Exploring Scaling Analysis: A Pathway to Understand Complexity in Natural Phenomena
Dr. Ivan Seleznov- Graduate School of Engineering Science Osaka University | Japan
Dr. Ivan Seleznov is a Post-doc researcher at the Department of Mechanical Science and Bioengineering at Osaka University in Japan, where he conducts cutting-edge research in the field of biomedical signals. In addition to his academic work, Ivan is also the Chief Technology Officer of Flora, a startup focused on using data analysis to enhance female well-being and improve working conditions for women.
His research has focused on the interpretation of electroencephalograms during cognitive workload and emotions, fractal analysis of electroencephalograms, human stabilograms, heart rate, and the development of new techniques in 2D scaling analysis. These contributions have received recognition in several peer-reviewed journals and conference proceedings.
In this tutorial, attendees will learn about scaling analysis (fractal analysis) – an innovative technique for analyzing complex signals in various natural phenomena. These complex signals have been shown to be the result of non-linear, non-equilibrium, and non-stationary processes, but traditional analytical tools and techniques often assume the stationarity and linearity of data. Conventional methods, such as analysis of means, standard deviations, and histogram features, are not enough to capture the hidden dynamics and information contained in such signals. The fractal analysis provides a way to uncover the underlying complexity of signals and extract valuable insights for researchers. It focuses on the self-similar patterns that exist within complex signals and use mathematical models to describe the scaling behavior of these patterns over different scales of observation. In this tutorial, attendees will learn the theory behind scaling analysis, as well as the tools and techniques used to perform such analysis. This will include a focus on the mathematical models used to describe scaling behavior, the use of scaling exponents to quantify complexity, and the comparison of scaling and fractal analysis to traditional methods. During the tutorial, we will also demonstrate practical applications of scaling analysis, emphasizing the usage of the analysis of seismic time series as well as human center-of-pressure time series. By the end of the tutorial, attendees will have a solid understanding of the principles of scaling and fractal analysis and will be able to apply these techniques to their own data and research