Time series versus Fourier transform methods for estimation of respiratory impedance spectra.

[1]  J. Mead,et al.  Mechanical factors in distribution of pulmonary ventilation. , 1956, Journal of applied physiology.

[2]  J. P. Burg,et al.  Maximum entropy spectral analysis. , 1967 .

[3]  H. Akaike.  A new look at the statistical model identification , 1974 .

[4]  E D Michaelson,et al.  Pulmonary mechanics by spectral analysis of forced random noise. , 1975, The Journal of clinical investigation.

[5]  F. Harris.  On the use of windows for harmonic analysis with the discrete Fourier transform , 1978, Proceedings of the IEEE.

[6]  Z Hantos,et al.  An improved forced oscillatory estimation of respiratory impedance. , 1982, International journal of bio-medical computing.

[7]  W. M. Carey,et al.  Digital spectral analysis: with applications , 1986 .

[8]  W A Zin,et al.  Respiratory resistance with histamine challenge by single-breath and forced oscillation methods. , 1986, Journal of applied physiology.

[9]  B. Suki,et al.  Forced oscillatory impedance of the respiratory system at low frequencies. , 1986, Journal of applied physiology.

[10]  K. Lutchen,et al.  Reliability of parameter estimates from models applied to respiratory impedance data. , 1987, Journal of applied physiology.

[11]  Z. Hantos,et al.  Importance of low-frequency impedance data for reliably quantifying parallel inhomogeneities of respiratory mechanics , 1988, IEEE Transactions on Biomedical Engineering.

[12]  K. Lutchen,et al.  Human respiratory input impedance from 4 to 200 Hz: physiological and modeling considerations. , 1988, Journal of applied physiology.

[13]  Steven Kay,et al.  Modern Spectral Estimation: Theory and Application , 1988 .