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Critical Condition Detection Using Lion Hunting Optimizer and SVM Classifier in a Healthcare WBAN

Critical Condition Detection Using Lion Hunting Optimizer and SVM Classifier in a Healthcare WBAN

Madhumita Kathuria, Sapna Gambhir
Copyright: © 2020 |Volume: 11 |Issue: 1 |Pages: 17
ISSN: 1947-315X|EISSN: 1947-3168|EISBN13: 9781799806899|DOI: 10.4018/IJEHMC.2020010104
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MLA

Kathuria, Madhumita, and Sapna Gambhir. "Critical Condition Detection Using Lion Hunting Optimizer and SVM Classifier in a Healthcare WBAN." IJEHMC vol.11, no.1 2020: pp.52-68. http://doi.org/10.4018/IJEHMC.2020010104

APA

Kathuria, M. & Gambhir, S. (2020). Critical Condition Detection Using Lion Hunting Optimizer and SVM Classifier in a Healthcare WBAN. International Journal of E-Health and Medical Communications (IJEHMC), 11(1), 52-68. http://doi.org/10.4018/IJEHMC.2020010104

Chicago

Kathuria, Madhumita, and Sapna Gambhir. "Critical Condition Detection Using Lion Hunting Optimizer and SVM Classifier in a Healthcare WBAN," International Journal of E-Health and Medical Communications (IJEHMC) 11, no.1: 52-68. http://doi.org/10.4018/IJEHMC.2020010104

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Abstract

A timely critical condition detection and early notification are two essential requirements in a healthcare wireless body area network for the correct treatment of patients. However, most of the systems have limited capabilities and so could not detect the exact condition in a precise time interval. In addition to these it needs a reduction in the false alert rate, as issuing alerts for the deviation in each incoming packet increases the false alert rate and these false alerts consume more network resources. In order to fulfill the above-mentioned requirements, a dynamic alert system has been designed in this regard to make it more efficient, also, a new kind of hybridization approach is being introduced to it with the additive support of a nature-inspired optimization strategy named Lion Hunting and a machine-learning technique called support vector machine. The simulation is done using a network simulator NS-2.35, and the proposed alerting system outperforms others.