Application-Specific Things Architectures For IOT-Based .
APPLICATION-SPECIFIC THINGS ARCHITECTURES FOR IOT-BASEDSMART HEALTHCARE SOLUTIONSPrabha Sundaravadivel, B.Tech., M.Tech.Dissertation Prepared for the Degree ofDOCTOR OF PHILOSOPHYUNIVERSITY OF NORTH TEXASMay 2018APPROVED:Saraju P. Mohanty, Major ProfessorElias Kougianos, Co-Major ProfessorBill Buckles, Committee MemberHui Zhao, Committee MemberBarrett Bryant, Chair of the Department ofComputer Science and EngineeringCostas Tsatsoulis, Dean of the College ofEngineeringVictor Prybutok, Dean of the ToulouseGraduate School
Sundaravadivel, Prabha. Application-Specific Things Architectures for IOT-BasedSmart Healthcare Solutions. Doctor of Philosophy (Computer Science and Engineering),May 2018, 94 pp., 10 tables, 47 figures, 85 numbered references.Human body is a complex system organized at different levels such as cells, tissuesand organs, which contributes to 11 important organ systems. The functional efficiencyof this complex system is evaluated as health. Traditional healthcare is unable toaccommodate everyone's need due to the ever-increasing population and medical costs.With advancements in technology and medical research, traditional healthcareapplications are shaping into smart healthcare solutions. Smart healthcare helps incontinuously monitoring our body parameters, which helps in keeping people healthaware. It provides the ability for remote assistance, which helps in utilizing the availableresources to maximum potential. The backbone of smart healthcare solutions is Internetof Things (IoT) which increases the computing capacity of the real-world components byusing cloud-based solutions. The basic elements of these IoT based smart healthcaresolutions are called “things.” Things are simple sensors or actuators, which have thecapacity to wirelessly connect with each other and to the internet. The research for thisdissertation aims in developing architectures for these things, focusing on IoT-based smarthealthcare solutions. The core for this dissertation is to contribute to the research in smarthealthcare by identifying applications which can be monitored remotely. For this,application-specific thing architectures were proposed based on monitoring a specific bodyparameter; monitoring physical health for family and friends; and optimizing the power
budget of IoT body sensor network using human body communications. The experimentalresults show promising scope towards improving the quality of life, through needle-lessand cost-effective smart healthcare solutions.
Copyright 2018byPrabha Sundaravadivelii
ACKNOWLEDGMENTSMy preparation towards pursuing a PhD started around 5 years ago. The first successful step towards achieving this long dream was when my mentor and major professor, Dr.Saraju P. Mohanty, accepted me into his lab. I would like to express my deepest gratitudeto him for his continuous support, guidance, and motivation throughout my doctoral studies. His kind attitude towards helping his students, his patience, and timely advice on myresearch and career, have been the catalyst for me to accomplish this task. I am extremelythankful to Dr. Elias Kougianos, for his guidance in my doctoral studies as my co-majorprofessor. His passion towards teaching (Embedded Systems) and timely suggestions withkindness, have inspired me to a great extent.I would like to thank my committee members, Dr. Bill Buckles, and Dr. Hui Zhao,for their valuable time and keen insights. I am very grateful to Dr. Barrett Bryant, and theDepartment of Computer Science and Engineering for funding my Doctoral Studies throughAssistantships, Scholarships and travel awards.I would like to thank my family without whom this milestone in my life wouldn’t havebeen possible. First, I would like to thank my husband, Lokeshwar, for his unconditionalsupport, inspiration and constant motivation which has helped me complete this journeysuccessfully. From guiding me in the application process to staying awake on my longnights, he has walked through each and every step of this journey with me. I am extremelythankful to my parents, Mr. Sundaravadivel and Mrs. Suseela Sundar, for all their sacrificesthroughout their life to help me and my sister, Dr. S. Bhuvanesswari, realize our dreams.I am thankful for their unconditional love, encouragement to take my own decisions andabove all, believing in me, even when I didn’t. I am very aware of how lucky I am to betheir daughter.Last but not least, I would like to thank my lab mates, CSE staff and all the friendlyfaces in UNT, for making each day brighter.iii
