Abstract
Different techniques originated in information theory and tools from nonlinear systems theory have been applied to the analysis of electro-physiological time series. Several clinically relevant results have emerged from the use of concepts, such as entropy, chaos and complexity, in analyzing electrocardiograms and electroencephalographic (EEG) records. In this work, we develop a method based on permutation entropy (PE) to characterize EEG records from different stages in the treatment of a chronic epileptic patient. Our results show that the PE is useful for clearly quantifying the evolution of the patient along a certain lapse of time and allows visualizing in a very convenient way the effects of the pharmacotherapy.
Highlights
An electroencephalogram (EEG) is a graphic representation of neural activity
We apply the scheme described above to the analysis of EEG records obtained from a 20-year-old patient, with an electro-clinical diagnosis of idiopathic generalized epilepsy, at different stages of pharmacological treatment
At a certain moment of the treatment, let us say at time T1, the dose of carbamazepine was reduced to mg/day, and the patient was co-medicated with a dose of 1000 mg/day of valproic acid (VPA)
Summary
An electroencephalogram (EEG) is a graphic representation of neural activity It is registered from electrodes placed on either inside the brain, over the cortex under the skull or certain locations over the scalp. The quantitative analysis of an EEG record has been based, mainly, on the use of classical techniques of signal processing. Several works have been devoted to quantifying the therapeutic effects of drugs from the analysis of EEG records by means of quantities arising in the theory of nonlinear systems [10]. One of these quantities is permutation entropy (PE).
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
