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Computation of QRS Vector of ECG Signal for Observation of It's Clinical Significance.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Pandu Rangan, C.
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Ghosh, Ashish
De, Rajat K.
Pal, Sankar K.
Mitra, S.
Mitra, M.
Source :
Pattern Recognition & Machine Intelligence (978-3-540-77045-9); 2007, p439-446, 8p
Publication Year :
2007

Abstract

An automated approach for computation of the frontal plane QRS vector and an important observation of its clinical significance is described in this paper. Frontal plane QRS vector is computed from the six frontal plane leads ( Standard leads I, II, III , AVR, AVL and AVF). The R-R interval of each ECG wave is detected by square derivative technique. The baseline or isoelectric level of every ECG wave is determined. After that the net positive or net negative deflection (NQD) of QRS complex is detected. Net positive or net negative deflection in any lead is obtained by subtracting the smaller deflection (+ve or -ve) from the larger deflection (-ve or +ve). An algorithm is developed for computation of the exact angle,amplitude and direction of the frontal plane QRS vector from maximum and minimum NQD. In the present work, the PTB diagnostic ECG database of normal and Myocardial Infarction (MI) subjects is used for computation of the QRS vector. An interesting clinical observation that, the rotation of QRS axis for MI data may significantly detect the region of the infarcted cardiac wall, is reported in this paper. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540770459
Database :
Complementary Index
Journal :
Pattern Recognition & Machine Intelligence (978-3-540-77045-9)
Publication Type :
Book
Accession number :
34135916
Full Text :
https://doi.org/10.1007/978-3-540-77046-6_54