| Research Title |
Applying GA-SVR to Derive 12-lead ECG from EASI-lead System. |
| Date of Distribution |
2 July 2017 |
| Conference |
| Title of the Conference |
The 32nd International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC 2017) |
| Organiser |
IEIE (The Institute of Electronics and Information Engineers) |
| Conference Place |
Haeundae Grand Hotel |
| Province/State |
Busan, Korea |
| Conference Date |
2 July 2017 |
| To |
5 July 2017 |
| Proceeding Paper |
| Volume |
2017 |
| Issue |
32 |
| Page |
95-98 |
| Editors/edition/publisher |
|
| Abstract |
For years, the 12-lead Electrocardiogram
(ECG) monitoring system has been the standard
clinical method of heart disease diagnose. Measuring
all 12 leads is often impractical. The EASI-lead
system was introduced by Gordon Dower in 1988 with
Dower’s equation. The EASI system is an ECG
monitoring system with five cables positioned in EASI
mode, a valid alternative to the standard 12-leas ECG
for cardiac rhythm abnormalities detection.
Therefore, the EASI system might be advantageous for
long-term patient monitoring. Ever since various
attempts have been explored to improve the synthesis
accuracy. This paper presents how Genetic
Algorithm-Support Vector Regression (GA-SVR) was
used to find a set of transfer function for deriving the
12-lead ECG from EASI-lead system. The
experiments were conducted to compare the results of
GA-SVR and those of Dower’s method against the
original data set from PhysioNet Database. The
results have shown that the performance obtained
from GA-SVR gave much less RMSE for all signals. |
| Author |
|
| Peer Review Status |
มีผู้ประเมินอิสระ |
| Level of Conference |
นานาชาติ |
| Type of Proceeding |
Full paper |
| Type of Presentation |
Oral |
| Part of thesis |
true |
| Presentation awarding |
false |
| Attach file |
|
| Citation |
0
|
|
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Publication
Journal Publication
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