Preprint Article Version 1 This version is not peer-reviewed

Complexity-Entropy Maps as a Tool for the Characterization of the Clinical Electrophysiological Evolution of Patients Under Pharmacological Treatment with Psychotropic Drugs

These authors contributed equally to this work.
Version 1 : Received: 26 July 2017 / Approved: 4 August 2017 / Online: 4 August 2017 (11:06:40 CEST)

A peer-reviewed article of this Preprint also exists.

Diaz, J.M.; Mateos, D.M.; Boyallian, C. Complexity-Entropy Maps as a Tool for the Characterization of the Clinical Electrophysiological Evolution of Patients under Pharmacological Treatment with Psychotropic Drugs. Entropy 2017, 19, 540. Diaz, J.M.; Mateos, D.M.; Boyallian, C. Complexity-Entropy Maps as a Tool for the Characterization of the Clinical Electrophysiological Evolution of Patients under Pharmacological Treatment with Psychotropic Drugs. Entropy 2017, 19, 540.

Journal reference: Entropy 2017, 19, 540
DOI: 10.3390/e19100540

Abstract

In the clinical electrophysiologic practice, the reading and comparing electroencephalographic (EEG) recordings some times is insufficient and take to much time. That is why in the last years it has begun to introduce new methods of EEG analysis, that give a better and faster understanding of the EEG dynamics and allow a rapid intervention in the patient's treatment. Tools coming from the information theory or nonlinear system as an entropy and complexity have been shown to be a very good alternative to address this problem. In this work we introduce a novel method -the permutation Lempel-ziv complexity vs permutation entropy map. This method was applied to EEG of two patients with specific diagnosed pathologies during respective follow up processes of pharmacological changes in order to detect changes that are not evident with the usual inspection method. Our results show that the proposed method are useful for observing an evolutionary retrospective clinical effects of pharmacological interventions in both patients, and from these, to follow the clinical response to the proposed treatment.

Subject Areas

permutation entropy; permutation complexity; pharmacological treatment

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