RSBagging: An ensemble classifier detecting the after-effects of ischemic stroke through EEG connectivity and microstates.

ABSTRACT:

Background and purpose

Stroke can lead to significant after-effects, including motor function impairments, language impairments (aphasia), disorders of consciousness (DoC), and cognitive deficits. Computer-aided analysis of EEG connectivity matrices and microstates from bedside EEG monitoring can replace traditional clinical observation methods, offering an automatic approach to monitoring the progression of these after-effects. This EEG-based method also enables quicker and more efficient assessments for medical practitioners.

Methods

In this study, we employed Functional Connectivity features that extract spatial representation and Microstate features that focus on the time domain representation to monitor the after-effects of ischemic stroke patients. As the dataset from

SUBMITTER: Wang F 

PROVIDER: S-EPMC11495553 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature