IEICE Transactions, Special issue on Sensing, Wireless Networking, Data Collection, Analysis and Processing Technologies for Ambient Intelligence with Internet of Things, 2019. Paper doi abstract bibtex
Electroencephalography (EEG) for biometric authentication has received some attention in recent years. In this paper, we explore the effect of three simple EEG related authentication tasks, namely resting, thinking about a picture, and moving a single finger, on mobile, low-cost, single electrode based EEG authentication. We present details of our authentication pipeline, including extracting features from the frequency power spectrum and MFCC, and training a multilayer perceptron classifier for authentication. For our evaluation we record an EEG dataset of 27 test subjects. We use a baseline, task-agnostic, and task-specific evaluation setup to investigate if different tasks can be used in place of each other for authentication. We further evaluate if tasks themselves can be told apart from each other. Evaluation results suggest that tasks differ, hence to some extent are distinguishable, as well as that our authentication approach can work in a task-specific as well as in a task-agnostic manner.