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Abstrakty
Nowadays healthcare is a standout amongst the most rapidly developing application zone in body area networks (BANs). BANs are anticipated to play a significant role in the stream of patient-health monitoring. To provide, secure BAN access to the entire system without disturbing the confidentiality of patients’ therapeutic data is a major challenge. Security of the BAN can be improved by using a polynomial curve-based steganography technique. The performance of the proposed BAN is evaluated by using a Fourier transform and Wavelet transform. The results of the proposed BAN are presented and compared for both the transforms.
Rocznik
Tom
Strony
171--177
Opis fizyczny
Bibliogr. 17 poz., rys., tab.
Twórcy
autor
- Department of ECE, SSN College of Engineering, 603110, Chennai, India
autor
- Department of ECE, SSN College of Engineering, 603110, Chennai, India
Bibliografia
- [1] UN (2014), World population ageing 2013, Statistical Papers - United Nations (Ser. A), Population and Vital Statistics Report, UN, New York, https://doi.org/10.18356/30d0966c-en.
- [2] Weinstein R. RFID: A technical overview and its application to the enterprise. IT Prof. 2005;7(3)27-33.
- [3] Bulling A, Blanke U, Schiele B. A tutorial on human activity recognition using body-worn inertial sensors. ACM Comput Surveys (CSUR). 2014;46(3):33.
- [4] Galzarano S, Giannantonio R, Liotta A, Fortino G. A task-oriented framework for networked wearable computing. IEEE Trans Autom Sci Eng. 2016;13(2)621-638.
- [5] Watanabe H, Kawarasaki M, Sato A, Yoshida K. Wearable ecg monitoring and alerting system associated with smartphone: iHeart. Int J E-Health Med Commun (IJEHMC). 2013;4(4)1-6.
- [6] Milenković A, Otto C, Jovanov E. Wireless sensor networks for personal health monitoring: issues and an implementation. Comput Commun. 2006;29(13):2521-2533.
- [7] Otto C, Milenković A, Sanders C, Jovanov E. System architecture of a wireless body area sensor network for ubiquitous health monitoring. J Mob Multimedia. 2006;1(4):307-326.
- [8] Movassaghi S, Abolhasan M, Lipman J, et al. Wireless body area networks: a survey. IEEE Commun Surv Tutor. 2014;16,(3):1658-1686
- [9] Gope P, Hwang T. BSN-Care: A secure IOT based modern healthcare system using body sensor network. IEEE Sensors J. 2016: 16(5):1368-1376.
- [10] Azariadi D, Tsoutsouras V, Xydis S, Dimitrios D. ECG signal analysis and arrhythmia detection on IoT wearable medical devices. 5th International Conference on Modern Circuits and Systems Technologies (MOCAST), 2016.
- [11] Venkatasubramanian KK, Banerjee A, Gupta S. Plethysmogram-based Secure Inter-Sensor Communication in Body Area Networks. In: Proceedings - IEEE Military Communications Conference MILCOM. 2008
- [12] Venkatasubramanian KK, Banerjee A, Gupta S. PSKA: Usable and Secure Key Agreement Scheme for Body Area Networks. IEEE Trans Information Technology in Biomedicine. 2010;14(1):60-68.
- [13] Wang W, Wang H, Peng D, Sharif H. Secure Stochastic ECG Signals Based on Gaussian Mixture Model for e-Healthcare systems. IEEE Systems Journal. 2011;5(4):564-573.
- [14] Yuce MR. Implementation of wireless body area networks for healthcare systems. Sensors and Actuators A: Physical. 2010;162(1):116-129.
- [15] Chakravorthy R. A Programmable service architecture for mobile medical care. 4th Annual. IEEE Int Conf Pervasive Comput Commun Workshop (PERSOMW). 2006.
- [16] Anbarjafari G Demirel H. Image super resolution based on interpolation of wavelet domain high frequency subbands and the spatial domain input image. ETRI J. 2010:32(3):390-394.
- [17] Moody GB, Mark RG. The impact of the mit-bih arrhythmia database. IEEE Eng Med Biol Mag. 2001;20(3):45-50.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-35c99fea-e7c2-4a35-b806-9810b3008665