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Artificial Intelligence Applications for Brain-Computer Interfaces. Artificial Intelligence Applications in Healthcare and Medicine

  • Book

  • January 2025
  • Elsevier Science and Technology
  • ID: 6006247

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.

Please Note: This is an On Demand product, delivery may take up to 11 working days after payment has been received.

Table of Contents

1. Introduction to brain-computer interface: research trends and applications
SAEED MIAN QAISAR AND ABDULHAMIT SUBASI
2. Preprocessing and feature extraction techniques for brain-computer interface
ABDULHAMIT SUBASI AND SAEED MIAN QAISAR
3. Emotional state monitoring and applications with brain-computer interfaces
EVIN SAHIN SADIK
4. Hand kinematics and decoding hindlimb kinematics using local field potentials using a deep neural network decoding framework
JIGAR SARDA, MILIND SHAH, ROHAN VAGHELA, DARSH VAISHNANI AND HIRVA PATEL
5. Closed-loop brain_computer interfaces for musculoskeletal impulse prediction
K. RANJINI, POOJA GOUD, AMBESHWAR KUMAR AND R. MANIKANDAN
6. Classification of motor imagery tasks in brain-computer interface using ensemble learning
ABDULHAMIT SUBASI AND SAEED MIAN QAISAR
7. The application of brain_computer interface in Alzheimer’s disease studies based on machine learning algorithms
HELIA GIVIAN
8. Brain_computer interfaces and deep learning methods for cognitive impairments
SEDA SASMAZ KARACAN
9. Prospects and challenges in decoding consumer behavior using neurotechnology
TARA CHAND, VASUNDHARAA S. NAIR, PARVATHANENI NAGA SRINIVASU AND VINOD JANGIR KUMAR
10. Electroencephalography-based emotion recognition with empirical mode decomposition and ensemble machine learning methods
ABDULHAMIT SUBASI, MUHAMMED ENES SUBASI AND SAEED MIAN QAISAR
11. Brain-computer interfaces for security and authentication
MOUMITA CHANDA, OLIVE MAZUMDER, SOUVIK PAUL AND TAWFIKUR RAHMAN
12. A case study on artifical intelligence based data processing in passive brain-computer interface
PARVEEN KUMAR SEKHARAMANTRY, USAMA A. SYED, UMER FAROOQ AND DINH DUNG VAN
13. Analyzing eyewitness recognition accuracy using event-related potential and eye-tracking analysis: an experimental investigation
SAMIKSHA DAS, DERICK H. LINDQUIST, TARA CHAND AND MOHITA JUNNARKAR
14. Ambient assisted living through passive brain-computer interface technology for assisting paralyzed people
SANCHITA GOSWAMI, PRITHU BANIK, ANIKET KUMAR MEENA AND ANJANEYULU BENDI
15. Challenges and future directions in brain-computer interface research for exoskeletons usage
HEMANTH P.K. SUDHANI, PRABHAKAR VATTIKUTI AND DASARI REKHA

Authors

Abdulhamit Subasi Institute of Biomedicine, Faculty of Medicine, University of Turku, Turku, Finland Department of Computer Science, College of Engineering, Effat University, Jeddah, Saudi Arabia.

Abdulhamit Subasi is a highly specialized expert in the fields of Artificial Intelligence, Machine Learning, and Biomedical Signal and Image Processing. 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. His career has spanned various prestigious institutions, including the Georgia Institute of Technology in Georgia, USA, where he served as a dedicated researcher. In recognition of his outstanding research contributions, Subasi received the prestigious Queen Effat Award for Excellence in Research in May 2018. His academic journey includes a tenure as a Professor of computer science at Effat University in Jeddah, Saudi Arabia, from 2015 to 2020. Since 2020, he has assumed the role of Professor of medical physics at the Faculty of Medicine, University of Turku in Turku, Finland

Saeed Mian Qaisar CESI LINEACT, Lyon, France College of Engineering, Effat University, Jeddah, Saudi Arabia. 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. Akash Kumar Bhoi Directorate of Research, Gangtok, Sikkim Manipal University, Sikkim, India.

Dr. Akash Kumar Bhoi, holds degrees in B.Tech, M.Tech, and Ph.D., and has been contributing to the field of computer science and engineering. He assumed the role of Assistant Professor (Research) at the Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology (SMIT), India, in 2012. In addition to his academic responsibilities, Dr. Bhoi extended his expertise during a research tenure as a Research Associate at the Wireless Networks (WN) Research Laboratory, Institute of Information Science and Technologies, National Research Council (ISTI-CRN) in Pisa, Italy, from January 20, 2021, to January 19, 2022. Dr. Bhoi further serves as the University Ph.D. Course Coordinator for "Research & Publication Ethics (RPE)." He is an active member of professional organizations such as IEEE, ISEIS, and IAENG, and holds associate membership with IEI and UACEE. He plays a significant role as an editorial board member and reviewer for esteemed Indian and international journals and regularly contributes as a reviewer. His research expertise encompasses a wide array of domains, including Biomedical Technologies, the Internet of Things, Computational Intelligence, Antenna technology, and Renewable Energy. Dr. Bhoi has a notable publication record, with multiple papers featured in national and international journals and conferences. Dr. Bhoi has played a pivotal role in the organization of international conferences and workshops, offering his expertise as a key contributor. Currently, he is involved in editing several books in collaboration with international publishers

Parvathaneni Naga Srinivasu Amrita School of Computing, Amrita Vishwa Vidyapeetham, Amaravati, Andhra Pradesh, India Department of Teleinformatics Engineering, Federal University of Cear�, Fortaleza, Brazil INTI International University, Nilai, Malaysia.

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.