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U N I V E R S I TAT I S O U L U E N S I S

ACTAC

TECHNICA

U N I V E R S I TAT I S O U L U E N S I S

ACTAC

TECHNICA

OULU 2010

C 373

Young-Dong Lee

WIRELESS VITAL SIGNS

MONITORING SYSTEM FOR

UBIQUITOUS HEALTHCARE

WITH PRACTICAL TESTS ANDRELIABILITY ANALYSIS

UNIVERSITY OF OULU,

FACULTY OF TECHNOLOGY,

DEPARTMENT OF ELECTRICAL AND INFORMATION ENGINEERING

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A CTA UNIVE RS ITA T I S O UL

C Techn i c a 37 3

YOUNG-DONG LEE

WIRELESS VITAL SIGNS

MONITORING SYSTEM FOR

UBIQUITOUS HEALTHCARE

WITH PRACTICAL TESTS AN

RELIABILITY ANALYSIS

Academic dissertation to be presented with

the Faculty of Technology of the Universitypublic defence in Auditorium TS101, Linna

December 2010, at 12 noon

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Copyright 2010

Acta Univ. Oul. C 373, 2010

Supervised byDocent Esko Alasaarela

Professor Risto Myllyl

Reviewed by

Professor Mohammed ElmusratiProfessor Jukka Vanhala

ISBN 978-951-42-6387-3 (Paperback)ISBN 978-951-42-6388-0 (PDF)

http://herkules.oulu.fi/isbn9789514263880/ISSN 0355-3213 (Printed)

ISSN 1796-2226 (Online)http://herkules.oulu.fi/issn03553213/

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Lee, Young-Dong, Wireless vital signs monitoring system for ubiquitou

with practical tests and reliability analysisUniversity of Oulu, Faculty of Technology, Department of Electrical and Engineering, P.O.Box 4500, FI-90014 University of Oulu, Finland

Acta Univ. Oul. C 373, 2010

Oulu, Finland

Abstract

The main objective of this thesis project is to implement a wireless vital signs mon

for measuring the ECG of a patient in the home environment. The research focuses o

research objectives: 1) the development of a distributed healthcare system fo

monitoring using wireless sensor network devices and 2) a practical test and

evaluation for the reliability for such low-rate wireless technology in ubiquitous hea

applications.

The first section of the thesis describes the design and implementation of

healthcare system constructed from tiny components for the home healthcare of el

The system comprises a smart shirt with ECG electrodes and acceleration senso

sensor network node, a base station and a server computer for the continuous monit

signals. ECG data is a commonly used vital sign in clinical and trauma care. The

displayed on a graphical user interface (GUI) by transferring it to a PDA or a term

smart shirt is a wearable T-shirt designed to collect ECG and acceleration signals fr

body in the course of daily life.

In the second section, a performance evaluation of the reliability of IEEE 802

wireless ubiquitous health monitoring is presented. Three scenarios of performan

applied through practical tests: 1) the effects of the distance between sensor no

station, 2) the deployment of the number of sensor nodes in a network and 3) data

using different time intervals. These factors were measured to analyse the reli

developed technology in low-rate wireless ubiquitous health monitoring application

The results showed how the relationship between the bit-error-rate (BER) and s

ratio (SNR) was affected when varying the distance between sensor node and base-st

the deployment of the number of sensor nodes in a network and through data trans

different time intervals.

Keywords: BER, ECG, IEEE 802.15.4, acceleration signal, personal are

reliability analysis, vital signs monitoring

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Acknowledgements

I wish to express my warm and sincere thanks to the University o

Dongseo University for giving me the opportunity and resources t

thesis through their excellent dual-degree program. This work wou

been possible without support from the dual-degree program b

University of Oulu and Dongseo University.

I would also like to express my deep and sincere gratitude to myProfessor Esko Alasaarela, for his understanding, encouragement a

throughout the work of this thesis. His wide knowledge and techni

have been of great value to me.

I am, as well, deeply grateful to my second supervisor, Pro

Myllyl, Head of the Optoelectronics and Measurement Techniques

for his important support throughout this work.

Furthermore, I wish to express my sincere thanks to Professor H

who gave me important guidance and untiring help during my difficul

Additionally, during this work I have collaborated with many co

whom I have great regard, and I wish to extend my warmest thanks

who have helped me with my work in the Optoelectronics and M

Techniques laboratory at the University of Oulu, and the USN l

Dongseo University, Korea.

Finally, I would like to convey my loving thanks to my wife Mi

my son Hyeong-Gyu, for their encouragement and understanding.

Oulu, March 2010 Youn

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List of terms, symbols and abbreviations

A/D Analog/Digital

ACK Acknowledgement

ADC Analog-to-Digital Converter

AWGN Additive White Gaussian Noise

BAN Body Area Network

BASN Body Area Sensor NetworkBER Bit Error Rate

BMAC Berkeley MAC

BSN Body Sensor Network

CCITT International Telegraph and Telephone Consultative Com

CRC Cyclic Redundancy Check

CTS Clear to Send

dB Decibels

dBm Decibels per Milliwatt

DMAC Distributed MAC

DSDV Destination Sequence Distance Vector

DSMAC Differential Service MAC

Eb/No Energy per Bit to Noise power spectral density ratio

ECG Electrocardiogram

EMT Emergency Medical Technician

g Gravitational constant

GHz Giga Hertz

GPRS General Packet Radio Service

GUI Graphic User Interface

HPF High Pass FilterI/O Input/Output

ID Identification

ISM Industrial Scientific Medical

ISP In System Programmer

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MB Mega Byte

MHz Mega Hertzmm Millimeter

NACK Negative Acknowledgement

nesC Network Embedded System C

O-QPSK Offset Quadrature Phase-Shift Keying

PCB Printed Circuit Board

PDA Personal Digital AssistantPER Packet Error Rate

PHY Physical Layer

PSK Phase-Shift Keying

QoS Quality of Service

RAM Random Access Memory

RF Radio Frequency

RS-232 Recommended Standard 232

RTS Request to Send

Rx Receiver

SMAC Sensor MAC

SNR Signal-to-Noise Ratio

SPI Serial Peripheral Interface Bus

SpO2 Oxygen Saturation

TCP/IP Transmission Control Protocol/Internet Protocol

TinyOS Tiny Micro Threading Operating System

TMAC Timeout MAC

Tx Transmitter

uA Micro-Ampere

UART Universal Asynchronous Receiver/TransmitterUbiMon Ubiquitous Monitoring Environment for Wearab

Sensors

UMTS Universal Mobile Telecommunication System

USB Universal Serial Bus

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List of original papers

I Lee Y-D, Lee D-S, Chung W-Y & Myllyl R (2006) A wireless se

platform for elderly persons at home. Rare metal materials and engin

9599.

