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Journal ArticleDOI

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

11 Oct 2018-Sensors (Sensors (Basel))-Vol. 18, Iss: 10, pp 3401
TL;DR: 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 is presented and the Symlet of 11-th order is found as the best of the wavelets that were tested.
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.
Citations
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Journal ArticleDOI
TL;DR: Evaluation demonstrates the usefulness of the proposed methodology in successfully embedding the patient information without distorting the important medical information in an ECG signal.
Abstract: At present, a patient’s demography, such as name, age, and gender are stored separately from the acquired electrocardiogram (ECG) signal. This multiple storage mechanisms can create a severe threat to the reliability of diagnostics if the link between the demography data and the ECG signal breaks, either intentionally or unintentionally. This issue has become more prominent in recent years due to the use of a large number of wearable devices for physiological signal collection, especially in remote or non-clinical settings. In order to address this problem, in this paper, we propose a novel mechanism to embed patient’s information within an ECG signal without degrading the accuracy of the physiological information contained in the ECG signal. In this work, a methodology is presented to find the less-significant region of the ECG signal. Then, the patient information is hidden in this region by modifying the selected discrete cosine transform (DCT) coefficients of the signal using our proposed embedding and decoding algorithms. Moreover, the patient information hidden in the ECG signal is able to resist filtering attack, such as high-pass filtering, which generally occur with the ECG signal processing. This is achieved via the use of error buffers in the embedding algorithm. The proposed mechanism can extract the embedded patient information, either in the presence or without the filtering attack. Moreover, a specifically designed synchronization sequence is added to identify the patient data embedded regions of the ECG signal at the decoding end. Further, as a security measure, the embedded patient details are scrambled using a secret key to protect the privacy of the patient. Our evaluation demonstrates the usefulness of the proposed methodology in successfully embedding the patient information without distorting the important medical information in an ECG signal.

8 citations


Cites methods from "Optimizing Wavelet ECG Watermarking..."

  • ...In [11], Swierkosz and Augustyniak presented a mechanism, which uses optimized DWT to embedwatermark...

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Journal ArticleDOI
TL;DR: A comprehensive survey on data hiding techniques for smart healthcare applications is presented in this article, where the authors introduce various aspects of data hiding along with major properties, generic embedding and extraction process, and recent applications.
Abstract: Due to smart healthcare systems highly connected information and communications technologies, sensitive medical information and records are easily transmitted over the networks. However, stealing of healthcare data is increasing crime every day to greatly impact on financial loss. In order to this, researchers are developing various cost-effective bio-signal based data hiding techniques for smart healthcare applications. In this paper, we first introduce various aspects of data hiding along with major properties, generic embedding and extraction process, and recent applications. This survey provides a comprehensive survey on data hiding techniques, and their new trends for solving new challenges in real-world applications. Then, we survey the various notable bio-signal based data hiding techniques. The summary of some notable techniques in terms of their objective, type of data hiding, methodology and database used, performance metrics, important features, and limitations are also presented in tabular form. At the end, we discuss the major issues and research directions to explore the promising areas for future research.

7 citations

Journal ArticleDOI
TL;DR: Simulations confirmed that hidden bits were extracted without distortion and the original ECG signal can be completely recovered and the efficient reversible data hiding method is robust against attacks such as noise addition, inversion, truncation, translations, and so on.
Abstract: Based on the processing of one-dimensional fast discrete cosine transform (1D FDCT) coefficients, we present an efficient reversible data hiding method for electrocardiogram (ECG) signal. The proposed method is implemented in two phases. The purpose of phase-I is to classify the FDCT (host) bundles, where each input bundle will be attributed to one of four different bundles. The aim of phase-II is to embed data bits in the selected coefficients of the classified bundles according to a predetermined bit-index table (which generated from phase-I) via adaptive least significant bit (LSB) technique. Simulations confirmed that hidden bits were extracted without distortion and the original ECG signal can be completely recovered. Furthermore, a good perceived quality and a hiding capacity superior to existing techniques were achieved. Moreover, our method is robust against attacks such as noise addition, inversion, truncation, translations, and so on. Notice that the robustness is rarely seen in conventional reversible ECG steganography methods. Since this method has a fast computation speed, it is feasible for real-time applications and can be installed in the health care devices such as the wearable ECG measure equipment.

5 citations

Journal ArticleDOI
TL;DR: The Modified Dynamic Classification (MDC) algorithm based on the features of the ECG signal is proposed and the novelty is implemented in the compression, embedding, and classification stages to improve the security of patient’s health information.
Abstract: The Electrocardiogram (ECG) signal processing is one of the exciting research areas in recent days. Ensuring security to the patient’s confidential information is a demanding critical task in many healthcare systems. So, the traditional works developed the security mechanisms for embedding the original ECG signal with the image, audio, or video. But, it does not focus on reducing the size of the original message before transmitting it to others. Also, it has significant limitations of inefficient security, increased complexity, and reduced classification accuracy. To rectify this issue, our research proposed the new embedding mechanism to improve the security of patient’s health information. In this system, the original ECG signals compressed at the initial stage by using the proposed Dictionary Matrix Generation (DMG) algorithm. Then, the compressed signals embedded within the cover image by using the Bitwise Embedding (BE) mechanism. At the receiver side, the bedded goal is de-embedded and decompressed by using the DMG and BE algorithms. The features such as spectral and peak values of the signal are extracted for increasing the efficiency of classification. Classification and detection of abnormality present in ECG signal of patient is the most essential part. To achieve this, we proposed the Modified Dynamic Classification (MDC) algorithm based on the features. In this work, the novelty is implemented in the compression, embedding, and classification stages. The proposed system reduces the data loss during transmission, memory storage and time complexity. The overall process evaluated by using PTB diagnostic ECG database. In experiments, the proposed classification technique provides the accuracy of 98.39% and it proved that the proposed method had highest performances than existing methods such as PNN, SVM and RF classification.

4 citations


Cites background from "Optimizing Wavelet ECG Watermarking..."

  • ...But, these mechanisms have the limitations of reduced visual quality, increased complexity, and inefficient security [39]....

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Journal ArticleDOI
TL;DR: An improved electrocardiogram (ECG) steganography for the protection of patients’ sensitive data, such as blood pressure, glucose level, lipid profile, and other personal health information is presented.

2 citations

References
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Journal ArticleDOI
TL;DR: This work explores both traditional and novel techniques for addressing the data-hiding process and evaluates these techniques in light of three applications: copyright protection, tamper-proofing, and augmentation data embedding.
Abstract: Data hiding, a form of steganography, embeds data into digital media for the purpose of identification, annotation, and copyright. Several constraints affect this process: the quantity of data to be hidden, the need for invariance of these data under conditions where a "host" signal is subject to distortions, e.g., lossy compression, and the degree to which the data must be immune to interception, modification, or removal by a third party. We explore both traditional and novel techniques for addressing the data-hiding process and evaluate these techniques in light of three applications: copyright protection, tamper-proofing, and augmentation data embedding.

3,037 citations


"Optimizing Wavelet ECG Watermarking..." refers result in this paper

  • ...These ideas correspond to a general principle of steganography [19] and were also followed in our previous research [20]....

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Journal ArticleDOI
TL;DR: A robust single-lead electrocardiogram (ECG) delineation system based on the wavelet transform (WT), outperforming the results of other well known algorithms, especially in determining the end of T wave.
Abstract: In this paper, we developed and evaluated a robust single-lead electrocardiogram (ECG) delineation system based on the wavelet transform (WT). In a first step, QRS complexes are detected. Then, each QRS is delineated by detecting and identifying the peaks of the individual waves, as well as the complex onset and end. Finally, the determination of P and T wave peaks, onsets and ends is performed. We evaluated the algorithm on several manually annotated databases, such as MIT-BIH Arrhythmia, QT, European ST-T and CSE databases, developed for validation purposes. The QRS detector obtained a sensitivity of Se=99.66% and a positive predictivity of P+=99.56% over the first lead of the validation databases (more than 980,000 beats), while for the well-known MIT-BIH Arrhythmia Database, Se and P+ over 99.8% were attained. As for the delineation of the ECG waves, the mean and standard deviation of the differences between the automatic and manual annotations were computed. The mean error obtained with the WT approach was found not to exceed one sampling interval, while the standard deviations were around the accepted tolerances between expert physicians, outperforming the results of other well known algorithms, especially in determining the end of T wave.

