Digital Signal Processing

    

Fast QRS Detection with an Optimized Knowledge-Based Method: Evaluation on 11 Standard ECG Databases

Authors: Mohamed Elgendi

The current state-of-the-art in automatic QRS detection methods show high robustness and almost negligible error rates. In return, the methods are usu- ally based on machine-learning approaches that require sucient computational re- sources. However, simple-fast methods can also achieve high detection rates. There is a need to develop numerically ecient algorithms to accommodate the new trend towards battery-driven ECG devices and to analyze long-term recorded signals in a time-ecient manner. A typical QRS detection method has been reduced to a basic approach consisting of two moving averages that are calibrated by a knowledge base using only two parameters. In contrast to high-accuracy methods, the proposed method can be easily implemented in a digital lter design.

Comments: 37 Pages. The paper is published in PLoS ONE and its citation is: Elgendi M (2013) Fast QRS Detection with an Optimized Knowledge-Based Method: Evaluation on 11 Standard ECG Databases. PLoS ONE 8(9): e73557

Download: PDF

Submission history

[v1] 2013-01-10 23:27:20 (removed)
[v2] 2013-02-17 18:45:47 (removed)
[v3] 2013-02-18 13:14:07 (removed)
[v4] 2013-04-10 17:56:01
[v5] 2013-09-16 17:50:46

Unique-IP document downloads: 1136 times

Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.

Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.

comments powered by Disqus