Evaluation of Resting-State Magnetoencephalogram Complexity in Alzheimer's Disease with Multivariate Multiscale Permutation and Sample Entropies

Hamed Azami, Keith Smith, Alberto Fernandez, Javier Escudero

Research output: Contribution to conferencePaperpeer-review

Abstract / Description of output

Alzheimer’s disease (AD) is one of the fastest growing neurological diseases in the world. We evaluate multivariate multiscale sample entropy (mvMSE) and multivariate multiscale permutation entropy (mvMPE) approaches to distinguish resting-state magnetoencephalogram (MEG) signals of 36 AD patients from those of 26 normal controls. We also discuss about choosing the appropriate embedding dimension value as an effective parameter for mvMPE and MPE for the first time. The results illustrate that both the mvMPE and mvMSE can be useful in the diagnosis of AD, although with different running times and abilities. In addition, our findings show that the MEG complexity analysis performed on deeper time scales by mvMPE and mvMSE may be a useful tool to characterize AD. In most scale factors, the average of the mvMPE and mvMSE values of AD patients are lower than those of controls.
Original languageEnglish
Pages7422-7425
Number of pages4
Publication statusPublished - 28 Aug 2015
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - MiCo, Milan, Italy
Duration: 26 Aug 201529 Aug 2015

Conference

Conference37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Country/TerritoryItaly
CityMilan
Period26/08/1529/08/15

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