II Amit P, Lee Y-D & Chung W-Y (2008) Triaxial MEMS acceleromet

monitoring of elderly person. Sensor Letters 6(6): 10541058.

III Lee Y-D & Chung W-Y (2009) Wireless sensor network based wearab

for ubiquitous health and activity monitoring. Sensors and Actuators140(2): 390395.

IV Walia G, Lee Y-D, Chung W-Y & Myllyl R (2006) Distribut

monitoring in an ad-hoc network using a wireless sensor network. P

11th International Meeting on Chemical Sensors, Brescia, Italy.

V Lee Y-D, Lee D-S, Walia G, Myllyl R & Chung W-Y (2006) Query

vital signal monitoring system using wireless sensor network fo

healthcare. Proceedings of World Congress on Medical Physics an

Engineering, Seoul, Korea: 396399.

VI Lee Y-D, Lee D-S, Walia G, Alasaarela E & Chung W-Y (2007

evaluation of query supported healthcare information system using w

ad-hoc network. Proceedings of International Conference on

Information Technology, Gyeongju, Korea: 9971002.

VII Lee Y-D, Alasaarela E & Chung W-Y (2007) A wireless health monito

multi-hop body sensor networks. Proceedings of 2nd International S

Medical Information and Communication Technology (ISMICT'07), OVIII Chung W-Y, Lee Y-D & Jung S-J (2008) A wireless sensor netwo

wearable u-healthcare monitoring system using integrated ECG, acce

SpO2. Proceedings of 30th Annual International Conference o

Engineering in Medicine and Biology Society (EMBC 2008), Vancou

15291532.

The objective of paper I was to design and implement a small size

healthcare system for the home care of elderly persons. The system

wireless sensor network node, base station and server computer for th

monitoring of ECG signals. ECG data, important vital heart sign

commonly used in clinical and trauma care, were displayed on a gr

i f (GUI) b f i h d PDA i l PC

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Wearable sensor devices are proposed in paper III that are

into a shirt, which are of small size, low power consumption awireless sensor network communication based on IEEE

mainly consists of sensors for continuous monitoring o

conductive fabrics to get the body signal, functioning as electr

Paper IV describes the development of a distributed healt

prototype for clinical and trauma patients using a commercial

sensor network platform. The system has been designed to msigns of the patients and transfer the health status wirelessl

station which was connected to a doctors PDA and terminal P

Paper V discusses the design issue for a query driven he

its implementation using a wireless sensor node in an ad-hoc

describes the system's architecture, including hardware desig

experimental setup, and results and performance analysis are

Papers VI and VII present a wireless health monitoring

body sensor networks using our ubiquitous sensor networ

based 3-electrodes ECG monitoring system operates in wirel

The ECG signal from multiple patients was relayed wireless

routing scheme to a base-station. The design and developm

Healthcare monitoring system using integrated ECG, accele

saturation sensors is introduced in paper VIII.

The author defined the research plan and carried out the l

wrote a manuscript presented in papers I-VIII. Experiment

were done by the author in association with the co-authors.

papers I, III-VIII, was written by the author with the kind he

The authors contribution to paper II was to design and

accelerometer sensor system using wireless sensor nodes. Thout the accelerometer sensor measurements together with Am

the first version of the manuscript, after discussions with the c

to the reviewers comments, the author wrote the revision of t

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Contents

Abstract

Acknowledgements

List of terms, symbols and abbreviations

List of original papers

Contents

1 Introduction 1.1 Related works ...........................................................................1.2 Objectives and outline of the thesis ........................................

2 Healthcare system requirements 2.1 Node lifetime ...........................................................................2.2 Packet recovery .......................................................................2.3 Data collection ........................................................................2.4 Dependent and independent waveforms .................................2.5 Scalability ................................................................................

3 Vital signs monitoring system 3.1 System architecture of a general u-Healthcare system ............3.2 MICAz node and ECG interface circuit ...................................3.3 USN platform for wireless sensor networking ........................3.4 Sensor boards for vital signs monitoring.................................

3.4.1 Single ECG interface circuit for MICAz node .............3.4.2 ECG & accelerometer sensor board ..............................3.4.3 Wearable sensor node with sensor board ......................

3.5 Sensor node software ..............................................................3.5.1 Sampling time for the ECG signal ................................3.5.2 Packet format ................................................................3.5.3 Routing protocol ............................................................

4 Reliable medical data transmission 4.1 Need for reliable medical data transmission ...........................4.2 Low-rate wireless personal area networks ..............................

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5.5 Reliability analysis .....................................................5.5.1 Reliability test in function of distance between

nodes ................................................................

5.5.2 Reliability test in the function of the number onodes ................................................................

5.5.3 Reliability test for different time intervals .......6 Discussion

6.1

Multi-hop network for wireless body area network ...6.2 Electrocardiogram and accelerometer sensor .............6.3 Wearable system for ubiquitous healthcare ................

7 Conclusion References

Original Papers

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1 Introduction

An increasingly aging population has raised the concern of many cou

its impact on health care systems. This has led to an urgent need

cheaper and smarter ways to provide health care for suffers of age rel

Recent advances in sensor, communication and information techno

enabled the development of novel vital signs monitoring system

various vital health parameters can be measured, like electrocardiog

body temperature, heart rate, blood pressure and oxygen saturation.

wireless healthcare related applications using wireless sensor network

assist residents and caregivers by providing non-invasive and invasiv

health monitoring with a minimum interaction of doctors and patient

there are some significant disparities, such as node lifetime, packet r

medical data collection between existing wireless sensor network

required for healthcare [5, 6]. In addition to the basic requiremen

wireless, a future healthcare system based on wireless sensor network

support for ad-hoc [7] networks, the mobility of patients or elderly p

ranges of data rates and a high degree of reliability. Also, these system

miniature in size, and should be easily wearable, thus causin

inconvenience to the patients.

