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Updated: Jul 17, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
Diagnostic potential of nonlinear analysis of biosignals
Maurice E Cohen1, Donna L Hudson
1California University, San Francisco, Fresno, CA 93703, USA. cohen@ucsfresno.edu
Abstract:
Biosignals have played an important role in medical diagnosis. The first biosignal to be used extensively was the electrocardiogram whose interpretation initially relied on manual analysis of paper tracings. Interpretation was based on variations of the normal QRS pattern associated with each heartbeat. Automated arrhythmia analysis was developed commercially and has been in standard clinical use for some time. The advent of Holter monitoring presented new challenges for the analysis of very long time series. New methods have been developed for this purpose, including nonlinear dynamical approaches. These methods have yielded important diagnostic clues. In this article, the diagnostic use of parameters derived from nonlinear analysis, both alone and in conjunction with other clinical information, is discussed.
