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PINTO, S. FELTON, C. SMITAL, L. GILBERT, B. HOLMES, D. HAIDER, C.
Original Title
Clinical Accuracy QRS Detector with Automatic Parameter Adjustment in an Autonomous, Real-Time Physiologic Monitor
Type
conference paper
Language
English
Original Abstract
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.
Keywords
Compact algorithm, Stockwell transform, Realtime, Physiologic monitoring, QRS detection, Embedded
Authors
PINTO, S.; FELTON, C.; SMITAL, L.; GILBERT, B.; HOLMES, D.; HAIDER, C.
Released
14. 11. 2017
Publisher
IEEE
Location
Montreal, QC, Kanada
ISBN
978-1-5090-5990-4
Book
2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
2376-4066
Periodical
IEEE Global Conference on Signal and Information Processing
State
United States of America
Pages from
1005
Pages to
1009
Pages count
5
URL
https://ieeexplore.ieee.org/document/8309112
BibTex
@inproceedings{BUT143750, author="Samuel Cerqueira {Pinto} and Christopher L. {Felton} and Lukáš {Smital} and Barry {Gilbert} and David {Holmes} and Clifton {Haider}", title="Clinical Accuracy QRS Detector with Automatic Parameter Adjustment in an Autonomous, Real-Time Physiologic Monitor", booktitle="2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP)", year="2017", journal="IEEE Global Conference on Signal and Information Processing", pages="1005--1009", publisher="IEEE", address="Montreal, QC, Kanada", doi="10.1109/GlobalSIP.2017.8309112", isbn="978-1-5090-5990-4", issn="2376-4066", url="https://ieeexplore.ieee.org/document/8309112" }