The design of a sensor network is application-specific, aapplications have different reliability [8] requirements. Re

communication is an important factor for the dependability and quali

(QoS) [911] in several applications of wireless sensor networks. I

this is the case for critical care applications of hospitals that allow the

monitoring of a patients vital signs. We must consider the reliabi

sensors, the sampling rate, the number of nodes in the same netwopacket sizes, as well as the reliability of the medical devices themse

closely related to the performance of the system in medical applicatio

1 1 Related works

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continuously monitored and receive advice when needed

patient/user is equipped with different vital constant sensors,pulse rate and ECG, interconnected via the healthcare BAN. T

is the central point of healthcare BAN, acting as a gateway

sensor measurements (intra-BAN communication based on

like Bluetooth [18] and Zigbee [19]) and transmitting the

system (extra-BAN communication based on GPRS and UM

located within the health broker premises or be part of a wirelFrom there, the measurements are dispatched to the healthca

medical personnel monitor them.

The ubiquitous monitoring environment for wearable and

project (UbiMon) [20] at Imperial College London aims to p

and unobtrusive monitoring system for patients in order to c

life threatening events. The basic framework of the UbiMon

sensor network (BSN) design. The system consists of five

namely the BSN nodes, the local processing unit, the centra

database and the workstation. With the current UbiMon str

wireless biosensors including 3-leads ECG, 2-leads ECG

saturation (SpO2) sensors have been developed. To facilitate

context information, sensor-based context awareness, includ

temperature and skin conductance sensors are also integrated

Furthermore, a compact flash BSN card is developed

assistants (PDAs), where sensor signals can be gathered, dis

by the PDA.

CodeBlue [21] has been designed to operate across a wi

including low power motes, PDAs and PCs, and addresses th

and security requirements of medical care settings. The dMICA2 [22] mote with a pulse oximetry signal processing

transmits periodic packets containing heart rate, SpO2 and p

waveform data. Vital sign data from multiple patients can

adaptive, multi-hop routing scheme either to a wired base-sta

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1.2 Objectives and outline of the thesis

The main objective of this thesis project is to implement a wireles

monitoring system for measuring the ECG of a patient in the home e

The research focuses on two specific research objectives: 1) devel

distributed healthcare system for vital signs monitoring using wir

network devices and 2) a practical test and performance evalua

reliability for such low-rate wireless technology in ubiquitous health

applications.

The content of this thesis is summarized as follows:

Chapter 2 addresses the requirements for a ubiquitous healthcare

main requirements for wireless healthcare such as node lifetime, pack

data collection, waveform and scalability are presented.

Chapter 3 presents the design and implementation of a ubiquitou

system that applies small-size components for the home care of elde

Two kinds of health monitoring systems have been developed; a

interface circuit for a MICAz [23] node and multiple sensors

accelerometer sensor systems. In addition to this, a wearable

healthcare system for vital signs monitoring is presented.

Chapter 4 discusses reliable medical data transmission for im

quality-of-service, including the need for reliable medical data transmrate wireless personal area networks (LR-WPAN) and error rate

reliability.

Chapter 5 presents the experimental results with a focus on

monitoring and performance evaluation.

Chapter 6 provides a summary of this work.

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2 Healthcare system requirements

Wireless healthcare should satisfy the main requirements such as no

packet recovery, data collection, waveform and scalability.

2.1 Node lifetime

The lifetime of a wireless sensor network is application-specific. With

healthcare application, it is necessary to monitor a patient

continuously (keep the wakeup sensor active) because

(electrocardiogram and heart rate) can occur at any time. An impor

wireless sensor networks for continuous healthcare application is to m

node lifetime while maintaining application or other constraints, su

and reliability [24, 25]. In order to maximize node lifetime for

healthcare application, power saving techniques should be conside

avoiding unnecessary packet recovery, efficient data collection a

packet losses.

2.2 Packet recovery

In continuous healthcare application, it is not necessary to use a pacmechanism because of packet loss, as it wastes resources. Any lost pa

replaced by the most recent update in the next transmission. Also, re

of packets will require more storage memory at the motes, which

limited. Since this is a healthcare scenario, where each node attached

transfers data independently of other nodes in the network, protocols

[26], TMAC [27] and DSMAC [28], which need RTS/CTS packet exlost packet recovery and have synchronized sleep and wake periods, a

SIFT [29] is a MAC protocol for event-driven wireless sens

environments. Although SIFT [29] achieves low latency at the c

increase in energy consumption, it needs a system-wide synchroni

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2.3 Data collection

While designing wireless sensor networks, the choice of a M

also depends on the application requirements, topology use

routing protocol. A healthcare system generally requires a sin

station, therefore a convergent type communication patter

choice, where data from the entire sensor network is finally

base-station. For convergent type communication, the DMA

good choice as it achieves very good latency compared

periods. Although DMAC does not avoid collision detection

collision are reduced by the fact that in healthcare environm

trigger all nodes simultaneously. The BMAC [31] protoc

possible choice, as it avoids packet collision and has a

scheme via low power listening, but unlike SMAC, it does no

retransmission or hidden terminal avoidance using RTS/CTS

best thing about BMAC is that it offers control to the protoco

the routing and application layers to change control paramet

communication is highly demanded in the designing

applications, where often each communication layer not on

with the intermediate layer, but also with the other layers dire

2.4 Dependent and independent waveforms

Healthcare data which is waveform independent does not n

transfer, and therefore data transfer should be initiated only

monitoring side, or in periods of finite durations. On the ot

dependent data requires long-term medical data transfer in co

application. Therefore, for waveform dependent data, data

would be well suited where a query or command from the

the data transfer. The waveform independent data can use ei

approach or the event-driven approach where data is transfe

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missed they can be replaced. For waveform dependent data, any pac

be a big problem as it will result in a loss of useful information or cafalse impression of abnormality about a patients health parameter.

2.5 Scalability

Another important issue is that the routing of message packets from o

nodes is more challenging, since stability becomes an important factor, in addition to energy and bandwidth etc. Since fast data delive

requirement in healthcare, proactive routing protocols will be efficien

this case, the path to be chosen is known in advance, before data t

Also, any change in topology is updated by timely updates. Am

proactive protocols, a DSDV [33] based protocol would b

implementation and supports a flat network. The key advantage of D

it guarantees loop freedom.

In a healthcare network, as data generated from different sensor

different rates, subject to different quality of service constraints and

multiple data delivery model, traditional methods of data aggregatio

applied. Scalability is also major issue because single gateway archit

scalable for a large set of sensors [34].

