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Mitigating interference in Wireless Body Area Networks and harnessing big data for healthcare

Jamthe, Anagha
http://orcid.org/0000-0002-8744-2439
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1445341798

Abstract Details

2015, PhD, University of Cincinnati, Engineering and Applied Science: Computer Science and Engineering.
Wireless Body Area Network (WBAN) has become an important field of research that could provide cost effective solution for ubiquitous health care monitoring of human body. In recent past, it has attracted attention from several researchers due to its potential applications in various disciplines including health care, sports-medicine, entertainment, etc. It is rapidly replacing wired counterparts due to its several attractive features such as light-weight easy portability, support for real time remote monitoring, ease of use, etc. Users of WBANs are increasing exponentially as more people are embracing wearable monitoring devices for numerous health care causes. Interference is considered to be one of the major issues in WBANs, which arises primarily due to close proximity of other WBANs, random human mobility, and distributed nature of people carrying WBANs. Coexisting WBANs have great chance of interference, which might degrade the network performance. If left unchecked, interference can cause serious threat to reliable operation of the network. It could cause to loss of critical medical data of patients, which might even prove to be life threatening. The primary motivation behind this dissertation is to avoid such a situation by using various interference mitigation techniques. Graceful coexistence could be ensured by scheduling the transmissions between co-existing WBANs. MAC layer is responsible for scheduling data transmissions and coordinating nodes’ channel access that avoids possible collisions during data transmissions. In this dissertation, we have attempted to address intra-WBAN and inter-WBAN interference issues. We model a fuzzy logic based inference engine to make decisions while scheduling transmissions in isolated WBANs. For coexisting WBANs, due to its distributed nature and lack of central coordinator, we propose a QoS based MAC scheduling approach that avoids inter-WBAN interference. Our proposed MAC scheduling scheme can be used for improving network performance, which is also confirmed from the results. We also discuss one of the important challenges in modeling such a MAC schemes, which is random human mobility. In this dissertation we also discuss leveraging big data technology for healthcare. The use of wearable devices is growing tremendously so is the data generated from it. In order to efficiently convert this big data into a useful resource of information, which can be used for diagnosis or prognosis, a need for distributed parallel framework arises. Using the latest big data solutions we can efficiently store and process the healthcare sensor data. This offers a cheaper, reliable and faster computation as compared to traditional database management systems. Various analytic methods for clinical prediction can be used with this framework to enable automated learning and accurate prediction. We discuss in this dissertation, the emerging technologies for WBAN such as implant medical sensor devices and the communication standards associated with them. The emerging technologies Near field communication and Beacon can be harnessed to develop a smart medicine management mobile application. We conclude this dissertation by identifying future directions on data security in WBANs and implementation of personalized medicine.
Dharma Agrawal, D.Sc. (Committee Chair)
Richard Beck, Ph.D. (Committee Member)
Prabir Bhattacharya, Ph.D. (Committee Member)
Chia Han, Ph.D. (Committee Member)
Wen-Ben Jone, Ph.D. (Committee Member)
Carla Purdy, Ph.D. (Committee Member)
119 p.
Computer Science
Wireless Body Area Networks; Big Data in healthcare; Interference mitigation; IEEE 802 15 6; coexistence in WBANs; sensor data analysis

Recommended Citations

Citations

  • Jamthe, A. (2015). Mitigating interference in Wireless Body Area Networks and harnessing big data for healthcare [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1445341798

    APA Style (7th edition)

  • Jamthe, Anagha. Mitigating interference in Wireless Body Area Networks and harnessing big data for healthcare. 2015. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1445341798.

    MLA Style (8th edition)

  • Jamthe, Anagha. "Mitigating interference in Wireless Body Area Networks and harnessing big data for healthcare." Doctoral dissertation, University of Cincinnati, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1445341798

    Chicago Manual of Style (17th edition)

ucin1445341798
1,103
© 2015, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.