Computers in biology and medicine
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In the present paper, an attempt was made to find waveform-derived variables that would be useful for a more precise diagnosis of hypovolemia. In attempting this, arterial blood pressure graphs of 18 hypovolemic postoperative patients were analysed using a discrete Fourier transform. ⋯ Based on the values of A1, a preliminary study was performed in which an additional group of 14 hypovolemic and 14 normovolemic patients were categorized into hypovolemic and normovolemic groups using logistic regression. The method proved to be successful in identifying hypovolemic patients: the prediction was correct in 80% and wrong only in 20%, indicating that A1 is potentially a useful parameter in detecting hypovolemia.
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In this paper a new technique for the extraction of respiratory signal from the single-lead ECG using generalized homomorphic filtering is presented. It is proposed to perform band pass filtering on the cepstrum of the ECG signal to extract the respiratory signal. For this study, transforms used in generalized homomorphic filtering are the discrete Fourier transform (DFT) and the discrete cosine transform (DCT). ⋯ It is observed from the comparisons that the EDR technique based on generalized homomorphic filtering using DFT performs better than the homomorphic filtering using DCT. The proposed EDR technique is also compared with the two well-known EDR techniques: principal component analysis and R peak amplitude algorithm. It is seen from the results that the proposed EDR technique (RDFT) performs significantly better than the R peak amplitude algorithm, but significant improvements are not observed when compared with the PCA based EDR technique.