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3 Vital signs monitoring system

3.1 System architecture of a general u-Healthcare system

Ubiquitous healthcare is built around the concept of placing unobtru

on a persons body to form a wirelessly connected network. Persona

networks [3537] make it possible to continually monitor pati

anywhere and immediately notify clinicians, the nearest hospital or anservice of any critical change in status. Such networks can quic

biomedical data from sensors deployed on the body to a server c

processing.

Fig. 1 illustrates the system architecture of a general ubiquitou

system for monitoring patient status. The system consists of

components, namely, a body area sensor network (BASN) node, loca

unit and central server.

Fig. 1. System architecture of ubiquitous healthcare system for vital sign

[I, published by permission of Rare Metal Materials and Engineering].

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receiving data from the wireless sensor node using an RF

storing and transferring the data to a mobile unit using TCPAn example of ubiquitous healthcare is provided by the ub

environment for wearable and implantable sensors (UbiM

Imperial College, London, UK. This project aims to provid

unobtrusive monitoring system for patient care in order to c

life threatening events. To this end, a compact flash BSN card

for PDAs, allowing sensor signals to be gathered, displayed

PDA. Apart from acting as the local processor, the PDA c

router between the BSN node and a central server to which

data will be transmitted through a WiFi/GPRS network for lo

trend analysis. Monitoring terminals are utilized to allow c

patient data using such portable handheld devices as laptop

phones. In addition to real-time sensor information, histori

retrieved and played back to assist the diagnosis. [Paper I]

3.2 MICAz node and ECG interface circuit

Fig. 2 shows the system architecture of the wireless senso

discussed in this thesis, consisting of four major parts:

acquisition board, ECG interface circuit and base-station. Astudy used the commercially available MICAz (Crossbow

USA). The MICAz has a Chipcon CC2420 radio chip set op

802.15.4 standard (Zigbee compatible), an Atmega 128L mi

Corporation, USA) with a data throughput of 250 kbps. T

board has a maximum of 11 input channels, each with its ow

digital converter (ADC).

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Fig. 2. Hardware configuration of the wireless sensor network [I, p

permission of Rare Metal Materials and Engineering].

One of most commonly monitored vital signs in clinical and trauma c

signals. A two- or three-electrode ECG is used to evaluate cardiac ac

extended period. Physicians, clinicians or the patients themselve

continuously watch for signs of deterioration in the patients cond

cardiac problems such as arrhythmia that occur intermittently, maybe

twice a day. In this thesis, an ECG signal generator was used to accurate ECG signal for our preliminary experiment. In the

experiments, the ECG signal was obtained from sensors attached to a

body.

After processing in an interface circuit, signals produced by the

generator were recorded by the MICAz wireless sensor node. MICAz

custom operating system called TinyOS [38], which supports mult

allowing the performance of a variety of tasks tailored specifically

sensor network applications. Each node is capable of sending an

specific wireless network packets called active messages. A similar M

was used as the base-station with an MIB510 serial PC interface

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Fig. 3. Block diagram of a MICAz sensor node [I, published by

Metal Materials and Engineering].

3.3 USN platform for wireless sensor networking

Fig. 4 shows a block diagram of the USN platform develope

The specifications of the USN platform are summarized in Ta

The USN platform features an ultra low power Texas I

micro-controller [39] with 10KB RAM, 48KB flash mem

converter. It supports several low power operating modes and

5.1uA in sleep mode and 1.8mA in active mode. The CC2420

[40] is IEEE 802.15.4 Zigbee compliant and has programma

maximum data rate of 250 kbps and hardware that provides P

layer functions. The CC2420 is controlled by the MSP430F

port and a series of digital I/O lines. The M25P80 is an 8 MB

with a write protection mechanism, accessible from a SPI b

size of the USN platform, the USB programming board was

module which is needed only when nodes are connected t

li i d l d h h d b i

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Fig. 4. Block diagram of the USN platform.

Recent research has focused on the development of wireless sensor n

pervasive monitoring systems that can monitor the status of a patient

temperature, blood pressure, SpO2, accelerometer, etc.) for ubiquitouapplications. Therefore, a low power operating ECG sensor board wa

for patient health monitoring, and the output of the ECG sensor

connected to a USN platform.

Table 1. Specifications of USN platform.

Item Specification Remark

Platform

Processor MSP430F1611

Memory 48 KB/10 KB Program flash/data RAM

Current draw 1.8 mA/5.1 uA Active/sleep mode

ADC 12 bit resolution 8 channels

Power 3V Battery

Connector Expansion/USB type

RF transceiver

Frequency band 2.42.485 GHz

Sensitivity 95 dBm

Transfer rate 250 Kbps

RF power 25 dBm 0 dBm

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3.4 Sensor boards for vital signs monitoring

3.4.1 Single ECG interface circuit for MICAz node

An ECG signal generator with an interface circuit was atta

node for the purpose of continuously supplying ECG signa

produced by an ECG sensor on a patients body.

Fig. 5 shows a block diagram of the ECG interface circui

circuit is required for the amplification of the output signal p

signal generator, signal conditioning and analog to digital con

Fig. 5. Block diagram of an ECG interface circuit [I, published b

Metal Materials and Engineering].

3.4.2 ECG & accelerometer sensor board

Fig. 6 illustrates the block diagram of the sensor board which

interface and a three-axis accelerometer sensor [Paper II] c

bioelectric signal which records the hearts electrical ac

therefore it is a very important and basic diagnostic tool

functions. An electrocardiogram is obtained by measuring

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from at least two leads are generally used in order to g

electrocardiogram representation of the cardiac electrical activiimportant part of home healthcare is to monitor behaviour and physic

daily life. There are many exisitng research studies [4143] to

detection systems using a 3-axis accelerometer. The system can

accelerometer signals to determine whether the person with the dev

has fallen or not.

ECG signals from the electrodes are amplified with a gain of 30

and filtered with the cut-off frequencies of 0.05 Hz and 123 Hz in

board. An ECG electrode has two conductive fabric electrodes (Polar

Finland) which are woven into the fabric. In addition, the sensor boa

three-axis accelerometer sensor (MMA7260Q, Freescale) [Paper II]

acceleration signals for the activity monitoring of a patient. The shap

board with a wireless sensor node is designed with a contoure

comfortable wear and convenience. [Paper III]

Fig. 6. Block diagram of a sensor board [III, published by permission of E

Table 2. Sensor board specification.

