Document Detail

ECG compression using Ziv-Lempel techniques.
MedLine Citation:
PMID:  7614825     Owner:  NLM     Status:  MEDLINE    
The strong regularity in an ECG recording suggests that data compression techniques based on finding and efficiently coding repetitions in the data are likely to be effective. It is shown how the LZ77 compression method due to Ziv and Lempel can be adapted to ECG compression. Experimental results show the new algorithm to be highly effective. Some enhancements to the basic compression algorithm to reduce noise in the decompressed trace are described and experimentally verified.
R N Horspool; W J Windels
Related Documents :
24894055 - Reconsidering "special needs" populations during a disaster.
24271505 - A class of distribution-free models for longitudinal mediation analysis.
20692715 - A patient specific electro-mechanical model of the heart.
24489535 - Unsupervised approach data analysis based on fuzzy possibilistic clustering: applicatio...
17271375 - Data mining techniques to detect motor fluctuations in parkinson's disease.
24187235 - Selecting the best number of synergies in gait: preliminary results on young and elderl...
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Computers and biomedical research, an international journal     Volume:  28     ISSN:  0010-4809     ISO Abbreviation:  Comput. Biomed. Res.     Publication Date:  1995 Feb 
Date Detail:
Created Date:  1995-08-24     Completed Date:  1995-08-24     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  0100331     Medline TA:  Comput Biomed Res     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  67-86     Citation Subset:  IM    
Department of Computer Science, University of Victoria, British Columbia, Canada.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Fourier Analysis
Pattern Recognition, Automated
Signal Processing, Computer-Assisted*
Software Design

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

Previous Document:  ARCADIA: a system for the integration of angiocardiographic data and images by an object-oriented DB...
Next Document:  Strategies for school-based response to loss: proactive training and postvention consultation.