基于混合深度q -神经网络的语音信号哮喘疾病检测技术

Q3 Social Sciences
Md. Asim Iqbal, K. Devarajan, Syed Musthak Ahmed
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引用次数: 0

摘要

近年来,哮喘患者严重感染新冠肺炎,哮喘已成为世界上最危险的疾病之一。此外,哮喘发生在所有年龄组,给患者的健康造成巨大损失。人类哮喘的主要检测方法是通过语音信号,随着哮喘严重程度的增加,语音信号的性质会受到影响。传统的分类方法无法从语音信号中提取出最大的特征,导致分类性能较差。因此,本文的重点是利用混合深度Q神经网络(HDQNN)从语音信号中实现实时哮喘疾病检测和识别技术。首先,采用Krill herd optimization (KHO)方法从语音信号中提取特征,提取详细的疾病特异性特征。在此基础上,采用混沌对抗磷虾群优化(COKHO)算法提取最优特征。然后,使用HDQNN对哮喘类型进行分类,如正常哮喘和哮喘病。此外,COKHO还用于优化HDQNN模型中产生的损失。仿真结果表明,与现有方法相比,所提出的HDQNN方法具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
HDQNN-Net: An Optimal Asthma Disease Detection Technique for Voice Signal Using Hybrid Deep Q-Neural Networks
Recently, asthma patients are severely suffering COVID-19 disease, thus the asthma has become one of the dangerous diseases in the world. Further, asthma is occurring in all age groups, which causing huge loss to patient’s health. The primary way to detect the asthma in humans is done by their speech signals, as the asthma severity is increases, which manipulates the properties of speech signal. The conventional methods are failed to extract the maximum features from the speech signals, which resulted in low classification performance. Thus, this article is focused on implementation of real time asthma disease detection and identification technique from speech signals using Hybrid Deep Q Neural Networks (HDQNN). Initially, the features from the speech signals are extracted by using Krill herd optimization (KHO) approach, which extracts the detailed disease specific features. Further, the optimal features are extracted by using chaotic opposition krill herd optimization (COKHO) algorithm. Then, HDQNN is used to classify the type of asthma such as normal, and stridor classes. Further, COKHO is also used to optimize the losses generated in the HDQNN model. The simulation results shows that the proposed HDQNN method resulted in superior performance as compared to state of art approaches.
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来源期刊
Journal of Mobile Multimedia
Journal of Mobile Multimedia Social Sciences-Communication
CiteScore
1.90
自引率
0.00%
发文量
80
期刊介绍: The scope of the journal will be to address innovation and entrepreneurship aspects in the ICT sector. Edge technologies and advances in ICT that can result in disruptive concepts of major impact will be the major focus of the journal issues. Furthermore, novel processes for continuous innovation that can maintain a disruptive concept at the top level in the highly competitive ICT environment will be published. New practices for lean startup innovation, pivoting methods, evaluation and assessment of concepts will be published. The aim of the journal is to focus on the scientific part of the ICT innovation and highlight the research excellence that can differentiate a startup initiative from the competition.
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