Specifications

ECG sensor specification

ECG type Chest-belt type

Gain 300 (24.8)dB

Bandwidth 0 05 123 Hz

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3.4.3 Wearable sensor node with sensor board

Fig. 7 shows the overall system architecture of the wear

ubiquitous health and activity monitoring, which consis

integrated wireless sensor nodes, a base-station and ser

monitoring. The wireless sensor network consists of a larg

nodes, which have built-in computing, power, sensors to a

and activity data from the human body and wireless transm

capability. The smart shirt is compatible with the wireless s

the individual physiological data from each smart shirt is tr

wireless communication for further processing using a wireles

The wearable sensor nodes are responsible for acquirin

data and transmitting it to the base-station. The sensor node

tiny in size and consume low operating power to reduce bat

also last for longer durations. The sensor node has a limited bas computing and communication capability, due to its physic

Fig. 7. System architecture of the u-Healthcare system with we

published by permission of Elsevier].

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shows the architecture of the designed wireless sensor node. The wi

node is round in shape and 40 mm in diameter.

(a)

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The smart shirt consists of a wireless sensor node, an EC

sensor board and conductive fabric electrodes for ECG measshirt design. To reduce the size of the integrated wearab

structure is made up of two round shaped PCB boards whic

wireless sensor node plate for communication in a wireless s

sensor board plate with an ECG interface & accelerometer.

node and sensor board are combined together as shown in

sensor node is placed in the top position and the sensor board

and accelerometer circuits is placed in the bottom position of

node structure. To obtain physiological ECG data, two

electrodes are extended from the ECG interface circuit of the

knitted into the shirt. The smart shirt is a wearable T-shirt

ECG and acceleration signals from the human body contin

The shirt contains ECG and accelerometer sensors that can

vital signs such as heart rate, ECG and acceleration. The doub

the wearable sensor node reduces the width of the normal s

sensor node structure with sensors and gives convenience in

size batteries. [Paper III]

Fig. 9. An integrated wearable sensor node combined with a wire

a sensor board in double layer structure.

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platform is implemented based on TinyOS [38]. TinyOS is a small,

embedded operating system developed by UC Berkeley. A stand-alconstrained operating system, TinyOS is application specific an

selected system components and custom components needed f

application. In the TinyOS operating system, libraries and application

in nesC [40], which is a structured component-based language. NesC

syntax, but supports the TinyOS concurrency model, as well as mec

structuring, naming and linking together software components

network embedded systems. TinyOS defines a number of important c

are expressed in nesC: (1) nesC applications are built out of comp

well-defined, bidirectional interfaces, (2) nesC defines a concurr

based on tasks and hardware event handlers and detects data-race

time. Races are avoided either by accessing a shared state only in ta

within atomic statements.

The component based architecture and event driven executio

TinyOS enables fine-grained power management while minimizin

keeping in view the memory constraints in wireless sensor net

architecture for software is based on the Active Message communic

The Healthcare application consists of several components like uHea

GenericComm and Routing. These components have specific fu

services that they provide/use to/from other connected componentstechniques of these have been developed, and some of the compone

shown in Fig. 10. [Paper IV, Paper V]

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The main application level component is uHealth which contro

handling of various hardware and software events. The composamples the ECG signal from the ECG sensor board. GenericCom

generic packet handling and a basic SendMsg and ReceiveMsg in

TinyOS messages. GenericComm will also interface to low lev

specific TinyOS hardware drivers. The Routing component p

function of routing data and topology updates to the application. [Pap

VII]

3.5.1 Sampling time for the ECG signal

The default value of the TIME_SCALE (local clocks of nodes) i

resolution of 100, indicating a 0.1 second sampling time in TinyOS. I

TIME_SCALE could be modified to 10, corresponding to a sampling

s. Thus, the ECG signal produced by the ECG signal generator passed

signal interface circuit and entered the MICAz. The analog ECG

collected at a sampling rate of 125Hz and converted into a digital sig

data. [Paper I]

3.5.2 Packet format

Digitized ECG data can be transmitted to other sensor nodes or the

connected to the server PC by an RS-232 serial interface in the IEE

(Zigbee compatible) standard format. The overall packet struct

developed system is composed of 36 bytes, as shown in Table 3. S

structure of tinyos message structure (TOS_MSG), the header part of

is comprised of a destination address, an active message handler, a gmessage length. This is followed by a data part of 29 bytes, which is c

7 bytes of multi-hop message attributes and data of 22 bytes. A 1 b

was included for indication of types of sensors. The sensor reading

and the rest are for internal management. The header and data part is

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Table 3. Packet structure for communication between sensor n

permission of Rare Metal Materials and Engineering].

Header Data Part Payload Data

Destination

address

Active

Message

handler

Group ID Message

Length

Mote ID Counter

2Bytes 1Byte 1Byte 1Byte 2Bytes 2Bytes

3.5.3 Routing protocol

For constructing our ad-hoc network, a variant of the De

Distance Vector (DSDV) algorithm [33] has been used

destination of data from all nodes is a single base statio

periodically broadcasts its identity, which is used by receivin

its routing information table. They then rebroadcast the new rnodes in their range. Thus, a hierarchy of nodes is formed wi

the top level, and all nodes target their data to the nodes w

them. Any change in topology is conveyed to the parent node

their tables.

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4 Reliable medical data transmission

4.1 Need for reliable medical data transmission

Quality of service is an important part of healthcare application. A c

is reliable medical data transmission, by which medical informa

monitored correctly by healthcare professionals. In a reliable m

transmission system, the receiver side BER may be affected by

channel noise, interference, distortion, attenuation, wireless multipath

A healthcare application has a dynamic duty cycle compared to

environmental monitoring applications. For example, environmenta

applications need a low duty cycle to collect environmental par

temperature, humidity etc. These applications have lower

requirements than the high duty cycle applications (healthcare appli

many applications, a fundamental problem is providing efficient and

transmission. In wireless sensor networks, the data transmission is un

to several factors such as [45]:

The wireless links can be unreliable, which leads to packet losses

The network congestions lead to packet losses as packets are

intermediate/routing nodes in the routing paths.

Interference, attenuation and fading are the main factors in un

transmission

Channel bit errors during wireless data transmissions.

