Publication detail

Privacy of online handwriting biometrics related to biomedical analysis

FAÚNDEZ ZANUY, M. MEKYSKA, J.

Original Title

Privacy of online handwriting biometrics related to biomedical analysis

English Title

Privacy of online handwriting biometrics related to biomedical analysis

Type

book chapter

Language

en

Original Abstract

Online handwritten signals analysis for biomedical applications has received lesser attention from the international scientific community than other biometric signals such as electroencephalogram (EEG), electrocardiogram (ECG), magnetic resonance imaging signals (MRI), speech, etc. However, handwritten signals are useful for biometric security applications, especially in the case of signature, but to support pathology diagnose/monitoring as well. Obviously, while utilising handwriting in one field, there are implications in the other one and privacy concerns can arise. A good example is a biometric security system that stores the whole biometric template. It is desirable to reduce the template to the relevant information required for security, removing those characteristics that can permit the identification of pathologies. In this paper, we summarize the main aspects of handwritten signals with special emphasis on medical applications (Alzheimer's disease, Parkinson's disease, mild cognitive impairment, essential tremor, depression, dysgraphia, etc.) and security. In addition, it is important to remark that health and security issues cannot be easily isolated, and an application in one field should take care of the other.

English abstract

Online handwritten signals analysis for biomedical applications has received lesser attention from the international scientific community than other biometric signals such as electroencephalogram (EEG), electrocardiogram (ECG), magnetic resonance imaging signals (MRI), speech, etc. However, handwritten signals are useful for biometric security applications, especially in the case of signature, but to support pathology diagnose/monitoring as well. Obviously, while utilising handwriting in one field, there are implications in the other one and privacy concerns can arise. A good example is a biometric security system that stores the whole biometric template. It is desirable to reduce the template to the relevant information required for security, removing those characteristics that can permit the identification of pathologies. In this paper, we summarize the main aspects of handwritten signals with special emphasis on medical applications (Alzheimer's disease, Parkinson's disease, mild cognitive impairment, essential tremor, depression, dysgraphia, etc.) and security. In addition, it is important to remark that health and security issues cannot be easily isolated, and an application in one field should take care of the other.

Keywords

biomedical analysis; online handwriting biometrics privacy; biometric signals; online handwritten signals analysis

Released

01.11.2017

Publisher

The Institution of Engineering and Technology

Location

London

ISBN

9781785612077

Book

User-Centric Privacy and Security in Biometrics

Pages from

17

Pages to

39

Pages count

23

URL

BibTex


@inbook{BUT142217,
  author="Marcos {Faúndez Zanuy} and Jiří {Mekyska}",
  title="Privacy of online handwriting biometrics related to biomedical analysis",
  annote="Online handwritten signals analysis for biomedical applications has received lesser attention from the international scientific community than other biometric signals such as electroencephalogram (EEG), electrocardiogram (ECG), magnetic resonance imaging signals (MRI), speech, etc. However, handwritten signals are useful for biometric security applications, especially in the case of signature, but to support pathology diagnose/monitoring as well. Obviously, while utilising handwriting in one field, there are implications in the other one and privacy concerns can arise. A good example is a biometric security system that stores the whole biometric template. It is desirable to reduce the template to the relevant information required for security, removing those characteristics that can permit the identification of pathologies. In this paper, we summarize the main aspects of handwritten signals with special emphasis on medical applications (Alzheimer's disease, Parkinson's disease, mild cognitive impairment, essential tremor, depression, dysgraphia, etc.) and security. In addition, it is important to remark that health and security issues cannot be easily isolated, and an application in one field should take care of the other.",
  address="The Institution of Engineering and Technology",
  booktitle="User-Centric Privacy and Security in Biometrics",
  chapter="142217",
  doi="10.1049/PBSE004E_ch",
  howpublished="print",
  institution="The Institution of Engineering and Technology",
  year="2017",
  month="november",
  pages="17--39",
  publisher="The Institution of Engineering and Technology",
  type="book chapter"
}