Artificial Intelligence and Multimodal Signal Processing in Human-Machine Interaction

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. In 23 chapters/sections "Artificial Intelligence and Multimodal Signal Processing in Human-Machine Interaction" covers different aspects of the multimodal signals, from the sensing to analysis using hardware/software, and making use of machine/ensemble/deep learning in the intended problem solving. The reader is 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. Each chapter starts with the importance, problem statement and motivation. The description of 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, 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.