In particular, ubiquitous health monitoring applications are related to

So, health management, precise measurement and reliable data

methods should be analysed before the designing of healthcare

applications. So far, a few research studies have been proposed

reliable data transmission using positive acknowledgement (ACK) a

acknowledgement (NACK) methods. The data retransmission app

most commonly used method for recovering packet error and losses. A

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4.2 Low-rate wireless personal area networks

Wireless technology for medical applications like IEEE 80

was used in this study The IEEE 802.15.4 standard was dev

demand for low power and low-cost in low-rate wireless per

(LR-WPAN). IEEE 802.15.4 deals with a low data rate, b

battery life (months or even years) and a very low complexity

802.15.4, defines the physical layer (PHY) and medium ac

sub-layer specifications for low-rate wireless personal ar802.15.4 defines two PHY layers; in the 2.4 GHz and 868/9

license free industrial scientific medical (ISM) 2.4 GHz

worldwide, while the ISM 868 MHz and 915 MHz bands are

and North America respectively. A total of 27 channels with

the-air data rates are allocated in 802.15.4: 16 channels wit

kbps in the 2.4 GHz band, 10 channels with a data rate of 40 band, and 1 channel with a data rate of 20 kb/s in the 868 MH

4.3 Error rate analysis for reliability

The bit error rate (BER) is the number of received binary

altered due to noise and interference, divided by the total nu

bits during a studied time interval. The BER can be considere

estimate of the bit error probability (bP ).

The packet error rate (PER) is the number of incorrectly tran

divided by the number of transferred packets. A packet is assu

if at least one bit is incorrect. Denote that the packet error p

expectation value of PER, which can be expressed for a data

bits as

1 (1 )Np bP P= .

The BER is often expressed as a function of the normalized

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0

2 be

EP Q

N

=

,

where ( )Q is the error function, bE is energy per bit, and 0N is the

spectral density ratio. The SNR as a function of transmission

expressed as

0

bE R

SNR

N B

= ,

where R is the channel data rate, and B is the channel bandwidth.

Fig. 11 shows the theoretical bit error rates of O-QPSK, 8-PSK a

The curves present that O-QPSK is better than 8-PSK and 16-PSK. I

higher-order modulations exhibit higher error-rates in exchange an

they deliver a higher raw data-rate.

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

BER

O-QPSK

8-PSK

16-PSK

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5 Results

5.1 Experimental setup and ECG signal measurement

In our tests, ECG data was obtained from the ECG signal generator

interface circuit, instead of an ECG sensor on the patients body. The

generator generates a synthesized ECG signal with a user-settable

signal duration, sampling frequency, QRS waves, etc. Fig. 12

oscilloscope output of the interface. This analog ECG signal, sup

MICAz wireless sensor node, is nearly identical to a theoretically cal

signal. The deflections in the tracing of the ECG comprise the Q, R, a

that represent the ventricular activity of the heart. The interval betw

peaks indicates the time between heartbeats. [Paper I]

Fig. 12. (a) ECG data from the ECG signal generator, (b) ECG signinterface circuit board, MICAz sensor node and base station with an RS-

[I, published by permission of Rare Metal Materials and Engineering].

5 2 Wearable u Healthcare monitoring

(a) (b)

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versatile framework for the incorporation of sensing, monitor

processing devices. Moreover, the smart shirt can be us

applications such as battlefield, public safety, health monito

fitness, among others [48, 49]. [Paper III]

Fig. 13. Smart shirt with an integrated wearable sensor nod

permission of Elsevier].

The monitoring of vital signs during the wearing of the desig

tested by real time monitoring of the ECG and acceleration

For the simultaneous monitoring of physiological ECG data a

smart shirt wearer, a treadmill was used. The speed of

controlled at a speed of 5km/h for walking and 8km/h for r

test on the treadmill was performed with the wearer standing

walking and running on the treadmill as shown in Fig. 14. F

results for walking, running and resting after the exercise.

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Fig. 14. ECG signal variations during walking, running and resting on the

published by permission of Elsevier].

The raw acceleration signals from a 3-axes accelerometer in the wea

node of a smart shirt during the exercise of a person on a treadmill we

in a wireless sensor network, as shown in Fig. 15. Acceleration sig

valuable information for the wearers activity classification, such

running and resting (standing). [Paper III]

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Fig. 15. Acceleration signals form a three-axes accelerometer du

and resting of a person on a treadmill [III, published by permissio

5.3 ECG data on the client display

Attached to the ECG signal generator and interface circuit

node collected the ECG signal at a sampling rate of 125 Hz.

also collected data at a 125 Hz sampling rate. Fig. 16 sho

sampled at a 12 bit resolution, in the terminal PCs GUI. A

ECG data obtained from the ECG signal generator via the int

12 (b) and the ECG data in the terminal PCs GUI in Fig. 1

sensor data were accurately transferred to the terminal PC

802.15.4 communication between the sensor node and the ba

is true concerning the transmission of data via TCP/IP betwee

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Fig. 16. ECG data in the terminal PCs GUI [IV, published by permission of

5.4 PDA display

A PDA (Personal Digital Assistant) was also used as a client termina

shows a PDA GUI snapshot of the PDA emulator, which displays rea

data sent from the server. The graphic user interface was developed t

PDA terminal to display the recorded ECG data in real time on the PD

and PDA screen, as shown in Fig.17 (a) and (b). [Paper I]

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5.5 Reliability analysis

The parameters used in the experiments are summarized i

measurement, a total of 500 packets were sent to the base-

packet size of 46 bytes in each packet. The measurements fo

made from a 1 to 100 meter distance between sensor nodes a

system operates at a 2.4 GHz band and offers a bit rate of 250

Table 4. Table 1 Reliability analysis parameters.

Parameters Value

Number of sent packets 500 (ECG data)

Number of packet size 46 bytes

Number of nodes 1~5

Topology configuration Randomized

Channel data rate 250 kbps

Ground distance 1~100 m

RF frequency 2.45 GHz

RF power 25~0 dBm

5.5.1 Reliability test in function of distance between

For empirical measurements, three scenarios were consider

distance between sensor nodes and the base-station, (2)

deployed sensor nodes in a network, (3) data transmissio

intervals. They were measured to analyse the reliability of th

rate wireless health monitoring applications. The PER is

received data that is analyzed to evaluate performance accord

All of the experiments were conducted using ECG sens

environment. The first experiment is about the measureme

function of distance, in a short communication range. The exp

built according to Table 4. The experiment scenario of differe

sensor node and base-station is shown in Fig. 18. For this ex

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Fig. 18. Measurement setup of network reliability of the distance bet

nodes and base-station.

