Affective Artificial Intelligence

N. Thillaiarasu, PhD is an Associate Professor in the School of Computing and Information Technology, REVA University, Bengaluru, Karnataka, India with more than 12 years of teaching experience. He has more than 70 publications to his credit. His areas of interest include cloud computing, security, IoT, and machine learning. G. Revathy, PhD is an Assistant Professor in the Department of Computer Science and Engineering in the Srinivasa Ramunjan Centre at SASTRA University, Kumbakonam, Tamil Nadu, India with more than 15 years of experience. She has published more than 35 international journal articles, ten books, and eight book chapters. Her research focuses on machine learning, computer vision, wireless mesh networks, Internet of Things and blockchain. T. Saravanan, PhD is an Assistant Professor at GITAM School of Technology, GITAM (Deemed to be University), Bengaluru, India with more than ten years of experience. He has published many research papers in international journals and conferences, book chapters, and Indian patents. His research interests include computer networks, fuzzy logic, and wireless sensor networks. V. Muthukumaran, PhD is an Assistant Professor in the Department of Mathematics at the SRM Institute of Science and Technology, Kattankulathur Campus, Tamil Nadu, India. He has 12 chapters, 12 patents, and has presented 25 papers in international conferences. His current research interests include machine learning, data science, blockchain, data mining, and algebraic cryptography. S. Balamurugan, PhD is the Director of Research at the Indian Technological Research and Consulting Firm. With 20 years of researching various cutting-edge technologies, he provides expert guidance in technology forecasting and decision making for leading companies and startups. He has published 75 books, 300 papers in international journals, and conferences, and 300 patents.

• Series Preface xviiPreface xixAcknowledgement xxiPart I: Fundamentals of Affective AI 11 Emotion Recognition Techniques: Facial Expression Analysis, Speech Emotion Recognition, Physiological Signal Processing, and Multimodal Approaches 3Monish L., Shaila S.G., Ramesh Chundi, Sumana S.G., Shivamma D. and Manjula M.2 Natural Language Processing for Sentiment and Emotion Analysis – AI-Driven Methods for Detecting the Emotions in Text, Chatbots, and Social Media 25Shaila S.G., Monish L., Sumana S.G. and Ramesh Chundi3 Affective Computing in Edge-Based Healthcare Systems 45Dhamarai Selvi K.V., G. Revathy, Raja Rajeswari Balaji and M. ShyamalagowriPart II: Machine Learning in Affective AI 774 Deep Learning for Emotion Recognition – CNNs, RNNs, Transformers, and Self-Supervised Learning Techniques 79Shivamma D., Shaila S.G., Monish L., Ramesh Chundi and Sumana S.G.5 Early Detection of Mental Health Disorders Using Affective AI on Social Media Textual Data 105A. Sumathi, V. Rishikeswaran and P. Umamaheswari6 Multi-Modal Emotion Detection System: Fusion of Facial Voice and Physiological Data for Improved Emotion Understanding 129Monish L., Shaila S.G., Ramesh Chundi, Sumana S.G. and Manjula M.7 Affective AI-Enhanced Ensemble Learning for Cardiac Disease Risk Prediction 153M. Sridevia, A. L. Sriramb, P. Veeraragavanc and P. MadhavasarmadPart III: Applications Affective AI 1758 Affective AI in Healthcare and Mental Health – AI-Driven Emotion Detection for Diagnosing Depression, Anxiety, and Autism Spectrum Disorders 177Shivamma D., Shaila S.G., Monish L., Ramesh Chundi and Sumana S.G.9 Emotionally Aware Machine Learning for X-Ray Fracture Classification: A SHAP-Driven Approach 193M. Sridevi, S. Venkatesh, P. Veeraragavan and P. Madhavasarma10 Understanding Affective AI: A Review of Emotion Detection Computation and Real-World Applications 211Umamaheswari P., Abiramasundari S. and Sumathi A.11 Smart Attendance System Using Face Emotion Recognition and Power BI for Affective AI 225S. Selvi, S. A. Dhanasekaran and B. VinaykrishnaPart IV: Real World Applications of Affective AI 24312 The Role of Logic in Emotion Understanding: A Neurosymbolic Perspective 245M. Thangavel, D. Ravikumar, S. Senthilvadivu and M. Santhosh Kumar13 Transfer Learning for Affective Computing: Challenges and Opportunities 265Madona B. Sahaai, D. R. Ashwin Kumar, A. Priyadharshini and S. Gokulraj14 Explainability and Interpretability in Affective AI Methods for Making AI-Driven Emotion Recognition Transparent and Trustworthy 285Farjana Farvin Sahapudeen and T. Vigneswari15 From EEG to Emotion: Spatio-Temporal Deep Learning for Real-Time Affective State Recognition 311S. Murali Mohan, B. Rupa Devi, R. Tharun, Arakonam Elen Kokila, Konkala Divya and M. SudhakaraReferences 349Index 353