Brain entropy, fractal dimensions and predictability: A review of complexity measures for EEG in healthy and neuropsychiatric populations
There has been an increasing trend towards the use of complexity analysis in quantifying
neural activity measured by electroencephalography (EEG) signals. On top of revealing …
neural activity measured by electroencephalography (EEG) signals. On top of revealing …
Nonlinear methods most applied to heart-rate time series: a review
The heart-rate dynamics are one of the most analyzed physiological interactions. Many
mathematical methods were proposed to evaluate heart-rate variability. These methods …
mathematical methods were proposed to evaluate heart-rate variability. These methods …
Practical method for determining the minimum embedding dimension of a scalar time series
L Cao - Physica D: Nonlinear Phenomena, 1997 - Elsevier
A practical method is proposed to determine the minimum embedding dimension from a
scalar time series. It has the following advantages:(1) does not contain any subjective …
scalar time series. It has the following advantages:(1) does not contain any subjective …
EEG signal analysis: a survey
The EEG (Electroencephalogram) signal indicates the electrical activity of the brain. They
are highly random in nature and may contain useful information about the brain state …
are highly random in nature and may contain useful information about the brain state …
Non-linear analysis of EEG signals at various sleep stages
Application of non-linear dynamics methods to the physiological sciences demonstrated that
non-linear models are useful for understanding complex physiological phenomena such as …
non-linear models are useful for understanding complex physiological phenomena such as …
[图书][B] Applied nonlinear time series analysis: applications in physics, physiology and finance
M Small - 2005 - books.google.com
Nonlinear time series methods have developed rapidly over a quarter of a century and have
reached an advanced state of maturity during the last decade. Implementations of these …
reached an advanced state of maturity during the last decade. Implementations of these …
State space reconstruction parameters in the analysis of chaotic time series—the role of the time window length
D Kugiumtzis - Physica D: Nonlinear Phenomena, 1996 - Elsevier
The most common state space reconstruction method in the analysis of chaotic time series is
the Method of Delays (MOD). Many techniques have been suggested to estimate the …
the Method of Delays (MOD). Many techniques have been suggested to estimate the …
Recurrence quantification analysis as a tool for nonlinear exploration of nonstationary cardiac signals
JP Zbilut, N Thomasson, CL Webber - Medical engineering & physics, 2002 - Elsevier
The complexity, nonlinearity and nonstationarity of the cardiovascular system typically defy
comprehensive and deterministic mathematical modeling, except from a statistical …
comprehensive and deterministic mathematical modeling, except from a statistical …
Weak and strong synchronization of chaos
K Pyragas - Physical Review E, 1996 - APS
It is shown that synchronization in unidirectionally coupled chaotic systems develops in two
stages as the coupling strength is increased. The first stage is characterized by a weak …
stages as the coupling strength is increased. The first stage is characterized by a weak …
Classification of heart rate data using artificial neural network and fuzzy equivalence relation
The electrocardiogram is a representative signal containing information about the condition
of the heart. The shape and size of the P-QRS-T wave, the time intervals between its various …
of the heart. The shape and size of the P-QRS-T wave, the time intervals between its various …