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Output details

13 - Electrical and Electronic Engineering, Metallurgy and Materials

University of Southampton

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Output 37 of 326 in the submission

Article title

An automated algorithm for online detection of fragmented QRS and identification of its various morphologies

Type

D - Journal article

DOI

10.1098/rsif.2013.0761

Title of journal

Journal of the Royal Society Interface

Article number

Volume number

Issue number

First page of article

20130761

ISSN of journal

1742-5689

Year of publication

2013

URL

http://www.eprints.soton.ac.uk/358997

Number of additional authors

Additional information

Significance of output:

This international collaboration developed an automated algorithm for detecting 22 types of fragmented QRS morphologies in ECG signals using novel time-frequency signal processing techniques facilitating early detection of developing heart abnormalities. Testing on 31 patients show detection sensitivity and specificity of 89.7% and 89.9% respectively. It forms part of a complete mobile wearable ECG analysis system currently under trial with 50 class-III CHF patients at Southampton General hospital, UK and Policlinico Umberto I, Italy, and has been identified as the potential solution for home monitoring of CVD patients by large enterprises like Philips Healthcare, Intracom telecom, Atos Origin and Barco.

Interdisciplinary

Cross-referral requested

Research group

None

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract