This paper presents a novel electrocardiogram (ECG) compression method for e-health applications by adapting an adaptive Fourier decomposition (AFD) algorithm hybridized with a symbol substitution (SS) technique. The compression consists of two stages: first stage AFD executes efficient lossy compression with high fidelity; second stage SS performs lossless compression enhancement and built-in data encryption, which is pivotal for e-health. Validated with 48 ECG records from MIT-BIH arrhythmia benchmark database, the proposed method achieves averaged compression ratio (CR) of 17.6–44.5 and percentage root mean square difference (PRD) of 0.8–2.0% with a highly linear and robust PRD-CR relationship, pushing forward the compression performance to an unexploited region. As such, this paper provides an attractive candidate of ECG compression method for pervasive e-health applications.

A Novel ECG Data Compression Method Using Adaptive Fourier Decomposition With Security Guarantee in e-Health Applications

A biometric system performs template matching of acquired biometric data against template biometric data [17.1]. These biometric data can be acquired from several sources like deoxyribonucleic acid (DNA), ear, face, facial thermogram, fingerprints, gait, hand geometry, hand veins, iris, keystroke, odor, palm print, retina, signature, voice, etc. According to previous research, DNA, iris and odor provide high measurement for biometric identifiers including universalities, distinctiveness and performance [17.1]. DNA provides a one dimensional ultimate unique code for accurate identification for a person, except for the case of identical twins. In biological terms “Central Dogma” refers to the basic concept that, in nature, genetic information generally flows from the DNA to RNA (ribonucleic acid) to protein. Eventually protein is responsible for the uniqueness provided by other biometric data (finger print, iris, face, retina, etc.). Therefore, it can be inferred that the uniqueness provided by the existing biometric entities is inherited from the uniqueness of DNA. It is imperative to note that shape of the hand or palm print or face or even the shape of particular organs like the heart has distinctive features which can be useful for successful identification. The composition, mechanism and electrical activity of the human heart inherit uniqueness from the individuality of DNA. An electrocardiogram (ECG) represents the electrical activities of the heart. Figure 17.1 shows the inheritance of uniqueness for ECG inherited from the DNA.

ECG-Based Authentication

Existing electrocardiography (ECG) based biometric systems are constantly being challenged by higher misclassification error, longer acquisition time, larger template size, slower processing time and pertinence of abnormal beats within the biometric template. These challenges are the prime hindrance for ECG based biometric being commercialized as a pervasive authentication mechanism. At least,ECGbased biometric can provide a secured mechanism for cardiac patients being monitored over telephony network. In this paper, we present a polynomial distance measurement (PDM) method for ECG based biometric authentication for the very first time, according to the literature and to the best of our knowledge. The proposed PDM method is up to 12 times faster than existing algorithms, requires up to 6.5 times less template storage, needs only 2.49 (average) acquisition time with the highest accuracy rate (up to 100 per cent) when experimented on a population size of 15. Moreover, this proposed ECG based biometric system was deployed on a mobile phone based telemonitoring scenario with multilayer authentication mechanism upholding its applicability.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sec.76

Polynomial distance measurement for ECG based biometric authentication

With the technological advancement in body area sensor networks (BASNs), low cost high quality electrocardiographic (ECG) diagnosis systems have become important equipment for healthcare service providers. However, energy consumption and data security with ECG systems in BASNs are still two major challenges to tackle. In this study, we investigate the properties of compressed ECG data for energy saving as an effort to devise a selective encryption mechanism and a two-rate unequal error protection (UEP) scheme. The proposed selective encryption mechanism provides a simple and yet effective security solution for an ECG sensor-based communication platform, where only one percent of data is encrypted without compromising ECG data security. This part of the encrypted data is essential to ECG data quality due to its unequally important contribution to distortion reduction. The two-rate UEP scheme achieves a significant additional energy saving due to its unequal investment of communication energy to the outcomes of the selective encryption, and thus, it maintains a high ECG data transmission quality. Our results show the improvements in communication energy saving of about 40%, and demonstrate a higher transmission quality and security measured in terms of wavelet-based weighted percent root-mean-squared difference.

/pdf/assurance-of-energy-efficiency-and-data-security-for-ecg-6ctcx9333w.pdf

Assurance of Energy Efficiency and Data Security for ECG Transmission in BASNs

Electrocardiography (ECG) signal is popularly used for diagnosing cardiovascular diseases (CVDs). However, in recent times ECG is being used for identifying person. As ECG signals contain sensitive private health information along with details for person identification, it needs to be encrypted before transmission through public media. Moreover, this encryption must be applied with minimal delay for authenticating CVD patients, as time is critical for saving CVD affected patient’s life. Within this paper, we propose the usage of multi-scroll chaos to encrypt ECG packets. ECG packets are being encrypted by the mobile phones using the chaos key by patients’ subscribed in tele-cardiology applications. On the other hand, doctors and hospital attendants receive the encrypted ECG packets, which can be decrypted using the same chaos key. Using the techniques described in this paper, end-to-end security can be applied to wireless tele-cardiology application, with minimal processing. Our experimentation with 12 ECG segments shows that with multi-scroll chaos implementation, CVD patients remain completely unidentified, upholding patients’ privacy and preventing spoof attacks. Most importantly, the proposed method is 18 times faster than permutation-based ECG encoding, 25 times faster than wavelet-based ECG annonymization techniques and 31 times faster than noise-based ECG obfuscation techniques, establishing the proposed technique as the fastest ECG encryption system according to the literature. Copyright © 2010 John Wiley & Sons, Ltd.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sec.226

A chaos‐based encryption technique to protect ECG packets for time critical telecardiology applications

Electrocardiogram (ECG) provides detail condition of the heart of a cardiac patient. ECG also contains some features, which can serve as a biometric entity for identification of a particular patient. Therefore, when ECG is transmitted for remote telehealth application, it is susceptible to patient's privacy. Interception of ECG data may release patients overall condition to the wrong hand. To protect patients' privacy HIPAA regulations are in place. However, according to the literature, research related to the securing (encryption) is scarce. In this paper, we proposed two methods of ECG encryption and distribution for a patient centric telehealth application. Using wavelet decomposition techniques only important portion of the ECG signal is selected for encryption. The remaining ECG coefficients (wavelet decomposition) are uploaded to a public ECG repository. The doctor downloads the publicly available coefficients and uses the encrypted coefficients, which has already been distributed to him from the patient, to retrieve the original ECG. Apart from providing complete security, this architecture provides faster ECG transmission by achieving a high compression ratio of up to 2.81.

I Khalil

Papers

A wavelet based secured ECG distribution technique for patient centric approach