ENGINEERING ANALYSIS OF BIOLOGICAL VARIABLES - AN EXAMPLE OF BLOOD-PRESSURE OVER 1 DAY

Almost all variables in biology are nonstationarily stochastic, For th ese variables, the conventional tools leave us a feeling that some val uable information is thrown away and that a complex phenomenon is pres ented imprecisely. Here, we apply recent advances initially made in th e study of ocean waves to study the blood pressure waves in the lung. We note first that, in a long wave train, the handling of the local me an is of predominant importance. It is shown that a signal can be desc ribed by a sum of a series of intrinsic mode functions, each of which has zero local mean at all times. The process of deriding this series is called the ''empirical mode decomposition method.'' Conventionally, Fourier analysis represents the data by sine and cosine functions, bu t no instantaneous frequency can be defined. In the new way, the data are represented by intrinsic mode functions, to which Hilbert transfor m can be used. Titchmarsh [Titchmarsh, E, C, (1948) Introduction to th e Theory of Fourier Integrals (Oxford Univ. Press, Oxford)] has shown that a signal and i times its Hilbert transform together define a comp lex variable, From that complex variable, the instantaneous frequency, instantaneous amplitude, Hilbert spectrum, and marginal Hilbert spect rum have been defined, In addition, the Gumbel extreme-value statistic s are applied. We present all of these features of the blood pressure records here for the reader to see how they look In the future, me hav e to learn how these features change with disease or interventions.