Microwave Sleep Apnoea Monitoring

307 Pages·2018·12.258 MB·English

by  Nemai Chandra Karmakar,Yang Yang,Abdur Rahim (auth.)

Series in BioEngineering
Nemai Chandra Karmakar
Yang Yang
Abdur Rahim
Microwave
Sleep
Apnoea
Monitoring
Series in BioEngineering
The Series in Bioengineering serves as an information source for a professional
audience in science and technology as well as for advanced students. It covers all
applications of the physical sciences and technology to medicine and the life
sciences.Itsscoperangesfrombioengineering,biomedicalandclinicalengineering
to biophysics, biomechanics, biomaterials, and bioinformatics.
More information about this series at http://www.springer.com/series/10358
Nemai Chandra Karmakar
Yang Yang Abdur Rahim
(cid:129)
Microwave Sleep Apnoea
Monitoring
123
NemaiChandra Karmakar Abdur Rahim
Department ofElectrical andComputer Department ofElectrical andComputer
SystemsEngineering SystemsEngineering
MonashUniversity MonashUniversity
Melbourne, VIC Melbourne, VIC
Australia Australia
Yang Yang
Schoolof Electrical andData Engineering
University of Technology Sydney
Ultimo, NSW
Australia
ISSN 2196-8861 ISSN 2196-887X (electronic)
Series in BioEngineering
ISBN978-981-10-6900-0 ISBN978-981-10-6901-7 (eBook)
https://doi.org/10.1007/978-981-10-6901-7
LibraryofCongressControlNumber:2017955356
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Preface
Themodernworldhasbeenevolving throughremarkablechangesinallaspectsof
life.Thetechnologicaladvancementsintheeraofinformationandcommunications
technology (ICT) have connected people from various regions so gracefully as if
they are living together in a virtual global village. The open market economic
infrastructures of the world bring healthy people mobilities, cultural infusions and
improved living qualities. The consequence is the rising economic power and
eradication of poverty in the Eastern nations, and the complex socio-political
equations between the Eastern and Western worlds. With the advent of new tech-
nologies and economic prosperities, a large pool of middle-class people can effort
many new amenities. As consequences, lifestyles have changed, and the physical
activities have reduced enormously with the advents of mobile communications
gadgets, easy accesses to private cars, entertainment activities, the Internet and
social media.
Tomaintainthehighlivingstandardsofthecurrentera,thelivesofpeoplehave
become more busy and stressful. The lifestyle and stress-related diseases such as
sleep deprivations, diabetics, blood pressures, cancers, heart attacks and strokes
have emerged as the most killing factors. These lifestyle diseases were very
uncommon in our previous generations because they were physically more active
and less stressed. Even the children are not immune to lifestyle diseases. In recent
decades,livinginnuclearfamiliesandlessphysicalactivitiesamongchildrenhave
becomeverycommonduetoeasyaccessandthepopularityofmobilegadgets,TVs
and Internet. Therefore, sleep apnoea is very common in children too. One of the
maingoalsofthecurrentresearchwastodevelopwirelesssleepapnoeamonitoring
system targeting the pediatric patients.
Prolonged sleep deprivation and sleep disorder can cause many diseases as
stated above. It also affects the mental health of a person and a child severely.
Therefore, sleep monitoring in an early stage is imperative to stop the high risk
of these killing diseases.
v
vi Preface
Sleep monitoring is a complex exercise. To understand the cause and effect
ofthesleepdisorder,atleast11–22physiologicalparametersofapatientareneeded
to be measured. That is why sleep test of a patient in a sleep laboratory may cost
more than a thousand dollars. The second important factor of identifying the sleep
disorderistomeasurethesephysiologicalparametersinapatient’snaturalsleeping
condition. In a laboratory setting, with many wires of the monitoring devices
attachedtothepatientinthebedofasleeplaboratory,apatientcannotprovidethe
naturalsleeppattern.Eventhisismoreseriousforpaediatricpatientsduetothefear
factors of tangling with many wires and electronic gadgets attached to the body.
The best solution is to develop a wireless sleep monitoring system that is easy to
retrofitwiththegarment.Thepatientcantakeithomeandsleepinhis/herbed.The
solution is also cheap as it will not involve any laboratory setting and presence of
nurses and doctors. With the cloud computing interface, the doctor and nurse can
downloadthedataateaseandinterprettheresults.Thecurrentbookhasaugmented
the vision of telemedicine by developing a microwave wireless sleep monitoring
systemthatiseasilymountabletothepatient'sbodywithoutanywire.Alocalbase
station gathers thephysiologicaldata fromthepatients duringhis/her regularsleep
in his/her own bed, and transmits the data via the WiFi and/or mobile phone
communications networks to the doctor and nurse. The doctor and nurse can
download the sleep monitoring data for further processing.
The book has two main hypotheses: (i) developing a wireless microwave fre-
quency dot, also called wireless microwave frequency transducer that collects the
heart rates in term of electrocardiogram (ECG) data, muscular activities in term
mechanomyogram (MMG) and brain activities in term of electroencephalogram
(EEG), and (ii) advanced-level signal processing called virtual multiple input
multiple output (MIMO) algorithm to enhance efficacy of the system by reducing
noise and interferences in the on-body wireless propagation channel. This book
covers four major areas so that a general reader who is not expert in the fields of
microwave engineering, antenna technologies, signal processing and even medi-
cine, can be benefited. The book includes the general background of wireless