In Fig. 19, the measured PER is shown as a function of the distan

sensor node and base-station. The average packet loss rate was obtain

RF signal strength to 0 dBm and 500 packets were sent to the base-

PER was calculated using the received packet loss rate. The x-axi

distance between sensor node and base-station. The PER increase

distance between sensor node and base-station was increased. The r

that the minimum and maximum packet losses are not much different

was found that the PER in the function of the distance jumped up su50 meters and was almost zero when node 1 and node 2 were dep

same time in a network.

The results of the measured PER versus SNR of different dis

such as D=10, 60 and 90 meter are shown in Fig. 20. The PER is 0

SNR is 8 dB.

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Fig. 19. Measured PER in the function of the distance between s

station.

10 20 30 40 50 60 700

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Distance [m]

PER

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Fig. 20. Measured PER versus SNR for different distance values, D=1

meter.

5.5.2 Reliability test in the function of the number of the se

nodes

The second set of experiments was to measure the PER as a fun

number of the sensor nodes, as shown in Fig. 21. In this ex

randomized topology was used and four sensor nodes and one base-

deployed in a network. It was assumed that each sensor node is abo

away from a base-station and RF signal strength was set to 5 dBm.

The PER, by deployment of the number of sensor nodes, is show

-15 -10 -5 0 510

-3

10-2

10-1

100

Eb/N

0(dB)

BER

DD

D

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PER increases with an increase in the number of nodes, du

packets.

Fig. 21. Measurement setup for deployment of the number of sen

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

PER

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Table 5. End-to-end success rate of number of transmission nodes.

Node ID Number of nodes Success rate (%)

1 1 99.56

2 1 99.32

2 99.44

3 1 72.4

2 71.64

3 72.52

4 1 59.32

2 50.52

3 59.96

4 43.8

5 1 39.72

2 47.76

3 41.56

4 35.56

5 37.96

5.5.3 Reliability test for different time intervals

For the last experiment, a scenario was considered for different time

different sensors using ECG and temperature sensors. Fig. 23 shows t

the PER for different sampling time intervals, when ECG data packeto the base-station at a rate of every 0.01 sec. On the other hand, the t

of the temperature sensor was set to 1 sec when sending the data

station. The PER of the temperature sensor is almost 0, when seven s

are deployed in a network. On the other hand, in the ECG experime

increased sharply for three or more sensor nodes in the network. As th

ECG sensor nodes increases, the PER also increases because of conte

multiple sensor nodes and data packet overflow.

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Fig. 23. Measured PER for different sampling time intervals,

temperature sensors (1 sec).

1 2 3 4 5 6 7 80

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Number of nodes

PE

R

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6 Discussion

The main objective of this thesis project was to study the use of wir

networks in a healthcare system as a low power consumption, low

hoc network. This thesis project focused on two specific research to

development of a distributed healthcare system for vital signs moni

wireless sensor network devices and 2) the empirical analysis of the

such low-rate wireless technology ubiquitous health monitoring applic

6.1 Multi-hop network for wireless body area network

This study proposes a ubiquitous healthcare system for vital signs m

Chapter 3. Since remote sensing techniques are to use wireless health

this thesis project sought to provide a reliable ECG signal for

healthcare monitoring. While technological advancements have changes in many aspects of daily life, there is still a significant gap

existing solutions and the needs in the medical field.

This thesis project is an endeavour to suggest a solution for utiliz

technologies and to provide a remote health monitoring system desi

medical environment. This system provides continuous and

monitoring for patient care in order to capture transient behaviour.

consists of three major components; a body sensor network node, loca

unit and a central server. Body sensor network nodes are attached on t

patient based on wireless sensor networks. The gathered data is

wirelessly over radio to the receiving base-station. Recent resear

focused on the development of wireless sensor networks and health

systems. For example, a number of wearable systems have been pr

integrated wireless transmission and local processing. The vital sign

systems worked fine in single-hop (ad-hoc network) data commun

revealed some scheduling problems in a multi-hop network. One

difficult constraints was that several wireless biological data sensor

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6.2 Electrocardiogram and accelerometer sensor

The electrocardiogram (ECG) is currently one of the mosmedical diagnostic procedures. ECG is usually used in a dia

monitoring mode. In the monitoring mode, the frequency

0.5Hz to 40Hz. In the diagnostic mode, the high-pass filter

the low-pass filter at 150Hz. The ECG sampling rate was

project, which allowed the bandwidth of the ECG (0.05 to 12

The ECG signal was amplified with a gain of 200 (24.8ddefault value of the sampling rate is fixed at a resolution of

seconds (10Hz). In this thesis project, we tried to apply

indicating 250Hz, with which an ECG signal cannot b

Therefore, we were interested in obtaining better performan

sampling rate, because according to well-known sampling th

rate must be more than two times the highest frequency

However, a bandpass-filter from 0.05 to 123Hz was used to li

converter (ADC) saturation and for anti-aliasing when the a

playback unit were digitized. Perhaps there are not very man

above 62Hz. The ADC was unipolar, with a 12-bit resolution

Sample values thus range from 0 to 2047 inclusive, wit

corresponding to zero volts. So, to convert a sample back

(millivolts), the ADC Zero 1024) is subtracted from the sam

divided by the gain.

Accelerometer sensors have been widely used to monito

movement parameters. We attached on the chest a three-ax

measure body acceleration as the reference signal. The subj

running on the treadmill. Acceleration signals provide valuab

as walking, running and resting (standing) in our experimacceleration signal, together with an ECG signal which includ

are measured as shown in Fig. 24. As seen in Fig. 24, Y-axis

the most sensitive to the motion artefact contained in the ECG

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Fig. 24. ECG signal with motion artefact and three-axes accelerometer sig

