Differential Watermarking of Multilead ECG Baseline

Digital watermarking has been widely recognized as an effective tool for embedment of auxiliary data in the host record. This paper presents a new method of watermarking using lead-to-lead difference of values in the baseline of the host electrocardiogram. The method starts with delineation of the baseline and uses Kirchoff voltage law or interpolation to predict any selected lead from the remaining ones. Next, the difference between the predicted and actual value is considered as noise and subjects to measurement of level and distribution in the time frame of baseline. The watermark with patient data or results of accompanying measurements is coded accordingly to mimic the noise. Replacement of the baseline noise with the watermark data ends the process. With 12-lead CSE files and respective reference borders of PQ and TP segments, the capacity of watermark achieved 3875 bits per second, while the diagnostic value of the ECG remains untouched.

[1]  Weiming Zhang,et al.  Protecting patient confidential information based on ECG reversible data hiding , 2015, Multimedia Tools and Applications.

[2]  Minghong Liao,et al.  Wavelet-Based Watermarking and Compression for ECG Signals with Verification Evaluation , 2014, Sensors.

[3]  P. Cochat,et al.  Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.

[4]  V. B. Raskar,et al.  SURVEY PAPER ON WAVELET BASED ECG STEGANOGRAPHY , 2015 .

[5]  Bor-Shing Lin,et al.  Preserving privacy of online digital physiological signals using blind and reversible steganography , 2017, Comput. Methods Programs Biomed..

[6]  Omar Farooq,et al.  Digital Watermarking of ECG Data for Secure Wireless Commuication , 2010, 2010 International Conference on Recent Trends in Information, Telecommunication and Computing.

[7]  Nilanjan Dey,et al.  Watermarking in Biomedical Signal Processing , 2017 .

[8]  S. Edward Jero,et al.  Curvelets-based ECG steganography for data security , 2016 .

[9]  Chien-Ding Lee,et al.  A Cryptographic Key Management Solution for HIPAA Privacy/Security Regulations , 2008, IEEE Transactions on Information Technology in Biomedicine.

[10]  P. Augustyniak.  Time-frequency modelling and discrimination of noise in the electrocardiogram. , 2003, Physiological measurement.

[11]  Walter Bender,et al.  Techniques for data hiding , 1995, Electronic Imaging.

[12]  P. Augustyniak.  Analysis of ECG bandwidth gap as a possible carrier for supplementary digital data , 2012, 2012 Computing in Cardiology.

[13]  K. P. Indiradevi,et al.  Integer-to-Integer Wavelet Transform Based ECG Steganography for Securing Patient Confidential Information , 2016 .

[14]  Piotr Augustyniak,et al.  Optimizing Wavelet ECG Watermarking to Maintain Measurement Performance According to Industrial Standard , 2018, Sensors.

[15]  Ayman Ibaida,et al.  Wavelet-Based ECG Steganography for Protecting Patient Confidential Information in Point-of-Care Systems , 2013, IEEE Transactions on Biomedical Engineering.