HDQNN-Net: An Optimal Asthma Disease Detection Technique for Voice Signal Using Hybrid Deep Q-Neural Networks

Authors

  • Md. Asim Iqbal Dept. of E.C.E, Annamalai University, Tamil Nadu, India
  • K. Devarajan Dept. of E.C.E, Annamalai University, Tamil Nadu, India
  • Syed Musthak Ahmed Dept. of E.C.E, SR University, Warangal, Telangana, India

DOI:

https://doi.org/10.13052/jmm1550-4646.1969

Keywords:

Asthma detection, HDQNN, chaotic opposition krill herd optimization, Deep Neural Network, krill herd optimization

Abstract

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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Author Biographies

Md. Asim Iqbal, Dept. of E.C.E, Annamalai University, Tamil Nadu, India

Md. Asim Iqbal received his M.Tech degree from the JNTU Hyderabad and pursuing Ph.D in Annamalai University. In 2013 he was appointed as Assistant Professor at KUCE&T, Kakatiya University. The author has over 24 international Journals, 4 National Conferences, and 1 book. His research interests include Speech Processing, Embedded Systems, and Wireless Networks. He is an active member of The Indian Society for Technical Education (ISTE), IETE and Institution of Engineers (India) (IEI). He received two prestigious awards like IEI Young Engineers award in the year 2021 and Bharat Vikas award in the year 2018.

K. Devarajan, Dept. of E.C.E, Annamalai University, Tamil Nadu, India

K. Devarajan received his M.E and Ph.D degree from the Annamalai University. In 2006 he was appointed as Assistant Professor at Annamalai University. The author has over 40 international Journals, 11 International, 2 National conference and 2 books. His research interests include Wireless Communication Networks and Security Management, Antenna Design. He is an active member of the International Association of Engineers (IAENG), Institute of Research Engineers and Doctors (IRED) and The Indian Society for Technical Education (ISTE) societies.

Syed Musthak Ahmed, Dept. of E.C.E, SR University, Warangal, Telangana, India

Syed Musthak Ahmed, perused his BE, and ME in Electronics from Bangalore University, Bangalore and Ph.D. from Vinayaka Mission’s University, Tamil Nadu. He has around 35 years of teaching experience, teaching UG, PG and guiding Research Scholars. Four Scholars perused Ph.D. under him and presently guiding 3 scholars of home University other Universities. He served at various capacities as Professor and Head of department, Dean of Academics, Dean of Students Affairs and presently working as Professor and Dean of Students welfare at SR University, Warangal, Telangana has published around 120+ papers at various National and International Conferences/Journals. He has completed a Sponsored research project under Department of Science and Technology, Govt. of India. He is life member of ISTE, IETE, SMIEEE, MIAENG and MIAMT. He served the IEEE professional society, IEEE Hyderabad Section at various capacities as Section Executive Member, Students Activities Chair, Mentor Young Professionals, Chair and Vice Chair of Education Society and presently nominated as Chair Education Society.

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Published

2023-10-14

How to Cite

Iqbal, M. A. ., Devarajan, K. ., & Ahmed, S. M. . (2023). HDQNN-Net: An Optimal Asthma Disease Detection Technique for Voice Signal Using Hybrid Deep Q-Neural Networks. Journal of Mobile Multimedia, 19(06), 1553–1582. https://doi.org/10.13052/jmm1550-4646.1969

Issue

Section

Intelligent Contactless sensors and Micro processing systems for Smart mHealth S