Clinical Accuracy QRS Detector with Automatic Parameter Adjustment in an Autonomous, Real-Time Physiologic Monitor

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F17%3APU126203" target="_blank" >RIV/00216305:26220/17:PU126203 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8309112" target="_blank" >https://ieeexplore.ieee.org/document/8309112</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/GlobalSIP.2017.8309112" target="_blank" >10.1109/GlobalSIP.2017.8309112</a>

Result language
angličtina
Original language name
Clinical Accuracy QRS Detector with Automatic Parameter Adjustment in an Autonomous, Real-Time Physiologic Monitor
Original language description
This paper presents a computationally and temporal data-compact QRS complex detection algorithm useful in embedded real-time electrocardiogram (ECG) waveform analysis. The aim of the compact algorithms is to provide high sensitivity and specificity, i.e. diagnostically useful QRS waveform detection, in a continuous ambulatory monitor setting. The proposed detector uses a multi-level approach: QRS highlighting by means of a Truncated Discrete Time Stockwell Transform (TDTST), peak discrimination, and a trained Neural Network to reduce the number of false positive QRS detections. An optimization method is presented that automatically adjust the detector’s parameters to minimize the computational cost. Results demonstrate that the compact TDTST algorithm exhibits high QRS detection accuracy, an error rate of 0.31%, and remains applicable to real-time embedded physiologic ambulatory monitors.
Czech name
—
Czech description
—

Project
<a href="/en/project/GAP102%2F12%2F2034" target="_blank" >GAP102/12/2034: Analysis of Relationship between Electrical Activity and Blood Flow at the Heart Ventricles</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
ISBN
978-1-5090-5990-4
ISSN
2376-4066
e-ISSN
—
Number of pages
5
Pages from-to
1005-1009
Publisher name
IEEE
Place of publication
Montreal, QC, Kanada
Event location
Montreal, Kanada
Event date
Nov 14, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000450053100199

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