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Related Experiment Videos

Bios data analyzer.

H Sabelli1, A Sugerman, L Kovacevic

  • 1Chicago Center for Creative Development, 2400 N. Lakeview #2802, Chicago, IL 60614, USA. Hector_Sabelli@rush.edu

Nonlinear Dynamics, Psychology, and Life Sciences
|October 1, 2005
PubMed
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The Bios Data Analyzer (BDA) detects creative phenomena in time series, like heartbeat intervals. This analysis distinguishes creative biosignals from random or chaotic processes using novel methods.

Area of Science:

  • Complex Systems Science
  • Biosignal Analysis
  • Time Series Analysis

Background:

  • Creative phenomena such as diversification and novelty are observed in various empirical time series.
  • Existing methods struggle to differentiate between random, chaotic, and genuinely creative processes.

Purpose of the Study:

  • Introduce the Bios Data Analyzer (BDA) for detecting and measuring creative phenomena in time series.
  • Define processes exhibiting diversification, novelty, and nonrandom complexity as creative.
  • Differentiate creative biosignals from random, chaotic, and stochastic processes.

Main Methods:

  • Utilized differencing, consecutive recurrence, and partial autocorrelation to identify nonrandom causation.
  • Employed embedding plots to distinguish causal creative processes from stochastic and chaotic ones.

Related Experiment Videos

  • Applied entropy and trigonometric transformations to analyze symmetry, variety, asymmetry, and coexisting opposites.

    • Main Results:

    • BDA successfully detects creative phenomena in diverse series, including biosignals (heartbeat intervals).
    • Nonrandom causation was indicated in biosignals, differentiating them from random walks and chaos.
    • Analysis revealed complexity is associated with asymmetry and biosignals exhibit bipolar feedback.

    Conclusions:

    • The Bios Data Analyzer provides a robust method for identifying and quantifying creative processes in time series.
    • Biosignals, exemplified by heartbeat intervals, exhibit creative properties generated by bipolar feedback.
    • This framework challenges standard concepts of opposites, proposing bipolarity as fundamental to biosystems.