monitoring technology and MIMO in wireless body area network (WBAN),
microwave hardware designs, virtual MIMO in WBAN, hardware system-level
implementation and field trials.
Australian Research Council (ARC) supported the project under the scheme
oftheprestigiousnationallycompetitiveLinkageProjectGrantLP0776796:Radio
Frequency Wireless Monitoring in Sleep Apnoea (Particularly for Paediatric
Patients). The project was partially sponsored by Regni Health and Sciences Pty.
Ltd, Melbourne, Australia. Completion of two PhD-level research projects exem-
plifies the significance of the research outcomes of the ARC Linkage project. The
research outcomes are: (i) the state-of-the-art 2.4/5.8 GHz wireless microwave
frequency transducer design from scratch for ECG/MMG/EEG signal capturing,
(ii) propagation modelling of 2.4/5.8 GHz around the patient’s body, (iii) spatial
Preface vii
diversity test of MIMO antennas using Alamuti coding, and finally, (iv) virtual
MIMO cooperative network for energy efficient transmission/reception of wireless
body area network (WBAN) signal. We conducted a successful demonstration
ofthewirelessmonitoringsysteminfrontoftheindustrysponsorinJune2013.We
believe that the microwave engineers, antenna technologists, signal processing
experts, biomedical engineering professionals and students, and the doctors and
nurses of the sleep apnoea laboratories will accept the book very well.
Melbourne, Australia Nemai Chandra Karmakar
May 2017 Yang Yang
Abdur Rahim
Contents
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 TheSignificanceofWirelessMonitoringTechnologyforSleep
Apnoea and MIMO. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 The Hypothesis and Motivation of the Book . . . . . . . . . . . . . . 3
1.3 Outline of the Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.4 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Part I Wireless Monitoring Technology and MIMO in WBAN
2 Vision of the Wireless Monitoring Techniques in Sleep Apnoea . . . 15
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2 Traditional Sleep Monitoring Systems . . . . . . . . . . . . . . . . . . . 17
2.2.1 Cable Based System. . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.2.2 Wireless System. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.3 Challenges and Limitations of Current Monitoring Systems. . . . 20
2.4 Motivations for a Novel Microwave Sleep Apnoea System . . . . 21
2.5 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3 Wireless Monitoring of Sleep Apnoea Patients . . . . . . . . . . . . . . . . 25
3.1 OverviewoftheMainPhysiologicalParametersfor Diagnosis
of Sleep Apnoea. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3.1.1 Electroencephalogram (EEG) . . . . . . . . . . . . . . . . . . . 27
3.1.2 Electrocardiogram (ECG) . . . . . . . . . . . . . . . . . . . . . . 27
3.1.3 Electrooculogram (EOG). . . . . . . . . . . . . . . . . . . . . . . 28
3.1.4 Electromyogram (EMG) . . . . . . . . . . . . . . . . . . . . . . . 29
3.2 Sleep Apnoea Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.3 Wireless Monitoring Technologies for Sleep Apnoea . . . . . . . . 31
3.3.1 Sleep Apnoea Monitoring. . . . . . . . . . . . . . . . . . . . . . 34
ix
x Contents
3.3.2 RF-Based Monitoring System . . . . . . . . . . . . . . . . . . . 35
3.3.3 Conclusion and Motivation. . . . . . . . . . . . . . . . . . . . . 36
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
4 Background of MIMO in Sleep Apnoea Monitoring. . . . . . . . . . . . 41
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.2 Existing Work on Sleep Apnoea Monitoring Systems . . . . . . . . 42
4.3 WBANs and Its Challenges in Sleep Apnoea Monitoring
System. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
4.4 Propagation Channel Model for WBAN. . . . . . . . . . . . . . . . . . 46
4.4.1 Channel Model Scenarios for Dynamic WBAN
System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
4.4.2 Statistical Fading Channel Model for WBAN. . . . . . . . 48
4.5 MIMO in Wireless Communication . . . . . . . . . . . . . . . . . . . . . 50
4.6 MIMO in WBAN Communication. . . . . . . . . . . . . . . . . . . . . . 52
4.6.1 MIMO Channel Model for WBAN . . . . . . . . . . . . . . . 53
4.7 Cooperative Communications . . . . . . . . . . . . . . . . . . . . . . . . . 54
4.8 Network Coding Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . 55
4.9 Proposed Research for Wireless Sleep Apnoea Monitoring . . . . 56
4.10 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
5 Network Coding Techniques in WBAN. . . . . . . . . . . . . . . . . . . . . . 63
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
5.2 Energy-Efficient Network Coding Techniques for Dynamic
WBAN System. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
5.3 Network Coding Enhances Throughput . . . . . . . . . . . . . . . . . . 67
5.3.1 Network Coding for Reliable Handling of Data from
Large Numbers of Sensors . . . . . . . . . . . . . . . . . . . . . 69
5.3.2 Network Coding Techniques for Very Highly Fading
or Dynamic Environments . . . . . . . . . . . . . . . . . . . . . 70
5.4 Outage Probability Analysis of Sensor Cooperation . . . . . . . . . 71
5.5 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Part II RF Wireless On-Body Sensor Designs
6 Wireless On-Body Sensor Architecture. . . . . . . . . . . . . . . . . . . . . . 79
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
6.2 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
6.3 System Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
6.3.1 Layer 1: On-Body Patch Antenna . . . . . . . . . . . . . . . . 82
6.3.2 Layer 2: Passive High Selectivity BPF . . . . . . . . . . . . 83
6.3.3 Layer 3: Integrated ECG Detection and Frequency
Upconversion Circuits . . . . . . . . . . . . . . . . . . . . . . . . 83