Authors:
Angelos Fylakis
;
Anja Keskinarkaus
;
Vesa Kiviniemi
and
Tapio Seppänen
Affiliation:
University of Oulu and Oulu University Hospital, Finland
Keyword(s):
Data Hiding, Data Management, Brain Research, Multimodality.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Cloud Computing
;
e-Health
;
Health Information Systems
;
Healthcare Management Systems
;
Platforms and Applications
;
Software Systems in Medicine
Abstract:
Simultaneous MREG and EEG recordings are vastly used in neurobiology, but so far they are stored and
handled as separate files. This paper proposes a method to combine those two entities with the objective of
establishing data management efficiency, while secondary objectives are confidentiality, availability and
reliability in data. To be more specific, it is a reversible data hiding method for hiding EEG in MREG with
the ability of fully recovering MREG and the embedded EEG signal. It is based on histogram shifting,
exploiting data quantization and Region of Interest segmentation. The embedding procedure maintains
temporal synchronization between EEG and 32-bit MREG making it a novel data hiding application. It is
demonstrated through experiments that MREG maintains high perceptual fidelity and also verified that after
EEG extraction and acquisition of every electrode’s sample, MREG is fully reversed to its exact initial state.