TABLE OF CONTENTSPageACKNOWLEDGMENTSiiiLIST OF TABLESviiLIST OF FIGURESviiiCHAPTER 1 INTRODUCTION11.1.Health and Human Body11.2.Significance of Smart Healthcare11.3.Internet of Things Trends in Smart Healthcare51.4.Motivation for this Dissertation61.4.1. Basal Body Temperature Monitoring through the IoT71.4.2. Human Activity Monitoring for Smart Families71.4.3. Energy Efficient Architectures using Human Body Communication8Organization of this Dissertation81.5.CHAPTER 2 PRIOR RESEARCH IN SMART HEALTHCARE102.1.Evolution of Wearables112.2.Design Considerations of Smart Healthcare Architectures112.2.1. Requirements for Smart Healthcare Design122.2.2. Components for Smart Healthcare Architectures132.2.3. Security Aspects of Smart Healthcare132.2.4. Services and Applications Available through Smart Healthcare142.2.5. Attributes of Smart Healthcare Designs162.3.Industry Trends in Smart Healthcare172.4.Novel Contributions of this Dissertation19iv
CHAPTER 3 IMPROVING QUALITY OF LIFE THROUGH BASAL BODYTEMPERATURE (BBT) MONITORING20BBT Monitoring through the IoT: A Broad Smart Health Perspective203.1.1. Background203.1.2. BBT Monitoring Sensor Design Considerations213.2.Related Prior Research233.3.Design of the Proposed BBT Monitoring Sensor as an IoT Component243.3.1. BBT Monitoring Sensor: Patient’s Module253.3.2. BBT Monitoring Sensor: IoT Cloud Solution283.3.3. BBT Monitoring Sensor: Doctor’s Module30Implementation and Validation of the BBT Monitoring Sensor303.4.1. Simulation Level Validation303.4.2. Learning Model of the BBT Analysis Engine373.4.3. Characterization of the Sensor Module393.1.3.4.CHAPTER 4 HUMAN ACTVITY MONITORING FOR SMART FAMILIES4.1.44The SmartWalk System in the IoT: A Broad Perspective444.1.1. Significance444.1.2. Design Considerations464.2.Related Prior Research474.3.System Level Design of the SmartWalk System494.3.1. Sensor Design494.3.2. Feature Extraction for Data Analysis524.3.3. Human Activity Monitoring Algorithm52Implementation and Validation of SmartWalk system544.4.1. Human Activity Learning Model544.4.2. Experimental Validation564.4.CHAPTER 5 ENERGY EFFICIENT ARCHITECTURES USING HUMAN BODYv
COMMUNICATION64Human Body Communication in the IoT: A Broad Perspective645.1.1. Background645.1.2. Design Considerations665.2.Related Prior Research685.3.Proposed Ambulatory Monitoring Body Area Network695.3.1. Array of Sensors695.3.2. Communication Channel715.1.5.4.Implementation and Validation of Ambulatory Monitoring Body AreaNetwork73CHAPTER 6 CONCLUSIONS836.1.Summary836.2.Future Directions of the Proposed Research84REFERENCES85vi
LIST OF TABLESPageTable 3.1.Frequency and time period values for various temperatures.Table 3.2.Normalized frequency and time period values along with raw data for 1334stage and 17 stage ring oscillator temperature sensors.38Table 3.3.Efficiency of the BBT analysis engine.40Table 3.4.Characterization table for different sensor architectures.42Table 3.5.Comparison of related research in temperature sensor design.43Table 4.1.Classifier evaluation for kurtosis values using WEKA.57Table 4.2.Classifier evaluation for minimum and maximum accelerometer valuesusing WEKA.57Table 4.3.Performance comparison with existing results.61Table 4.4.Characterization of SmartWalk system.62Table 5.1.Characterization table of the proposed ambulatory monitoring BAN.82vii
LIST OF FIGURESPage1.1Anatomy of the human body (Image Courtesy of Creative Commons,pixabay.com).1.22Difference between traditional healthcare and smart healthcare (ImageCourtesy of Creative Commons, pixabay.com).31.3Classification of smart healthcare.41.4Internet of Things for smart healthcare.61.5Organization of this dissertation.92.1Evolution of wearables (Image Courtesy of Creative Commons,pixabay.com).102.2Design considerations of smart healthcare.122.3Ubiquituous computing in the smart watch (Image Courtesy of CreativeCommons, pixabay.com).173.1Functions of the thyroid gland.223.2Basic architecture for smart health monitoring.233.3Architecture of BBT monitoring sensor as an IoT component.253.4Inverter: (a) Basic type; (b) Current starved with output-switching; (c)Current starved with symmetrical load.273.5Thermal sensor using a ring oscillator and an XOR gate.283.6Support vector machine based BBT analysis engine.293.7Flow diagram of data flow across the modules.313.8Simulink R implementation of current starved ring oscillator with balancedload.3.933Time period vs. temperature for different sensor architecture simulationsin Simulink R .35viii
3.10Frequency vs. temperature for different sensor architecture simulations inSimulink R .3.1136Comparison of oscillator output vs. normalized time period for 17 stagetemperature sensor in Simulink R .3.1239Surface plot for time period and frequency values in the current starvedring oscillator.403.13BBT analysis engine in Simulink R .414.1Working of a 3-axis accelerometer.454.2Design phases involved in health monitoring systems.464.3Framework of the SmartWalk system (Image Courtesy of CreativeCommons, pixabay.com).484.4Datapath for efficient parameter estimation.504.5Classification of accelerometers.514.6Algorithm for human step detection.534.7Total number of input instances grouped under 6 activities.554.8Kurtosis analysis in WEKA.564.9Human activity monitoring classifier evaluation using kurtosis as afeature.4.1058TI MSP432 integrated with the sensor board, Educational BoosterPackMKII.4.1159Kurtosis values in different postures such as sitting, standing and walkingobtained from 3 different subjects.604.12User interface to display the human step values.635.1Different layers of the network and their corresponding protocols.655.2Anatomy of the human skin (Image Courtesy of Creative Commons,pixabay.com).665.3Different types of area networks.675.4Transceiver model for human body communication.68ix
