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http://hdl.handle.net/10603/451594
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DC Field | Value | Language |
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dc.coverage.spatial | ||
dc.date.accessioned | 2023-01-23T04:16:56Z | - |
dc.date.available | 2023-01-23T04:16:56Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/451594 | - |
dc.description.abstract | As the recent pandemic COVID-19 shakes the whole world, the role of IoT and newlinecloud computing has become significant in the healthcare industry. In IoT based newlinehealthcare applications, wireless body area networks (WBANs) play a critical newlinerole in facilitating accurate, energy-efficient, and cost-effective healthcare facilities. newlineHowever, the wide-scale adoption and deployment of WBAN are hindered newlineby challenges in data management, data vulnerability, and data privacy. Data newlinemanagement becomes an issue due to the need for handling the large volume newlineof data generated by the sensor nodes for continuous monitoring, processing newlineand analysis. The sensitive nature of private health data causes concerns on vulnerability newlineand privacy during wireless transmission and cloud processing. The newlinetwo primary operations that address these challenges are efficient data compression newlineand data security. Most of the compression and security solutions proposed newlinefor networks like wireless sensor networks (WSNs) cannot be directly applied to newlineresource-constrained WBAN. newlineAccording to the world health organization (WHO), cardiovascular disease newline(CVD) is the leading cause of death globally, causing about an estimated 17.9 newlinemillion deaths each year. To reduce the incidence, prevalence, morbidity, and newlinemortality of CVD,WHOjoins hands with countries and various healthcare partners newlineto develop cost-effective and feasible innovations for detecting CVD accurately. newlineThe widely used and inexpensive diagnostic method to investigate CVD is the newlineelectrocardiogram (ECG) monitoring. The ability to acquire, process, and transmit newlineECG in conjunction with the ability to automatically verify and provide decisions newlinebased on the remotely perceived ECG, help the medical practitioners to tackle newlinethe dangers of CVD considerably. newline | |
dc.format.extent | ||
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | Efficient and secure lightweight system for ecg telemonitoring in wireless body area network | |
dc.title.alternative | ||
dc.creator.researcher | Koya, Aneesh M | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Engineering | |
dc.subject.keyword | Engineering Electrical and Electronic | |
dc.subject.keyword | ||
dc.subject.keyword | Sensor networks | |
dc.description.note | ||
dc.contributor.guide | P P, Deepthi | |
dc.publisher.place | Calicut | |
dc.publisher.university | National Institute of Technology Calicut | |
dc.publisher.institution | Department of Electronics and Communication Engineering | |
dc.date.registered | 2015 | |
dc.date.completed | 2021 | |
dc.date.awarded | 2021 | |
dc.format.dimensions | ||
dc.format.accompanyingmaterial | DVD | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Department of Electronics and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 105.43 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 866.42 kB | Adobe PDF | View/Open | |
03_content.pdf | 111.7 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 70.78 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 589.96 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 3.32 MB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 2.42 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 1.62 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 517.14 kB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 774.94 kB | Adobe PDF | View/Open | |
11_annexures.pdf | 124.82 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 115.12 kB | Adobe PDF | View/Open |
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