Electroencephalography (EEG) based biometric systems are gaining attention for their anti-
spoofing capability but lack accuracy due to signal variability at different psychological and …

Harnessing the inherent anti-spoofing quality from electroencephalogram (EEG) signals has
become a potential field of research in recent years. Although several studies have been …

The electroencephalogram (EEG) signal represents a subject's specific brain activity
patterns and is considered as an ideal biometric given its superior forgery prevention …

Security systems using brain signals or Electroencephalography (EEG), is an emerging field
of research. Brain signal characteristics such as chaotic nature and uniqueness, make it an …

As human brain activities, represented by EEG brainwave signals, are more confidential,
sensitive, and hard to steal and replicate, they hold great promise to provide a far more …

A multimodal biometric system integrates information from more than one biometric modality
to improve the performance of each individual biometric system and make the system robust …

EEG-based human recognition is increasingly becoming a popular modality for biometric
authentication. Two important features of EEG signals are liveliness and the robustness …

Electroencephalography (EEG), a method of continuously recording the electrical activity of
the brain, provides signals that are among the most promising types of information usable in …

This letter proposes a new multi-level approach for human biometric authentication using
Electro-Encephalo-Gram (EEG) signals (brain waves) and eye blinking Electro-Oculo-Gram …

Background Electroencephalogram (EEG) signals of a brain contain a unique pattern for
each person and the potential for biometric applications. Authentication and security is a …