5.5Datapath across the ambulatory monitoring body area network.705.6Block diagram of a simple MEMS based gyroscope.725.7HBC block diagram with FSBT modulator.745.8Gyroscope block diagram in Simulink R .765.9Body modeled as a spreading resistance. The transmitter and receiver arecapacitively coupled to the body.775.10Output of gyroscope sensor module with white noise.785.11Frequency spectrum after BPF in HBC implementation.785.12A mesh of Walsh code for n 64, i.e. M64 64 of all 1s and 0s.795.13Performance of HBC with FSBT.805.14Frequency response for BCC channel.81x
CHAPTER 1INTRODUCTION1.1. Health and Human BodyFrom an engineering perspective, the human body can be defined as a combinationof multiple subsystems where each component of the subsystem needs to function smoothly.This complex system, the human body, is organized at different levels such as cells, tissuesand organs, which together contribute to 11 important organ systems. Figure 1.1 shows theanatomy of the human body.A imbalance in any of these organizational levels can affect the equilibrium of theentire system. The overall functional efficiency and stability of this system is evaluatedas health. The World Health Organization (WHO) defines human health as a state ofcomplete physical, mental and social well-being [1]. Advancements in technological andmedical research, coupled with increased awareness about health and hygiene, have resultedin an increase in life expectancy of individuals [37]. However, the increasing costs of medicaltreatments and ever increasing population, is causing major healthcare inequality in termsof geographical limitations, economic status, lifestyle etc. [42]. Due to these inequalities,there exists a vast gap between the group of people that strive to contribute to the humanwell-being, and people who are in need of these resources.1.2. Significance of Smart HealthcareA smart solution for a smart city is a combination of one or more intelligent components that helps in improving the living standards of its citizens [45, 44, 29]. Components ofa smart solution may include sensing elements such as sensors and actuators, computationalelements such as processors, workstations, servers etc., connected to each other to performubiquitous computing. Smart transportation, smart buildings, smart energy, smart governance, and smart healthcare are notable components of smart city solutions [46]. With anaim towards improving the healthy living of citizens, smart healthcare plays a significantrole in a smart city. The costs involved in treating chronic diseases have been constantly1
BrainHypothalamusPharynxLarynxLymph nodesThyroidLungsArteriesHeartBone inesUrinary bladderFigure 1.1: Anatomy of the human body (Image Courtesy of Creative Commons, pixabay.com).increasing. By 2025, this cost is expected to increase to a total of 60 % of total healthcare costs. In addition to this, the healthcare inequalities amongst individuals require anyhealthcare solution to enhance remote assistance. This has been the driving force for tradi2
tional healthcare applications shaping into smart healthcare solutions. Figure 1.2 shows thedifference between traditional healthcare and smart healthcare.Traditional HealthcareSmart HealthcareFigure 1.2: Difference between traditional healthcare and smart healthcare (Image Courtesyof Creative Commons, pixabay.com).In recent days, the concentration of research in healthcare is on continuous monitoringsolutions which aim in preventing major chronic diseases. One of the key aspects of smarthealthcare is its ability to keep users health-aware. It helps users to manage emergencysituations and improves the quality of their lives. By deploying smart healthcare solutionsthe available resources are best utilized to their maximum potential. By providing the abilityfor remote assistance, smart healthcare reduces the overall healthcare costs.Figure 1.3 shows a classification of smart healthcare based on design aspects andcommercial aspects. In terms of design aspects, connectivity technologies contribute moretowards faster data transfer, power budget and size of the solution. Irrespective of theapplication, any component in the smart healthcare architecture requires a wireless protocolto be used for facilitating remote assistance. Depending upon the range and proximity ofthe devices placed, the connectivity technologies are chosen. The medical devices used in the3
