A robust ECG steganography method

Optimizing Wavelet ECG Watermarking to Maintain Measurement Performance According to Industrial Standard

Abstract: Watermarking is currently investigated as an efficient and safe method of embedding additional patient or environment-related data into the electrocardiogram. This paper presents experimental work on the assessment of the loss of ECG (electrocardiogram signal) diagnostic quality from the industrial standard EN60601-2-25:2015 point of view. We implemented an original time-frequency watermarking technique with an adaptive beat-to-beat lead-independent data container design. We tested six wavelets, six coding bit depth values (including the automatic noise-dependent one) and two types of watermark content to find the conditions that are necessary for watermarked ECG to maintain the compliance with International Electrotechnical Commission (IEC) requirements for interpretation performance. Unlike other authors, we did not assess the differences of signal values, but errors in ECG wave delineation results. The results of a total of 7300 original and watermarked 10 s ECGs were statistically processed to reveal possible interpretation quality degradation due to watermarking. Finally we found (1) the Symlet of 11-th order as the best of the wavelets that were tested; (2) the important role of ECG wave delineation and noise tracking procedures; (3) the high influence of the watermark-to-noise similarity of amplitude and values distribution and (4) the stability of the watermarking capacity for different heart rates in atrial rhythms.

Steganography techniques for ECG signals : A survey

Abstract: Medical Images have been widely used to diagnose and detect the abnormalities in the human body. In this study, we have focused on ECG (Electrocardiography) signals which play a vital role in diagnosing Cardio Vascular Disease (CVD). CVD is most prevalent among the people because of changing lifestyle, Age, Tobacco, etc. According to the WHO (World Health Organization) report in 2012, around 17 million people die each year because of CVD, which represents 31% of the overall death rate. Due to the advancement in the e-Health care system, most of the ECG signals along with the patient's sensitive data are transmitted among doctors and hospitals for detailed analysis. According to the HIPAA act, it should be made sure that patient's details are to be sent securely during the transmission. In this study various ECG Steganography techniques that have been used by researchers are discussed; in which patient details and diagnosis report are embedded into ECG signals.

A Brief Survey of Steganographic Methods for ECG Signal

Abstract: The following paper represents a survey of steganography techniques suitable for usage in ECG. A few steganographic methods have been discussed below, it has been believed that these methods can be exploited to bring out more techniques suitable for ECG. The objective of this paper is to provide a comprehensive survey of existing steganographic techniques for ECG.

A new steganographic method using Contourlet Transform

Abstract: The technique, digital steganography is a secret data hiding scheme which involves hiding data in multimedia files. Steganographic methods embed secret data in the cover media with minimum visual and statistical distortion. This paper introduces a new steganographic method in transform domain based on contourlet PDFB (pyramidal directional filter bank) based transform. Contourlet is a multiscale and multidirectional transform domain, which provides the both spatial and frequency domain information. This method also uses the wavelet based compression technique like that of JPEG2000 on the secret data for transferring more information with fewer data. The approximation sub-band is embedded in the contourlet coefficients of the cover image. Approximation subband is multiplied by a constant factor k, which is determined experimentally. Modified values of approximation sub-band are embedded in the contourlet subband of the cover image by replacing them directly. Experimental results give that the proposed method has a good imperceptibility and to show this, the method uses four different visual quality metrics.

A Real-Time QRS Detection Algorithm

Abstract: We have developed a real-time algorithm for detection of the QRS complexes of ECG signals. It reliably recognizes QRS complexes based upon digital analyses of slope, amplitude, and width. A special digital bandpass filter reduces false detections caused by the various types of interference present in ECG signals. This filtering permits use of low thresholds, thereby increasing detection sensitivity. The algorithm automatically adjusts thresholds and parameters periodically to adapt to such ECG changes as QRS morphology and heart rate. For the standard 24 h MIT/BIH arrhythmia database, this algorithm correctly detects 99.3 percent of the QRS complexes.

Security and Privacy Issues in Wireless Sensor Networks for Healthcare Applications

Abstract: The use of wireless sensor networks (WSN) in healthcare applications is growing in a fast pace. Numerous applications such as heart rate monitor, blood pressure monitor and endoscopic capsule are already in use. To address the growing use of sensor technology in this area, a new field known as wireless body area networks (WBAN or simply BAN) has emerged. As most devices and their applications are wireless in nature, security and privacy concerns are among major areas of concern. Due to direct involvement of humans also increases the sensitivity. Whether the data gathered from patients or individuals are obtained with the consent of the person or without it due to the need by the system, misuse or privacy concerns may restrict people from taking advantage of the full benefits from the system. People may not see these devices safe for daily use. There may also possibility of serious social unrest due to the fear that such devices may be used for monitoring and tracking individuals by government agencies or other private organizations. In this paper we discuss these issues and analyze in detail the problems and their possible measures.

The MIT-BIH Arrhythmia Database on CD-ROM and software for use with it

Abstract: A compact-disk ROM containing the Massachusetts Institute of Technology (MIT)-Boston's Beth Israel Hospital (BIH) Arrhythmia Database as well as a large number of supplementary recordings assembled for various research projects was produced. In all, the CD-ROM contains approximately 600 megabytes of digitized electrocardiograms (ECG) recordings, most with beat-by-beat annotations, having a total duration in excess of 200 hours. The CD-ROM format makes this substantial collection of ECGs accessible to researchers with PCs as well as those with larger computer systems. The contents of the CD-ROM and the issues involved in its production are described. Software for use with the CD-ROM as well as for development of similar databases is also described. >

ECG data compression using cut and align beats approach and 2-D transforms

Abstract: A new electrocardiogram (ECG) data compression method is presented which employs a two dimensional (2-D) transform. This 2-D transform method utilizes the fact that ECG signals generally show two types of redundancies-between adjacent heartbeats and between adjacent samples. A heartbeat data sequence is cut and beat-aligned to form a 2-D data array. Any 2-D compression method can then be applied. Transform coding using the 2-D discrete cosine transform (DCT) [2-D DCT] is employed here as an example. Using selections from the MIT-BIH arrhythmia and Medtronic databases, results are presented that illustrate substantial improvement in compression ratio over one-dimensional methods for comparable percent root-mean-square difference (PRD).

An optimized watermarking technique based on self-adaptive DE in DWT-SVD transform domain

Abstract: The performance of differential evolution (DE) algorithm is significantly affected by its parameters setting that are highly problem dependent. In this paper, an optimal discrete wavelet transform-singular value decomposition (DWT-SVD) based image watermarking scheme using self-adaptive differential evolution (SDE) algorithm is presented. SDE adjusts the mutation factor F and the crossover rate Cr dynamically in order to balance an individual's exploration and exploitation capability for different evolving phases. Two-level DWT is applied to the cover image to transform it into sub-bands of different frequencies and then apply the SVD to each sub-band at level second. After applying one-level DWT to the watermark and subsequent application of SVD, the principal components of each sub-band are properly scaled down by multiplying with different scaling factors to make the watermark invisible. These scaled principal components are inserted into the singular value matrix of the corresponding blocks of the host image. The scaling factors are optimized using the self-adaptive DE algorithm to obtain the highest possible robustness with better imperceptibility. Experimental results show that the proposed scheme maintains a satisfactory image quality and watermark can still be identified after various attacks even though the watermarked image is seriously distorted.