About the Book
AI-Driven Human-Machine Interaction for Biomedical Engineering: Concepts, Applications, and Methodologies offers a comprehensive examination of the intricate relationship between humans and machines, particularly through the transformative lens of artificial intelligence (AI). As AI technologies rapidly evolve, understanding their implications for human-machine interaction (HMI) has become essential across various domains, especially healthcare. This book addresses the pressing need for insights into AI-driven methodologies, providing scholars, practitioners, and learners with foundational knowledge and practical applications that enhance collaboration between human cognition and machine capabilities. Structured into well-defined chapters, the book begins with an introduction to AI-driven HMI, laying the groundwork for understanding its significance in sustainable healthcare and beyond. Subsequent chapters explore critical topics such as machine learning principles, advanced biomedical data classification methods, and the role of AI in telemedicine. Readers will delve into cutting-edge techniques, from deep learning to non-invasive computer vision, and examine the implications of these technologies across industries. Each chapter equips readers with actionable insights and highlights emerging trends, ethical considerations, and the future of AI in HMI, ensuring a well-rounded perspective on this dynamic field. AI-Driven Human-Machine Interaction for Biomedical Engineering: Concepts, Applications, and Methodologies is an invaluable resource for researchers, academics, and students in the fields of Biomedical Engineering, Computer Science, Data Science, Artificial Intelligence, and Healthcare Technology. By bridging theoretical foundations with practical applications, this book empowers its readers to effectively harness AI technologies, driving innovation and improving outcomes in healthcare and various sectors.
Table of Contents:
1. Introduction to AI-driven Human-Machine Interaction
2. Basics, Constraints, and Future Potential of Machine Learning in HMI
3. Cutting-edge Methods for Biomedical Data Classification based on Machine Learning
4. AI in Telemedicine
5. Applications Across Industries
6. Two-stage Verifications for Multi-Instance Feature Selection: A Machine Learning-Based Approach
7. A practical EMG-based Intelligent human-computer interface
8. Computer Vision for Human-Computer Interaction Using Non-invasive Technology
9. Human-computer interaction principles for cardiac feedback
10. The Future of AI-Driven HMI
11. Biomechanics computation for medical image interpretation
12. Large-scale demographic imaging biomarkers based on machine learning
13. Support vector machine in the processing of medical images
14. Computer-aided interventional therapy
15. HMI in healthcare imaging and medical treatments
About the Author :
Dr. Kapil Gupta earned his Ph.D. from the Indian Institute of Information Technology, Design and Manufacturing (IIITDM), Jabalpur, India. He served as an Assistant Professor in Electronics and Communication Engineering at Oriental College of Technology, Bhopal, from 2013 to 2020. He holds a B.E. with Honors in Electronics and Communication Engineering and an M.Tech. in Nano Technology. His research interests encompass signal processing in biomedical applications, time-frequency analysis, artificial intelligence, and cardiovascular systems. Dr. Gupta has published extensively in reputed journals and serves as a reviewer for IEEE and Elsevier. He has organized numerous national and international conferences and has been involved in various technical committees. Dr. Varun Bajaj is an Associate Professor in Electronics and Communication Engineering at Maulana Azad National Institute of Technology Bhopal, India, starting January 2024. Previously, he served at the Indian Institute of Information Technology, Design and Manufacturing (IIITDM) Jabalpur from 2014 to 2024, initially as an Assistant Professor and later as an Associate Professor. He earned his Ph.D. in Electrical Engineering from IIT Indore in 2014, following an M.Tech. in Microelectronics and VLSI Design in 2009, and a B.E. in Electronics and Communication Engineering in 2006. Dr. Bajaj holds various editorial roles, including Associate Editor for the IEEE Sensor Journal and Subject Editor-in-Chief for IET Electronics Letters. A Senior Member of IEEE since 2020, he actively reviews for numerous journals and has delivered over 50 expert talks. He has received multiple awards for his research and has been recognized among the top 2% of researchers globally by Stanford University from 2020 to 2023. Dr. Deepak Kumar Jain is an Associate Professor at the School of Control Science and Engineering at Dalian University of Technology, China, since July 2023. Previously, he was an Assistant Professor at Chongqing University of Posts and Telecommunications. He earned his Bachelor of Engineering in 2010 and a Master of Technology in 2012 from Indian institutions, followed by a Ph.D. at the University of Chinese Academy of Sciences in 2018, supported by the CAS-TWAS Presidential Fellowship. Recognized as a "Foreign Expert" by the Shandong Taian Administration, Dr. Jain has also served as an Adjunct Professor at Symbiosis International University in India. He has approximately fifty publications with a citation count of 3000 and has contributed to numerous peer-reviewed journals. A senior member of IEEE, he is involved in several editorial roles and conferences, including delivering keynote talks internationally. His research focuses on deep learning, machine learning, pattern recognition, and computer vision. Dr. Raul Villamarin Rodriguez is the Vice President of Woxsen University, where he holds the Steven Pinker Professorship in Cognitive Psychology and the Classavo Chair in Integrative Research and Digital Learning. He is also an Adjunct Professor at Universidad del Externado in Colombia and serves on the International Advisory Boards of IBS Ranepa in Russia and the University of Pécs Faculty of Business and Economics. Dr. Rodriguez represents India on the PRME i5 Expert Pedagogy Group and holds a Ph.D. in Artificial Intelligence and Robotics Process Automation in Human Resources. His expertise includes machine learning, deep learning, natural language processing, and quantum artificial intelligence. He is a registered expert in these fields with the European Commission and was nominated for the Forbes 30 Under 30 Europe 2020 list. Dr. Rodriguez has co-authored two reference books, published over 70 research papers, and is a regular contributor to various magazines on analytics and emerging technologies. He also serves as a journal reviewer and associate editor for several publications, including IEEE.
Dr. Hemachandran Kannan is a Professor in the Department of Artificial Intelligence & Business Analytics at Woxsen University, India, where he holds the Zita Zoltay Paprika Chair in Decision Sciences and Business Economics, as well as the Course5i Chair in Business Analytics and Machine Learning. With 15 years of teaching and 5 years of research experience, he is a dedicated educator skilled in AI and Business Analytics. After earning a Ph.D. in Embedded Systems, Dr. Kannan shifted his focus to interdisciplinary research. He has served as a resource person at numerous national and international conferences and has lectured on AI and Business Analytics topics. Recognized as Best Faculty at Woxsen University (2021-2022) and Ashoka Institute of Engineering & Technology (2019-2020), he has expertise in Natural Language Processing, Computer Vision, and autonomous systems.
