On the application of the auto mutual information rate of decrease to biomedical signals.
Escudero, J, Hornero, R, Abásolo, D and López, M (2008) On the application of the auto mutual information rate of decrease to biomedical signals.
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Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?...
The auto mutual information function (AMIF) evaluates the signal predictability by assessing linear and non-linear dependencies between two measurements taken from a single time series. Furthermore, the AMIF rate of decrease (AMIFRD) is correlated with signal entropy. This metric has been used to analyze biomedical data, including cardiac and brain activity recordings. Hence, the AMIFRD can be a relevant parameter in the context of biomedical signal analysis. Thus, in this pilot study, we have analyzed a synthetic sequence (a Lorenz system) and real biosignals (electroencephalograms recorded with eyes open and closed) with the AMIFRD. We aimed at illustrating the application of this parameter to biomedical time series. Our results show that the AMIFRD can detect changes in the non-linear dynamics of a sequence and that it can distinguish different physiological conditions.
|Item Type:||Conference or Workshop Item (Paper)|
|Additional Information:||Copyright 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Uncontrolled Keywords:||Algorithms, Computer Simulation, Electroencephalography, Entropy, Humans, Nonlinear Dynamics, Normal Distribution, Pilot Projects, Signal Processing, Computer-Assisted|
|Divisions:||Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences|
|Deposited By:||Symplectic Elements|
|Deposited On:||14 Nov 2012 13:46|
|Last Modified:||16 Feb 2013 16:45|
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