smart healthcare design can be classified based on whether the device is placed on the humanbody or is a stationary medical device used in creating a smart environment. Body sensorsare mainly designed for physiological monitoring. Wearables such as smart watches, activitytrackers, smart clothing, and wearable cameras are designed with a focus on obtaining oneor more physical parameters from the human body. These wearables are designed eitherfor a single condition such as activity monitoring, drug delivery system [48], or a clusterof multiple conditions such as fitness monitoring, assisted living etc. [2]. Ingestible sensorsinvolve devices which can be swallowed in order to monitor the human body from the inside.On the commercial perspective, smart healthcare can be classified based on the end-usermarket and system management.Classification of Smart HealthcareBased on Design AspectsConnectivityProtocolsServices FC*ZigBee*Cell phones Wearables*SatellitesBased on Commercial AspectsStationaryMedicalDevicesEnd-user rs*Individuals*Hospitals*Government Organizations*Clinical Research Institutes*Diagnostic LaboratoriesSystemmanagement*Database Management*Remote Management*Network Management*Security ManagementFigure 1.3: Classification of smart healthcare.In the present digital era, most of the smart healthcare solutions can be categorized asconnected health, which is a collective term for subsets such as assistance-based applications,and sensing based applications. Assistance-based applications include telemedicine and emedicine which help users find resources to educate themselves, enhance self-care, providefeedback to the user, and complement it with remote-care. Assistance-based healthcaresolutions help the users receive feedback from the clinicians whenever required. Sensingbased applications require a sensing element such as a sensor or actuator to monitor aparameter, either continuously or periodically, depending upon the application. The role4
of connected health in sensing-based applications is primarily determined by the end usermarket. For example, in designing a blood pressure monitor, the cost, area, power andoverall architecture varies depending upon the end-user market. In a hospital scenario, ablood pressure monitor would be connected to the main database maintaining health records,whereas a blood pressure monitor designed for individual use must be of smaller form factorto be placed in the body as a wearable device. This end-user market defines the economy ofsmart healthcare.1.3. Internet of Things Trends in Smart HealthcareThe Internet of Things (IoT) helps the real-world electronic components of smallerform factor to perform advanced computing using cloud-based solutions. It makes these realworld components self-sufficient and gives them the benefit of remote-access and faster datasharing [47]. Sensors are simple electronic devices which convert a physical quantity suchas temperature, humidity, proximity, light intensity etc., into numerical values [55]. Withadvancements in technology, portable electronic devices such as phones, tablets, and smartwatches, are embedded with multiple sensors which help in sensing many physical parameters. IoT based solutions store these numerical quantities of the physical parameters in thecloud where meaningful interpretation to this data can be obtained. Due to the faster datasharing and ability to be self-sufficient, the IoT has has been widely used in transportation,healthcare, agriculture, energy conservation, building construction, and surveillance [31].Any healthcare solution starts from identifying a healthcare application, towards which theproduct can be further developed. The IoT offers a multitude of benefits and advanced solutions which make it an integral component of many smart healthcare applications. Smarthealthcare solutions based on the IoT range from diagnosing chronic diseases to efficientmanagement of pharmacy inventories [70]. The confluence of research in smart electronicsystems combined with medical science has made IoT based smart healthcare a billion dollarindustry. Figure 1.4 illustrates the different aspects of the IoT in smart healthcare.IoT-based smart healthcare solutions help in reducing the distance between doctorand patient and make healthcare more affordable and attainable. With enormous potential5
SmartnodesLab encyServicesConnectivityBig dataSecurityFigure 1.4: Internet of Things for smart healthcare.benefits, the IoT has made many biomedical applications very diverse, which makes it tobe redefined as the “Internet of Everything” [43]. Improving quality of life through remoteassistance and helping users be health-aware, are the key driving factors of smart healthcaresolutions. Certain applications involve non-diagnosis based solutions, such as inventorymonitoring where IoT based solutions help in organizing drugs efficiently, maintaining digi
3.1. BBT Monitoring through the IoT: A Broad Smart Health Perspective20 3.1.1. Background20 3.1.2. BBT Monitoring Sensor Design Considerations21 3.2. Related Prior Research23 3.3. Design of the Proposed BBT Monitoring Sensor as an IoT Component24 3.3.1. BBT Monitoring Sensor: Patient’s Module25 3.3.2. BBT Monitoring Sensor: IoT Cloud .
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