Chaotic Encryption of ECG Signals with a Random Kernel Approach

[1]     Alan Jovic1, Kresimir Jozic, Davor Kukolja, Kresimir Friganovic, Mario Cifrek.: Challenges in Designing Software Architectures for Web Based Biomedical Signal Analysis. INA - industrija nafte, d.d Avenija Veceslava Holjevca 10, p.p. 555, HR-10002 Zagreb (2018)

[2]     Fontana, J.M.; Farooq, M.; Sazonov, E. Automatic Ingestion Monitor: A Novel Wearable Device for Monitoring of Ingestive Behavior. IEEE Trans. Biomed. Eng. 2014, 61, 1772–1779.

[3]     K. Wellington, Cyber-attacks on medical devices and hospital networks: legal gaps and regulatory solutions. Santa Clara High Tech. L. J. 139 (2013)

[4]     J. Wang et al., A research on security and privacy issues for patient related data in medical organization system. Int. J. Secur. Appl., 287–298 (2013)

[5]     EU Directive 95. http://www.dataprotection.ie/docs/EU_Directive_95/46/EC_Chapter1/92.htm The Department of Health, Australian Government. PCEHR: Personally Controlled Electronic Health Record System Operator: Annual Report 2012–2013

[6]     Health information privacy beyond HIPAA: a 2018 environmental scan of major trends and challenges. National Committee on Vital and Health Statistics. https://www.ncvhs.hhs.gov/wp- content/uploads/2018/02/NCVHS-Beyond-HIPAA_Report-Final-02- 08-18.pdf. Accessed April 3, 2018.

[7]     Recommendations on de-identification of protected health information under HIPAA. National Committee on Vital and Health Statistics. https://www.ncvhs.hhs.gov/wp-content/uploads/2013/12/2017-Ltr-Privacy-DeIdentification-Feb-23-Final-w-sig.pdf. Accessed April 3, 2018.

[8]     Hoe Tung Yew,  Yudha Aditya, Haikal Satrial1, Eko Supriyanto and Yuan Wen Hau1 Telecardiology System for fourth generation heterogeneous wireless networks. Asian Research Publishing Network (ARPN), 2015.

[9]     Sufi F, Khalil I. Enforcing secured ECG transmission for real-time telemonitoring: a joint encoding, compression, encryption mechanism. security and communication networks. Security and Communication Networks 2008

[10]  Cryptography and Network Security Fourth Edition by William Stallings

[11]  Ching-Kun Chen, Chun-Liang Lin, Shyan-Lung Lin and Cheng-Tang Chiang. Data Encryption and Transmission Based on Personal ECG Signals. International Journal of sensor networks 2015.

[12]  Shalini Sahay, A.K.Wadhwani and Sulochana Wadhwani: A Survey Approach on ECG Feature Extraction Techniques. International Journal of Computer Applications (0975 – 8887), 2015.

[13]  Kamal Nasrollahi, Mohammad A. Haque, Ramin Irani and Thomas B. Moeslund: Contact-Free Heartbeat Signal for Human Identification and Forensics. Springer International Publishing AG 2017.

[14]  Mohamad O. Diab, Alaa Seif, Mohamad El-Abed, Maher Sabbah. Individual Identification Using ECG Signals. Journal of Computer and Communications, 2018

[15]  Sufi F, Khalil I, Hu J. Chapter 17: ECG-Based Authentication, Handbook of Information and Communication Security, Stavroulakis P, Stamp M (Eds.), Springer 2010, ISBN978-3-642-04116-7 (Print) 978-3-642-04117-4 (Online) DOI10.1007/978-3-642-04117-4; 309–331

[16]  Diana P. Tobón and Tiago H. Falk. Online ECG quality assessment for context-aware wireless body area networks. 2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE).

[17]  Jusak Jusak and Seedahmed S. Mahmoud. A Novel and Low Processing Time ECG Security Method Suitable for Sensor Node Platforms. International Journal of Communication Networks and Information Security (IJCNIS) 2018

[18]  Seedahmed S.Mahmoud and Jusak Jusak. Wavelets in ECG Security Application. Published in IntechOpen, 2018.

[19]  Interpreting ECGs in Clinical Practice (2nd edn). Sercan Okutucu and Ali Oto, 2018.

[20]  Maria Salsone,Basilio Vescio,Andrea Quattrone,Ferdinando Roccia,Miriam Sturniolo,Francesco Bono,Umberto Aguglia,Antonio Gambardella and Aldo Quattrone. Cardiac parasympathetic index identifies subjects with adult obstructive sleep apnea: A simultaneous polysomnographic-heart rate variability studys. PLoS ONE 13(3): e0193879,2018

[21]  M. BASSIOUNI, W.KHALEFA, E.A. El-DAHSHAN and ABDEL-BADEEH. M. SALEM. A Machine Learning Technique for Person Identification using ECG Signals. Published in International Journal of Applied Physics, 2016.

[22]  Chao-Jun Hu, Jian-Bo Pan, Guang Song, Xiao-Ting Wen, Zi-Yan Wu, Si Chen, Wen-Xiu Mo, Feng-Chun Zhang, Jiang Qian, Heng Zhu and Yong-Zhe Li : Identification of Novel Biomarkers for Behcet Disease Diagnosis Using Human Proteome Microarray Approach. Molecular & Cellular Proteomics, 2017

[23]  R. Kubichek, “Mel-Cepstral Distance Measure for Objective Speech Quality Assessment,” Proceedings of The IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, pp. 125–128, 1993, Victoria, BC.

[24]  S. Wang, A. Sekey, A. Gersho, “An Objective Measure for Predicting Subjective Quality of Speech Coders,” IEEE Journal on selected areas in communications, Vol. 10, No. 5,pp. 819–829, 1992.

[25]  W. Yang, M. Benbouchta, R. Yantorno, “Performance of the Modified bark Spectral Distortion as an Objective Speech Quality Measure,” Proceedings of the IEEE International Conf.on Acoustic, Speech and Signal Processing (ICASSP), Vol. 1, Washington, USA,pp. 541–544. 1998

[27] R. E. Crochiere, J. E. Tribolet, and L. R. Rabiner, “An Interpretation of The Log Likelihood Ratio as a Measure of Waveform Coder Performance,” IEEE Transactions on Acoustics, Speech, And Signal Processing, Vol. Assp-28, No. 3, pp. 318–323, 1980.