Artificial Intelligence Applications for Brain–Computer Interfaces (Artificial Intelligence Applications in Healthcare and Medicine)

Artificial Intelligence Applications for Brain-Computer Interfaces focuses on the advancements, challenges, and prospects of future technologies involving noninvasive brain-computer interfaces (BCIs). It includes the processing and analysis of multimodal signals, integrated computation-acquisition devices, and implantable neuro techniques.

This book not only provides cross-disciplinary research in BCI but also presents divergent applications on telerehabilitation, emotion recognition, neuro-rehabilitation, cognitive workload assessments, and ambient assisted living solutions.

In 15 chapters, this book describes how BCIs connect the brain with external devices like computers and electronic gadgets. It analyzes the neural signals from the brain to obtain insights from the brain patterns using multiple noninvasive wearable sensors. It gives insight into how sensor outcomes are processed through machine-intelligent models to draw inferences. Each chapter starts with the importance, problem statement, and motivation. A description of the proposed methodology is provided, and related works are also presented.

Each chapter can be read independently, and therefore, the book is a valuable resource for researchers, health professionals, postgraduate students, postdoc researchers, and academicians in the fields of BCI, prosthesis, computer vision, and mental state estimation, and all those who wish to broaden their knowledge in the allied field.

• Focuses on the advancements, challenges, and prospects for future technologies over noninvasive brain computer interfaces (BCIs), including the processing and analysis of multimodal signals, integrated calculation-acquisition devices, and implantable technologies.
• Presents theories, algorithms, realizations, applications, approaches, and challenges that will have their impact and contribution in the design and development of modern and effective BCIs.
• Assists in understanding the predominance of BCI technology in various applications.

Abdulhamit Subasi is a highly specialized expert in the fields of Artificial Intelligence, Machine Learning, and Biomedical Signal and Image Analysis and Security. His extensive expertise in applying machine learning across diverse domains is evident in his numerous contributions, including the authorship of multiple book chapters, as well as the publication of a substantial body of research in esteemed journals and conferences.

Dr. Qaisar currently holds the position of Research & Innovation Department Head for the South-East Region at CESI LINEACT, located in France. In recognition of his teaching and learning excellence, he was honored with the Queen Effat Award in May 2016. Dr. Qaisar's accomplishments encompass two granted patents, as well as an extensive portfolio of published works spanning journal articles, book chapters, and conference papers. Furthermore, Dr. Qaisar contributes to the academic community as an editor for various international journals and is actively involved in the technical and review committees of several international journals and conferences. His current areas of research focus include signal processing, circuits and systems, artificial intelligence, event-driven systems, biomedical and bioinformatics applications, smart grid technology, energy storage, and sampling theory.

Dr. Akash Kumar Bhoi accomplished academic and researcher with over a decade of experience in Computer Science and Engineering, Artificial Intelligence, Machine Learning, Data Science, and Biomedical Computing. Recognized globally for research excellence, ranked in the Top 0.5% of Scholars worldwide (ScholarGPS, 2024 & 2025) and listed among the World’s Top 2% Scientists (Stanford University & Elsevier, 2022, 2023 & 2025). Prolific contributor with 200+ Scopus-indexed publications, multiple edited books with Springer/Elsevier, and an h-index of 39 (Google Scholar). Dr. Bhoi is currently associated with Graphic Era Deemed to be University, Dehradun. More than a decade of academic & research experience in India, Italy, Australia, and South Korea. Expertise spans computational intelligence, data analytics, healthcare informatics, biomedical signal and image processing, cloud/edge computing, and IoT applications.

Parvathaneni Naga Srinivasu has earned his Ph.D. degree at GITAM (Deemed to be University) and his areas of research include Biomedical Imaging, Image Enhancement, Image Segmentation, Object Recognition, Image Encryption, Optimization Algorithms, Soft computing, and Natural Language Processing. He is working as an Assistant Professor at the Department of Computer Science and Engineering, GIT, GITAM (Deemed to be University), Visakhapatnam. He is a member of CSI, IAENG, IARA and a regular reviewer for Scopus indexed journals like JCS and IJAIP, Inderscience. He is a guest editor for the special issues and books that are published by reputed publishers like Bentham Science, Springer, and Elsevier. He is a passionate researcher and his articles have been published in national and international journals alongside conferences.