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Journal Publication
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
567040042-0 Mr. PIROON KAEWFOONGRUNGSI [Main Author]
Engineering Doctoral Degree

Peer Review Status มีผู้ประเมินอิสระ 
Level of Conference นานาชาติ 
Type of Proceeding Full paper 
Type of Presentation Oral 
Part of thesis true 
Presentation awarding false 
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