6.3 Wearable system for ubiquitous healthcare

A wearable system for ubiquitous healthcare should provide stable si

the patients daily activities. Resistance to motion artefact remains

challenge for wearable systems. Efforts are ongoing to eliminate

improving hardware design and applying signal processing algorith

studies have been devoted to the development of ring, watch, band

based wearable monitors, to improve the patients tolerance. In our sm

is still not very clear how to reduce the motion artefacts. Further impr

artefact reduction will remain critical for improvements in the wearab

acceptance and medical value of existing wearable systems. These c

are limited by factors including hardware design constraints associa

sensing of human status, power consumption, data storage and signal

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7 Conclusion

The main objective of this thesis project is to implement a wireles

monitoring system for measuring ECG from a patient in the home e

The research focuses on two specific research objectives: 1) the deve

distributed healthcare system for vital signs monitoring using wir

network devices and 2) a practical test and performance evalua

reliability for such low-rate wireless technology in ubiquitous health

applications.The first section of the thesis describes the design and impleme

ubiquitous healthcare system with tiny devices for the home car

persons. The system has been designed using a commercially availa

sensor network platform (MICAz, Crossbow Technology Inc., USA)

is capable of obtaining physiological data from a sensor attached to

body and transfers the data wirelessly to a remote base-station inetwork following the IEEE 802.15.4 standard for wireless pe

networks. The system concept can be used for ad-hoc routing o

monitoring signals to base-stations within the hospital premises, a

applications that require monitoring from the patients home. A wi

monitoring system has potential to provide an improved service

doctors and caregivers through continuous health monitoring. In addi

shirt with wireless sensor network compatibility is designed and fabri

continuous monitoring of physiological ECG signals and physical act

from an accelerometer simultaneously. To collect physiological EC

activity of the smart shirt wearer simultaneously, the performance tes

a treadmill by a wearer who is resting, walking and running on the

various speeds. Thus, the developed smart shirt system can be

improving the accuracy of a patient's diagnosis by continuous monit

non-invasive, comfortable and convenient shirt to wear in a wir

network environment.

In the experimental tests, ECG data was displayed on a Gra

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Three scenarios of performance studies were conside

measurement: 1) the effects of the distance between sensor no

2) the number of the deployed sensor nodes in a network and

by different time intervals. They were measured to analyse

technology in low-rate wireless u-Healthcare monitoring appl

In this thesis project, three scenarios were considere

reliability of low-rate wireless u-Healthcare monitoring. In

using ECG data, the PER is higher (about 104) than the env

coming from a temperature sensor. Moreover, reliability basenetworks, in particular, low-rate wireless medical monitori

distance between sensor node and base-station, the number o

network and different time intervals affect reliability perfor

experimental results. It was found that the PER of distance j

after 50 meters and was almost zero when node 1 and nod

same time in a network. To apply low-rate wireless techubiquitous health monitoring applications, the sampling rat

and data packet sizes, as well as reliable medical devices, a

the overall reliability of the system.

R f

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between IEEE 802.15.4 and IEEE 802.11b using Qualnet

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I Lee Y-D, Lee D-S, Chung W-Y & Myllyl R (2006) A wireless seplatform for elderly persons at home. Rare metal materials and engin

9599.

II Amit P, Lee Y-D & Chung W-Y (2008) Triaxial MEMS acceleromet

monitoring of elderly person. Sensor Letters 6(6): 10541058.

III Lee Y-D & Chung W-Y (2009) Wireless sensor network based wearab

for ubiquitous health and activity monitoring. Sensors and Actuators

140(2): 390395.IV Walia G, Lee Y-D, Chung W-Y & Myllyl R (2006) Distribut

monitoring in an ad-hoc network using a wireless sensor network. P

11th International Meeting on Chemical Sensors, Brescia, Italy.

V Lee Y-D, Lee D-S, Walia G, Myllyl R & Chung W-Y (2006) Query

vital signal monitoring system using wireless sensor network fo

healthcare. Proceedings of World Congress on Medical Physics an

Engineering, Seoul, Korea: 396399.

VI Lee Y-D, Lee D-S, Walia G, Alasaarela E & Chung W-Y (2007

evaluation of query supported healthcare information system using w

ad-hoc network. Proceedings of International Conference on

Information Technology, Gyeongju, Korea: 9971002.

VII Lee Y-D, Alasaarela E & Chung W-Y (2007) A wireless health monito

multi-hop body sensor networks. Proceedings of 2nd International S

Medical Information and Communication Technology (ISMICT'07), O

VIII Chung W-Y, Lee Y-D & Jung S-J (2008) A wireless sensor netwowearable u-healthcare monitoring system using integrated ECG, acce

SpO2. Proceedings of 30th Annual International Conference o

Engineering in Medicine and Biology Society (EMBC 2008), Vancou

15291532.

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Letters (II), Elsevier (III), IEEE (VI, VIII), Springer (V), IMCS

ISMICT2007 (VII).

Original publications are not included in the electronic version of the

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A C T A U N I V E R S I T A T I S O U L U E N S I S

S E R I E S C T E C H N I C A

355 Ronkainen Sami (2010) Designing for ultra-mobile interaction : experiences and a

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Book orders:

Granum: Virtual book store

http://granum.uta.fi/granum/

355. Ronkainen, Sami (2010) Designing for ultra-mobile interaction : experiences and a

method

356. Loikkanen, Mikko (2010) Design and compensation of high performance class ABamplifiers

357. Puikko, Janne (2010) An exact management method for demand driven, industrial

operations

358. Ylioinas, Jari (2010) Iterative detection, decoding, and channel estimation in

MIMO-OFDM

359. Tervonen, Pekka (2010) Integrated ESSQ management : as a part of excellent

operational and business managementa framework, integration and maturity

360. Putkonen, Ari (2010) Macroergonomic approach applied to work system

modelling in product development contexts

361. Ou, Zhonghong (2010) Structured peer-to-peer networks: Hierarchical

architecture and performance evaluation

362. Sahlman, Kari (2010) Elements of strategic technology management

363. Isokangas, Ari (2010) Analysis and management of wood room

364. Vnnen, Mirja (2010) Communication in high technology product development

projects : project personnels viewpoint for improvement

365. Korhonen, Esa (2010) On-chip testing of A/D and D/A converters : static linearitytesting without statistically known stimulus

366. Palukuru, Vamsi Krishna (2010) Electrically tunable microwave devices using BST-

LTCC thick films

367. Saarenp, Ensio (2010) Good construction quality : the realisation of good

construction quality in Finnish construction regulations

368. Vartiainen, Johanna (2010) Concentrated signal extraction using consecutive

mean excision algorithms

369. Nousiainen, Olli (2010) Characterization of second-level lead-free BGA

interconnections in thermomechanically loaded LTCC/PWB assemblies

370. Taskila, Sanna (2010) Improved enrichment cultivation of selected food-

contaminating bacteria

371. Haapala, Antti (2010) Paper machine white water treatment in channel flow :

integration of passive deaeration and selective flotation

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