Abstract
Recently, ECG-derived respiration methods (EDR) have become a widely used tool in respiratory monitoring. In this paper, four new methods are presented for EDR signal estimation. The first two methods we have developed are based on ECG interval and QRS energy measurement. A wavelet transform method, based on the Mexican-Hat wavelet is also used in the present study. The final EDR signal method we have proposed is obtained by summing the first three estimated ECG-derived respiration signals. Correlation and magnitude squared coherence coefficients are used to evaluate the performance of the proposed EDR techniques. Compared to other recent works cited in the literature, the proposed algorithms allow us to achieve high estimation performances.
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