1,490 citations

Journal ArticleDOI
TL;DR: This paper quantifies the potential of the emerging compressed sensing (CS) signal acquisition/compression paradigm for low-complexity energy-efficient ECG compression on the state-of-the-art Shimmer WBSN mote and shows that CS represents a competitive alternative to state- of- the-art digital wavelet transform (DWT)-basedECG compression solutions in the context of WBSn-based ECG monitoring systems.
Abstract: Wireless body sensor networks (WBSN) hold the promise to be a key enabling information and communications technology for next-generation patient-centric telecardiology or mobile cardiology solutions. Through enabling continuous remote cardiac monitoring, they have the potential to achieve improved personalization and quality of care, increased ability of prevention and early diagnosis, and enhanced patient autonomy, mobility, and safety. However, state-of-the-art WBSN-enabled ECG monitors still fall short of the required functionality, miniaturization, and energy efficiency. Among others, energy efficiency can be improved through embedded ECG compression, in order to reduce airtime over energy-hungry wireless links. In this paper, we quantify the potential of the emerging compressed sensing (CS) signal acquisition/compression paradigm for low-complexity energy-efficient ECG compression on the state-of-the-art Shimmer WBSN mote. Interestingly, our results show that CS represents a competitive alternative to state-of-the-art digital wavelet transform (DWT)-based ECG compression solutions in the context of WBSN-based ECG monitoring systems. More specifically, while expectedly exhibiting inferior compression performance than its DWT-based counterpart for a given reconstructed signal quality, its substantially lower complexity and CPU execution time enables it to ultimately outperform DWT-based ECG compression in terms of overall energy efficiency. CS-based ECG compression is accordingly shown to achieve a 37.1% extension in node lifetime relative to its DWT-based counterpart for “good” reconstruction quality.

680 citations


"Optimizing Wavelet ECG Watermarking..." refers methods in this paper

  • ...We used three mother wavelets that were commonly applied for ECG compression due to their similarity to the QRS complex [34,35]: Daubechies (db), Symlets (sym) and Biorthogonal (bior)....

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Journal ArticleDOI
TL;DR: This paper proposes a time-spread echo as an alternative to the single echo in conventional echo hiding, and shows good imperceptibility and robustness against typical signal processing.
Abstract: Conventional watermarking techniques based on echo hiding provide many benefits, but also have several disadvantages, for example, a lenient decoding process, weakness against multiple encoding attacks, etc. In this paper, to improve the weak points of conventional echo hiding, we propose a time-spread echo as an alternative to the single echo in conventional echo hiding. Spreading an echo in the time domain is achieved by using pseudonoise (PN) sequences. By spreading the echo, the amplitude of each echo can be reduced, i.e., the energy of each echo becomes small, so that the distortion induced by watermarking is imperceptible to humans while the decoding performance of the embedded watermarks is better maintained as compared with the case of conventional echo hiding, as shown by computer simulations, in which several parameters, such as the amplitude and length of PN sequences and analysis window length, were varied. Robustness against typical signal processing was also evaluated in these simulations and showed fair performance. Results of a listening test using some pieces of music showed good imperceptibility.

165 citations


"Optimizing Wavelet ECG Watermarking..." refers methods in this paper

  • ...Digital watermarking is a data processing method that is aimed at hiding auxiliary information in a data carrier according to steganography rules [1]....

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Journal ArticleDOI
TL;DR: A wavelet-based steganography technique has been introduced which combines encryption and scrambling technique to protect patient confidential data and it is found that the proposed technique provides high-security protection for patients data with low distortion and ECG data remain diagnosable after watermarking.
Abstract: With the growing number of aging population and a significant portion of that suffering from cardiac diseases, it is conceivable that remote ECG patient monitoring systems are expected to be widely used as point-of-care (PoC) applications in hospitals around the world. Therefore, huge amount of ECG signal collected by body sensor networks from remote patients at homes will be transmitted along with other physiological readings such as blood pressure, temperature, glucose level, etc., and diagnosed by those remote patient monitoring systems. It is utterly important that patient confidentiality is protected while data are being transmitted over the public network as well as when they are stored in hospital servers used by remote monitoring systems. In this paper, a wavelet-based steganography technique has been introduced which combines encryption and scrambling technique to protect patient confidential data. The proposed method allows ECG signal to hide its corresponding patient confidential data and other physiological information thus guaranteeing the integration between ECG and the rest. To evaluate the effectiveness of the proposed technique on the ECG signal, two distortion measurement metrics have been used: the percentage residual difference and the wavelet weighted PRD. It is found that the proposed technique provides high-security protection for patients data with low (less than 1%) distortion and ECG data remain diagnosable after watermarking (i.e., hiding patient confidential data) and as well as after watermarks (i.e., hidden data) are removed from the watermarked data.

162 citations


"Optimizing Wavelet ECG Watermarking..." refers background or methods in this paper

  • ...Ibaida et al. proposed an efficient method of low complexity to increase the integrity of the ECG and patient meta-data....

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  • ...64 measured in time-scale domain, three unspecified Physionet records Ibaida [18] 0....

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  • ...In the conference paper [17], they presented a method with a Least Significant Bit (LSB) watermarking algorithm which was then combined with encryption and scrambling techniques to protect confidential patient data [18]....

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