Using Hilbert-Huang Transform to assess EEG slow wave activity during anesthesia in post-cardiac arrest patients

摘要

Hypoxic ischemic encephalopathy (HIE) is a severe consequence of cardiac arrest (CA) representing a substantial diagnostic challenge. We have recently designed a novel method for the assessment of HIE after CA. The method is based on estimating the severity of the brain injury by analyzing changes in the electroencephalogram (EEG) slow wave activity while the patient is exposed to an anesthetic drug propofol in a controlled manner. In this paper, Hilbert-Huang Transform (HHT) was used to analyze EEG slow wave activity during anesthesia in ten post-CA patients. The recordings were made in the intensive care unit 36-48 hours after the CA in an experiment, during which the propofol infusion rate was incrementally decreased to determine the drug-induced changes in the EEG at different anesthetic levels. HHT was shown to successfully capture the changes in the slow wave activity to the behavior of intrinsic mode functions (IMFs). While, in patients with good neurological outcome defined after a six-month control period, propofol induced a significant increase in the amplitude of IMFs representing the slow wave activity, the patients with poor neurological outcome were unable to produce such a response. Consequently, the proposed method offer substantial prognostic potential by providing a novel approach for early estimation of HIE after CA.