Guldenring, Daniel, Finlay, D, Nugent, CD and Donnelly, Mark (2010) Extended multiple linear regression in the derivation of electrocardiographic leads. In: Computing in Cardiology, Belfast, UK. Computing in Cardiology. 4 pp. [Conference contribution]
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In this study we investigate the performance of an approach for deriving electrocardiographic leads with the aim of improving derivation accuracy. We focus our attention on a limited lead system that uses leads I, II, V2 and V5 to derive the remaining precordial leads. Our extended multiple linear regression based lead transformation (EMLRLT) approach extends the standard multiple linear regression based lead transformation (MLRLT) approach by combining the data from the recorded leads with quadratic and cross product terms from the same leads. It was found that all missing leads were more accurately derived using an EMLRLT approach in comparison with the MLRLT approach. Using the standard MLRLT approach, the median RMSEs for the QRST were found to be 44.2μV, 42.7μV, 40.3μV and 19.3μV for leads V1, V3, V4 and V6, respectively. Using the EMLRLT approach, the median RMSEs for the QRST were found to be 28.2μV, 29.3μV, 25.1μV and 13.4μV for leads V1, V3, V4 and V6, respectively. According to the sign test, all differences were statistically significant with p<0.05. In conclusion, it has been shown that alternative methods for lead transformation have the potential to improve derivation accuracy.
|Item Type:||Conference contribution (Paper)|
|Faculties and Schools:||Faculty of Computing & Engineering|
Faculty of Computing & Engineering > School of Computing and Mathematics
|Research Institutes and Groups:||Computer Science Research Institute|
Computer Science Research Institute > Smart Environments
|Deposited By:||Dr Mark Donnelly|
|Deposited On:||30 Mar 2011 15:39|
|Last Modified:||23 Nov 2015 15:34|
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