BAN 기반 심전도 모니터링의 에너지 효율과 신뢰성 향상을 위한 온노드 프로세싱 및 우선순위 MAC

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With the development of wireless communication, sensor design, and energy storage technologies, wireless sensor networks (WSNs) have become a reality. Currently, monitoring human body physiological parameters is an interesting application of WSNs. However, the well-designed WSNs are not ideally suited to these applications. For example, the power consumption of a sensor node should be reduced to the minimum to sustain long term monitoring, and the transmission reliability should be further emphasized with life threatening information delivered through the network. Therefore, it is necessary to develop a body area network (BAN) to meet the needs of these healthcare applications with lower power consumption and reliable transmission. BAN based continuous monitoring systems have great potential for managing people’s chronic health conditions. Many healthcare applications based on BANs have been researched, among which the continuous monitoring of people who are suffering from heart illnesses is the most remarkable. A BAN based ECG monitoring system allows doctors to pervasively monitor patients’ heart conditions in any environment without any restriction of the patients’ activities.
Energy efficiency is one of the biggest challenges to the ECG monitoring application of BANs, because the battery powered sensor node has very limited energy capacity. It cannot afford the long term monitoring by continuously sensing and transmitting the ECG signals to the doctor. However, the energy can be used in a more efficient way to prolong the life time of the sensor node. Thus far, there are three main ways for saving energy of the sensor node: low power hardware design, light weight software design, and smart working mechanism. Many efforts have been devoted to designing energy efficient hardware such as low power transceivers, processors, and software such as light weight MAC protocols and routing protocols. However, only a few works, either directly porting existing ECG analysis algorithms or simply measuring duration and amplitude of ECG signals, have been done from the system working mechanism point of view to save power consumption of the sensor node.
Our motivation is to use smart working mechanism of the sensor node for saving energy. We put some intelligence on the sensor node by trading computation for communication so that continuous transmission is not necessary all the time. In this work, we thoroughly analyze the power consumption of sensor nodes and setup the framework of an intelligent sensor node based ECG monitoring system. Then, we propose a light weight ECG analysis algorithm for local diagnosis, which achieves a sufficiently high classification accuracy and energy efficiency. The proposed ECG analysis algorithm classifies ECG cycles into normal or abnormal by computing the Euclidean distance between a tested ECG cycle and a normal ECG cycle. We also extend by including a prioritized MAC protocol to improve the reliability of reporting abnormal information. The prioritized MAC protocol is characterized by two features: i) It prioritizes packets by increasing the backoff time of non-urgent packets; ii) The channel is also cleared for the urgent packets by ceasing the transmission of all other non-urgent packets.
Moreover, we provide extensive experimental simulation and implementation results for validating the efficiency of these proposed schemes. The local ECG analysis algorithm is evaluated from two aspects-the power consumption and diagnosis accuracy. The prioritized MAC protocol is estimated from three aspects, namely, the average packet delay, the retransmission probability, and throughput. These results demonstrate the energy efficiency and reliability of the intelligent sensor node based ECG monitoring system.
Alternative Title
On-Node Processing and Priority Aware Medium Access for Energy-Efficient and Reliable ECG Monitoring over Body Area Networks
Alternative Author(s)
Min Zeng
조선대학교 일반대학원
일반대학원 컴퓨터공학과
Awarded Date
Table Of Contents
Table of Contents

List of Tables iv
List of Figures v
ABSTRACT (Korean) vii
I. Introduction 1
A. Overview 1
B. Motivation 6
C. Contributions 9
D. Thesis Outline 10
II. Background and Related Work 11
A. Traditional BAN based Continuous Monitoring System 11
1. System Architecture 11
2. Sensor Node 14
B. Related Work 16
1. BAN based Continuous Monitoring Systems 16
2. Power Consumption Issues and Existing Solutions 19
3. Transmission Reliability Issues and Existing Solutions 27
III. On-Node Processing and Priority Aware Medium Access for ECG Monitoring System 29
A. Intelligent Sensor Node based BAN Architecture 29
1. System Overview 30
2. System Operation 31
B. On-Node ECG Analysis Algorithms 34
1. ECG Signal Details 34
2. ECG Cycle Modeling 36
3. ECG Cycle Classification 39
C. Prioritized MAC Protocol over BAN 44
1. Reliability Issues in Intelligent Sensor Node based BANs 44
2. Prioritized MAC Protocol 45
IV. Experimental Results 48
A. Simulation Tools and Implementation 48
B. Simulation Results of the On Node ECG Analysis Algorithm 52
1. Power Consumption Results and Evaluation 53
2. Diagnosis Accuracy Results and Evaluation 58
C. Implementation of the Prioritized MAC Protocol 62
1. Network Settings 62
2. Performance Evaluation 63
V. Conclusions and Future Work 70
Bibliography 72
ABSTRACT (English) 81
증민. (2011). BAN 기반 심전도 모니터링의 에너지 효율과 신뢰성 향상을 위한 온노드 프로세싱 및 우선순위 MAC.
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General Graduate School > 4. Theses(Ph.D)
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