Abstract
Research on using electroencephalographic signals for biometric recognition has made considerable progress and is attracting growing attention in recent years. However, the usability aspects of the proposed biometric systems in the literatures have not received significant attention. In this paper, we present a comprehensive survey to examine the development and current status of various aspects of electroencephalography (EEG)-based biometric recognition. We first compare the characteristics of different stimuli that have been used for evoking biometric information bearing EEG signals. This is followed by a survey of the reported features and classifiers employed for EEG biometric recognition. To highlight the usability challenges of using EEG for biometric recognition in real-life scenarios, we propose a novel usability assessment framework which combines a number of user-related factors to evaluate the reported systems. The evaluation scores indicate a pattern of increasing usability, particularly in recent years, of EEG-based biometric systems as efforts have been made to improve the performance of such systems in realistic application scenarios. We also propose how this framework may be extended to take into account Aging effects as more performance data becomes available.
Highlights
E LECTROENCEPHALOGRAPHY (EEG) is the recording of the electrical activities of the brain along the scalp, measuring the small voltage fluctuations resulting from ionic currents within the brain [1]
This paper provided a review of the recent literature on EEGbased biometric person recognition
As this is a relatively new biometric modality, the literature has been focused on establishing the presence of biometric information in EEG signals
Summary
E LECTROENCEPHALOGRAPHY (EEG) is the (generally noninvasive) recording of the electrical activities of the brain along the scalp, measuring the small voltage fluctuations resulting from ionic currents within the brain [1]. Considering the physiological differences between the brains of different people, EEG signals may be expected to possess the potential to indicate the brain’s functions, and dissimilarities between individuals as manifested by the electrical activity of their brains. Previous surveys in [7] and [8] have addressed the theoretical aspects of EEG-biometric systems, reviewing the state-of-theart methods and their future perspectives The goal of this investigation is to review the recent work on EEG-based biometric recognition systems while focusing on issues of practicality and usability which are key to achieving the wider deployment of such systems.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
