EEG-based optimization of eye state classification using modified-BER metaheuristic algorithm.

ABSTRACT: This article introduces the Modified Al-Biruni Earth Radius (MBER) algorithm, which seeks to improve the precision of categorizing eye states as either open (0) or closed (1). The evaluation of the proposed algorithm was assessed using an available EEG dataset that applied preprocessing techniques, including scaling, normalization, and elimination of null values. The MBER algorithm's binary format is specifically designed to select features that can significantly enhance the accuracy of classification. The proposed algorithm and competing ones, namely, Al-Biruni Earth Radius (BER), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WAO), Grey Wolf Optimizer (GWO) and Genetic Algorithm (GA) were evaluated using predefined sets of assessment criteria. The statistical analysis e

SUBMITTER: Elshewey AM 

PROVIDER: S-EPMC11492230 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature