Linked Life Data

10230133

Source:http://linkedlifedata.com/resource/pubmed/id/10230133

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
1999-6-3
pubmed:abstractText
Sinus rhythm (SR), ventricular tachycardia (VT) and ventricular fibrillation (VF) belong to different nonlinear physiological processes with different complexity. In this study, we present a novel, and computationally fast method to detect VT and VF, which utilizes a complexity measure suggested by Lempel and Ziv [1]. For a specific window length (i.e., the length of data segment to be analyzed), the method first generates a 0-1 string by comparing the raw electrocardiogram (ECG) data to a selected suitable threshold. The complexity measure can be obtained from the 0-1 string only using two simple operations, comparison and accumulation. When the window length is 7 s, the detection accuracy for each of SR, VT, and VF is 100% for a test set of 204 body surface records (34 SR, 85 monomorphic VT, and 85 VF). Compared with other conventional time- and frequency-domain methods, such as rate and irregularity, VF-filter leakage, and sequential hypothesis testing, the new algorithm is simple, computationally efficient, and well suited for real-time implementation in automatic external defibrillators (AED's).
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
0018-9294
pubmed:author
pubmed:issnType
Print
pubmed:volume
46
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
548-55
pubmed:dateRevised
2009-11-11
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
Detecting ventricular tachycardia and fibrillation by complexity measure.
pubmed:affiliation
Department of Biomedical Engineering, College of Life Science and Biotechnology, Shanghai Jiao Tong University, China. zhangx5@rpi.edu
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't