Spectral analysis of clinical signals: an interface between medical statisticians and medical engineers.
This paper reviews the current use of spectral analysis in clinical medicine. We cover the problems of aliasing and estimation of the spectrum using windowing and autoregressive techniques. These techniques are modified for nonstationary data to include evolutionary spectral analysis and recursive autoregressive methods. The relationship between evolutionary spectral analysis and the time-frequency methods such as the Wigner-Ville distribution is discussed. Other techniques covered are Walsh Transforms and cosinor analysis. The methods are shown to apply in the analysis of signals from heart rate, blood pressure, EEG, other electrical signals and hormone levels. The engineering and statistical approaches are contrasted.
Campbell
M J
MJ
University of Southampton, Department of Medical Statistics and Computing, Southampton General Hospital, UK.
D001794:Blood Pressure / Q000502:physiology; D004569:Electroencephalography / Q000706:statistics & numerical data; D005583:Fourier Analysis; D006339:Heart Rate / Q000502:physiology; D006728:Hormones / Q000097:blood; D006801:Humans; D008991:Monitoring, Physiologic / Q000706:statistics & numerical data*; D012044:Regression Analysis; D012815:Signal Processing, Computer-Assisted
D006728:Hormones