Intelligent Systems for Neurocognition and Human-Robot-Computer Interaction explores the transformative potential of intelligent systems in enhancing human well-being through advancements in neurocognitive technologies, robotics, and AI-driven healthcare. This book addresses the fragmented knowledge at the intersection of these fields, enabling readers to understand the latest advancements and discover practical strategies for implementation. It highlights the importance of ethical considerations and governance in deploying AI and robotics in healthcare settings. Each chapter covers various aspects, including personalized medicine, human-robot interaction, cognitive robotics, wearable technologies, and the role of AI in mental health. The book also discusses the implications of cloud computing, big data, and human-computer interaction in enhancing cognitive and emotional well-being.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. Contributors - p. xvi 7. Section 1. Foundations of neurocognition and well-being - p. S1 8. Chapter 1. The role of natural green spaces in enhancing neurocognition - p. 3 9. Chapter 2. The happiness formula: Integrating purpose, spirituality, and relationships, with neurocognitive well-being - p. 19 10. Section 2. Human-computer interaction - p. S2 11. Chapter 3. Human–computer interaction for cognitive, emotional and learning well-being - p. 43 12. Chapter 4. Toward emotionally intelligent interfaces: An HCI approach to cognitive and learning support - p. 67 13. Chapter 5. Embedded system integration for adaptive human–computer interaction - p. 93 14. Section 3. Human-robot interaction - p. S3 15. Chapter 6. Human-Robot Interaction (HRI) for well-being and social robotics - p. 109 16. Chapter 7. Human-robot interaction (HRI) and social robotics in industry 5.0: Drivers, barriers, and implications for sustainable development - p. 127 17. Section 4. AI in education - p. S4 18. Chapter 8. Empowering learning: How AI drives innovation, enhances deep learning, and elevates student well-being - p. 155 19. Chapter 9. AI in education: transforming learning and enhancing student well-being - p. 183 20. Chapter 10. Data-driven education: Leveraging big data, AI, and machine learning for smarter learning environments - p. 203 21. Section 5. AI in healthcare - p. S5 22. Chapter 11. Chatbots in health care: AI-based personalization and EHR integration in patient–doctor communication - p. 229 23. Chapter 12. Designing reliable algorithms to improve patient outcomes by deploying AI in medical domain - p. 243 24. Chapter 13. AI-driven precision prevention and prediction: a roadmap for transformative healthcare for wellbeing - p. 267 25. Chapter 14. Enhancing well-being with predictive healthcare: AI-ML for accurate pollen outbreak forecasting and management - p. 289 26. Chapter 15. AI in action: Uncovering autism patterns through machine learning - p. 317 27. Section 6. Emerging technologies - p. S6 28. Chapter 16. Transforming sectors: VR and AR applications in healthcare, education, and social robotics—A case study - p. 343 29. Chapter 17. Immersive futures: Expanding role of virtual and augmented reality in digital health, instructional design and human-centered robotics - p. 369 30. Section 7. Ethical considerations - p. S7 31. Chapter 18. The dangers of AI friendship: Adolescent mental health and ethical oversight - p. 385 32. Chapter 19. Ethical AI in education: Fostering well-being and responsible learning through intelligent systems - p. 423 33. Index - p. 453
Intelligent Systems for Neurocognition and Human-Robot-Computer Interaction explores the transformative potential of intelligent systems in enhancing human well-being through advancements in neurocognitive technologies, robotics, and AI-driven healthcare. This book addresses the fragmented knowledge at the intersection of these fields, enabling readers to understand the latest advancements and discover practical strategies for implementation. It highlights the importance of ethical considerations and governance in deploying AI and robotics in healthcare settings. Each chapter covers various aspects, including personalized medicine, human-robot interaction, cognitive robotics, wearable technologies, and the role of AI in mental health. The book also discusses the implications of cloud computing, big data, and human-computer interaction in enhancing cognitive and emotional well-being.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. Contributors - p. xvi 7. Section 1. Foundations of neurocognition and well-being - p. S1 8. Chapter 1. The role of natural green spaces in enhancing neurocognition - p. 3 9. Chapter 2. The happiness formula: Integrating purpose, spirituality, and relationships, with neurocognitive well-being - p. 19 10. Section 2. Human-computer interaction - p. S2 11. Chapter 3. Human–computer interaction for cognitive, emotional and learning well-being - p. 43 12. Chapter 4. Toward emotionally intelligent interfaces: An HCI approach to cognitive and learning support - p. 67 13. Chapter 5. Embedded system integration for adaptive human–computer interaction - p. 93 14. Section 3. Human-robot interaction - p. S3 15. Chapter 6. Human-Robot Interaction (HRI) for well-being and social robotics - p. 109 16. Chapter 7. Human-robot interaction (HRI) and social robotics in industry 5.0: Drivers, barriers, and implications for sustainable development - p. 127 17. Section 4. AI in education - p. S4 18. Chapter 8. Empowering learning: How AI drives innovation, enhances deep learning, and elevates student well-being - p. 155 19. Chapter 9. AI in education: transforming learning and enhancing student well-being - p. 183 20. Chapter 10. Data-driven education: Leveraging big data, AI, and machine learning for smarter learning environments - p. 203 21. Section 5. AI in healthcare - p. S5 22. Chapter 11. Chatbots in health care: AI-based personalization and EHR integration in patient–doctor communication - p. 229 23. Chapter 12. Designing reliable algorithms to improve patient outcomes by deploying AI in medical domain - p. 243 24. Chapter 13. AI-driven precision prevention and prediction: a roadmap for transformative healthcare for wellbeing - p. 267 25. Chapter 14. Enhancing well-being with predictive healthcare: AI-ML for accurate pollen outbreak forecasting and management - p. 289 26. Chapter 15. AI in action: Uncovering autism patterns through machine learning - p. 317 27. Section 6. Emerging technologies - p. S6 28. Chapter 16. Transforming sectors: VR and AR applications in healthcare, education, and social robotics—A case study - p. 343 29. Chapter 17. Immersive futures: Expanding role of virtual and augmented reality in digital health, instructional design and human-centered robotics - p. 369 30. Section 7. Ethical considerations - p. S7 31. Chapter 18. The dangers of AI friendship: Adolescent mental health and ethical oversight - p. 385 32. Chapter 19. Ethical AI in education: Fostering well-being and responsible learning through intelligent systems - p. 423 33. Index - p. 453
