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Mobile Brainwaves: On the Interchangeability of Simple Authentication Tasks with Low-Cost, Single-Electrode EEG Devices
Eeva-Sofia HAUKIPURO Ville KOLEHMAINEN Janne MYLLÄRINEN Sebastian REMANDER Janne SALO Tuomas TAKKO Le Ngu NGUYEN Stephan SIGG Rainhard Dieter FINDLING
Publication
IEICE TRANSACTIONS on Communications
Vol.E102-B
No.4
pp.760-767 Publication Date: 2019/04/01 Publicized: 2018/10/15 Online ISSN: 1745-1345
DOI: 10.1587/transcom.2018SEP0016 Type of Manuscript: Special Section PAPER (Special Section on Sensing, Wireless Networking, Data Collection, Analysis and Processing Technologies for Ambient Intelligence with Internet of Things) Category: Keyword: biometrics, classification, EEG, mobile, user authentication,
Full Text: PDF(1.6MB)>>
Summary:
Biometric authentication, namely using biometric features for authentication is gaining popularity in recent years as further modalities, such as fingerprint, iris, face, voice, gait, and others are exploited. We explore the effectiveness of three simple Electroencephalography (EEG) related biometric authentication tasks, namely resting, thinking about a picture, and moving a single finger. We present details of the data processing steps we exploit for authentication, including extracting features from the frequency power spectrum and MFCC, and training a multilayer perceptron classifier for authentication. For evaluation purposes, we record an EEG dataset of 27 test subjects. We use three setups, baseline, task-agnostic, and task-specific, to investigate whether person-specific features can be detected across different tasks for authentication. We further evaluate, whether different tasks can be distinguished. Our results suggest that tasks are distinguishable, as well as that our authentication approach can work both exploiting features from a specific, fixed, task as well as using features across different tasks.
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