Extraction des dynamiques du système nerveux autonome : Une approche basée sur la séparation aveugle de sources.
Résumé
This paper presents a method to estimate the Sympathetic and Parasympathetic Autonomic Nervous System components (SNAS and SNAP respectively) by using an indicator obtained from surface ECGs. The long-term goal of the project is to quantitatively analyze the ratio between SNAS and SNAP in order to better characterize certain pathologies. An approach based on Independent Component Analysis (ICA), which exploits the di erent activation delays of SNAS and SNAP is proposed and applied to a database with normal subjects and diabetic patients. Preliminary results show a good separation, in the frequency domain, of SNAS and SNAP dynamics, including a di erentiation of SNAS and SNAP in the low-frequency band. Results are promising for a better quanti cation of the autonomic state of the patients.
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