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Intelligent IoT-based Diagnostic and Assistive Systems for Neurological Disorders

  • 1st Edition - September 1, 2026
  • Latest edition
  • Editors: Hanif Heidari, Murugappan Murugappan
  • Language: English

Intelligent IoT-based Diagnostic and Assistive Systems for Neurological Disorders discusses the latest developed methods in IoT and its applications in neurological disord… Read more

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Description

Intelligent IoT-based Diagnostic and Assistive Systems for Neurological Disorders discusses the latest developed methods in IoT and its applications in neurological disorders that emphasize end-user requirements. Intelligent IoT is used to explore the intersection between medicine, data science, biomedical engineering, and healthcare systems. A comprehensive overview of modelling and analyzing the requirements of people with neurological disorders is presented in this book. Signals and images of biological activity are collected and analyzed based on patient specifications to facilitate more accurate diagnosis and treatment. The book also discusses cutting-edge AI methods for IoT devices designed to treat neurological conditions.

Key features

  • Provides practical strategies and insights for improving medical decision-making and helping in the design of intelligent neurological disorder diagnosis systems using artificial intelligence
  • Discusses different types of IoT algorithms, deployment strategies, challenges in IoT system design, future trends, and wearable IoT technologies for neurological disorders
  • Presents practical case studies, illustrating how IoT can be used to improve the quality of life and safety of patients suffering from neurological disorders
  • Provides practical knowledge, insights, and strategies for successfully leveraging IoT in neurology

Readership

Researchers and industry professionals in the fields of biomedical engineering, medical informatics, and neuroscience

Table of contents

1. Review on IoMT Applications for Advancements in Oral Cancer

2. Review on various IoT Technologies to Assess and diagnose Parkinson's Disease

3. Chest respiratory classification by quantum regression neural network

4. Analyzing Sports Activity and Neurodegenerative Disease Progression Through IoT and Video Data Validation Methods

5. Expert and Crowd-Guided Affect Annotation and Prediction

6. Compressed Sensing Framework for Energy-Efficient IoT Enabled EEG Monitoring

7. Sparse Representation Based Brain Wave Extraction for IoT Edge Deep EEG Analytics

8. Intelligent IoMT wearable technology for Neurological disorder diagnostic systems

9. Deep Learning and Internet of Thing based Autism Spectrum Disorder Detection using Facial Images

10. Design and Development of Intelligent IoT based assistive system for ICD Patients

11. Artificial Intelligence based Neurological Disorder Diagnosis using EEG Signals

12. A Novel Automated Diagnosis System for Stroke using Electroencephalogram Signals

Product details

  • Edition: 1
  • Latest edition
  • Published: September 1, 2026
  • Language: English

About the editors

HH

Hanif Heidari

Dr. Hanif Heidari is an assistant professor in the Department of Applied Mathematics, Damghan University, Damghan, Iran. His research interests are in quantum machine learning, time series classification and prediction, grey system theory, and theoretical aspects of metaheuristic optimization methods. With over twelve years of experience, his foundations have been published in the high quality interdisciplinary scientific journals. He has also had given more than 20 talks in international conferences and supervised 22 graduate students in applied mathematics and computer science. Hanif enjoys of international scientific collaboration for solving complex practical problems using mathematical methods.
Affiliations and expertise
Assistant Professor, Department of Applied Mathematics, Damghan University, Damghan, Iran

MM

Murugappan Murugappan

Professor Dr. M. Murugappan is a Full Professor in Electronics at Kuwait College of Science and Technology (KCST) since 2016. Additionally, he serves as a Visiting Professor at the School of Engineering at Vels Institute of Science, Technology, and Advanced Studies in India, and an International Visiting Fellow at the Centre of Excellence in Unmanned Aerial Systems at Universiti Malaysia Perlis in Malaysia.

He holds an M.E. degree in Applied Electronics from Anna University, India, and received his Ph.D. in Mechatronic Engineering from Universiti Malaysia Perlis in 2010. Between 2010 and 2016, he worked as a Senior Lecturer at the School of Mechatronics Engineering, where he taught courses related to biomedical and mechatronics engineering.

Professor Murugappan has an outstanding research record, with numerous awards and research grants. His research in affective computing has received significant funding from Malaysia, Kuwait, and the UK.

He has published over 140 peer-reviewed conference proceedings papers, journal articles, and book chapters. Professor Murugappan is also a member of the editorial boards of prestigious journals, including PLOS ONE, Human Centric Information Sciences, Journal of Medical Imaging and Health Informatics, and International Journal of Cognitive Informatics.

Furthermore, he actively contributes to various IEEE Transactions as a reviewer and holds leadership roles, such as Chair of the IEEE Kuwait Section's Educational Activities Committee.

Affiliations and expertise
Full Professor, Kuwait College of Science and Technology, Kuwait