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A wavelet based secured ECG distribution technique for patient centric approach

F Sufi, +2 more
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TLDR
In this paper, the authors 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.
Abstract
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.

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Journal ArticleDOI

A New Feature Detection Mechanism and Its Application in Secured ECG Transmission with Noise Masking

TL;DR: A new ECG feature detection mechanism was presented, which was compared against existing cross correlation (CC) based template matching algorithms and a newECG obfuscation method was designed and implemented on 15 subjects using added noises corresponding to each of the ECG features.
Journal ArticleDOI

Encryption by Heart (EbH)Using ECG for time-invariant symmetric key generation

TL;DR: Experimental results over 24h for 199 users show that EbH, under certain settings, can produce permanent seeds (thus time-invariant keys) computed on-the-fly and different for each user up to 95.97% of users produce unique keys.
Proceedings ArticleDOI

On supporting anonymity in a BAN biometric framework

TL;DR: A privacy oriented body area network, with electrocardiogram (ECG) based recognition, is presented for supporting anonymity, in this framework, service providers are equipped with the possibility of pervasive subject monitoring, potentially eliminating the need for authenticated identities, while offering an automatic way of managing personal information.

A summary of: Encryption by Heart (EbH) - Using ECG for time-invariant symmetric key generation

TL;DR: In this paper, the authors explored the use of ElectroCardioGram (ECG) data to encrypt data and proposed EbH, a mechanism for persistent key generation based on ECG.
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