| Title |
QT interval analysis on ambulatory electrocardiogram recordings: a selective beat averaging approach
|
|---|---|
| Published in |
Medical & Biological Engineering & Computing, January 1999
|
| DOI | 10.1007/bf02513269 |
| Pubmed ID | |
| Authors |
F. Badilini, P. Maison-Blanche, R. Childers, P. Coumel |
| Abstract |
A computerised method for the analysis of QT intervals in ambulatory ECG recordings is presented. This approach is based on selective beat averaging which allows one to process P-QRS-T complexes together with the environment that characterises them. Long-term autonomic nervous system influences are accounted for by separating the analysis over different circadian periods. Effects of QT recovery time are taken into account by requiring a stable heart rate preceding each beat to be averaged. Before averaging, beats are resampled and realigned with respect to the R-wave peak estimated by parabolic interpolation. Averaged ECG templates are then analysed with an algorithm which automatically detects QRS complex and T-wave features. Repolarisation analysis is based on first and second derivatives of lowpass filtered ECG (recursive Butterworth filter). The QT/RR relationship and the circadian QT variation at identical heart rate were analysed in 14 normal individuals. When performed at stable heart rate conditions and when confined to well-defined circadian periods, the QT/RR relationship was strongly linear (r = 0.95 +/- 0.06); in addition, the slope of this relation changed between day and night (respectively, 0.197 +/- 0.07 and 0.139 +/- 0.03, p < 0.01). The range of circadian QT variation at identical heart rate was approximately 20 ms for both males and females. |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 9% |
| Portugal | 1 | 5% |
| Italy | 1 | 5% |
| Unknown | 18 | 82% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor | 4 | 18% |
| Researcher | 4 | 18% |
| Other | 3 | 14% |
| Student > Ph. D. Student | 3 | 14% |
| Student > Bachelor | 2 | 9% |
| Other | 4 | 18% |
| Unknown | 2 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 36% |
| Engineering | 5 | 23% |
| Mathematics | 2 | 9% |
| Agricultural and Biological Sciences | 1 | 5% |
| Veterinary Science and Veterinary Medicine | 1 | 5% |
| Other | 2 | 9% |
| Unknown | 3 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 May 2010.
All research outputs
#5,446,210
of 25,371,288 outputs
Outputs from Medical & Biological Engineering & Computing
#167
of 2,053 outputs
Outputs of similar age
#10,337
of 109,585 outputs
Outputs of similar age from Medical & Biological Engineering & Computing
#1
of 7 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,053 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done well, scoring higher than 77% of its peers.
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