Using Cross-Layer Techniques for ECG Transmissions in Body Area Sensor Networks

Using Cross-Layer Techniques for ECG Transmissions in Body Area Sensor Networks

Tao Ma, Michael Hempel, Dongming Peng, Hamid Sharif, Fahimeh Rezaei, Pradhumna L. Shrestha, Hsiao-Hwa Chen
Copyright: © 2012 |Pages: 18
DOI: 10.4018/978-1-4666-0960-0.ch005
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Abstract

Body Area Sensor Networks (BASN) with miniature sensors providing wireless communications capabilities have become a promising tool for monitoring and logging vital parameters of patients suffering from chronic diseases such as diabetes, asthma, and heart diseases. Particularly, as the technical development in BASN, a low-cost, high-quality, convenient Electrocardiographic (ECG) diagnosis system becomes a future major tool for healthcare systems. However, numerous important research issues remain to be addressed in BASN for ECG transmissions. Among these, communication energy efficiency and security are the most concerning issues. In this chapter, the authors introduce, survey, and analyze effective cross-layer strategies for wireless ECG transmissions in BASN. The key idea of these cross-layer communication techniques is to take advantage of both source data properties and communication strategies for the optimization of the system energy efficiency while providing secure wireless ECG transmissions. The goal of improving communication energy efficiency is achieved by matching the source coding of ECG signals with the channel coding strategy. In addition one can leverage biometric ECG properties to implement an energy-efficient cross-layer security strategy. As an example the authors showcase two security methods in this chapter—selective encryption and self-authentication. Thanks to the dependency property of the compressed ECG data, a selective encryption algorithm needs only to be applied on a very small portion of the transmitted data, and at the same time it provides a level of security equivalent to traditional full-scale encryption using block or stream ciphers without the burden of the associated energy and computational expense. In the example authentication scheme, sensors for the same body can authenticate each other by common traits such as inter-pulse intervals. The authors analyzed the proposed cross-layer techniques for ECG transmissions and validated the achieved energy efficiency improvements by both simulation and experimental results.
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Background

Heart disease, stroke, cancer, chronic respiratory diseases, and diabetes are the major causes of mortality in the world, representing 60% of all deaths. Since chronic diseases often have asymptomatic or intermittent properties, long-term continuous health monitoring is essential in detecting and treating such diseases. For example, long-term monitoring of ECG data helps detecting these diseases at an early stage and improves the chance of successful treatments. For preventing strokes, real time ECG information monitoring is essential for heart rate control and prompt re-treatment. Long-term monitoring requires the transmission of a large amount of data in a reliable, convenient, energy-efficient and secure manner. Thus, it generates a huge challenge for today’s technology.

Recently, with advances in wireless networks and sensor miniaturization, BASN becomes a promising solution to help meet this demand. A BASN consists of multiple wearable sensor nodes. These nodes are able to sample, process, and communicate vital signals of information such as heart rate, blood pressure, oxygen saturation. These sensors are usually so small in size that they can be placed on a human body as tiny patches or hidden in users’ clothes. There have been many recent efforts focused on wearable systems for health monitoring and ECG data collection, which are briefly summarized in the following paragraphs.

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