Review of Nonlinear Methods and Modelling

Abstract

The first part of this Review describes a few of the main methods that have been employed in non-linear time series analysis with special reference to biological applications (biomechanics). The second part treats the physical basis of posturogram data (human balance) and EMG (electromyography, a measure of muscle activity).

72 pages, 10 figures. Written as part of a Biosignals Project

References in corpus (13)

• Practical implementation of nonlinear time series methods: The TISEAN package
• Magnitude and Sign Correlations in Heartbeat Fluctuations
• Scale Invariance in the Nonstationarity of Physiological Signals
• An integrated approach to the assessment of long range correlation in time series data
• Scaling Properties of Fluctuations in Human Electroencephalogram
• Fluctuation Analysis of Human Electroencephalogram
• Recurrence Quantification Analysis and Principal Components in the Detection of Short Complex Signals
• Stochastic Resonance in Ion Channels Characterized by Information Theory
• Defibrillation via the Elimination of Spiral Turbulence in a Model for Ventricular Fibrillation
• A Pinned Polymer Model of Posture Control
• Noise Effects on the Complex Patterns of Abnormal Heartbeats
• Phase space embedding of electrocardiograms
• Scaling Properties of Long-Range Correlated Noisy Signals