Reversible Data Hiding Scheme for ECG Signal

Introduction

In remote health monitoring system, using Internet as main medium of data dissipation introduces new vulnerability and security threats as well as data integrity issues. Due to the various regulations for the acquisition and safe distribution of health-related data it has become mandatory to protect and safeguard the data against different kind of attacks. Government has initiated, the Health Insurance Portability and Accountability Act of 1996 (HIPAA) which specifies clauses of mandatory privacy rules to protect personal health information as an intellectual property:

• 1.

  Patient privacy: A patient should have right over his/her confidential health data. Patient personal data such as name, address, telephone number, and Medicare number etc. must not be shared without his/her consent. As a result, the security protocol should provide further control on who can access patient’s data and who cannot;

• 2.

  Security: Any computer software deployed for this purpose should be compliant with standard security methods that protect the data in transit as well as at rest (on hospital servers).

It is essential to ensure the security and integrity of personal health data. Even a small error in health data like biological readings can lead to catastrophe result due to wrong perception of data and treatment.

Digital watermarking techniques facilitate embedding of protected information in less sensitive host media like image or 1D signal that can act as a tool to ensure the intellectual property rights and provide authentication. Various data hiding algorithms use image as a cover to embed data leaving the original image distorted indelibly. As discussed earlier digital watermarking as an application of data hiding technique has wide application in telemedicine systems. Patient’s identity can also be hidden inside the physiological readings like ECG. Some hiding techniques permanently degrade the host signal’s quality. These changes in biomedical signals may not be permissible during medical diagnosis. Reversible data hiding algorithms can eradicate this problem by facilitating ‘reversibility’ which means to embed data into host digital media and extract the original secret media from marked one in a lossless manner. Performance of a reversible algorithm can be measured by following parameters:

• 1.

  Payload capacity limit: Every watermarked work is used to convey a hidden message. So, it is important to know the maximum size of the payload that the host signal can carry;

• 2.

  Signal fidelity: Degradation of the signal’s quality should be as low as possible, so no obvious visual change in the signal’s fidelity can be precepted after extraction.

The electrocardiogram (ECG) records the heart electric activity graphically in the order of millivolts (mV), which can be used to detect various types of deficits in heart rate, like arrhythmia or tachycardia. In e-health care systems, it is common practice to use ECG signal to embed the patient’s confidential data along with the readings from different sensors. ECG becomes suitable choice because it is collected in real-time basis and large enough in size to hide private data. As mentioned ECG is recorded in huge amount hiding scheme must not increase the size of host signal. The proposed algorithm aims at preserving the diagnostic features of host ECG signal even after extraction of confidential data. Embedding scheme doesn’t increase the size of original signal. Metrics used to measure the signal distortion is MSE (Mean Square Error) and PRD (Percent Residual Difference), payload capacity is calculated in Kilo bits (Kb).

Existing Work

Number of works has been done on securing patient’s information in telemedicine systems by embedding it in ECG signal. Zheng and Qian (2008) presented a novel reversible watermarking algorithm for ECG signal based on wavelet transform. Their method applied B-spline wavelet transform to identify QRS- complex of the ECG and again lifting based Haar wavelet transform is applied on the original ECG signal. Secret message is embedded in non-QRS coefficient of high frequency sub band to achieve invisibility. First problem with this method is that embedding scheme relies on correct identification of QRS complex which may not be always possible with abnormal ECG. So, algorithm fails to perform well for abnormal ECG signals. Second short coming is low embedding capacity which is up to 74.6kb.