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. Covers advances in the multimodal signal processing and artificial intelligence assistive HMIsPresents theories, algorithms, realizations, applications, approaches, and challenges that will have their impact and contribution in the design and development of modern and effective HMI (Human Machine Interaction) systemPresents 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 INDICE: 1. Introduction to the human-machine interaction and its applications2. Artificial intelligence techniques for the human-machine interaction3. Pre-processing and feature extraction techniques for the human-machine interaction4. An overview of techniques and best practices to create intuitive and user-friendly human-machine interfaces5. An overview of AI and multimodal signal processing for Neurological and Neuro behavioural disorders6. An overview of speech based emotion detection for human-machine interaction7. Speech driven human-machine interaction using Mel-frequency cepstral coefficients and Machine learning8. EEG based brain computer interface using wavelet packet decomposition and ensemble learning9. EEG based neurocognitive processing in dyslexic children10. EEG signal processing with ensemble learning for emotion recognition11. EEG based stress identification using oscillatory mode decomposition and artificial neural network12. EEG signal processing with deep learning for alcoholism detection13. Machine learning and signal processing for ECG based emotion recognition14. EoG based human-machine interaction using artificial intelligence15. Surface EMG based gesture recognition using wavelet transform and ensemble learning16. Haptic feedback based tactile sensations to feel virtual objects and/or textures17. Patient rehabilitation assessment using 3D skeletal data and deep learning based approach18. Vision based action recognition for the human-machine interaction19. Natural language processing based assistance and customer services20. Immersive virtual reality and augmented reality in human-machine interaction21. Adaptive systems and personalization in human-machine interaction22. Security and authentication in human-machine interaction23. Applications of human-machine interaction

• ISBN: 978-0-443-29150-0
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 316
• Fecha Publicación: 11/11/2024
• Nº Volúmenes: 1
• Idioma: Inglés