundancies. Moreover, a new preprocessing technique, named as segmentation by similarity (SbS), which has the potential to enhance the exploitation of intra- and intersegment correlations, is introduced, the percentage difference sorting (PDS) algorithm is employed, with different image compressors, and results with the high efficiency video coding (HEVC), H.264/AVC, and JPEG2000 encoders are presented.Results: Experiments were carried out with real isometric and dynamic records, acquired in laboratory. Dynamic signals compressed with H.264/AVC and HEVC, when combined with preprocessing techniques, resulted in good percent root-mean-square difference [Formula: see text] compression factor figures, for low and high compression factors, respectively. Besides, regarding isometric signals, the modified two-dimensional MMP algorithm outperformed state-of-the-art schemes, for low compression factors, the combination between SbS and HEVC proved to be competitive, for high compression factors, and JPEG2000, combined with PDS, provided good performance allied to low computational complexity, all in terms of percent root-mean-square difference [Formula: see text] compression factor.Conclusion: The proposed schemes are effective and, specifically, the modified MMP algorithm can be considered as an interesting alternative for isometric signals, regarding traditional SEMG encoders. Besides, the approach based on off-the-shelf image encoders has the potential of fast implementation and dissemination, given that many embedded systems may already have such encoders available, in the underlying hardware/software architecture.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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