Research Topic

Geometrical methods for analysing physiological variability signals

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About this Research Topic

Aims:
Geometrical methods are visualization tools for time-series signals of geometric patterns and various mathematical descriptors have been used to derive variability and dynamical information of physiological variability signals. Geometric measures also portray the nature of time-series ...

Aims:
Geometrical methods are visualization tools for time-series signals of geometric patterns and various mathematical descriptors have been used to derive variability and dynamical information of physiological variability signals. Geometric measures also portray the nature of time-series fluctuations in a higher dimensional plane and provide a quantitative-visual technique. These techniques provide summary information as well as detailed information about the fluctuations or variations in the signal.

Geometrical techniques of time-series analysis are based on various types of linear and nonlinear methods including histogram, Poincaré plot, second order difference plot, 3-D return map, recurrence analysis and others. These methods are mostly applicable to both short and long length signals and capable of capturing linear, non-linear and dynamical information about the time-series signal. For example, mathematical descriptors of the Poincaré plot of beat to beat heart rate signals were developed to quantify autonomic nervous system activity (sympathetic and parasympathetic modulation of heart rate). Poincaré plot analysis was also used in various clinical diagnostic settings like diabetes, chronic heart failure, chronic renal failure and sleep apnea syndrome to analyse and describe changes in the dynamics of measured time signals. The primary aim of quantification of physiological time series by geometrical methods is to discriminate healthy physiological systems from pathological conditions and to classify the stage of disease. These methods have opened up ample opportunities for important clinical and research applications.
The goal of this Research Topic is to present current paradigm of research and application studies using geometrical approaches to analyze physiological time-series signals in general. We will solicit and welcome high quality papers in all theoretical and applied aspects of physiological time series analysis focusing on geometrical methodologies.

Scope:
Potential topics of research include, but are not limited to:
• Novel metrics for quantifying geometric patterns
• Analysing system dynamics
• Physiological explanation of existing metrics
• Analysing asymmetry characteristics
• Higher order system characteristics
• Analysing system complexity
• Innovative applications in physiological signals
• Theoretical frameworks of geometrical approaches


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