Neuromorphic Computing for Brain Computer Interfaces
Enhanced Synergies in Mind and Machine
- 1st Edition - May 1, 2026
- Latest edition
- Editors: Seifedine Kadry, Rajesh Kumar Dhanaraj, Lalitha Krishnasamy, Michael Moses Thiruthuvanathan
- Language: English
Neuromorphic Computing for Brain Computer Interfaces: Enhanced Synergies in Mind and Machine examines practical situations where interpretability is crucial, going beyond theore… Read more
Neuromorphic Computing for Brain Computer Interfaces: Enhanced Synergies in Mind and Machine examines practical situations where interpretability is crucial, going beyond theoretical considerations and providing case studies and examples to illustrate how Brain Computer Interfaces could be implemented in the real world. The book encompasses novel concepts, cutting-edge research, frameworks, and tools that facilitate comprehension of neuromorphic computing models. It is an ideal, comprehensive reference for professionals, researchers, and students who want to grasp the fundamental concepts and most recent developments in brain-computer interfaces (BCIs) and neuromorphic computing.
- Provides an in-depth study of the principles, technology, and applications that drive neuromorphic computing and brain-computer interfaces
- Offers an interdisciplinary approach that includes cognitive science, neuroscience, artificial intelligence, and biomedical engineering
- Presents actionable insights and methodologies that can be applied to real-world challenges by presenting practical implementations and case studies
Researchers in neuroscience, and Cognitive Scientists, Biomedical Engineers, those with an interest in the application of technology to brain research
1. Physiological Brain Signals
2. Signal Acquisition Sensors
3. Neuromorphic Algorithms
4. Adaptive Learning Architectures
5. Cognitive Fusion
6. BCI Intelligence
7. Deep Neural Network Models
8. Enhanced Decision-Making
9. Neuromorphic Edge Computing
10. Case Study on Mindful Healthcare
11. Case Study on Neuromorphic Vision Systems: BCI-Infused Technologies for Advanced Image Processing
12. Case Study on Neuromorphic Audio Processing: BCI-Driven Innovations in Sound Recognition and Synthesis
13. Case Study on Education Revolution: Neuromorphic and BCI Technologies Shaping Personalized Learning Environments
14. Future of BCIs: Problems and Prospects. Research and Development
2. Signal Acquisition Sensors
3. Neuromorphic Algorithms
4. Adaptive Learning Architectures
5. Cognitive Fusion
6. BCI Intelligence
7. Deep Neural Network Models
8. Enhanced Decision-Making
9. Neuromorphic Edge Computing
10. Case Study on Mindful Healthcare
11. Case Study on Neuromorphic Vision Systems: BCI-Infused Technologies for Advanced Image Processing
12. Case Study on Neuromorphic Audio Processing: BCI-Driven Innovations in Sound Recognition and Synthesis
13. Case Study on Education Revolution: Neuromorphic and BCI Technologies Shaping Personalized Learning Environments
14. Future of BCIs: Problems and Prospects. Research and Development
- Edition: 1
- Latest edition
- Published: May 1, 2026
- Language: English
SK
Seifedine Kadry
Seifedine Kadry is a Professor in the Department of Mathematics and Computer Science, at Norrof University College, in Norway. He has a Bachelor’s degree in 1999 from Lebanese University, MS degree in 2002 from Reims University (France) and EPFL (Lausanne), PhD in 2007 from Blaise Pascal University (France), HDR degree in 2017 from Rouen University. At present, his research focuses on data Science, education using technology, system prognostics, stochastic systems, and applied mathematics. He is an ABET program evaluator for computing, and ABET program evaluator for Engineering Tech. He is a Fellow of IET, Fellow of IETE, and Fellow of IACSIT. He is a distinguished speaker of IEEE Computer Society.
Affiliations and expertise
Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon; Department of Applied Data Science, Noroff University College, Kristiansand, NorwayRD
Rajesh Kumar Dhanaraj
Dr. Rajesh Kumar Dhanaraj is a professor at the Symbiosis International (Deemed University) in Pune, India. His research and publication interests include cyber-physical systems, wireless sensor networks, and cloud computing. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE), a member of the Computer Science Teacher Association (CSTA) and member of the International Association of Engineers (IAENG). He is an expert advisory panel member of Texas Instruments Inc. (USA), and an associate editor of International Journal of Pervasive Computing and Communications (Emerald Publishing).
Affiliations and expertise
Professor, Symbiosis International (Deemed University), Pune, IndiaLK
Lalitha Krishnasamy
Dr. Lalitha Krishnasamy is currently working as a Professor in the Department of Artificial Intelligence and Data Science, Nandha Engineering College, Erode, Tamil Nadu, India. She completed her Ph.D., from Anna University, Chennai, India in 2019 and M.Tech from Anna University, Coimbatore, India in 2009. She pursued her research in the field of Wireless Sensor Networks. She possesses seventeen+ years of teaching expertise. Her thrust areas of research include Internet of Things, Machine Learning, Deep Learning and Artificial Intelligence. She has published 45+ papers in various International Journals and International Conferences. She has contributed multiple book chapters in reputed publications. She has acted as a session chair and reviewer in numerous international conferences. She obtained 5 patents. Her professional membership includes IEEE, CSI and IAENG.
Affiliations and expertise
Nandha Engineering College, IndiaMT
Michael Moses Thiruthuvanathan
Dr. Michael Moses Thiruthuvanathan is an Assistant Professor of Computer Science and Engineering at Christ University in Bangalore, India. He holds a Ph.D. in Computer Science and Engineering and also leads the NCC cadets of Airwing of the university. He holds the Rank of Flying officer conferred to him from the Indian Air Force. He is a highly respected academic who has contributed significantly to computer science and engineering. He has authored several research papers in top-tier journals and has presented his work at various national and international conferences. His research interests include Computer Vision, Deep learning, Artificial intelligence, Health Informatics and machine learning. He is known for his innovative research methods and ability to bridge the gap between theory and practice. Apart from his research, Dr. Michael is a dedicated teacher whom his students highly regard. He is known for his ability to explain complex concepts in a simple and easy-to-understand manner, and for his commitment to helping students achieve their academic and professional goals.
Affiliations and expertise
CHRIST University, India