An Overview of Brain Fingerprint Identification Based on Various Neuroimaging Technologies

As a novel category of biometric features, research on brain fingerprints has become a hot topic in neuroscience, not only for its reliable performance on individual identification but also for specifying the brain activity of different humans. Such unique biometric data are extracted using various neuroimaging technologies. Although the literature has reviewed the extraction and application of brain fingerprints via electroencephalogram (EEG), little work has been done in presenting a comprehensive review that covers various neuroimaging techniques for extracting brain fingerprints. This article presents a systematic review of recent scientific literature that focuses on brain fingerprint identification using four major neuroimaging techniques, namely, EEG, magnetic resonance imaging (MRI), magnetoencephalography (MEG), and functional near-infrared spectroscopy (fNIRS). It first summarizes the data acquisition methods and the popular data sets, which are organized in the form of graphs and tables for intuitive comparison. Next, this article analyzes the advantages and disadvantages of brain fingerprint feature extraction methods based on different neuroimaging techniques and proposes an application trend and comparative analysis of identity recognition algorithms from the perspective of computational technology. Finally, we elaborate on the open questions and potential for further research.