Key result
An automatic algorithm using the rescaled maximum energy density curve measured QT intervals with a root mean square error of 27.89 ms compared to reference QT in 549 subjects.
Why the study?
Does a novel algorithm based on wavelet techniques accurately measure the QT interval in ECGs?
Does a novel algorithm based on wavelet techniques accurately measure the QT interval in ECGs?
Answers are grounded in this paper and cite their sources.
A novel automatic algorithm using continuous wavelet transform and RMED curve provides fast and simple QT interval measurement with an RMS error of 27.89 ms.
HYPOTHESIS/OBJECTIVE: Prolonged QT interval is an index of propensity for dangerous ventricular tachyarrhythmias. The aim of this article is to establish an automatic algorithm for QT interval measurement. METHOD: The proposed method is based on the continuous wavelet transform. In this method, the concepts of the rescaled wavelet coefficients and dominant scales of the electrocardiogram (ECG) components are used to perform detection of ECG characteristic points. A new concept of rescaled maximum energy density is introduced so as to perform the estimation of the QT interval. RESULTS AND CONCLUSION: We have applied the algorithm to the PTB database of the Physiobank∖Physionet in lead II. Then, the results were evaluated using pertinent reference QT. The criterion used for evaluation of the method's performance is the root mean square (RMS) error. The method approached the RMS error of 27.89 ms for 549 subjects. The proposed method is fast, simple and is applicable to a wide range of ECG cardio cycle morphologies.
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Ghasemi et al. (2010) studied this question. RMED curve algorithm based on continuous wavelet transform vs. Reference QT was evaluated on Root mean square (RMS) error. An automatic algorithm using the rescaled maximum energy density curve measured QT intervals with a root mean square error of 27.89 ms compared to reference QT in 549 subjects.
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