Biometric Identification System Using Eeg Signals: A Review

Abstract

An overview of current developments in high accuracy EEG biometric user identification is given in this review paper. In addition to highlighting the most recent findings and advancements in this area, the article addresses the prospective of EEG biometrics for trustworthy and secure user identification. The paper also looks at the drawbacks and restrictions of EEG biometrics and considers possible future paths for study and advancement. This paper's overall goal is to give readers a thorough overview of the state of high precision user identification with EEG biometrics today and to provide guidance for future developments in this field.Analyses of brain waves obtained using a consumer-grade EEG equipment explore the device's potential for user authentication and identification. The P300 element of event-related potential (ERP) information gathered from 14-channel-related EEGs on 25 patients is statistically significant, to start. Next, alternative combination of a method for reducing dimensionality and a classification algorithm are used, and their user identification performance is compared using a range of machine learning techniques.