Medical biometrics in mobile health monitoring

This work investigates the feasibility of ECG-based identity management in mobile health monitoring applications. A body area network that operates in conjunction with ECG biometric recognition is explored for mobile monitoring of patients, rescuers, pilots, soldiers, or field agents in general. Among the major challenges of this technology is the stability of the signals over the monitoring duration. Time dependency is responsible for ECG destabilization, which becomes a significant issue for reliable monitoring. We propose a novel framework that addresses this inadequacy, by updating a gallery template when feature matching is compromised. In addition, strategies for tackling privacy issues in medical data management are proposed. A protocol level solution is discussed, to deal with the ethical issues of this technology. An automatic way of aggregating and managing personal information is presented, designated to operate on the basis of anonymity. The experimental performance measured over long-ECG recordings demonstrates promising results. Copyright © 2010 John Wiley & Sons, Ltd.

[1]  Brenda K. Wiederhold,et al.  ECG to identify individuals , 2005, Pattern Recognit..

[2]  Carmen C. Y. Poon,et al.  A novel biometrics method to secure wireless body area sensor networks for telemedicine and m-health , 2006, IEEE Communications Magazine.

[3]  Dimitrios Tzovaras,et al.  Unobtrusive Multimodal Biometric Authentication: The HUMABIO Project Concept , 2008, EURASIP J. Adv. Signal Process..

[4]  Adriaan van Oosterom,et al.  Geometrical aspects of the interindividual variability of multilead ECG recordings , 2001, IEEE Transactions on Biomedical Engineering.

[5]  G. Andrassy,et al.  Mental Stress May Induce QT‐Interval Prolongation and T‐Wave Notching , 2007, Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc.

[6]  Dimitrios Hatzinakos,et al.  Biometric Methods for Secure Communications in Body Sensor Networks: Resource-Efficient Key Management and Signal-Level Data Scrambling , 2008, EURASIP J. Adv. Signal Process..

[7]  Yuan-Ting Zhang,et al.  Physiological Signal Based Entity Authentication for Body Area Sensor Networks and Mobile Healthcare Systems , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[8]  H. Rau,et al.  Responses of the T-wave amplitude as a function of active and passive tasks and beta-adrenergic blockade. , 1991, Psychophysiology.

[9]  L. Biel,et al.  ECG analysis: a new approach in human identification , 1999, IMTC/99. Proceedings of the 16th IEEE Instrumentation and Measurement Technology Conference (Cat. No.99CH36309).

[10]  Yu Hen Hu,et al.  One-lead ECG for identity verification , 2002, Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology.

[11]  T. Ho,et al.  Heart rate variability of children with mitral valve prolapse. , 2000, Journal of electrocardiology.

[12]  H. Pipberger,et al.  The Corrected Orthogonal Electrocardiogram and Vectorcardiogram in 510 Normal Men (Frank Lead System) , 1964, Circulation.

[13]  Yongjin Wang,et al.  Integrating Analytic and Appearance Attributes for Human Identification from ECG Signals , 2006, 2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference.

[14]  D. Hatzinakos,et al.  Fusion of ECG sources for human identification , 2008, 2008 3rd International Symposium on Communications, Control and Signal Processing.

[15]  D. Hatzinakos,et al.  A receiver-based variable-size-burst equalization strategy for spectrally efficient wireless communications , 2005, IEEE Transactions on Signal Processing.

[16]  William Stallings,et al.  Cryptography and Network Security: Principles and Practice , 1998 .

[17]  A. Szabo,et al.  The combined effects of orthostatic and mental stress on heart rate, T-wave amplitude, and pulse transit time , 2004, European Journal of Applied Physiology and Occupational Physiology.

[18]  D. Hatzinakos,et al.  Secure methods for fuzzy key binding in biometric authentication applications , 2008, 2008 42nd Asilomar Conference on Signals, Systems and Computers.

[19]  Jiankun Hu,et al.  Corresponding author’s address: , 2022 .

[20]  A Nava,et al.  The effects of sympathetic stimulation induced by mental stress on signal-averaged electrocardiogram. , 1995, International journal of cardiology.

[21]  Jonathan Klein,et al.  Frustrating the user on purpose: a step toward building an affective computer , 2002, Interact. Comput..

[22]  D. Watenpaugh,et al.  Interactive effects of mental and physical stress on cardiovascular control. , 2002, Journal of applied physiology.

[23]  Yong Wang,et al.  ISAR Imaging of Rotating Target with Equal Changing Acceleration Based on the Cubic Phase Function , 2008, EURASIP J. Adv. Signal Process..

[24]  W. Eichinger,et al.  RT and systolic blood pressure variability after sympathetic stimulation during positive tilt in healthy volunteers , 1994, Computers in Cardiology 1994.

[25]  Dimitrios Hatzinakos,et al.  ECG biometric analysis in cardiac irregularity conditions , 2009, Signal Image Video Process..

[26]  Martin Wattenberg,et al.  A fuzzy commitment scheme , 1999, CCS '99.

[27]  Nilanjan Sarkar,et al.  Online stress detection using psychophysiological signals for implicit human-robot cooperation , 2002, Robotica.

[28]  Dimitrios Hatzinakos,et al.  Analysis of Human Electrocardiogram for Biometric Recognition , 2008, EURASIP J. Adv. Signal Process..

[29]  D. Hatzinakos,et al.  ECG Biometric Recognition Without Fiducial Detection , 2006, 2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference.

[30]  Konstantinos N. Plataniotis,et al.  Electrocardiogram (ECG) Biometric for Robust Identification and Secure Communication , 2010 .

[31]  E. Krouk,et al.  Error Correcting Coding and Security for Data Networks: Analysis of the Superchannel Concept , 2007 .

[32]  A. van Oosterom,et al.  Geometrical factors affecting the interindividual variability of the ECG and the VCG. , 2000, Journal of electrocardiology.