Representation Learning and Pattern Recognition in Cognitive Biometrics: A Survey

Min Wang, Xuefei Yin, Yanming Zhu, Jiankun Hu

Research output: Contribution to journalReview articlepeer-review

16 Citations (Scopus)

Abstract

Cognitive biometrics is an emerging branch of biometric technology. Recent research has demonstrated great potential for using cognitive biometrics in versatile applications, including biometric recognition and cognitive and emotional state recognition. There is a major need to summarize the latest developments in this field. Existing surveys have mainly focused on a small subset of cognitive biometric modalities, such as EEG and ECG. This article provides a comprehensive review of cognitive biometrics, covering all the major biosignal modalities and applications. A taxonomy is designed to structure the corresponding knowledge and guide the survey from signal acquisition and pre-processing to representation learning and pattern recognition. We provide a unified view of the methodological advances in these four aspects across various biosignals and applications, facilitating interdisciplinary research and knowledge transfer across fields. Furthermore, this article discusses open research directions in cognitive biometrics and proposes future prospects for developing reliable and secure cognitive biometric systems.

Original languageEnglish
Article number5111
Pages (from-to)1-34
Number of pages34
JournalSensors
Volume22
Issue number14
DOIs
Publication statusPublished - 1 Jul 2022
Externally publishedYes

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