Steady-State and Dynamic Myoelectric Signal Compression Using Embedded Zero-Tree Wavelets

Abstract

Within the field on biomedical engineering, the majority of compression research has focused on encoding medical images, electrocardiograms, and electroencephalograms. Although long-term myoelectric signal (MES) acquisition is important for neuro-muscular system analysis and telemedicine applications, very few studies have been published on MES compression. This research investigates static and dynamic MES compression using the embedded zero-tree wavelet (EZW) compression algorithm and compares its performance to a standard wavelet compression technique.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA410098

Entities

People

  • D. Lovely
  • J. A. Norris
  • K. Englehart

Organizations

  • University of New Brunswick

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Biomedical Engineering
  • Classification
  • Coding
  • Coefficients
  • Compression
  • Computational Complexity
  • Data Compression
  • Data Processing
  • Decoding
  • Differential Pulse Code Modulation
  • Engineering
  • Floating Point Operations
  • Frequency
  • Pulse Code Modulation
  • Standards
  • Steady State

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Image Processing and Computer Vision.
  • Robotics and Automation.

Technology Areas

  • Biotechnology