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Model-based detection of heart rate turbulence.

Solem, Kristian LU ; Laguna, Pablo ; Martínez, Juan Pablo and Sörnmo, Leif LU (2008) In IEEE Transactions on Biomedical Engineering 55(12). p.2712-2722
Abstract
In this study, the integral pulse frequency modulation model is extended to account for the presence of ectopic beats and heart rate turbulence (HRT). Based on this model, a new statistical approach to the detection and characterization of HRT is presented. The detector structure involves a set of Karhunen-LoEve basis functions and a generalized likelihood ratio test statistic T(x) . The three most significant basis functions reflect the difference in heart rate prior to a ventricular ectopic beat (VEB) compared to after HRT, the "average" HRT, and a delayed contribution to HRT, respectively. Detector performance was studied on both simulated and ECG signals. Three different simulations were performed for the purpose of studying the... (More)
In this study, the integral pulse frequency modulation model is extended to account for the presence of ectopic beats and heart rate turbulence (HRT). Based on this model, a new statistical approach to the detection and characterization of HRT is presented. The detector structure involves a set of Karhunen-LoEve basis functions and a generalized likelihood ratio test statistic T(x) . The three most significant basis functions reflect the difference in heart rate prior to a ventricular ectopic beat (VEB) compared to after HRT, the "average" HRT, and a delayed contribution to HRT, respectively. Detector performance was studied on both simulated and ECG signals. Three different simulations were performed for the purpose of studying the influence of SNR, QRS jitter, and ECG sampling rate. The results show that the HRT test statistic T(x) performs better in all simulations than do the commonly used parameters known as turbulence onset (TO) and turbulence slope (TS). In order to attain the same performance as T(x), TS needs at least twice the amount of VEBs for averaging, and TO at least four times. The detector performance was also studied on ECGs acquired from eight patients who underwent hemodialysis treatment with the goal to discriminate between patients considered to be hypotension-resistant (HtR) and hypotension-prone (HtP). The results show that T(x) exhibits larger mean values in HtR patients than in HtP, suggesting that HRT is mostly present in HtR patients. The overlap between the two groups was larger for TO and TS than for T(x). (Less)
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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
IEEE Transactions on Biomedical Engineering
volume
55
issue
12
pages
2712 - 2722
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • pmid:19126450
  • wos:000262541400004
  • scopus:58149250387
  • pmid:19126450
ISSN
1558-2531
DOI
10.1109/TBME.2008.2002113
language
English
LU publication?
yes
id
f8648cc2-dd46-4bd0-ba4c-4fc35d03c397 (old id 1289895)
date added to LUP
2016-04-01 14:47:20
date last changed
2022-01-28 02:31:19
@article{f8648cc2-dd46-4bd0-ba4c-4fc35d03c397,
  abstract     = {{In this study, the integral pulse frequency modulation model is extended to account for the presence of ectopic beats and heart rate turbulence (HRT). Based on this model, a new statistical approach to the detection and characterization of HRT is presented. The detector structure involves a set of Karhunen-LoEve basis functions and a generalized likelihood ratio test statistic T(x) . The three most significant basis functions reflect the difference in heart rate prior to a ventricular ectopic beat (VEB) compared to after HRT, the "average" HRT, and a delayed contribution to HRT, respectively. Detector performance was studied on both simulated and ECG signals. Three different simulations were performed for the purpose of studying the influence of SNR, QRS jitter, and ECG sampling rate. The results show that the HRT test statistic T(x) performs better in all simulations than do the commonly used parameters known as turbulence onset (TO) and turbulence slope (TS). In order to attain the same performance as T(x), TS needs at least twice the amount of VEBs for averaging, and TO at least four times. The detector performance was also studied on ECGs acquired from eight patients who underwent hemodialysis treatment with the goal to discriminate between patients considered to be hypotension-resistant (HtR) and hypotension-prone (HtP). The results show that T(x) exhibits larger mean values in HtR patients than in HtP, suggesting that HRT is mostly present in HtR patients. The overlap between the two groups was larger for TO and TS than for T(x).}},
  author       = {{Solem, Kristian and Laguna, Pablo and Martínez, Juan Pablo and Sörnmo, Leif}},
  issn         = {{1558-2531}},
  language     = {{eng}},
  number       = {{12}},
  pages        = {{2712--2722}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{IEEE Transactions on Biomedical Engineering}},
  title        = {{Model-based detection of heart rate turbulence.}},
  url          = {{http://dx.doi.org/10.1109/TBME.2008.2002113}},
  doi          = {{10.1109/TBME.2008.2002113}},
  volume       = {{55}},
  year         = {{2008}},
}