Detection of Heart Rate Turbulence Using an Extended IPFM Model
Author
Summary, in English
In this study, the IPFM model is extended to account
for the presence of ectopic beats and heart rate turbulence
(HRT). Based on the model extension, a new approach to
characterize HRT is presented based on a set of Karhunen-
Loeve (KL) basis functions. The three most significant
basis functions possess attractive physiological interpretations
which reflect the difference in heart rate prior to the
ventricular ectopic beat (VEB) compared to after HRT, an
“average” HRT, and a delayed “average” HRT, respectively.
HRT detection is based on the IPFM model extension,
and involves a test statistic that results from a linear
model. The HRT test statistic was studied on patients who
underwent hemodialysis treatment. The goal was to distinguish
between patients considered to be hypotensionresistant
(HtR) and hypotension-prone (HtP). The results
show that the test statistic of the two groups formed two
non-overlapping clusters. The HtR-cluster exhibited much
larger values than did the HtP-cluster (mean values 51 and
2, respectively), suggesting that HRT is mostly present in
HtR patients.
for the presence of ectopic beats and heart rate turbulence
(HRT). Based on the model extension, a new approach to
characterize HRT is presented based on a set of Karhunen-
Loeve (KL) basis functions. The three most significant
basis functions possess attractive physiological interpretations
which reflect the difference in heart rate prior to the
ventricular ectopic beat (VEB) compared to after HRT, an
“average” HRT, and a delayed “average” HRT, respectively.
HRT detection is based on the IPFM model extension,
and involves a test statistic that results from a linear
model. The HRT test statistic was studied on patients who
underwent hemodialysis treatment. The goal was to distinguish
between patients considered to be hypotensionresistant
(HtR) and hypotension-prone (HtP). The results
show that the test statistic of the two groups formed two
non-overlapping clusters. The HtR-cluster exhibited much
larger values than did the HtP-cluster (mean values 51 and
2, respectively), suggesting that HRT is mostly present in
HtR patients.
Publishing year
2006
Language
English
Pages
905-908
Publication/Series
[Host publication title missing]
Volume
33
Full text
- Available as PDF - 111 kB
- Download statistics
Document type
Conference paper
Publisher
Computers in Cardiology
Topic
- Electrical Engineering, Electronic Engineering, Information Engineering
Conference name
Computers in Cardiology, 2006
Conference date
2006-09-17 - 2006-09-20
Conference place
Valencia, Spain
Status
Published
Research group
- Signal Processing
ISBN/ISSN/Other
- ISSN: 0276-6574