Document Detail


A software sensor using neural networks for detection of patient workload.
MedLine Citation:
PMID:  9825319     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The morphology of intracardiac electrograms (IEGMs) was used for pacemaker patient workload estimation. The body posture also was studied as another characteristic. The IEGMs were obtained and recorded via temporary transcutaneous leads connected to the implanted pacemaker. IEGMs were recorded during exercise and at rest. Recordings at rest were performed in different body positions. The morphology was analyzed visually in order to observe changes due to workload and posture. The recordings were digitized and processed by a computer-simulated neural network. The network was used as an automatic IEGM classifier based on the morphology. Our results show that the morphology of the IEGM may be used as an indicator of patient workload and body posture. The necessary information is found mainly in the ST segment. We conclude that neural networks seem to be useful in an active cardiac device.
Authors:
J L Andersson; S E Hedberg; J Hirschberg; H Schüller
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Pacing and clinical electrophysiology : PACE     Volume:  21     ISSN:  0147-8389     ISO Abbreviation:  Pacing Clin Electrophysiol     Publication Date:  1998 Nov 
Date Detail:
Created Date:  1999-02-10     Completed Date:  1999-02-10     Revised Date:  2004-11-17    
Medline Journal Info:
Nlm Unique ID:  7803944     Medline TA:  Pacing Clin Electrophysiol     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  2204-8     Citation Subset:  IM    
Affiliation:
Lund University Hospital, Sweden. jonas.andersson@pacesetter.se
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MeSH Terms
Descriptor/Qualifier:
Aged
Aged, 80 and over
Algorithms
Cardiac Pacing, Artificial
Computer Simulation
Electrocardiography
Female
Heart Block / therapy
Humans
Male
Middle Aged
Neural Networks (Computer)*
Pacemaker, Artificial*
Posture
Signal Processing, Computer-Assisted
Software*

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


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