The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
A autenticação biométrica, nomeadamente a utilização de funcionalidades biométricas para autenticação, está a ganhar popularidade nos últimos anos, à medida que outras modalidades, como impressão digital, íris, rosto, voz, marcha e outras, são exploradas. Exploramos a eficácia de três tarefas simples de autenticação biométrica relacionadas à eletroencefalografia (EEG), ou seja, descansar, pensar em uma imagem e mover um único dedo. Apresentamos detalhes das etapas de processamento de dados que exploramos para autenticação, incluindo a extração de recursos do espectro de potência de frequência e MFCC, e o treinamento de um classificador perceptron multicamadas para autenticação. Para fins de avaliação, registramos um conjunto de dados de EEG de 27 cobaias. Usamos três configurações, linha de base, independente de tarefa e específica de tarefa, para investigar se recursos específicos de pessoa podem ser detectados em diferentes tarefas para autenticação. Avaliamos ainda se diferentes tarefas podem ser distinguidas. Nossos resultados sugerem que as tarefas são distinguíveis, bem como que nossa abordagem de autenticação pode funcionar tanto explorando recursos de uma tarefa específica e fixa quanto usando recursos em tarefas diferentes.
Eeva-Sofia HAUKIPURO
Aalto University
Ville KOLEHMAINEN
Aalto University
Janne MYLLÄRINEN
Aalto University
Sebastian REMANDER
Aalto University
Janne SALO
Aalto University
Tuomas TAKKO
Aalto University
Le Ngu NGUYEN
Aalto University
Stephan SIGG
Aalto University
Rainhard Dieter FINDLING
Aalto University
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Eeva-Sofia HAUKIPURO, Ville KOLEHMAINEN, Janne MYLLÄRINEN, Sebastian REMANDER, Janne SALO, Tuomas TAKKO, Le Ngu NGUYEN, Stephan SIGG, Rainhard Dieter FINDLING, "Mobile Brainwaves: On the Interchangeability of Simple Authentication Tasks with Low-Cost, Single-Electrode EEG Devices" in IEICE TRANSACTIONS on Communications,
vol. E102-B, no. 4, pp. 760-767, April 2019, doi: 10.1587/transcom.2018SEP0016.
Abstract: 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.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2018SEP0016/_p
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@ARTICLE{e102-b_4_760,
author={Eeva-Sofia HAUKIPURO, Ville KOLEHMAINEN, Janne MYLLÄRINEN, Sebastian REMANDER, Janne SALO, Tuomas TAKKO, Le Ngu NGUYEN, Stephan SIGG, Rainhard Dieter FINDLING, },
journal={IEICE TRANSACTIONS on Communications},
title={Mobile Brainwaves: On the Interchangeability of Simple Authentication Tasks with Low-Cost, Single-Electrode EEG Devices},
year={2019},
volume={E102-B},
number={4},
pages={760-767},
abstract={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.},
keywords={},
doi={10.1587/transcom.2018SEP0016},
ISSN={1745-1345},
month={April},}
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TY - JOUR
TI - Mobile Brainwaves: On the Interchangeability of Simple Authentication Tasks with Low-Cost, Single-Electrode EEG Devices
T2 - IEICE TRANSACTIONS on Communications
SP - 760
EP - 767
AU - Eeva-Sofia HAUKIPURO
AU - Ville KOLEHMAINEN
AU - Janne MYLLÄRINEN
AU - Sebastian REMANDER
AU - Janne SALO
AU - Tuomas TAKKO
AU - Le Ngu NGUYEN
AU - Stephan SIGG
AU - Rainhard Dieter FINDLING
PY - 2019
DO - 10.1587/transcom.2018SEP0016
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E102-B
IS - 4
JA - IEICE TRANSACTIONS on Communications
Y1 - April 2019
AB - 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.
ER -