1st Edition
Explainable Computational Intelligence for Neurological Disorders
Chapter 1
Artificial Intelligence in Medical-based Systems for Neurological Disorders
Ashish Aggarwal
Chapter 2
A Review on Autonomic Biomarkers in Health and Neurological Disorders: Heart Rate Variability, Skin Conductance, and Entropy-Based Analysis
Ankita Soni, Tushar Tyagi, Amit Dutt
Chapter 3
Advanced Computational Techniques for Neurological Disorder Screening through Wearable Sensor-Based Human Activity Recognition
Divya Yadav, Deepika Rani, Om Prakash Verma
Chapter 4
Sleep Apnea Disorder Detection using Wearable Sensors
Maryala Sravani, Kondu Srimukha, Banothu Bhanusri, Ashwini, Santhosh Kumar Veeramalla
Chapter 5
An Integrated Study of Biomarkers, Diagnostics and Therapeutic Approaches for Alzheimer’s Disease
Priyanka Gautam, Manjeet Singh
Chapter 6
Designing Hybrid Models for Neuro-Disease Classification
Ashish Aggarwal
Chapter 7
Interpretability and Explainability of Machine Learning and Deep Learning Models in ECG Disease Detection
Pranshu Sharma, Tanu Wadhera, Ankur Kumar
Chapter 8
Advanced Computational Analysis of Brain Connectivity Using EEG data
Ujwala Kalva, Anitha Shivarathri, Thupakula Tejasri, Myakala Kaveri
Chapter 9
Feature Engineering and Machine Learning Approaches for EEG Based Imagined Speech Recognition
Dilnawaz, R.S Anand
Chapter 10
Machine Learning Based Huntington’s Disease Detection
Aditi Sinha, Saksham Tripathi, Saksham Mittal, Piyush Bagla
Chapter 11
Clinically Meaningful Epileptic Seizure Prediction Using iEEG Features and Random Forest
Uttam Mittal, Padmavati Khandnor, Deepti R. Bathula
Chapter 12
Intracranial EEG analysis for predicting Surgery Outcomes of Drug-Resistant Epilepsy subjects using Machine Learning
Kanika Sharma, Padmavati Khandnor
Chapter 13
Explainable Hybrid CNN–Transformer Framework for Dynamic Word-Level Indian Sign Language Recognition in Neurological Disorder Communication Assistance Systems
Diksha Kumari, R S Anand
Chapter 14
Framework for Design and Evaluation of Virtual Reality based Interventions for Improving Vocational Skills in Individuals with Autism Spectrum Disorder
Hiten Rajpurohit, Arun Khosla
Chapter 15
Stem Cells in Neurology: Advancing Regenerative Therapies for Neurodegenerative Disorders
Suhani Jain, Anterpreet Kaur Bedi
Chapter 16
Integrating Multi-Modal Biomarkers for the Early Detection of Pancreatic Ductal Adenocarcinoma: A Comprehensive Review
Tanishka Chopra, Anterpreet Kaur Bedi
Biography
Barjinder Singh Saini is a professor in the Electronics and Communication department at Dr B. R. Ambedkar National Institute of Technology, Jalandhar, India, with 24 years of academic experience. He received his M.Tech. degree in the Department of Electronics and Communication Engineering from REC, Kurukshetra, and a Ph.D. in Electronics and Communication Engineering from Dr B. R. Ambedkar National Institute of Technology, Jalandhar. His research interests include Signal and Image processing, Medical Image Analysis, Microprocessors, and Microcontrollers. He has contributed more than 100 research papers in reputed journals, and more than 200 conference articles are there to his credit.
Savita Gupta is a Professor in the Department of Computer Science and Engineering, University Institute of Engineering and Technology (UIET), Panjab University. She received her M.E. degree from Thapar University and a Ph.D. in Computer Science and Engineering from Punjab Technical University, Jalandhar. She passionately performs her research activities in Signal and Image Processing, Medical Image Analysis, Wavelets Signal and Image processing, Artificial Intelligence, and Cognitive neuroscience. Her contributions to speckle noise reduction in ultrasound images are widely acknowledged in biomedical engineering. She has contributed more than 200 research papers in reputed journals, and more than 400 conference articles are there to her credit.
Indu Saini received her Bachelor of Technology degree in Electronics and Communication Engineering from Guru Nanak Dev University Amritsar and her master’s in technology and PhD from NIT Jalandhar. She works as an Associate Professor in the Department of Electronics and Communication Engineering at NIT Jalandhar. She has received sponsored projects from MeitY and MHRD, New Delhi. She was also awarded the Distinguished Woman in Engineering award from the Centre for Advanced Research and Design (CARD) of Venus International Foundation and the Bharat Excellence Award by FFI, India, in 2019. She has been credited with 02 granted and 02 filed patents. Her research interests include Biomedical Signal and Image Processing, Machine Learning Algorithms, and VLSI Design. She is also a Co-founder of a Start-Up named INS Technology Private Limited.
Radhika Malhotra is currently associated with the Department of Electronics and Communication Engineering at Punjab Engineering College, Chandigarh, India. She did her Bachelor of Technology degree in Electronics and Communication Engineering and Master of Technology in Microelectronics and VLSI Design. She has one and a half years of research experience and worked as a Research Associate at IIT Ropar. Her research interests include biomedical image processing, artificial intelligence, classification, prognosis, and survival prediction of neurodevelopmental disorders.
Nikita Aggarwal works in the Biomedical Lab of the Department of Electronics and Communication Engineering at Dr B R Ambedkar National Institute of Technology, Jalandhar, India. In 2012, she received a Bachelor of Technology degree in Electronics and Communication Engineering from Punjab Technical University, Jalandhar, and completed her master’s in engineering from the National Institute of Technical Teachers Training & Research (NITTTR), Panjab University, Chandigarh. She has more than five years of experience in teaching and research. Her research interests include biomedical image processing, artificial intelligence, Remote sensing, and early diagnosis of neurodevelopmental disorders.
Karan Veer received his Ph.D. in Electrical and Instrumentation Engineering from Thapar University, Patiala, India, in 2015. He was awarded the Dr. D. S. Kothari Postdoctoral Fellowship (UGC) in 2016 and a Research Associateship (ICMR) in 2018. He has over ten years of teaching and research experience in biomedical instrumentation and has published more than 90 SCI-indexed research articles, along with two research books and six book chapters. He has been recognized among the top 2% scientists worldwide by Stanford University and Elsevier for 2023–2024 and 2024–2025. Currently, he is an Assistant Professor in the Department of Instrumentation and Control Engineering at Dr. B. R. Ambedkar National Institute of Technology (NIT), Jalandhar, India. His research interests include biomedical instrumentation, healthcare analytics, rehabilitation engineering, and Ayurveda-based biomedical applications.
