Optimization Driven Deep Learning Approach for Health Monitoring and Risk Assessment in Wireless Body Sensor Networks

Author:

Alameen Abdalla1,Gupta Ashu1

Affiliation:

1. College of Arts and Sciences, Prince Sattam Bin Abdulaziz University, Al Kharj, Saudi Arabia

Abstract

Wireless body sensor networks (WBSNs) plays a vital role in monitoring health conditions of patients and is a low-cost solution for dealing with several healthcare applications. Processing large amounts of data and making feasible decisions in emergency cases are the major challenges for WBSNs. Thus, this article addresses these challenges by designing a deep learning approach for health risk assessment by proposing a Fractional Cat-based Salp Swarm Algorithm (FCSSA). At first, the WBSN nodes are utilized for sensing data from patient health records to acquire certain parameters for making the assessment. Based on the obtained parameters, WBSN nodes transmit the data to the target node. Here, the hybrid Harmony Search Algorithm and Particle Swarm Optimization (hybrid HSA-PSO) is used for determining the optimal cluster head. Then, the results produced by the hybrid HSA-PSO are given to the target node, in which the Deep Belief Network (DBN) is used for classifying the health records for the health risk assessment. Here, the DBN is trained using the proposed FCSSA, which is developed by integrating a Fractional Cat Swarm Optimization (FCSO) and Salp Swarm Algorithm (SSA) for initiating the classification. The proposed FCSSA shows better performance using metrics, namely accuracy, energy and throughput with values 94.604, 0.145, and 0.058, respectively.

Publisher

IGI Global

Subject

Computer Networks and Communications,Management Information Systems

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Enhancing Cryptography Using Regression And Feature Selection;2024 International Conference on Communication, Computing and Internet of Things (IC3IoT);2024-04-17

2. Multibiosensor Data Sampling and Transmission Reduction With Decision-Making for Remote Patient Monitoring in IoMT Networks;IEEE Sensors Journal;2023-07-01

3. A sensing-based patient classification framework for efficient patient-nurse scheduling;Sustainable Computing: Informatics and Systems;2023-04

4. Improved invasive weed bird swarm optimization algorithm (IWBSOA) enabled hybrid deep learning classifier for diabetic prediction;Journal of Ambient Intelligence and Humanized Computing;2022-10-27

5. Modeling the Performance of Wireless Body Sensor Networks;2022 5th International Conference on Engineering Technology and its Applications (IICETA);2022-05-31

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3