DocumentCode :
3747104
Title :
On the derivation of the spatial QRS-T angle from Mason-Likar leads I, II, V2 and V5
Author :
Daniel Guldenring;Dewar D Finlay;Raymond R Bond;Alan Kennedy;James McLaughlin;Kieran Moran
Author_Institution :
University of Ulster, Belfast, United Kingdom
fYear :
2015
Firstpage :
165
Lastpage :
168
Abstract :
The spatial QRS-T angle (SA) has been identified as a marker for changes in the ventricular depolarization and repolarization sequence. The determination of the SA requires vectorcardiographic (VCG) data. However, VCG data is seldom recorded in monitoring applications. This is mainly due to the fact that the number and location of the electrodes required for recording the Frank VCG complicate the recording of VCG data in monitoring applications. Alternatively, reduced lead systems (RLS) allow for the derivation of the Frank VCG from a reduced number of electrocardiographic (ECG) leads. Derived Frank VCGs provide a practical means for the determination of the SA in monitoring applications. One widely studied RLS that is used in clinical practice is based upon Mason-Likar leads I, II, V2 and V5 (MLRL). The aim of this research was two-fold. First, to develop a linear ECG lead transformation matrix that allows for the derivation of the Frank VCG from the MLRL system. Second, to assess the accuracy of the MLRL derived SA (MSA). We used ECG data recorded from 545 subjects for the development of the linear ECG lead transformation matrix. The accuracy of the MSA was assessed by analyzing the differences between the MSA and the SA using the ECG data of 181 subjects. The differences between the MSA and the SA were quantified as systematic error (mean difference) and random error (span of Bland-Altman 95% limits of agreement). The systematic error between the MSA and the SA was found to be 9.38° [95% confidence interval: 7.03° to 11.74°]. The random error was quantified as 62.97° [95% confidence interval: 56.55° to 70.95°].
Keywords :
"Electrocardiography","Monitoring","Electrodes","Systematics","Lead","Sociology","Statistics"
Publisher :
ieee
Conference_Titel :
Computing in Cardiology Conference (CinC), 2015
ISSN :
2325-8861
Print_ISBN :
978-1-5090-0685-4
Electronic_ISBN :
2325-887X
Type :
conf
DOI :
10.1109/CIC.2015.7408612
Filename :
7408612
Link To Document :
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