Multiscale depth of anaesthesia prediction for surgery using frontal cortex electroencephalography.

ABSTRACT: Hypnotic and sedative anaesthetic agents are employed during multiple medical interventions to prevent patient awareness. Careful titration of agent dosing is required to avoid negative side effects; the accuracy thereof may be improved by Depth of Anaesthesia Monitoring. This work investigates the potential of a patient specific depth monitoring prediction using electroencephalography recorded neural oscillation from the frontal lobe of 10 patients during sedation, where a comparison of the prediction accuracy was made across five different approaches to post-processing; Noise Assisted-Empirical Mode Decomposition, the Raw Signal, Linear Series Decomposition Learner, Deep Wavelet Scattering and Deep Learning features. These methods towards anaesthesia depth prediction were investigated us

SUBMITTER: Nsugbe E 

PROVIDER: S-EPMC9160818 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature