Mathematics – Numerical Analysis
Scientific paper
2011-05-09
Mathematics
Numerical Analysis
Scientific paper
The acquisition of information about respiratory patterns without directly recording the respiratory signals would be beneficial in many clinical settings. The electrocardiogram (ECG)-derived respiration (EDR) algorithm, which derives the respiratory pattern by using the information encoded in ECG signals, enables data acquisition in this manner. However, the traditional EDR algorithm cannot be used in patients with atrial fibrillation (AF) because they have highly irregular heart rates. In this paper, we first provide a definition of ideal instantaneous frequency (IIF) of respiratory signals and then describe how a novel time-frequency representation technique referred to as the Synchrosqueezing transform (SST) was used for the accurate estimation of the IIF of respiratory signals, i.e., SST-IF. Then, we introduce a new EDR algorithm based on the evaluation of the SST-IF. We tested the applicability of our new EDR algorithm in patients with comorbid cardiovascular diseases, most of which were complicated by AF. The study population comprised 16 patients each with sinus rhythm (SR) and persistent AF. The proposed IIF was found to match our intuitions, and it was estimated from the ECG signals with the relative median errors as low as 0.32% and 1.12% in the SR group and AF group, respectively. The EDR algorithm exhibited high accuracy in the evaluation of oscillatory respiratory patterns. To the best of our knowledge, this is the first EDR algorithm that can be used in patients with obvious atrial arrhythmias.
Chi-Tai Kuo
Hau-Tieng Wu
Shu-Shya Hseu
Yi-Hsin Chan
Yung-Hsin Yeh
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