Ai-Driven Human-Machine Interaction for Biomedical Engineering: Concepts, Applications, and Methodologies
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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. 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, while also examining 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. This is an invaluable resource for researchers, academics, and students in the fields of Biomedical Engineering, Computer Science, Data Science, Artificial Intelligence, and Healthcare Technology.Bajaj, Varun: - 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.
Gupta, Kapil: - 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.
Jain, Deepak Kumar: - 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.
Kannan, Hemachandran: -
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.
Rodriguez, Raul Villamarin: -
Dr. Raul Villamarin Rodriguez is Vice President of Woxsen University and holds professorships in cognitive psychology and integrative research. He also serves as an Adjunct Professor at Universidad del Externado in Colombia and sits on international advisory boards in Europe and Russia. He holds a PhD in artificial intelligence and robotic process automation in human resources and specialises in machine learning, deep learning, natural language processing, and emerging areas such as quantum AI. He contributes to global academic initiatives, including expert groups focused on responsible management education and pedagogy. Dr. Rodriguez is recognised as an expert by the European Commission and actively contributes to research, publishing, and academic service through authorship, editorial roles, and peer review for leading journals. His work focuses on advancing AI-driven innovation, analytics, and digital learning in higher education and applied research contexts.
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