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- W3046207364 abstract "Biometric authentication is becoming popular in a varied range of applications because of its unique specificity for an individual user. In this context, electro-encephalogram (EEG) signals from a user is an interesting candidate for authentication. In this work, we specifically focus on the EEG signal corresponding to the human eye-blink to create an authentication system that could be used to distinguish between multiple users accurately and efficiently while also being burden-less and convenient to the users. We use a dataset of eye-blink related EEG signals, collected from 20 users, to study our solution. Our results show that blink signals can be used for accurately distinguishing between different users and hence can be used for authentication." @default.
- W3046207364 created "2020-08-03" @default.
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- W3046207364 date "2020-06-01" @default.
- W3046207364 modified "2023-10-16" @default.
- W3046207364 title "Blink to Get In: Biometric Authentication for Mobile Devices using EEG Signals" @default.
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- W3046207364 doi "https://doi.org/10.1109/icc40277.2020.9148741" @default.
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