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Authentication Study for Brain-Based Computer Interfaces Using Music Stimulations

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Book cover Algorithms and Architectures for Parallel Processing (ICA3PP 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12454))

Abstract

Electroencephalography (EEG) brain signals have been used in a number of pattern recognition studies. Due to the high degree of uniqueness and inherent security, EEG-based brain signals have been considered as a potential pattern for biometrics, especially for continuous authentication. Although previous research has been conducted with different visual stimuli, music stimuli for brain signal authentication are rarely considered. One unresolved question is whether these brain signals that change over time will affect the authentication results. An EEG database with 16 volunteers has been employed in the analysis to observe any changes in brain wave patterns as well as changes in authentication rates. The data were regularly collected over a period of four months while exposed to three different genres of music.

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Acknowledgment

Thank Mr. Leonard Marino and Ms. Vineetha Alluri for their support on the data collection.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, Adelphi University, Garden City, NY, 11530, USA

    Sukun Li

  2. Department of Computer Science, Texas A&M University-Commerce, Commerce, TX, 75428, USA

    Meikang Qiu

Authors
  1. Sukun Li
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  2. Meikang Qiu
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Corresponding author

Correspondence to Sukun Li .

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Editors and Affiliations

  1. Columbia University, New York, NY, USA

    Meikang Qiu

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Li, S., Qiu, M. (2020). Authentication Study for Brain-Based Computer Interfaces Using Music Stimulations. In: Qiu, M. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2020. Lecture Notes in Computer Science(), vol 12454. Springer, Cham. https://doi.org/10.1007/978-3-030-60248-2_46

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