Experimental study on the effects of watermarking techniques on EEG-based application system performance

Trung Duy Pham, Dat Tran, Wanli Ma

Research output: A Conference proceeding or a Chapter in BookConference contribution

Abstract

Watermarking has been suggested as a means to improve security of e-Health systems or to add additional functionalities to such system. All watermarking methods alter the host signal to some extent, though the acceptability of this modification varies with the watermarking scheme and depends on a particular application. However, the effect of watermarking methods on Electroencephalogram (EEG)-based applications has not been investigated. In this paper, we propose a robust EEG watermarking scheme and experimentally investigate the impact of applying the proposed method on the recognition performance of some EEG-based application systems such as emotion recognition and user authentication. We have found that the proposed EEG watermarking scheme results in a small degradation of performance.

Original languageEnglish
Title of host publicationNeural Information Processing - Proceedings of the 24th International Conference (ICONIP 2017)
Place of PublicationGuangzhou, China
PublisherSpringer-Verlag London Ltd.
Pages662-671
Number of pages10
ISBN (Print)9783319701356
DOIs
Publication statusPublished - 26 Oct 2017
Event24th International Conference on Neural Information Processing, ICONIP 2017 - Guangzhou, China
Duration: 14 Nov 201718 Nov 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10639 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference24th International Conference on Neural Information Processing, ICONIP 2017
CountryChina
CityGuangzhou
Period14/11/1718/11/17

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Pham, T. D., Tran, D., & Ma, W. (2017). Experimental study on the effects of watermarking techniques on EEG-based application system performance. In Neural Information Processing - Proceedings of the 24th International Conference (ICONIP 2017) (pp. 662-671). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10639 LNCS). Guangzhou, China: Springer-Verlag London Ltd.. https://doi.org/10.1007/978-3-319-70136-3_70