26 January 2017 Transfer entropy to characterize brain-heart topology in sleep apnea patients treated with continuous positive airway pressure
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Proceedings Volume 10160, 12th International Symposium on Medical Information Processing and Analysis; 1016003 (2017); doi: 10.1117/12.2256836
Event: 12th International Symposium on Medical Information Processing and Analysis, 2016, Tandil, Argentina
Abstract
Transfer entropy (TE) is a nonlinear metric employed recently in polysomnography (PSG) recordings to quantify the topological characteristics of the brain-heart physiological network. The present study applies the TE to evaluate its usefulness to identify quantitative differences in PSG registers of patients diagnosed with oclusive sleep apnea (OSA), before and after a continuous positive air pressure (CPAP) therapy. PSG recordings corresponding to 19 OSA patients were analysed under the rationale that the set of EEG subbands represents the sympathetic activity of the autonomic nervous system (ANS), and the high frequency component of the heart rate variability (HRV) represents the parasympathetic activity. The TE was computed based on a binning estimation and the results were analyzed via effect size calculation. The results showed that the sympathetic activity is increased in the presence of OSA, which is represented by the increased flow of information among brain subsystems and dropping to values close to zero during CPAP therapy. In contrast, the parasympathetic activity showed to be reduced in the presence of OSA and augmented during the CPAP therapy.
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Alexander Cerquera, Alvaro Orjuela-Cañón, Jessica Roa-Huertas, Jan A. Freund, Gabriel Juliá-Serdá, Antonio Ravelo-García, "Transfer entropy to characterize brain-heart topology in sleep apnea patients treated with continuous positive airway pressure", Proc. SPIE 10160, 12th International Symposium on Medical Information Processing and Analysis, 1016003 (26 January 2017); doi: 10.1117/12.2256836; http://dx.doi.org/10.1117/12.2256836
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KEYWORDS
Electroencephalography

Polysomnography

Brain

Electrocardiography

Heart

Databases

Complex systems

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