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Analysis of biological rhythms using an interactive structured autoregressive modelling technique

D A Linkens, P M Morrish

Computer Programs in Biomedicine

|January 1, 1979

Summary

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This study introduces a portable autoregressive modeling method for analyzing rhythmic biomedical data. The technique efficiently identifies significant spectral components, even with limited data cycles.

Area of Science:

Biomedical Signal Processing
Time Series Analysis
Computational Biology

Background:

Rhythmic biomedical data analysis often requires sophisticated spectral techniques.
Existing methods may lack portability and ease of use across different computing platforms.

Purpose of the Study:

To present a portable spectral-type analysis method for rhythmic biomedical data.
To develop software in FORTRAN 4 for broad machine compatibility.
To enable interactive analysis and visualization of spectral components.

Main Methods:

Utilizes autoregressive (AR) modeling techniques for spectral analysis.
Programs are written in FORTRAN 4 for portability.
Features an interactive mode for displaying pre-filtering, model coefficients, pole-zero plots, residuals, AR spectrum, and Fast Fourier Transform (FFT).

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Main Results:

The method effectively analyzes rhythmic biomedical data using AR modeling.
Achieves portability across data-processing machines (ICL 1900 series).
Provides direct readout of significant spectral components from a small number of cycles.

Conclusions:

The developed AR modeling method offers a portable and efficient approach for spectral analysis of biomedical data.
The interactive program structure enhances usability and data interpretation.
This technique facilitates the identification of key spectral features in biological rhythms.