Overview

Artificial Intelligence and Multimodal Signal Processing in Human-Machine Interaction presents an overview of an emerging field that is concerned with exploiting multiple modalities of communication in both Artificial Intelligence and Human-Machine Interaction. The book not only provides cross disciplinary research in the fields of multimodal signal acquisition and sensing, analysis, IoTs (Internet of Things), Artificial Intelligence, and system architectures, it also evaluates the role of Artificial Intelligence I in relation to the realization of contemporary Human Machine Interaction (HMI) systems. Readers are introduced to the multimodal signals and their role in the identification of the intended subjects, mental state and the realization of HMI systems are explored, and the applications of signal processing and machine/ensemble/deep learning for HMIs are assessed. A description of proposed methodologies is provided, and related works are also presented. This is a valuable resource for researchers, health professionals, postgraduate students, post doc researchers and faculty members in the fields of HMIs, Brain-Computer Interface (BCI), Prosthesis, Computer vision, and Mental state estimation, and all those who wish to broaden their knowledge in the allied field.

Full Product Details

Author:   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) ,  Saeed Mian Qaisar, PhD (CESI LINEACT, Lyon, France College of Engineering, Effat University, Jeddah, Saudi Arabia) ,  Humaira Nisar, PhD (Universiti Tunku, Malaysia)
Publisher:   Elsevier Science Publishing Co Inc
Imprint:   Academic Press Inc
Weight:   0.450kg
ISBN:  

9780443291500

ISBN 10:   0443291500
Pages:   424
Publication Date:   24 September 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1. Introduction to the human-machine interaction and its applications 2. Artificial intelligence techniques for the human-machine interaction 3. Pre-processing and feature extraction techniques for the human-machine interaction 4. An overview of techniques and best practices to create intuitive and user-friendly human-machine interfaces 5. An overview of AI and multimodal signal processing for Neurological and Neuro behavioural disorders 6. An overview of speech based emotion detection for human-machine interaction 7. Speech driven human-machine interaction using Mel-frequency cepstral coefficients and Machine learning 8. EEG based brain computer interface using wavelet packet decomposition and ensemble learning 9. EEG based neurocognitive processing in dyslexic children 10. EEG signal processing with ensemble learning for emotion recognition 11. EEG based stress identification using oscillatory mode decomposition and artificial neural network 12. EEG signal processing with deep learning for alcoholism detection 13. Machine learning and signal processing for ECG based emotion recognition 14. EoG based human-machine interaction using artificial intelligence 15. Surface EMG based gesture recognition using wavelet transform and ensemble learning 16. Haptic feedback based tactile sensations to feel virtual objects and/or textures 17. Patient rehabilitation assessment using 3D skeletal data and deep learning based approach 18. Vision based action recognition for the human-machine interaction 19. Natural language processing based assistance and customer services 20. Immersive virtual reality and augmented reality in human-machine interaction 21. Adaptive systems and personalization in human-machine interaction 22. Security and authentication in human-machine interaction 23. Applications of human-machine interaction

Reviews

Author Information

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 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. Humaira Nisar has a B.S (Honours) in Electrical Engineering from the University of Engineering and Technology, Lahore, Pakistan, M.S in Nuclear Engineering from Quaid-i-Azam University, Islamabad, Pakistan, another M.S in Mechatronics, and Ph.D. in Information and Mechatronics from Gwangju Institute of Science and Technology, Gwangju, South Korea. She has more than twenty years of research experience. Currently, she is working as a Full Professor in the Department of Electronic Engineering, Universiti Tunku Abdul Rahman, Kampar, Malaysia. Her research interests include signal and image processing, biomedical imaging, neuro-signal processing and analysis, Brain-Computer Interface, and Neurofeedback. She has published hundreds international journal and conference papers. She is a senior member of IEEE

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