DocumentCode :
3562212
Title :
A real-time ST-segment monitoring algorithm based on a multi-channel waveform-length-transform method for Q-onset and J-point detection
Author :
Wei Zong ; Kresge, Scott ; Haisheng Lu ; Wang, John
Author_Institution :
Philips Healthcare, Andover, MA, USA
fYear :
2014
Firstpage :
641
Lastpage :
644
Abstract :
In the paper, we present a fully automated real-time multi-lead ST-segment monitoring algorithm. For a representative normal beat in each ST measurement interval, the ECG leads with low signal quality are excluded and the remaining leads are used in a multi-lead waveform-length transformation to form a length signal for Q-onset (Q) and J-point (J) determination. From Q, the isoelectric point is determined and used with the J to measure the ST-segment at J or J plus an offset for all available leads. A development set of 158 records and a test set of 60 records with cardiologists´ beat-by-beat Q and J annotations were used to develop and evaluate the Q and J detection. The ESC ST-T Database and a 60-patient annotated 12-lead PTCA dataset were used to evaluate the algorithm´s ST performance. Detailed statistical results are given in the paper. The test results demonstrate that the described ST-segment monitoring algorithm is effective and reliable.
Keywords :
bioelectric potentials; electrocardiography; medical signal processing; patient diagnosis; real-time systems; wavelet transforms; ECG S wave; ECG T wave; ECG leads; ECG records; ESC ST-T database; J detection development; J detection evaluation; J plus; J-point detection; J-point determination; Q detection development; Q detectionevaluation; Q-onset length signal; ST measurement interval; ST-segment measurement; algorithm ST performance evaluation; cardiologist beat-by-beat J annotation; cardiologist beat-by-beat Q annotation; electrocardiogram S wave; electrocardiogram T wave; electrocardiogram leads; electrocardiogram records; fully automated ST-segment monitoring algorithm; isoelectric point determination; low signal quality; multichannel waveform-length-transform method; multilead ST-segment monitoring algorithm; multilead waveform-length transformation; patient annotated 12-lead PTCA dataset; real-time ST-segment monitoring algorithm; representative normal beat; Abstracts; Electrocardiography; Lead; Myocardium; Noise; Q measurement; Reliability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing in Cardiology Conference (CinC), 2014
ISSN :
2325-8861
Print_ISBN :
978-1-4799-4346-3
Type :
conf
Filename :
7043124
Link To Document :
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