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Personalized Mobile eHealth Services for Secure User Access Through a Multi Feature Biometric Framework

Author

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  • Georgios C. Manikis

    (Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Greece)

  • Marios Spanakis

    (Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Greece)

  • Emmanouil G. Spanakis

    (Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Greece)

Abstract

Humans have various features that differentiates one person from another which can be used to identify an individual for security purposes. These biometrics can authenticate or verify a person's identity and can be sorted in two classes, physiological and behavioural. In this article, the authors present their results of experimentation on publicly available facial images and the efficiency of a prototype version of SpeechXRays, a multi-modal biometric system that uses audio-visual characteristics for user authentication in eHealth platforms. Using the privacy and security mechanism provided, based on audio and video biometrics, medical personnel are able to be verified and subsequently identified for two different eHealth applications. These verified persons are then able to access control, identification, workforce management or patient record storage. In this work, the authors argue how a biometric identification system can greatly benefit healthcare, due to the increased accuracy of identification procedures.

Suggested Citation

  • Georgios C. Manikis & Marios Spanakis & Emmanouil G. Spanakis, 2019. "Personalized Mobile eHealth Services for Secure User Access Through a Multi Feature Biometric Framework," International Journal of Reliable and Quality E-Healthcare (IJRQEH), IGI Global, vol. 8(1), pages 40-51, January.
    • Handle: RePEc:igg:jrqeh0:v:8:y:2019:i:1:p:40-51
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    Cited by:

    1. Xiaochen Wang & Tao Wang, 2023. "Construction and Application of a Big Data Analysis Platform for College Music Education for College Students' Mental Health," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 19(4), pages 1-16, April.

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